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Majós C, Pons-Escoda A, Naval P, Güell A, Lucas A, Vidal N, Cos M, Bruna J. Proton MR spectroscopy shows improved performance to segregate high-grade astrocytoma subgroups when defined with the new 2021 World Health Organization classification of central nervous system tumors. Eur Radiol 2024; 34:2174-2182. [PMID: 37740778 DOI: 10.1007/s00330-023-10138-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 06/24/2023] [Accepted: 07/06/2023] [Indexed: 09/25/2023]
Abstract
OBJECTIVES The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors prioritizes isocitrate dehydrogenase (IDH) mutation to define tumor types in diffuse gliomas, in contrast to the 2016 classification, which prioritized histological features. Our objective was to investigate the influence of this change in the performance of proton MR spectroscopy (1H-MRS) in segregating high-grade diffuse astrocytoma subgroups. METHODS Patients with CNS WHO grade 3 and 4 diffuse astrocytoma, known IDH mutation status, and available 1H-MRS were retrospectively retrieved and divided into 4 groups based on IDH mutation status and histological grade. Differences in 1H-MRS between groups were analyzed with the Kruskal-Wallis test. The points on the spectrum that showed the greatest differences were chosen to evaluate the performance of 1H-MRS in discriminating between grades 3 and 4 tumors (WHO 2016 defined), and between IDH-mutant and IDH-wildtype tumors (WHO 2021). ROC curves were constructed with these points, and AUC values were calculated and compared. RESULTS The study included 223 patients with high-grade diffuse astrocytoma. Discrimination between IDH-mutant and IDH-wildtype tumors showed higher AUC values (highest AUC short TE, 0.943; long TE, 0.864) and more noticeable visual differences than the discrimination between grade 3 and 4 tumors (short TE, 0.885; long TE, 0.838). CONCLUSION Our findings suggest that 1H-MRS is more applicable to classify high-grade astrocytomas defined with the 2021 criteria. Improved metabolomic robustness and more homogeneous groups yielded better tumor type discrimination by 1H-MRS with the new criteria. CLINICAL RELEVANCE STATEMENT The 2021 World Health Organization classification of brain tumors empowers molecular criteria to improve tumor characterization. This derives in greater segregation of high-grade diffuse astrocytoma subgroups by MR spectroscopy and warrants further development of brain tumor classification tools with spectroscopy. KEY POINTS • The new 2021 updated World Health Organization classification of central nervous system tumors maximizes the role of molecular diagnosis in the classification of brain tumors. • Proton MR spectroscopy performs better to segregate high-grade astrocytoma subgroups when defined with the new criteria. • The study provides additional evidence of improved metabolic characterization of brain tumor subgroups with the new criteria.
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Affiliation(s)
- Carles Majós
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain.
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain.
- Centro de Investigación Biomédica en Red, BioingenieríaBiomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain.
| | - Albert Pons-Escoda
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Pablo Naval
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Anna Güell
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Anna Lucas
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Radiation Oncology Department, Institut Català d'Oncologia (ICO), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Noemí Vidal
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- Pathology Department, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Mònica Cos
- Radiology Department, Institut deDiagnòstic Per LaImatge (IDI), Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Jordi Bruna
- Neurooncology Unit, Institutd'InvestigacióBiomèdica deBellvitge-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
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Ungan G, Arús C, Vellido A, Julià-Sapé M. A comparison of non-negative matrix underapproximation methods for the decomposition of magnetic resonance spectroscopy data from human brain tumors. NMR IN BIOMEDICINE 2023; 36:e5020. [PMID: 37582395 DOI: 10.1002/nbm.5020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/18/2023] [Accepted: 07/21/2023] [Indexed: 08/17/2023]
Abstract
Magnetic resonance spectroscopy (MRS) is an MR technique that provides information about the biochemistry of tissues in a noninvasive way. MRS has been widely used for the study of brain tumors, both preoperatively and during follow-up. In this study, we investigated the performance of a range of variants of unsupervised matrix factorization methods of the non-negative matrix underapproximation (NMU) family, namely, sparse NMU, global NMU, and recursive NMU, and compared them with convex non-negative matrix factorization (C-NMF), which has previously shown a good performance on brain tumor diagnostic support problems using MRS data. The purpose of the investigation was 2-fold: first, to ascertain the differences among the sources extracted by these methods; and second, to compare the influence of each method in the diagnostic accuracy of the classification of brain tumors, using them as feature extractors. We discovered that, first, NMU variants found meaningful sources in terms of biological interpretability, but representing parts of the spectrum, in contrast to C-NMF; and second, that NMU methods achieved better classification accuracy than C-NMF for the classification tasks when one class was not meningioma.
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Affiliation(s)
- Gulnur Ungan
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
| | - Alfredo Vellido
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- IDEAI-UPC Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politècnica de Catalunya (UPC) BarcelonaTech, Barcelona, Spain
| | - Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red (CIBER), Madrid, Spain
- Departament de Bioquímica i Biologia Molecular and Institut de Biotecnologia i Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
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Sollmann N, Zhang H, Kloth C, Zimmer C, Wiestler B, Rosskopf J, Kreiser K, Schmitz B, Beer M, Krieg SM. Modern preoperative imaging and functional mapping in patients with intracranial glioma. ROFO-FORTSCHR RONTG 2023; 195:989-1000. [PMID: 37224867 DOI: 10.1055/a-2083-8717] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Magnetic resonance imaging (MRI) in therapy-naïve intracranial glioma is paramount for neuro-oncological diagnostics, and it provides images that are helpful for surgery planning and intraoperative guidance during tumor resection, including assessment of the involvement of functionally eloquent brain structures. This study reviews emerging MRI techniques to depict structural information, diffusion characteristics, perfusion alterations, and metabolism changes for advanced neuro-oncological imaging. In addition, it reflects current methods to map brain function close to a tumor, including functional MRI and navigated transcranial magnetic stimulation with derived function-based tractography of subcortical white matter pathways. We conclude that modern preoperative MRI in neuro-oncology offers a multitude of possibilities tailored to clinical needs, and advancements in scanner technology (e. g., parallel imaging for acceleration of acquisitions) make multi-sequence protocols increasingly feasible. Specifically, advanced MRI using a multi-sequence protocol enables noninvasive, image-based tumor grading and phenotyping in patients with glioma. Furthermore, the add-on use of preoperatively acquired MRI data in combination with functional mapping and tractography facilitates risk stratification and helps to avoid perioperative functional decline by providing individual information about the spatial location of functionally eloquent tissue in relation to the tumor mass. KEY POINTS:: · Advanced preoperative MRI allows for image-based tumor grading and phenotyping in glioma.. · Multi-sequence MRI protocols nowadays make it possible to assess various tumor characteristics (incl. perfusion, diffusion, and metabolism).. · Presurgical MRI in glioma is increasingly combined with functional mapping to identify and enclose individual functional areas.. · Advancements in scanner technology (e. g., parallel imaging) facilitate increasing application of dedicated multi-sequence imaging protocols.. CITATION FORMAT: · Sollmann N, Zhang H, Kloth C et al. Modern preoperative imaging and functional mapping in patients with intracranial glioma. Fortschr Röntgenstr 2023; 195: 989 - 1000.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, United States
| | - Haosu Zhang
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Christopher Kloth
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- TranslaTUM - Central Institute for Translational Cancer Research, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Johannes Rosskopf
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Kornelia Kreiser
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Department of Radiology and Neuroradiology, Universitäts- und Rehabilitationskliniken Ulm, Ulm, Germany
| | - Bernd Schmitz
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
- Section of Neuroradiology, Bezirkskrankenhaus Günzburg, Günzburg, Germany
| | - Meinrad Beer
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Sandro M Krieg
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, München, Germany
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
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Ortega-Martorell S, Olier I, Hernandez O, Restrepo-Galvis PD, Bellfield RAA, Candiota AP. Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks. Cancers (Basel) 2023; 15:4002. [PMID: 37568818 PMCID: PMC10417313 DOI: 10.3390/cancers15154002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/26/2023] [Accepted: 08/05/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation. METHODS This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation. RESULTS The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method. CONCLUSIONS The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.
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Affiliation(s)
- Sandra Ortega-Martorell
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Ivan Olier
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Orlando Hernandez
- Escuela Colombiana de Ingeniería Julio Garavito, Bogota 111166, Colombia; (O.H.); (P.D.R.-G.)
| | | | - Ryan A. A. Bellfield
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Ana Paula Candiota
- Centro de Investigación Biomédica en Red: Bioingeniería, Biomateriales y Nanomedicina, 08193 Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain
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Antkowiak L, Zimny M, Starszak K, Sordyl R, Mandera M. Surgical Treatment of Pediatric Incidentally Found Brain Tumors: A Single-Center Experience. Brain Sci 2023; 13:brainsci13050746. [PMID: 37239218 DOI: 10.3390/brainsci13050746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 05/28/2023] Open
Abstract
There remains much debate about the correct management of incidentally found brain tumors in the pediatric population. This study aimed to evaluate the efficacy and safety of surgical treatment of incidentally found pediatric brain tumors. A retrospective analysis of pediatric patients who underwent surgical resection of incidentally found brain tumors between January 2010 and April 2016 was performed. A total of seven patients were included. The median age at the time of diagnosis was 9.7 years. The reasons for performing neuroimaging were as follows: impeded speech development (n = 2), shunt control (n = 1), paranasal sinuses control (n = 1), behavior changes (n = 1), head trauma (n = 1), and preterm birth (n = 1). Five patients underwent gross total tumor resection (71.4%), while subtotal resection was performed in two patients (28.6%). There was no surgery-related morbidity. Patients were followed up for a mean of 79 months. One patient with atypical neurocytoma experienced tumor recurrence 45 months following primary resection. All patients remained neurologically intact. The majority of pediatric incidentally found brain tumors were histologically benign. Surgery remains a safe therapeutic approach associated with favorable long-term outcomes. Considering the expected long lifetime of pediatric patients, as well as the psychological burden associated with having a brain tumor as a child, surgical resection can be considered an initial approach.
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Affiliation(s)
- Lukasz Antkowiak
- Department of Pediatric Neurosurgery, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Mikolaj Zimny
- Department of Neurosurgery, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Krzysztof Starszak
- Department of Pediatric Neurosurgery, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
- Department of Human Anatomy, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Ryszard Sordyl
- Department of Pediatric Neurosurgery, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
| | - Marek Mandera
- Department of Pediatric Neurosurgery, Medical University of Silesia in Katowice, 40-752 Katowice, Poland
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Candiota AP, Arús C. Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives. Metabolites 2022; 12:metabo12030243. [PMID: 35323686 PMCID: PMC8950145 DOI: 10.3390/metabo12030243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 11/16/2022] Open
Abstract
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.
