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Keller DS, Kimura CMS, Kin CJ, Chu DI, Smith BP, Dhala A, Arrington AK, Clark CJ, Winslow ER, Al-Refaie WB, Khaitan PG. Society for Surgery of the Alimentary Tract State-of-the-Art Session 2022: Frailty in Surgery. J Gastrointest Surg 2024; 28:158-163. [PMID: 38445937 DOI: 10.1016/j.gassur.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2023] [Revised: 10/25/2023] [Accepted: 10/28/2023] [Indexed: 03/07/2024]
Abstract
Given the exponentially aging population and rising life expectancy in the United States, surgeons are facing a challenging frail population who may require surgery but may not qualify based on their general fitness. There is an urgent need for greater awareness of the importance of frailty measurement and the implementation of universal assessment of frail patients into clinical practice. Pairing risk stratification with stringent protocols for prehabilitation and minimally invasive surgery and appropriate enhanced recovery protocols could optimize and condition frail patients before, during, and immediately after surgery to mitigate postoperative complications and consequences on patient function and quality of life. In this paper, highlights from the 2022 Society for Surgery of the Alimentary Tract State-of-the-Art Session on frailty in surgery are presented. This work aims to improve the understanding of the impact of frailty on patients and the methods used to augment the outcomes for frail patients during their surgical experience.
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Affiliation(s)
- Deborah S Keller
- Lankenau Medical Center and Lankenau Institute for Medical Research, Mainline Health, Wynnewood, PA, United States.
| | - Cintia M S Kimura
- Division of Colorectal Surgery, Department of Surgery, Stanford University, Palo Alto, CA, United States
| | - Cindy J Kin
- Division of Colorectal Surgery, Department of Surgery, Stanford University, Palo Alto, CA, United States
| | - Daniel I Chu
- Department of Surgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Burke P Smith
- Department of Surgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Atiya Dhala
- Department of Surgery, Houston Methodist Hospital, Houston, TX, United States
| | - Amanda K Arrington
- Department of Surgery, Houston Methodist Hospital, Houston, TX, United States
| | - Clancy J Clark
- Division of Surgical Oncology, Department of Surgery, Wake Forest University Baptist Health Medical Center, Winston-Salem, NC, United States
| | - Emily R Winslow
- Department of Surgery, Medstar Georgetown Medical Center, Washington, DC, United States
| | - Waddah B Al-Refaie
- Department of Surgery, Creighton School of Medicine and Catholic Health Initiatives Health Clinic, Omaha, NE, United States
| | - Puja G Khaitan
- Department of Thoracic Surgery, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates
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Fennessy FM, Maier SE. Quantitative diffusion MRI in prostate cancer: Image quality, what we can measure and how it improves clinical assessment. Eur J Radiol 2023; 167:111066. [PMID: 37651828 PMCID: PMC10623580 DOI: 10.1016/j.ejrad.2023.111066] [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: 07/05/2023] [Revised: 08/19/2023] [Accepted: 08/24/2023] [Indexed: 09/02/2023]
Abstract
Diffusion-weighted imaging is a dependable method for detection of clinically significant prostate cancer. In prostate tissue, there are several compartments that can be distinguished from each other, based on different water diffusion decay signals observed. Alterations in cell architecture, such as a relative increase in tumor infiltration and decrease in stroma, will influence the observed diffusion signal in a voxel due to impeded random motion of water molecules. The amount of restricted diffusion can be assessed quantitatively by measuring the apparent diffusion coefficient (ADC) value. This is traditionally calculated using a monoexponential decay formula represented by the slope of a line produced between the logarithm of signal intensity decay plotted against selected b-values. However, the choice and number of b-values and their distribution, has a significant effect on the measured ADC values. There have been many models that attempt to use higher-order functions to better describe the observed diffusion signal decay, requiring an increased number and range of b-values. While ADC can probe heterogeneity on a macroscopic level, there is a need to optimize advanced diffusion techniques to better interrogate prostate tissue microstructure. This could be of benefit in clinical challenges such as identifying sparse tumors in normal prostate tissue or better defining tumor margins. This paper reviews the principles of diffusion MRI and novel higher order diffusion signal analysis techniques to improve the detection of prostate cancer.