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Affiliation(s)
- Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Correspondence:
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Davies NP, Rose HEL, Manias KA, Natarajan K, Abernethy LJ, Oates A, Janjua U, Davies P, MacPherson L, Arvanitis TN, Peet AC. Added value of magnetic resonance spectroscopy for diagnosing childhood cerebellar tumours. NMR IN BIOMEDICINE 2022; 35:e4630. [PMID: 34647377 PMCID: PMC11478925 DOI: 10.1002/nbm.4630] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 08/20/2021] [Accepted: 09/15/2021] [Indexed: 06/13/2023]
Abstract
1 H-magnetic resonance spectroscopy (MRS) provides noninvasive metabolite profiles with the potential to aid the diagnosis of brain tumours. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. The aim of the current study was to evaluate, prospectively, the diagnostic accuracy of a previously established classifier for diagnosing the three major childhood cerebellar tumours, and to determine added value compared with standard reporting of conventional imaging. Single-voxel MRS (1.5 T, PRESS, TE 30 ms, TR 1500 ms, spectral resolution 1 Hz/point) was acquired prospectively on 39 consecutive cerebellar tumours with histopathological diagnoses of pilocytic astrocytoma, ependymoma or medulloblastoma. Spectra were analysed with LCModel and predefined quality control criteria were applied, leaving 33 cases in the analysis. The MRS diagnostic classifier was applied to this dataset. A retrospective analysis was subsequently undertaken by three radiologists, blind to histopathological diagnosis, to determine the change in diagnostic certainty when sequentially viewing conventional imaging, MRS and a decision support tool, based on the classifier. The overall classifier accuracy, evaluated prospectively, was 91%. Incorrectly classified cases, two anaplastic ependymomas, and a rare histological variant of medulloblastoma, were not well represented in the original training set. On retrospective review of conventional MRI, MRS and the classifier result, all radiologists showed a significant increase (Wilcoxon signed rank test, p < 0.001) in their certainty of the correct diagnosis, between viewing the conventional imaging and MRS with the decision support system. It was concluded that MRS can aid the noninvasive diagnosis of posterior fossa tumours in children, and that a decision support classifier helps in MRS interpretation.
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Affiliation(s)
- Nigel P. Davies
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Department of Medical PhysicsUniversity Hospitals Birmingham NHS Foundation TrustBirminghamUK
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Heather E. L. Rose
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Karen A. Manias
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Kal Natarajan
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Department of Medical PhysicsUniversity Hospitals Birmingham NHS Foundation TrustBirminghamUK
| | | | - Adam Oates
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Umair Janjua
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Paul Davies
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Lesley MacPherson
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
| | - Theodoros N. Arvanitis
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
- Institute of Digital Healthcare, WMGUniversity of WarwickCoventryUK
| | - Andrew C. Peet
- Institute of Cancer and Genomic SciencesUniversity of BirminghamBirminghamUK
- Birmingham Women's and Children's Hospital NHS Foundation TrustBirminghamUK
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Priya S, Liu Y, Ward C, Le NH, Soni N, Pillenahalli Maheshwarappa R, Monga V, Zhang H, Sonka M, Bathla G. Radiomic Based Machine Learning Performance for a Three Class Problem in Neuro-Oncology: Time to Test the Waters? Cancers (Basel) 2021; 13:2568. [PMID: 34073840 PMCID: PMC8197204 DOI: 10.3390/cancers13112568] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 04/28/2021] [Accepted: 05/04/2021] [Indexed: 01/06/2023] Open
Abstract
Prior radiomics studies have focused on two-class brain tumor classification, which limits generalizability. The performance of radiomics in differentiating the three most common malignant brain tumors (glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and metastatic disease) is assessed; factors affecting the model performance and usefulness of a single sequence versus multiparametric MRI (MP-MRI) remain largely unaddressed. This retrospective study included 253 patients (120 metastatic (lung and brain), 40 PCNSL, and 93 GBM). Radiomic features were extracted for whole a tumor mask (enhancing plus necrotic) and an edema mask (first pipeline), as well as for separate enhancing and necrotic and edema masks (second pipeline). Model performance was evaluated using MP-MRI, individual sequences, and the T1 contrast enhanced (T1-CE) sequence without the edema mask across 45 model/feature selection combinations. The second pipeline showed significantly high performance across all combinations (Brier score: 0.311-0.325). GBRM fit using the full feature set from the T1-CE sequence was the best model. The majority of the top models were built using a full feature set and inbuilt feature selection. No significant difference was seen between the top-performing models for MP-MRI (AUC 0.910) and T1-CE sequence with (AUC 0.908) and without edema masks (AUC 0.894). T1-CE is the single best sequence with comparable performance to that of multiparametric MRI (MP-MRI). Model performance varies based on tumor subregion and the combination of model/feature selection methods.
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Affiliation(s)
- Sarv Priya
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA; (N.S.); (R.P.M.); (G.B.)
| | - Yanan Liu
- College of Engineering, University of Iowa, Iowa City, IA 52242, USA; (Y.L.); (N.H.L.); (H.Z.); (M.S.)
| | - Caitlin Ward
- Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USA;
| | - Nam H. Le
- College of Engineering, University of Iowa, Iowa City, IA 52242, USA; (Y.L.); (N.H.L.); (H.Z.); (M.S.)
| | - Neetu Soni
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA; (N.S.); (R.P.M.); (G.B.)
| | | | - Varun Monga
- Department of Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA;
| | - Honghai Zhang
- College of Engineering, University of Iowa, Iowa City, IA 52242, USA; (Y.L.); (N.H.L.); (H.Z.); (M.S.)
| | - Milan Sonka
- College of Engineering, University of Iowa, Iowa City, IA 52242, USA; (Y.L.); (N.H.L.); (H.Z.); (M.S.)
| | - Girish Bathla
- Department of Radiology, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, USA; (N.S.); (R.P.M.); (G.B.)
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Radiomics-Based Differentiation between Glioblastoma, CNS Lymphoma, and Brain Metastases: Comparing Performance across MRI Sequences and Machine Learning Models. Cancers (Basel) 2021. [DOI: 10.3390/cancers13092261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Prior radiomics studies have focused on two-class brain tumor classification, which limits generalizability. The performance of radiomics in differentiating the three most common malignant brain tumors (glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and metastatic disease) is assessed; factors affecting the model performance and usefulness of a single sequence versus multiparametric MRI (MP-MRI) remain largely unaddressed. This retrospective study included 253 patients (120 metastatic (lung and brain), 40 PCNSL, and 93 GBM). Radiomic features were extracted for whole a tumor mask (enhancing plus necrotic) and an edema mask (first pipeline), as well as for separate enhancing and necrotic and edema masks (second pipeline). Model performance was evaluated using MP-MRI, individual sequences, and the T1 contrast enhanced (T1-CE) sequence without the edema mask across 45 model/feature selection combinations. The second pipeline showed significantly high performance across all combinations (Brier score: 0.311–0.325). GBRM fit using the full feature set from the T1-CE sequence was the best model. The majority of the top models were built using a full feature set and inbuilt feature selection. No significant difference was seen between the top-performing models for MP-MRI (AUC 0.910) and T1-CE sequence with (AUC 0.908) and without edema masks (AUC 0.894). T1-CE is the single best sequence with comparable performance to that of multiparametric MRI (MP-MRI). Model performance varies based on tumor subregion and the combination of model/feature selection methods.
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Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
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Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
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Characterization of dysregulated glutamine metabolism in human glioma tissue with 1H NMR. Sci Rep 2020; 10:20435. [PMID: 33235296 PMCID: PMC7686482 DOI: 10.1038/s41598-020-76982-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 11/04/2020] [Indexed: 02/06/2023] Open
Abstract
Gliomas are one of the most common types of brain tumors. Given low survival and high treatment resistance rates, particularly for high grade gliomas, there is a need for specific biomarkers that can be used to stratify patients for therapy and monitor treatment response. Recent work has demonstrated that metabolic reprogramming, often mediated by inflammation, can lead to an upregulation of glutamine as an energy source for cancer cells. As a result, glutamine pathways are an emerging pharmacologic target. The goal of this pilot study was to characterize changes in glutamine metabolism and inflammation in human glioma samples and explore the use of glutamine as a potential biomarker. 1H high-resolution magic angle spinning nuclear magnetic resonance spectra were acquired from ex vivo glioma tissue (n = 16, grades II–IV) to quantify metabolite concentrations. Tumor inflammatory markers were quantified using electrochemiluminescence assays. Glutamate, glutathione, lactate, and alanine, as well as interleukin (IL)-1β and IL-8, increased significantly in samples from grade IV gliomas compared to grades II and III (p ≤ .05). Following dimension reduction of the inflammatory markers using probabilistic principal component analysis, we observed that glutamine, alanine, glutathione, and lactate were positively associated with the first inflammatory marker principal component. Our findings support the hypothesis that glutamine may be a key marker for glioma progression and indicate that inflammation is associated with changes in glutamine metabolism. These results motivate further in vivo investigation of glutamine as a biomarker for tumor progression and treatment response.
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Soleman J, Kozyrev DA, Ben-Sira L, Constantini S, Roth J. Management of incidental brain tumors in children: a systematic review. Childs Nerv Syst 2020; 36:1607-1619. [PMID: 32377829 DOI: 10.1007/s00381-020-04658-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 04/28/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Due to technical advancements and availability of neuroimaging, detection of incidental pediatric brain tumors (IPBT) is growing rapidly. The management of these asymptomatic lesions remains unclear; radiological, pathological, and clinical risk factors for further growth and malignant transformation (MT) are not well defined. METHODS We systematically reviewed the literature on the dilemmas and management of IPBT suggestive of a low-grade brain tumor (LGBT). Keyword searches of the PubMed and Medline (NCBI) databases identified studies on IPBT describing the prevalence, neuroimaging, management, or risk of MT through July 2019. References of the identified articles were also reviewed. RESULTS A total of 2021 records were screened. Fifty-nine full-text articles were reviewed, and 34 published studies were included. IPBT are diagnosed in 0.2-5.7% of children undergoing brain imaging for various reasons. The accepted approach for management of lesions showing radiological characteristics suggestive of LGBT is radiological follow-up. The rate at which additional intervention is required during follow-up for these apparently low-grade lesions is 9.5%. Nevertheless, the dilemma of early surgical resection or biopsy vs. clinical and radiological follow-up of IPBT is still unresolved. The risk in these cases is missing a transformation to a higher grade tumor. However, MT of pediatric LGBT is very rare, occurring in less than 3% of the cases of proven low-grade gliomas in children. The risk of future MT in pediatric low-grade gliomas seems to be greater in the presence of specific molecular markers such as BRAF V-600E, CDKN2A, and H3F3A K27M. CONCLUSIONS The natural history, management, and prognosis of IPBT remain ambiguous. It seems that lesions suggestive of LGBT can initially be followed, since many of these lesions remain stable over time and MT is rare. However, controversy among centers concerning the ideal approach still exists. Further observational and prospective cohort studies, focusing on potential clinical and radiological characteristics or risk factors suggestive of high-grade tumors, tumor progress, or MT of IPBT, are needed.
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Affiliation(s)
- Jehuda Soleman
- Department of Pediatric Neurosurgery, Tel Aviv Medical Center & Dana Children's Hospital Tel Aviv, Weizman Street 12, Tel Aviv, Israel.
- Departments of Neurosurgery and Pediatric Neurosurgery, University Hospital and Children's University Hospital of Basel, Basel, Switzerland.
- Faculty of Medicine, University of Basel, Basel, Switzerland.
| | - Danil A Kozyrev
- Department of Pediatric Neurosurgery, Tel Aviv Medical Center & Dana Children's Hospital Tel Aviv, Weizman Street 12, Tel Aviv, Israel
| | - Liat Ben-Sira
- Department of Pediatric Neuroradiology, Tel Aviv Medical Center & Dana Children's Hospital Tel Aviv, Tel Aviv, Israel
| | - Shlomi Constantini
- Department of Pediatric Neurosurgery, Tel Aviv Medical Center & Dana Children's Hospital Tel Aviv, Weizman Street 12, Tel Aviv, Israel
- Tel-Aviv University, Tel Aviv, Israel
| | - Jonathan Roth
- Department of Pediatric Neurosurgery, Tel Aviv Medical Center & Dana Children's Hospital Tel Aviv, Weizman Street 12, Tel Aviv, Israel
- Tel-Aviv University, Tel Aviv, Israel
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13
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Kozyrev DA, Constantini S, Tsering D, Keating R, Basal S, Roth J. Pediatric posterior fossa incidentalomas. Childs Nerv Syst 2020; 36:601-609. [PMID: 31492982 DOI: 10.1007/s00381-019-04364-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 08/30/2019] [Indexed: 12/23/2022]
Abstract
PURPOSE Pediatric brain incidentalomas are increasingly being diagnosed. As the posterior fossa (PF) is the location of most brain tumors in children, lesions of this region are of special interest. Currently, the natural history of incidental lesions in the PF is unknown. We present our experience treating such lesions. METHODS A retrospective study was carried out in two large tertiary pediatric centers. Patients were included if they had an incidental PF lesion suspected of being a tumor, and diagnosed before the age of 20 years. We analyzed treatment strategy, pathology, and outcome of operated and non-operated cases. RESULTS Seventy children (31 females) with a mean age of 8.4 ± 6.1 years were included. The three most common indications for imaging were headaches (16, assumed to be unrelated to the lesions), workup of unrelated conditions (14), and unspecified reasons (14). Twenty-seven patients (39%) were operated immediately, and 43 followed, of which 12 were eventually operated due to radiological changes, 28.9 ± 16.2 months after diagnosis. The most commonly found pathology was pilocytic astrocytomas (21 of 39 operated cases). Almost 10% were found to be malignant tumors including medulloblastomas (5) and ATRT (1). CONCLUSION Incidental PF lesions in children include both benign and malignant tumors. While certain lesions may be followed, others may require surgical treatment. Specific treatment decisions are based on initial radiological appearance, change in radiological characteristics over time, location, and evolving symptoms. The surgical risks must be balanced vis-à-vis the risk of missing a high-grade tumor and the very rare risk of malignant transformation.
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Affiliation(s)
- Danil A Kozyrev
- Department of Pediatric Neurosurgery, Dana Children's Hospital, Tel Aviv Medical Center, Tel Aviv University, 6 Weizmann Street, 64239, Tel Aviv, Israel
| | - Shlomi Constantini
- Department of Pediatric Neurosurgery, Dana Children's Hospital, Tel Aviv Medical Center, Tel Aviv University, 6 Weizmann Street, 64239, Tel Aviv, Israel
| | - Deki Tsering
- Children's National Medical Center, Washington, DC, USA
| | | | - Sharif Basal
- Department of Pediatric Neurosurgery, Dana Children's Hospital, Tel Aviv Medical Center, Tel Aviv University, 6 Weizmann Street, 64239, Tel Aviv, Israel
| | - Jonathan Roth
- Department of Pediatric Neurosurgery, Dana Children's Hospital, Tel Aviv Medical Center, Tel Aviv University, 6 Weizmann Street, 64239, Tel Aviv, Israel.
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Gharzeddine K, Hatzoglou V, Holodny AI, Young RJ. MR Perfusion and MR Spectroscopy of Brain Neoplasms. Radiol Clin North Am 2019; 57:1177-1188. [PMID: 31582043 DOI: 10.1016/j.rcl.2019.07.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Advances in imaging techniques, such as MR perfusion and spectroscopy, are increasingly indispensable in the management and treatment plans of brain neoplasms: from diagnosing, molecular/genetic typing and grading neoplasms, augmenting biopsy results and improving accuracy, to ultimately directing and monitoring treatment and response. New developments in treatment methods have resulted in new diagnostic challenges for conventional MR imaging, such as pseudoprogression, where MR perfusion has the widest current application. MR spectroscopy is showing increasing promise in noninvasively determining genetic subtypes and, potentially, susceptibility to molecular targeted therapies.
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Affiliation(s)
- Karem Gharzeddine
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, Weill Medical College of Cornell University, 1275 York Avenue, New York, NY 10065, USA
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan-Kettering Cancer Center, Weill Medical College of Cornell University, Weill Cornell Graduate School of Medical Sciences, 1275 York Avenue, New York, NY 10065, USA.
| | - Robert J Young
- Brain Imaging, Neuroradiology Research, Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
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15
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Julià-Sapé M, Candiota AP, Arús C. Cancer metabolism in a snapshot: MRS(I). NMR IN BIOMEDICINE 2019; 32:e4054. [PMID: 30633389 DOI: 10.1002/nbm.4054] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 11/02/2018] [Accepted: 11/05/2018] [Indexed: 06/09/2023]
Abstract
The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by 13 C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-13 C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr 13 C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the 13 C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. 31 P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole 1 H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.
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Affiliation(s)
- Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
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Shooli H, Dadgar H, Wáng YXJ, Vafaee MS, Kashuk SR, Nemati R, Jafari E, Nabipour I, Gholamrezanezhad A, Assadi M, Larvie M. An update on PET-based molecular imaging in neuro-oncology: challenges and implementation for a precision medicine approach in cancer care. Quant Imaging Med Surg 2019; 9:1597-1610. [PMID: 31667145 PMCID: PMC6785513 DOI: 10.21037/qims.2019.08.16] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 08/19/2019] [Indexed: 12/17/2022]
Abstract
PET imaging using novel radiotracers show promises for tumor grading and molecular characterization through visualizing molecular and functional properties of the tumors. Application of PET tracers in brain neoplasm depends on both type of the neoplasm and the research or clinical significance required to be addressed. In clinical neuro-oncology, 18F-FDG is used mainly to differentiate tumor recurrence from radiation-induced necrosis, and novel PET agents show attractive imaging properties. Novel PET tracers can offer biologic information not visible via contrast-enhanced MRI or 18F-FDG PET. This review aims to provide an update on the complementary role of PET imaging in neuro-oncology both in research and clinical settings along with presenting interesting cases in this context.
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Affiliation(s)
- Hossein Shooli
- The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Habibollah Dadgar
- Cancer Research Center, RAZAVI Hospital, Imam Reza International University, Mashhad, Iran
| | - Yì-Xiáng J Wáng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
| | - Manochehr Seyedi Vafaee
- Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark
- Translational Neuroscience, BRIDGE, University of Southern Denmark, Odense, Denmark
- Neuroscience Research Center, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Saman Rassaei Kashuk
- The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Reza Nemati
- Department of Neurology, Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Esmail Jafari
- The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Iraj Nabipour
- The Persian Gulf Marine Biotechnology Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Ali Gholamrezanezhad
- Department of Diagnostic Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Majid Assadi
- The Persian Gulf Nuclear Medicine Research Center, Department of Molecular Imaging and Radionuclide Therapy (MIRT), Bushehr Medical University Hospital, Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Mykol Larvie
- Department of Nuclear Medicine, Cleveland Clinic, Cleveland, OH 44195, USA
- Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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17
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Manias KA, Gill SK, MacPherson L, Oates A, Pinkey B, Davies P, Zarinabad N, Davies NP, Babourina-Brooks B, Wilson M, Peet AC. Diagnostic accuracy and added value of qualitative radiological review of 1H-magnetic resonance spectroscopy in evaluation of childhood brain tumors. Neurooncol Pract 2019; 6:428-437. [PMID: 31832213 DOI: 10.1093/nop/npz010] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Background 1H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI. Methods Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end. Results Radiologists' principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology. Conclusions MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.
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Affiliation(s)
- Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
| | - Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
| | | | - Adam Oates
- Department of Radiology, Birmingham Children's Hospital, UK
| | | | - Paul Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK
| | | | - Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK.,Department of Imaging and Medical Physics, University Hospitals Birmingham NHS Foundation Trust, UK
| | | | | | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, UK
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Hellström J, Romanos Zapata R, Libard S, Wikström J, Ortiz-Nieto F, Alafuzoff I, Raininko R. Evaluation of the INTERPRET decision-support system: can it improve the diagnostic value of magnetic resonance spectroscopy of the brain? Neuroradiology 2018; 61:43-53. [PMID: 30443796 PMCID: PMC6336758 DOI: 10.1007/s00234-018-2129-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 11/01/2018] [Indexed: 12/05/2022]
Abstract
Purpose We evaluated in a clinical setting the INTERPRET decision-support system (DSS), a software generated to aid in MRS analysis to achieve a specific diagnosis for brain lesions. Methods The material consisted of 100 examinations of focal intracranial lesions with confirmed diagnoses. MRS was obtained at 1.5 T using TE 20–30 ms. Data were processed with the LCModel for conventional analysis. The INTERPRET DSS 3.1. was used to obtain specific diagnoses. MRI and MRS were reviewed by one interpreter. DSS analysis was made by another interpreter, in 80 cases by two interpreters. The diagnoses were compared with the definitive diagnoses. For comparisons between DSS, conventional MRS analysis, and MRI, the diagnoses were categorised: high-grade tumour, low-grade tumour, non-neoplastic lesion. Results Interobserver agreement in choosing the diagnosis from the INTERPRET database was 75%. The diagnosis was correct in 38/100 cases, incorrect in 57 cases. No good match was found in 5/100 cases. The diagnostic category was correct with DSS/conventional MRS/MRI in 67/58/52 cases, indeterminate in 5/8/20 cases, incorrect in 28/34/28 cases. Results with DSS were not significantly better than with conventional MRS analysis. All definitive diagnoses did not exist in the INTERPRET database. In the 61 adult patients with the diagnosis included in the database, DSS/conventional MRS/MRI yielded a correct diagnosis category in 48/32/29 cases (DSS vs conventional MRS: p = 0.002, DSS vs MRI: p = 0.0004). Conclusion Use of the INTERPRET DSS did not improve MRS categorisation of the lesions in the unselected clinical cases. In adult patients with lesions existing in the INTERPRET database, DSS improved the results, which indicates the potential of this software with an extended database. Electronic supplementary material The online version of this article (10.1007/s00234-018-2129-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- J Hellström
- Department of Radiology, Uppsala University, Uppsala, Sweden.
| | | | - S Libard
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.,Department of Pathology, Uppsala University Hospital, Uppsala, Sweden
| | - J Wikström
- Department of Radiology, Uppsala University, Uppsala, Sweden
| | - F Ortiz-Nieto
- Department of Radiology, Uppsala University, Uppsala, Sweden
| | - I Alafuzoff
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.,Department of Pathology, Uppsala University Hospital, Uppsala, Sweden
| | - R Raininko
- Department of Radiology, Uppsala University, Uppsala, Sweden
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The value of magnetic resonance spectroscopy as a supplement to MRI of the brain in a clinical setting. PLoS One 2018; 13:e0207336. [PMID: 30440005 PMCID: PMC6237369 DOI: 10.1371/journal.pone.0207336] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 10/30/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND There are different opinions of the clinical value of MRS of the brain. In selected materials MRS has demonstrated good results for characterisation of both neoplastic and non-neoplastic lesions. The aim of this study was to evaluate the supplemental value of MR spectroscopy (MRS) in a clinical setting. MATERIAL AND METHODS MRI and MRS were re-evaluated in 208 cases with a clinically indicated MRS (cases with uncertain or insufficient information on MRI) and a confirmed diagnosis. Both single voxel spectroscopy (SVS) and chemical shift imaging (CSI) were performed in 105 cases, only SVS or CSI in 54 and 49 cases, respectively. Diagnoses were grouped into categories: non-neoplastic disease, low-grade tumour, and high-grade tumour. The clinical value of MRS was considered very beneficial if it provided the correct category or location when MRI did not, beneficial if it ruled out suspected diseases or was more specific than MRI, inconsequential if it provided the same level of information, or misleading if it provided less or incorrect information. RESULTS There were 70 non-neoplastic lesions, 43 low-grade tumours, and 95 high-grade tumours. For MRI, the category was correct in 130 cases (62%), indeterminate in 39 cases (19%), and incorrect in 39 cases (19%). Supplemented with MRS, 134 cases (64%) were correct, 23 cases (11%) indeterminate, and 51 (25%) incorrect. Additional information from MRS was beneficial or very beneficial in 31 cases (15%) and misleading in 36 cases (17%). CONCLUSION In most cases MRS did not add to the diagnostic value of MRI. In selected cases, MRS may be a valuable supplement to MRI.
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Abstract
Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.
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Affiliation(s)
- Geoffrey S Payne
- University Hospitals Southampton NHS Foundation Trust, Tremona Road, Southampton SO16 6YD, United Kingdom
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Manias KA, Harris LM, Davies NP, Natarajan K, MacPherson L, Foster K, Brundler MA, Hargrave DR, Payne GS, Leach MO, Morgan PS, Auer D, Jaspan T, Arvanitis TN, Grundy RG, Peet AC. Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours. Pediatr Radiol 2018; 48:1630-1641. [PMID: 30062569 PMCID: PMC6153873 DOI: 10.1007/s00247-018-4182-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 05/10/2018] [Accepted: 06/10/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND A tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data. OBJECTIVE To determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset. MATERIALS AND METHODS Magnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total. RESULTS Of the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features. CONCLUSION The original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data.
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Affiliation(s)
- Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Birmingham Children's Hospital, Birmingham, UK
| | - Lisa M Harris
- Department of Radiological Science, Brighton and Sussex University Hospitals NHS Trust, Brighton, UK
| | - Nigel P Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Medical Physics and Imaging, University Hospital Birmingham, Birmingham, UK
| | - Kal Natarajan
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Medical Physics and Imaging, University Hospital Birmingham, Birmingham, UK
| | | | | | | | | | | | - Martin O Leach
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, London, SW7 3RP, UK
| | - Paul S Morgan
- Medical Physics, Nottingham University Hospitals, Nottingham, UK
| | - Dorothee Auer
- Radiological and Imaging Sciences, University of Nottingham, Nottingham, UK
| | - Tim Jaspan
- Radiology Department, University Hospital Nottingham, Nottingham, UK
| | - Theodoros N Arvanitis
- Birmingham Children's Hospital, Birmingham, UK
- Institute of Digital Healthcare, WMG, University of Warwick, Warwick, UK
| | - Richard G Grundy
- The Childhood Brain Tumour Research Centre, The Medical School, University of Nottingham, Nottingham, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.
- Birmingham Children's Hospital, Birmingham, UK.
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22
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Wu M, Shu J. Multimodal Molecular Imaging: Current Status and Future Directions. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:1382183. [PMID: 29967571 PMCID: PMC6008764 DOI: 10.1155/2018/1382183] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 04/11/2018] [Accepted: 05/10/2018] [Indexed: 12/12/2022]
Abstract
Molecular imaging has emerged at the end of the last century as an interdisciplinary method involving in vivo imaging and molecular biology aiming at identifying living biological processes at a cellular and molecular level in a noninvasive manner. It has a profound role in determining disease changes and facilitating drug research and development, thus creating new medical modalities to monitor human health. At present, a variety of different molecular imaging techniques have their advantages, disadvantages, and limitations. In order to overcome these shortcomings, researchers combine two or more detection techniques to create a new imaging mode, such as multimodal molecular imaging, to obtain a better result and more information regarding monitoring, diagnosis, and treatment. In this review, we first describe the classic molecular imaging technology and its key advantages, and then, we offer some of the latest multimodal molecular imaging modes. Finally, we summarize the great challenges, the future development, and the great potential in this field.
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Affiliation(s)
- Min Wu
- Department of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Jian Shu
- Department of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
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23
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Nandu H, Wen PY, Huang RY. Imaging in neuro-oncology. Ther Adv Neurol Disord 2018; 11:1756286418759865. [PMID: 29511385 PMCID: PMC5833173 DOI: 10.1177/1756286418759865] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 01/18/2018] [Indexed: 12/11/2022] Open
Abstract
Imaging plays several key roles in managing brain tumors, including diagnosis, prognosis, and treatment response assessment. Ongoing challenges remain as new therapies emerge and there are urgent needs to find accurate and clinically feasible methods to noninvasively evaluate brain tumors before and after treatment. This review aims to provide an overview of several advanced imaging modalities including magnetic resonance imaging and positron emission tomography (PET), including advances in new PET agents, and summarize several key areas of their applications, including improving the accuracy of diagnosis and addressing the challenging clinical problems such as evaluation of pseudoprogression and anti-angiogenic therapy, and rising challenges of imaging with immunotherapy.
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Affiliation(s)
- Hari Nandu
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02445, USA
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24
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Manias K, Gill SK, Zarinabad N, Davies P, English M, Ford D, MacPherson L, Nicklaus-Wollenteit I, Oates A, Solanki G, Adamski J, Wilson M, Peet AC. Evaluation of the added value of 1H-magnetic resonance spectroscopy for the diagnosis of pediatric brain lesions in clinical practice. Neurooncol Pract 2017; 5:18-27. [PMID: 29692921 PMCID: PMC5909808 DOI: 10.1093/nop/npx005] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background Magnetic resonance spectroscopy (MRS) aids noninvasive diagnosis of pediatric brain tumors, but use in clinical practice is not well documented. We aimed to review clinical use of MRS, establish added value in noninvasive diagnosis, and investigate potential impact on patient care. Methods Sixty-nine children with lesions imaged using MRS and reviewed by the tumor board from 2014 to 2016 met inclusion criteria. Contemporaneous MRI diagnosis, spectroscopy analysis, histopathology, and clinical information were reviewed. Final diagnosis was agreed on by the tumor board at study end. Results Five cases were excluded for lack of documented MRI diagnosis. The principal MRI diagnosis by pediatric radiologists was correct in 59%, increasing to 73% with addition of MRS. Of the 73%, 19.1% (95% CI, 9.1%-33.3%) were incorrectly diagnosed with MRI alone. MRS led to a significant improvement in correct diagnosis over all tumor types (P = .012). Of diagnoses correctly made with MRI, confidence increased by 37% when adding MRS, with no patients incorrectly re-diagnosed. Indolent lesions were diagnosed noninvasively in 85% of cases, with MRS a major contributor to 91% of these diagnoses. Of all patients, 39% were managed without histopathological diagnosis. MRS contributed to diagnosis in 68% of this group, modifying it in 12%. MRS influenced management in 33% of cases, mainly through avoiding and guiding biopsy and aiding tumor characterization. Conclusion MRS can improve accuracy and confidence in noninvasive diagnosis of pediatric brain lesions in clinical practice. There is potential to improve outcomes through avoiding biopsy of indolent lesions, aiding tumor characterization, and facilitating earlier family discussions and treatment planning.
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Affiliation(s)
- Karen Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Simrandip K Gill
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Niloufar Zarinabad
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Paul Davies
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Martin English
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Daniel Ford
- Department of Clinical Oncology, Queen Elizabeth Hospital, Birmingham, UK
| | - Lesley MacPherson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Radiology, Birmingham Children's Hospital, Birmingham, UK
| | - Ina Nicklaus-Wollenteit
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Histopathology, Birmingham Children's Hospital, Birmingham, UK
| | - Adam Oates
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Radiology, Birmingham Children's Hospital, Birmingham, UK
| | - Guirish Solanki
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Neurosurgery, Birmingham Children's Hospital, Birmingham, UK
| | - Jenny Adamski
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Martin Wilson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,School of Psychology, University of Birmingham, Birmingham, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Department of Pediatric Oncology, Birmingham Children's Hospital, Birmingham, UK
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25
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Sakata A, Fushimi Y, Okada T, Arakawa Y, Kunieda T, Minamiguchi S, Kido A, Sakashita N, Miyamoto S, Togashi K. Diagnostic performance between contrast enhancement, proton MR spectroscopy, and amide proton transfer imaging in patients with brain tumors. J Magn Reson Imaging 2017; 46:732-739. [PMID: 28252822 DOI: 10.1002/jmri.25597] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 11/28/2016] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To explore the relationship among parameters of magnetic resonance spectroscopy (MRS) and amide proton transfer (APT) imaging, and to assess the diagnostic performance of MRS and APT imaging for grading brain tumors in comparison with contrast enhancement of conventional MRI for preoperative grading in patients with brain tumor. MATERIALS AND METHODS Institutional Review Board approval and written informed consent were obtained. Forty-one patients with suspected brain tumors were enrolled in the study. Single-voxel MRS and 2D APT imaging of the same slice level were conducted using a 3T MRI scanner. Positive or negative contrast enhancement on T1 -weighted images was assessed by two neuroradiologists. Correlations among metabolite concentrations, metabolite ratios, and calculated histogram parameters, including mean APT (APTmean ) and the 90th percentile of APT (APT90 ) were assessed using Spearman's correlation coefficient. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for contrast enhancement and MRS and APT imaging. Values of P < 0.05 were considered statistically significant. RESULTS Positive correlations with statistical significance were found between total concentration of choline (Cho) and APT90 (r = 0.49), and between Cho/creatine (Cr) and APTmean (r = 0.65) as well as APT90 (r = 0.49). A negative correlation with statistical significance was observed between NAA/Cr and APTmean (r = -0.52). According to ROC curves, Cho/Cr, APTmean , APT90 , demonstrated higher area under the curve (AUC) values than that of contrast enhancement in grading gliomas. CONCLUSION Significant correlations were observed between metabolite concentrations and ratios on MRS and APT values. MRS and APT imaging showed comparable diagnostic capability for grading brain tumors, suggesting that both MRS and APT imaging offer potential for quantitatively assessing similar biological characteristics in brain tumors on noncontrast MRI. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:732-739.
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Affiliation(s)
- Akihiko Sakata
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Yasutaka Fushimi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Tomohisa Okada
- Kyoto University Graduate School of Medicine, Human Brain Research Center, Kyoto, Japan
| | - Yoshiki Arakawa
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Takeharu Kunieda
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Sachiko Minamiguchi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Pathology, Kyoto, Japan
| | - Aki Kido
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Naotaka Sakashita
- Toshiba Medical Systems Corporations, MRI Systems Development Department, Otawara, Japan
| | - Susumu Miyamoto
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Kaori Togashi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
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Gottschalk M, Troprès I, Lamalle L, Grand S, Le Bas JF, Segebarth C. Refined modelling of the short-T2 signal component and ensuing detection of glutamate and glutamine in short-TE, localised, (1) H MR spectra of human glioma measured at 3 T. NMR IN BIOMEDICINE 2016; 29:943-951. [PMID: 27197077 DOI: 10.1002/nbm.3548] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Revised: 03/22/2016] [Accepted: 04/07/2016] [Indexed: 06/05/2023]
Abstract
Short-TE (1) H MRS has great potential for brain cancer diagnostics. A major difficulty in the analysis of the spectra is the contribution from short-T2 signal components, mainly coming from mobile lipids. This complicates the accurate estimation of the spectral parameters of the resonance lines from metabolites, so that a qualitative to semi-quantitative interpretation of the spectra dominates in practice. One solution to overcome this difficulty is to measure and estimate the short-T2 signal component and to subtract it from the total signal, thus leaving only the metabolite signals. The technique works well when applied to spectra obtained from healthy individuals, but requires some optimisation during data acquisition. In the clinical setting, time constraints hardly allow this. Here, we propose an iterative estimation of the short-T2 signal component, acquired in a single acquisition after measurement of the full spectrum. The method is based on QUEST (quantitation based on quantum estimation) and allows the refinement of the estimate of the short-T2 signal component after measurement. Thus, acquisition protocols used on healthy volunteers can also be used on patients without further optimisation. The aim is to improve metabolite detection and, ultimately, to enable the estimation of the glutamine and glutamate signals distinctly. These two metabolites are of great interest in the characterisation of brain cancer, gliomas in particular. When applied to spectra from healthy volunteers, the new algorithm yields similar results to QUEST and direct subtraction of the short-T2 signal component. With patients, up to 12 metabolites and, at least, seven can be quantified in each individual brain tumour spectrum, depending on the metabolic state of the tumour. The refinement of the short-T2 signal component significantly improves the fitting procedure and produces a separate short-T2 signal component that can be used for the analysis of mobile lipid resonances. Thus, in brain tumour spectra, distinct estimates of signals from glutamate and glutamine are possible. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
| | - Irène Troprès
- Univ. Grenoble Alpes, IRMaGe, CNRS, UMR 3552, INSERM, US17 and CLUNI, CHU de Grenoble, IRMaGe, F-38000, Grenoble, France
| | - Laurent Lamalle
- Univ. Grenoble Alpes, IRMaGe, CNRS, UMR 3552, INSERM, US17 and CLUNI, CHU de Grenoble, IRMaGe, F-38000, Grenoble, France
| | - Sylvie Grand
- Université des Alpes Grenoble 1, Grenoble Institut des Neurosciences, Equipe 5, Clinique Universitaire de Neuroradiologie et IRM (CLUNI) and Centre Hospitalier Universitaire de Grenoble et des Alpes (CHUGA), Grenoble, France
| | - Jean-François Le Bas
- Université des Alpes Grenoble 1, Grenoble Institut des Neurosciences, Equipe 5, Clinique Universitaire de Neuroradiologie et IRM (CLUNI) and Centre Hospitalier Universitaire de Grenoble et des Alpes (CHUGA), Grenoble, France
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27
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Xu YJ, Cui Y, Li HX, Shi WQ, Li FY, Wang JZ, Zeng QS. Noninvasive evaluation of radiation-enhanced glioma cells invasiveness by ultra-high-field (1)H-MRS in vitro. Magn Reson Imaging 2016; 34:1121-7. [PMID: 27215950 DOI: 10.1016/j.mri.2016.05.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2016] [Accepted: 05/16/2016] [Indexed: 01/30/2023]
Abstract
INTRODUCTION Glioma is the most common type of the primary CNS tumor. Radiotherapy is an important treatment measure after surgery. However, its highly invasive character is the main reason of postoperative recurrence. The aim of the study was to probe the correlation between the invasion ability and the metabolite characteristics of glioma cells at the cellular level after irradiation by using 14.7T high-resolution nuclear proton magnetic resonance spectroscopy ((1)H-MRS). METHODS To determine the matrix metalloproteinase-2 (MMP-2) activity and metabolite ratios of glioma cells after irradiation with different doses of X-rays, U87 and C6 glioma cells were exposed to X-ray irradiation of 0, 1, 5, 10, and 15Gy. After 20h, the perchloric acid (PCA) extraction method was used to evaluate water-soluble metabolites [choline (Cho), creatine (Cr), and N-acetylaspartate (NAA)], and (1)H-MRS patterns and changes in metabolite ratios were observed in vitro by 14.7T high resolution (1)H-MRS. Matrigel invasion assays and gelatin zymography were performed to test the invasion ability of U87 and C6 glioma cells. RESULTS Good MR spectra were obtained from PCA method extracts of U87 and C6 glioma cells. Both radiation-induced MMP-2 activity and the Cho/Cr and Cho/NAA ratios increased after irradiation, and their increase occurred in a dose-dependent manner. The MMP-2 activity and the Cho/Cr and Cho/NAA ratios of glioma cells increased after irradiation up to 10Gy and decreased thereafter. In particular, the Cho/NAA ratio of U87 cells increased from 3.55±0.06 (0Gy) to 9.13±0.30 (10Gy) and then declined to 5.94±0.15 (15Gy). Furthermore, the invasion ability of glioma cells had a strong positive correlation with the Cho/Cr and Cho/NAA ratios. Both the Cho/Cr ratio and the Cho/NAA ratio of U87 glioma cells were highly positively correlated with the number of invading cells in the Matrigel invasion assay. The Pearson's correlation coefficient (r) values of U87 cells were 0.89 (Cho/Cr ratio versus invasion ability) and 0.91 (Cho/NAA ratio versus invasion ability) (P<0.01). C6 cells exhibited similar changes to those of U87 cells. CONCLUSIONS In vitro high-resolution (1)H-MRS is useful for detecting glioma invasiveness at the cellular level.
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Affiliation(s)
- Yan-Jie Xu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Yi Cui
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Hong-Xia Li
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Wen-Qi Shi
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Fu-Yan Li
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Jian-Zheng Wang
- Department of Radiotherapy, Qilu Hospital of Shandong University, Jinan, China
| | - Qing-Shi Zeng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
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Carrera I, Richter H, Beckmann K, Meier D, Dennler M, Kircher PR. Evaluation of intracranial neoplasia and noninfectious meningoencephalitis in dogs by use of short echo time, single voxel proton magnetic resonance spectroscopy at 3.0 Tesla. Am J Vet Res 2016; 77:452-62. [DOI: 10.2460/ajvr.77.5.452] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Automated Quality Control for Proton Magnetic Resonance Spectroscopy Data Using Convex Non-negative Matrix Factorization. BIOINFORMATICS AND BIOMEDICAL ENGINEERING 2016. [DOI: 10.1007/978-3-319-31744-1_62] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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30
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Ratai EM, Gilberto González R. Clinical magnetic resonance spectroscopy of the central nervous system. HANDBOOK OF CLINICAL NEUROLOGY 2016; 135:93-116. [PMID: 27432661 DOI: 10.1016/b978-0-444-53485-9.00005-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Proton magnetic resonance spectroscopy (1H MRS) is a noninvasive imaging technique that can easily be added to the conventional magnetic resonance (MR) imaging sequences. Using MRS one can directly compare spectra from pathologic or abnormal tissue and normal tissue. Metabolic changes arising from pathology that can be visualized by MRS may not be apparent from anatomy that can be visualized by conventional MR imaging. In addition, metabolic changes may precede anatomic changes. Thus, MRS is used for diagnostics, to observe disease progression, monitor therapeutic treatments, and to understand the pathogenesis of diseases. MRS may have an important impact on patient management. The purpose of this chapter is to provide practical guidance in the clinical application of MRS of the brain. This chapter provides an overview of MRS-detectable metabolites and their significance. In addition some specific current clinical applications of MRS will be discussed, including brain tumors, inborn errors of metabolism, leukodystrophies, ischemia, epilepsy, and neurodegenerative diseases. The chapter concludes with technical considerations and challenges of clinical MRS.
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Affiliation(s)
- Eva-Maria Ratai
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, and Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA.
| | - R Gilberto González
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, and Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA
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31
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Julià-Sapé M, Griffiths JR, Tate AR, Howe FA, Acosta D, Postma G, Underwood J, Majós C, Arús C. Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes. NMR IN BIOMEDICINE 2015; 28:1772-1787. [PMID: 26768492 DOI: 10.1002/nbm.3439] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Revised: 07/15/2015] [Accepted: 10/01/2015] [Indexed: 06/05/2023]
Abstract
The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection of MR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra from brain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future.
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Affiliation(s)
- Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | | | - A Rosemary Tate
- School of Informatics, University of Sussex, Falmer, Brighton, UK
| | - Franklyn A Howe
- Cardiovascular and Cell Sciences Research Institute, St George's, University of London, London, UK
| | - Dionisio Acosta
- CHIME, University College London, The Farr Institute of Health Informatics Research, London, UK
| | - Geert Postma
- Radboud University Nijmegen, Institute for Molecules and Materials, Analytical Chemistry, Nijmegen, The Netherlands
| | | | - Carles Majós
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Institut de Diagnòstic per la Imatge (IDI), CSU de Bellvitge, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
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Macnaught G, Ananthakrishnan G, Hinksman L, Yadavali R, Bryden F, Lassman S, Ritchie M, Gallacher K, Hay C, Moss JG. Can 1H MR Spectroscopy be Used to Assess the Success of Uterine Artery Embolisation? Cardiovasc Intervent Radiol 2015; 39:376-84. [DOI: 10.1007/s00270-015-1179-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Accepted: 07/04/2015] [Indexed: 12/26/2022]
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Shiroishi MS, Panigrahy A, Moore KR, Nelson MD, Gilles FH, Gonzalez-Gomez I, Blüml S. Combined MRI and MRS improves pre-therapeutic diagnoses of pediatric brain tumors over MRI alone. Neuroradiology 2015; 57:951-6. [PMID: 26141852 DOI: 10.1007/s00234-015-1553-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 06/22/2015] [Indexed: 11/25/2022]
Abstract
INTRODUCTION The specific goal of this study was to determine whether the inclusion of MRS had a measureable and positive impact on the accuracy of pre-surgical MR examinations of untreated pediatric brain tumors over that of MRI alone in clinical practice. METHODS Final imaging reports of 120 pediatric patients with newly detected brain tumors who underwent combined MRI/MRS examinations were retrospectively reviewed. Final pathology was available in all cases. Group A comprised 60 subjects studied between June 2001 and January 2005, when MRS was considered exploratory and radiologists utilized only conventional MRI to arrive at a diagnosis. For group B, comprising 60 subjects studied between January 2005 and March 2008, the radiologists utilized information from both MRI and MRS. Furthermore, radiologists revisited group A (blind review, time lapse >4 years) to determine whether the additional information from MRS would have altered their interpretation. RESULTS Sixty-three percent of patients in group A were diagnosed correctly, whereas in 10% the report was partially correct with the final tumor type mentioned (but not mentioned as most likely tumor), while in 27% of cases the reports were wrong. For group B, the diagnoses were correct in 87%, partially correct in 5%, and incorrect in 8% of the cases, which is a significant improvement (p < 0.005). Re-review of combined MRI and MRS of group A resulted 87% correct, 7% partially correct, and 7% incorrect diagnoses, which is a significant improvement over the original diagnoses (p < 0.05). CONCLUSION Adding MRS to conventional MRI significantly improved diagnostic accuracy in preoperative pediatric patients with untreated brain tumors.
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Affiliation(s)
- Mark S Shiroishi
- Department of Radiology, Children's Hospital Los Angeles/Keck School of Medicine of USC, MS 81, 4650 Sunset Boulevard, Los Angeles, CA, 90027, USA
| | - Ashok Panigrahy
- Department of Radiology, Children's Hospital Los Angeles/Keck School of Medicine of USC, MS 81, 4650 Sunset Boulevard, Los Angeles, CA, 90027, USA
- Department of Pediatric Radiology, Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Kevin R Moore
- Department of Radiology, Primary Children's Medical Center, Salt Lake City, UT, USA
| | - Marvin D Nelson
- Department of Radiology, Children's Hospital Los Angeles/Keck School of Medicine of USC, MS 81, 4650 Sunset Boulevard, Los Angeles, CA, 90027, USA
| | - Floyd H Gilles
- Department of Pathology, Children's Hospital Los Angeles/Keck School of Medicine of USC, Los Angeles, CA, USA
| | | | - Stefan Blüml
- Department of Radiology, Children's Hospital Los Angeles/Keck School of Medicine of USC, MS 81, 4650 Sunset Boulevard, Los Angeles, CA, 90027, USA.
- Rudi Schulte Research Institute, Santa Barbara, CA, USA.
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Abstract
Advanced MR imaging techniques have found extensive utility in the clinical practice of neuroradiology. A variety of these techniques are incorporated into imaging protocols for routine use, specific applications to particular disease entities, or as problem-solving tools on an ad hoc basis. This article summarizes and illustrates the spectrum of advanced MR imaging tools used clinically in the practice of neuroradiology.
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Delgado-Goñi T, Julià-Sapé M, Candiota AP, Pumarola M, Arús C. Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma. NMR IN BIOMEDICINE 2014; 27:1333-1345. [PMID: 25208348 DOI: 10.1002/nbm.3194] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2014] [Revised: 07/24/2014] [Accepted: 07/27/2014] [Indexed: 06/03/2023]
Abstract
Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.
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Affiliation(s)
- Teresa Delgado-Goñi
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain; Cancer Research UK and EPSRC Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK
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Raschke F, Jones TL, Barrick TR, Howe FA. Delineation of gliomas using radial metabolite indexing. NMR IN BIOMEDICINE 2014; 27:1053-1062. [PMID: 25042619 DOI: 10.1002/nbm.3154] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2013] [Revised: 05/18/2014] [Accepted: 05/20/2014] [Indexed: 06/03/2023]
Abstract
(1) H MRSI has demonstrated the ability to characterise and delineate brain tumours, but robust data analysis methods are still needed. In this study, we present an objective analysis method for MRSI data to delineate tumour abnormality regions. The presented method is a development of the choline-to-N-acetylaspartate index (CNI), which uses perpendicular distances in a choline versus N-acetylaspartate plot as a measure of abnormality. We propose a radial CNI (rCNI) method that uses the choline to N-acetylaspartate ratio directly as an abnormality measure. To avoid problems with small or zero denominators, we perform an arctangent transformation. CNI abnormality contours were evaluated using a z-score threshold of 2 (CNI2) and 2.5 (CNI2.5) and compared with rCNI2. Simulations modelling low-grade (LGG) and high-grade (HGG) gliomas with different tissue compartments and partial volume effects suggest improved specificity of rCNI2 (LGG 92%/HGG 91%) over CNI2 (LGG 69%/HGG 69%) and CNI2.5 (LGG 74%/HGG 75%), whilst retaining a similar sensitivity to both CNI2 and CNI2.5. Our simulation results also confirm a previously reported increase in specificity of CNI2.5 over CNI2 with little penalty in sensitivity. The analysis of MRSI data acquired from 10 patients with low-grade glioma at 3 T suggests a more robust delineation of the lesions using rCNI with respect to conventional imaging compared with standard CNI. Further analysis of 29 glioma datasets acquired at 1.5 T, together with previously published estimated tumour proportions, suggests that rCNI has higher sensitivity and specificity for the identification of abnormal MRSI voxels.
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Affiliation(s)
- F Raschke
- Neurosciences Research Centre, Cardiovascular and Cell Sciences Institute, St George's, University of London, London, UK
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Julià-Sapé M, Majós C, Camins À, Samitier A, Baquero M, Serrallonga M, Doménech S, Grivé E, Howe FA, Opstad K, Calvar J, Aguilera C, Arús C. Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification. NMR IN BIOMEDICINE 2014; 27:1009-1018. [PMID: 25042391 DOI: 10.1002/nbm.3144] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2013] [Revised: 04/14/2014] [Accepted: 05/03/2014] [Indexed: 06/03/2023]
Abstract
In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.0), with a short-TE classifier, provided the best results. Since then, the DSS evolved into a version 2.0 that contains an additional long-TE classifier. This study has two objectives. First, to determine whether clinicians with no experience of spectroscopy are comparable with spectroscopists in the use of the system, when only minimum training in the use of the system was given. Second, to assess whether or not a version with another TE is better than the initial version. We undertook a second study with the same cases and nine evaluators to assess whether the diagnostic accuracy of DSS 2.0 was comparable with the values obtained with DSS 1.0. In the second study, the analysis protocol was flexible in comparison with the first one to mimic a clinical environment. In the present study, on average, each case required 5.4 min by neuroradiologists and 9 min by spectroscopists for evaluation. Most classes and superclasses of tumours gave the same results as with DSS 1.0, except for astrocytomas of World Health Organization (WHO) grade III, in which performance measured as the area under the curve (AUC) decreased: AUC = 0.87 (0.72-1.02) with DSS 1.0 and AUC = 0.62 (0.55-0.70) with DSS 2.0. When analysing the performance of radiologists and spectroscopists with respect to DSS 1.0, the results were the same for most classes. Having data with two TEs instead of one did not affect the results of the evaluation.
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Affiliation(s)
- Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain; Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, UAB, Cerdanyola del Vallès, Spain; Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, UAB, Cerdanyola del Vallès, Spain
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Chaumeil MM, Larson PEZ, Woods SM, Cai L, Eriksson P, Robinson AE, Lupo JM, Vigneron DB, Nelson SJ, Pieper RO, Phillips JJ, Ronen SM. Hyperpolarized [1-13C] glutamate: a metabolic imaging biomarker of IDH1 mutational status in glioma. Cancer Res 2014; 74:4247-57. [PMID: 24876103 DOI: 10.1158/0008-5472.can-14-0680] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Mutations of the isocitrate dehydrogenase 1 (IDH1) gene are among the most prevalent in low-grade glioma and secondary glioblastoma, represent an early pathogenic event, and are associated with epigenetically driven modulations of metabolism. Of particular interest is the recently uncovered relationship between the IDH1 mutation and decreased activity of the branched-chain amino acid transaminase 1 (BCAT1) enzyme. Noninvasive imaging methods that can assess BCAT1 activity could therefore improve detection of mutant IDH1 tumors and aid in developing and monitoring new targeted therapies. BCAT1 catalyzes the transamination of branched-chain amino acids while converting α-ketoglutarate (α-KG) to glutamate. Our goal was to use (13)C magnetic resonance spectroscopy to probe the conversion of hyperpolarized [1-(13)C] α-KG to hyperpolarized [1-(13)C] glutamate as a readout of BCAT1 activity. We investigated two isogenic glioblastoma lines that differed only in their IDH1 status and performed experiments in live cells and in vivo in rat orthotopic tumors. Following injection of hyperpolarized [1-(13)C] α-KG, hyperpolarized [1-(13)C] glutamate production was detected both in cells and in vivo, and the level of hyperpolarized [1-(13)C] glutamate was significantly lower in mutant IDH1 cells and tumors compared with their IDH1-wild-type counterparts. Importantly however, in our cells the observed drop in hyperpolarized [1-(13)C] glutamate was likely mediated not only by a drop in BCAT1 activity, but also by reductions in aspartate transaminase and glutamate dehydrogenase activities, suggesting additional metabolic reprogramming at least in our model. Hyperpolarized [1-(13)C] glutamate could thus inform on multiple mutant IDH1-associated metabolic events that mediate reduced glutamate production.
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Affiliation(s)
| | | | | | - Larry Cai
- Departments of Radiology and Biomedical Imaging
| | | | - Aaron E Robinson
- Pathology, and Neurological Surgery, Helen Diller Research Center; and Brain Tumor Research Center, University of California San Francisco, San Francisco, California
| | | | | | | | - Russell O Pieper
- Neurological Surgery, Helen Diller Research Center; and Brain Tumor Research Center, University of California San Francisco, San Francisco, California
| | - Joanna J Phillips
- Pathology, and Neurological Surgery, Helen Diller Research Center; and Brain Tumor Research Center, University of California San Francisco, San Francisco, California
| | - Sabrina M Ronen
- Departments of Radiology and Biomedical Imaging, Brain Tumor Research Center, University of California San Francisco, San Francisco, California
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Tsolaki E, Kousi E, Svolos P, Kapsalaki E, Theodorou K, Kappas C, Tsougos I. Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques. World J Radiol 2014; 6:72-81. [PMID: 24778769 PMCID: PMC4000611 DOI: 10.4329/wjr.v6.i4.72] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Revised: 01/23/2014] [Accepted: 03/18/2014] [Indexed: 02/06/2023] Open
Abstract
In recent years, advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy, diffusion weighted imaging, diffusion tensor imaging and perfusion weighted imaging have been used in order to resolve demanding diagnostic problems such as brain tumor characterization and grading, as these techniques offer a more detailed and non-invasive evaluation of the area under study. In the last decade a great effort has been made to import and utilize intelligent systems in the so-called clinical decision support systems (CDSS) for automatic processing, classification, evaluation and representation of MRI data in order for advanced MRI techniques to become a part of the clinical routine, since the amount of data from the aforementioned techniques has gradually increased. Hence, the purpose of the current review article is two-fold. The first is to review and evaluate the progress that has been made towards the utilization of CDSS based on data from advanced MRI techniques. The second is to analyze and propose the future work that has to be done, based on the existing problems and challenges, especially taking into account the new imaging techniques and parameters that can be introduced into intelligent systems to significantly improve their diagnostic specificity and clinical application.
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40
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Non-invasive in vivo assessment of IDH1 mutational status in glioma. Nat Commun 2014; 4:2429. [PMID: 24019001 DOI: 10.1038/ncomms3429] [Citation(s) in RCA: 105] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2013] [Accepted: 08/12/2013] [Indexed: 12/19/2022] Open
Abstract
Gain-of-function mutations of the isocitrate dehydrogenase 1 (IDH1) gene are among the most prevalent in low-grade gliomas and secondary glioblastoma. They lead to intracellular accumulation of the oncometabolite 2-hydroxyglutarate, represent an early pathogenic event and are considered a therapeutic target. Here we show, in this proof-of-concept study, that [1-(13)C] α-ketoglutarate can serve as a metabolic imaging agent for non-invasive, real-time, in vivo monitoring of mutant IDH1 activity, and can inform on IDH1 status. Using (13)C magnetic resonance spectroscopy in combination with dissolution dynamic nuclear polarization, the metabolic fate of hyperpolarized [1-(13)C] α-ketoglutarate is studied in isogenic glioblastoma cells that differ only in their IDH1 status. In lysates and tumours that express wild-type IDH1, only hyperpolarized [1-(13)C] α-ketoglutarate can be detected. In contrast, in cells that express mutant IDH1, hyperpolarized [1-(13)C] 2-hydroxyglutarate is also observed, both in cell lysates and in vivo in orthotopic tumours.
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41
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Öz G, Alger JR, Barker PB, Bartha R, Bizzi A, Boesch C, Bolan PJ, Brindle KM, Cudalbu C, Dinçer A, Dydak U, Emir UE, Frahm J, González RG, Gruber S, Gruetter R, Gupta RK, Heerschap A, Henning A, Hetherington HP, Howe FA, Hüppi PS, Hurd RE, Kantarci K, Klomp DWJ, Kreis R, Kruiskamp MJ, Leach MO, Lin AP, Luijten PR, Marjańska M, Maudsley AA, Meyerhoff DJ, Mountford CE, Nelson SJ, Pamir MN, Pan JW, Peet AC, Poptani H, Posse S, Pouwels PJW, Ratai EM, Ross BD, Scheenen TWJ, Schuster C, Smith ICP, Soher BJ, Tkáč I, Vigneron DB, Kauppinen RA. Clinical proton MR spectroscopy in central nervous system disorders. Radiology 2014; 270:658-79. [PMID: 24568703 PMCID: PMC4263653 DOI: 10.1148/radiol.13130531] [Citation(s) in RCA: 464] [Impact Index Per Article: 42.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
A large body of published work shows that proton (hydrogen 1 [(1)H]) magnetic resonance (MR) spectroscopy has evolved from a research tool into a clinical neuroimaging modality. Herein, the authors present a summary of brain disorders in which MR spectroscopy has an impact on patient management, together with a critical consideration of common data acquisition and processing procedures. The article documents the impact of (1)H MR spectroscopy in the clinical evaluation of disorders of the central nervous system. The clinical usefulness of (1)H MR spectroscopy has been established for brain neoplasms, neonatal and pediatric disorders (hypoxia-ischemia, inherited metabolic diseases, and traumatic brain injury), demyelinating disorders, and infectious brain lesions. The growing list of disorders for which (1)H MR spectroscopy may contribute to patient management extends to neurodegenerative diseases, epilepsy, and stroke. To facilitate expanded clinical acceptance and standardization of MR spectroscopy methodology, guidelines are provided for data acquisition and analysis, quality assessment, and interpretation. Finally, the authors offer recommendations to expedite the use of robust MR spectroscopy methodology in the clinical setting, including incorporation of technical advances on clinical units.
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Affiliation(s)
- Gülin Öz
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Jeffry R. Alger
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Peter B. Barker
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Robert Bartha
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Alberto Bizzi
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Chris Boesch
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Patrick J. Bolan
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Kevin M. Brindle
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Cristina Cudalbu
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Alp Dinçer
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Ulrike Dydak
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Uzay E. Emir
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Jens Frahm
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Ramón Gilberto González
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Stephan Gruber
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Rolf Gruetter
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Rakesh K. Gupta
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Arend Heerschap
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Anke Henning
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Hoby P. Hetherington
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Franklyn A. Howe
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Petra S. Hüppi
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Ralph E. Hurd
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Kejal Kantarci
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Dennis W. J. Klomp
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Roland Kreis
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Marijn J. Kruiskamp
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Martin O. Leach
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Alexander P. Lin
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Peter R. Luijten
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Małgorzata Marjańska
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Andrew A. Maudsley
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Dieter J. Meyerhoff
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Carolyn E. Mountford
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Sarah J. Nelson
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - M. Necmettin Pamir
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Jullie W. Pan
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Andrew C. Peet
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Harish Poptani
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Stefan Posse
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Petra J. W. Pouwels
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Eva-Maria Ratai
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Brian D. Ross
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Tom W. J. Scheenen
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Christian Schuster
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Ian C. P. Smith
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Brian J. Soher
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Ivan Tkáč
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
| | - Daniel B. Vigneron
- From the Center for Magnetic Resonance Research, University of Minnesota,
2021 6th St SE, Minneapolis, MN 55455 (G.O.)
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A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data. PLoS One 2013; 8:e83773. [PMID: 24376744 PMCID: PMC3871596 DOI: 10.1371/journal.pone.0083773] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Accepted: 11/08/2013] [Indexed: 11/19/2022] Open
Abstract
Background The clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal. Methodology/Principal Findings Non-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification. Conclusions/Significance We show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing.
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Gill SK, Wilson M, Davies NP, MacPherson L, English M, Arvanitis TN, Peet AC. Diagnosing relapse in children's brain tumors using metabolite profiles. Neuro Oncol 2013; 16:156-64. [PMID: 24305716 DOI: 10.1093/neuonc/not143] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Malignant brain tumors in children generally have a very poor prognosis when they relapse and improvements are required in their management. It can be difficult to accurately diagnose abnormalities detected during tumor surveillance, and new techniques are required to aid this process. This study investigates how metabolite profiles measured noninvasively by (1)H magnetic resonance spectroscopy (MRS) at relapse reflect those at diagnosis and may be used in this monitoring process. METHODS Single-voxel MRS (1.5 T, point-resolved spectroscopy, echo time 30 ms, repetition time 1500 ms was performed on 19 children with grades II-IV brain tumors during routine MRI scans prior to treatment for a suspected brain tumor and at suspected first relapse. MRS was analyzed using TARQUIN software to provide metabolite concentrations. Paired Student's t-tests were performed between metabolite profiles at diagnosis and at first relapse. RESULTS There was no significant difference (P > .05) in the level of any metabolite, lipid, or macromolecule from tumors prior to treatment and at first relapse. This was true for the whole group (n = 19), those with a local relapse (n = 12), and those with a distant relapse (n = 7). Lipids at 1.3 ppm were close to significance when comparing the level at diagnosis with that at distant first relapse (P = .07, 6.5 vs 12.9). In 5 cases the MRS indicative of tumor preceded a formal diagnosis of relapse. CONCLUSIONS Tumor metabolite profiles, measured by MRS, do not change greatly from diagnosis to first relapse, and this can aid the confirmation of the presence of tumor.
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Affiliation(s)
- Simrandip K Gill
- Corresponding author: Andrew C. Peet, MRCPCH, PhD, Institute of Child Health, Clinical Research Block, Whittall Street, Birmingham B4 6NH, UK.
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Sáez C, Martí-Bonmatí L, Alberich-Bayarri A, Robles M, García-Gómez JM. Randomized pilot study and qualitative evaluation of a clinical decision support system for brain tumour diagnosis based on SV ¹H MRS: evaluation as an additional information procedure for novice radiologists. Comput Biol Med 2013; 45:26-33. [PMID: 24480160 DOI: 10.1016/j.compbiomed.2013.11.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2013] [Revised: 11/13/2013] [Accepted: 11/18/2013] [Indexed: 11/28/2022]
Abstract
The results of a randomized pilot study and qualitative evaluation of the clinical decision support system Curiam BT are reported. We evaluated the system's feasibility and potential value as a radiological information procedure complementary to magnetic resonance (MR) imaging to assist novice radiologists in diagnosing brain tumours using MR spectroscopy (1.5 and 3.0T). Fifty-five cases were analysed at three hospitals according to four non-exclusive diagnostic questions. Our results show that Curiam BT improved the diagnostic accuracy in all the four questions. Additionally, we discuss the findings of the users' feedback about the system, and the further work to optimize it for real environments and to conduct a large clinical trial.
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Affiliation(s)
- Carlos Sáez
- Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València Camino de Vera s/n, 46022 Valéncia, Spain.
| | - Luis Martí-Bonmatí
- Department of Radiology, Hospital Quirón Valencia, Valencia, Spain; Radiology, Department of Medicine, Universidad de Valencia, Spain
| | | | - Montserrat Robles
- Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València Camino de Vera s/n, 46022 Valéncia, Spain
| | - Juan M García-Gómez
- Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València Camino de Vera s/n, 46022 Valéncia, Spain
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Shah NJ, Oros-Peusquens AM, Arrubla J, Zhang K, Warbrick T, Mauler J, Vahedipour K, Romanzetti S, Felder J, Celik A, Rota-Kops E, Iida H, Langen KJ, Herzog H, Neuner I. Advances in multimodal neuroimaging: hybrid MR-PET and MR-PET-EEG at 3 T and 9.4 T. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 229:101-115. [PMID: 23317760 DOI: 10.1016/j.jmr.2012.11.027] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2012] [Revised: 11/28/2012] [Accepted: 11/29/2012] [Indexed: 06/01/2023]
Abstract
Multi-modal MR-PET-EEG data acquisition in simultaneous mode confers a number of advantages at 3 T and 9.4 T. The three modalities complement each other well; structural-functional imaging being the domain of MRI, molecular imaging with specific tracers is the strength of PET, and EEG provides a temporal dimension where the other two modalities are weak. The utility of hybrid MR-PET at 3 T in a clinical setting is presented and critically discussed. The potential problems and the putative gains to be accrued from hybrid imaging at 9.4 T, with examples from the human brain, are outlined. Steps on the road to 9.4 T multi-modal MR-PET-EEG are also illustrated. From an MR perspective, the potential for ultra-high resolution structural imaging is discussed and example images of the cerebellum with an isotropic resolution of 320 μm are presented, setting the stage for hybrid imaging at ultra-high field. Further, metabolic imaging is discussed and high-resolution images of the sodium distribution are presented. Examples of tumour imaging on a 3 T MR-PET system are presented and discussed. Finally, the perspectives for multi-modal imaging are discussed based on two on-going studies, the first comparing MR and PET methods for the measurement of perfusion and the second which looks at tumour delineation based on MRI contrasts but the knowledge of tumour extent is based on simultaneously acquired PET data.
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Affiliation(s)
- N Jon Shah
- Institute of Neuroscience and Medicine-4, Research Centre Jülich, 52425 Jülich, Germany.
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Abstract
Imaging is a key component in the management of brain tumours, with MRI being the preferred modality for most clinical scenarios. However, although conventional MRI provides mainly structural information, such as tumour size and location, it leaves many important clinical questions, such as tumour type, aggressiveness and prognosis, unanswered. An increasing number of studies have shown that additional information can be obtained using functional imaging methods (which probe tissue properties), and that these techniques can give key information of clinical importance. These techniques include diffusion imaging, which can assess tissue structure, and perfusion imaging and magnetic resonance spectroscopy, which measures tissue metabolite profiles. Tumour metabolism can also be investigated using PET, with 18F-deoxyglucose being the most readily available tracer. This Review discusses these methods and the studies that have investigated their clinical use. A strong emphasis is placed on the measurement of quantitative parameters, which is a move away from the qualitative nature of conventional radiological reporting and presents major challenges, particularly for multicentre studies.
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Raschke F, Davies NP, Wilson M, Peet AC, Howe FA. Classification of single-voxel 1H spectra of childhood cerebellar tumors using LCModel and whole tissue representations. Magn Reson Med 2012; 70:1-6. [PMID: 22886824 DOI: 10.1002/mrm.24461] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Revised: 07/18/2012] [Accepted: 07/19/2012] [Indexed: 01/13/2023]
Abstract
In this study, mean tumor spectra are used as the basis functions in LCModel to create a direct classification tool for short echo time (1)H magnetic resonance spectroscopy of pediatric brain tumors. LCModel is a widely used analysis tool designed to fit a linear combination of individual metabolite spectra to in vivo spectra. Here, we have used LCModel to fit mean spectra and corresponding variability components of childhood cerebellar tumors, as calculated using principal component analysis, and assessed for classification accuracy. Classification was performed according to the highest estimated tumor proportion. This method was tested in a leave-one-out analysis discriminating between pediatric brain tumor spectra of medulloblastoma vs. pilocytic astrocytoma and medulloblastoma vs. pilocytic astrocytoma vs. ependymoma. Additionally, the effect of accepting different Cramér-Rao Lower Bound cut-off criteria on classification accuracy and estimated tissue proportions was investigated. The best classification results differentiating medulloblastoma vs. pilocytic astrocytoma and medulloblastoma vs. pilocytic astrocytoma vs. ependymoma were 100 and 87.7%, respectively. These results are comparable to a specialized pattern recognition analysis of this data set and give easy to interpret results in the form of estimated tissue proportions. The method requires minimal user input and is easily transferable across sites and to other magnetic resonance spectroscopy classification problems.
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Affiliation(s)
- Felix Raschke
- Division of Clinical Sciences, St. George's University of London, London, UK.
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Neuner I, Kaffanke JB, Langen KJ, Kops ER, Tellmann L, Stoffels G, Weirich C, Filss C, Scheins J, Herzog H, Shah NJ. Multimodal imaging utilising integrated MR-PET for human brain tumour assessment. Eur Radiol 2012; 22:2568-80. [PMID: 22777617 DOI: 10.1007/s00330-012-2543-x] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2012] [Revised: 04/27/2012] [Accepted: 05/09/2012] [Indexed: 10/28/2022]
Abstract
OBJECTIVES The development of integrated magnetic resonance (MR)-positron emission tomography (PET) hybrid imaging opens up new horizons for imaging in neuro-oncology. In cerebral gliomas the definition of tumour extent may be difficult to ascertain using standard MR imaging (MRI) only. The differentiation of post-therapeutic scar tissue, tumour rests and tumour recurrence is challenging. The relationship to structures such as the pyramidal tract to the tumour mass influences the therapeutic neurosurgical approach. METHODS The diagnostic information may be enriched by sophisticated MR techniques such as diffusion tensor imaging (DTI), multiple-volume proton MR spectroscopic imaging (MRSI) and functional MRI (fMRI). Metabolic imaging with PET, especially using amino acid tracers such as (18)F-fluoroethyl-L-tyrosine (FET) or (11)C-L-methionine (MET) will indicate tumour extent and response to treatment. RESULTS The new technologies comprising MR-PET hybrid systems have the advantage of providing comprehensive answers by a one-stop-job of 40-50 min. The combined approach provides data of different modalities using the same iso-centre, resulting in optimal spatial and temporal realignment. All images are acquired exactly under the same physiological conditions. CONCLUSIONS We describe the imaging protocol in detail and provide patient examples for the different imaging modalities such as FET-PET, standard structural imaging (T1-weighted, T2-weighted, T1-weighted contrast agent enhanced), DTI, MRSI and fMRI. KEY POINTS Hybrid MR-PET opens up new horizons in neuroimaging. Hybrid MR-PET allows brain tumour assessment in one stop. Hybrid MR-PET allows simultaneous acquisition of structural, functional and molecular images.
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Affiliation(s)
- Irene Neuner
- Institute of Neuroscience and Medicine 4, INM 4, Forschungszentrum Jülich, 52428, Jülich, Germany.
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McIntyre DJO, Madhu B, Lee SH, Griffiths JR. Magnetic resonance spectroscopy of cancer metabolism and response to therapy. Radiat Res 2012; 177:398-435. [PMID: 22401303 DOI: 10.1667/rr2903.1] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Magnetic resonance spectroscopy allows noninvasive in vivo measurements of biochemical information from living systems, ranging from cultured cells through experimental animals to humans. Studies of biopsies or extracts offer deeper insights by detecting more metabolites and resolving metabolites that cannot be distinguished in vivo. The pharmacokinetics of certain drugs, especially fluorinated drugs, can be directly measured in vivo. This review briefly describes these methods and their applications to cancer metabolism, including glycolysis, hypoxia, bioenergetics, tumor pH, and tumor responses to radiotherapy and chemotherapy.
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Affiliation(s)
- Dominick J O McIntyre
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
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