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Affiliation(s)
- Fiona M Fennessy
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
| | - Stephan E Maier
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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Li C, Deng M, Zhong X, Ren J, Chen X, Chen J, Xiao F, Xu H. Multi-view radiomics and deep learning modeling for prostate cancer detection based on multi-parametric MRI. Front Oncol 2023; 13:1198899. [PMID: 37448515 PMCID: PMC10338012 DOI: 10.3389/fonc.2023.1198899] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 06/08/2023] [Indexed: 07/15/2023] Open
Abstract
Introduction This study aims to develop an imaging model based on multi-parametric MR images for distinguishing between prostate cancer (PCa) and prostate hyperplasia. Methods A total of 236 subjects were enrolled and divided into training and test sets for model construction. Firstly, a multi-view radiomics modeling strategy was designed in which different combinations of radiomics feature categories (original, LoG, and wavelet) were compared to obtain the optimal input feature sets. Minimum-redundancy maximum-relevance (mRMR) selection and least absolute shrinkage selection operator (LASSO) were used for feature reduction, and the next logistic regression method was used for model construction. Then, a Swin Transformer architecture was designed and trained using transfer learning techniques to construct the deep learning models (DL). Finally, the constructed multi-view radiomics and DL models were combined and compared for model selection and nomogram construction. The prediction accuracy, consistency, and clinical benefit were comprehensively evaluated in the model comparison. Results The optimal input feature set was found when LoG and wavelet features were combined, while 22 and 17 radiomic features in this set were selected to construct the ADC and T2 multi-view radiomic models, respectively. ADC and T2 DL models were built by transferring learning from a large number of natural images to a relatively small sample of prostate images. All individual and combined models showed good predictive accuracy, consistency, and clinical benefit. Compared with using only an ADC-based model, adding a T2-based model to the combined model would reduce the model's predictive performance. The ADCCombinedScore model showed the best predictive performance among all and was transformed into a nomogram for better use in clinics. Discussion The constructed models in our study can be used as a predictor in differentiating PCa and BPH, thus helping clinicians make better clinical treatment decisions and reducing unnecessary prostate biopsies.
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Affiliation(s)
- Chunyu Li
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ming Deng
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaoli Zhong
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Jinxia Ren
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaohui Chen
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | | | - Feng Xiao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Klingebiel M, Weiland E, Boschheidgen M, Ullrich T, Arsov C, Radtke JP, Benkert T, Nickel M, Strecker R, Wittsack HJ, Albers P, Antoch G, Schimmöller L. Improved diffusion-weighted imaging of the prostate: Comparison of readout-segmented and zoomed single-shot imaging. Magn Reson Imaging 2023; 98:55-61. [PMID: 36649807 DOI: 10.1016/j.mri.2023.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 01/12/2023] [Accepted: 01/12/2023] [Indexed: 01/15/2023]
Abstract
OBJECTIVES Diffusion weighted imaging (DWI) is the most important sequence for detection and grading prostate cancer (PCa), but it is considerably prone to artifacts. New approaches like zoomed single-shot imaging (z-EPI) with advanced image processing or multi-shot readout segmentation (rs-EPI) try to improve DWI quality. This study evaluates objective and subjective image quality (IQ) of rs-EPI and z-EPI with and without advanced processing. MATERIALS AND METHODS Fifty-six consecutive patients (67 ± 8 years; median PSA 8.3 ng/ml) with mp-MRI performed at 3 Tesla between February and October 2019 and subsequently verified PCa by targeted plus systematic MRI/US-fusion biopsy were included in this retrospective single center cohort study. Rs-EPI and z-EPI were prospectively acquired in every patient. Signal intensities (SI) of PCa and benign tissue in ADC, b1000, and calculated high b-value images were analyzed. Endpoints were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), PCa contrast intensity (CI), and subjective IQ on a 5-point scale evaluated by three blinded readers. Wilcoxon signed rank test, Friedman test and Cohen's kappa coefficient was calculated. RESULTS SNR, CNR, and PCa CI of z-EPI with and without advanced processing was superior to rs-EPI (p < 0.01), whereas no significant differences were observed between z-EPI with and without advanced processing. Subjective IQ was significantly higher for z-EPI with advanced processing compared rs-EPI for ADC, b1000, and calculated high b-values (p < 0.01). Compared to z-EPI without advanced processing, z-EPI with advanced processing was superior for ADC and calculated high b-values (p < 0.01), but no significant differences were shown for b1000 images. CONCLUSIONS Z-EPI with and without advanced processing was superior to rs-EPI regarding objective imaging parameters and z-EPI with advanced processing was superior to rs-EPI regarding subjective imaging parameters for the detection of PCa.
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Affiliation(s)
- M Klingebiel
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - E Weiland
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany.
| | - M Boschheidgen
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - T Ullrich
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - C Arsov
- University Dusseldorf, Medical Faculty, Department of Urology, D-40225 Dusseldorf, Germany.
| | - J P Radtke
- University Dusseldorf, Medical Faculty, Department of Urology, D-40225 Dusseldorf, Germany.
| | - T Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany.
| | - M Nickel
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany.
| | - R Strecker
- Siemens Healthcare GmbH, Europe, Middle East & Africa, Karlheinz-Kaske-Str. 2, 91052 Erlangen, Germany.
| | - H J Wittsack
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - P Albers
- University Dusseldorf, Medical Faculty, Department of Urology, D-40225 Dusseldorf, Germany.
| | - G Antoch
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
| | - L Schimmöller
- University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, D-40225 Dusseldorf, Germany.
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Sen S, Valindria V, Slator PJ, Pye H, Grey A, Freeman A, Moore C, Whitaker H, Punwani S, Singh S, Panagiotaki E. Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models. Diagnostics (Basel) 2022; 12:1631. [PMID: 35885536 PMCID: PMC9319485 DOI: 10.3390/diagnostics12071631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 06/29/2022] [Accepted: 07/02/2022] [Indexed: 11/16/2022] Open
Abstract
False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.
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Affiliation(s)
- Snigdha Sen
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Vanya Valindria
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Paddy J. Slator
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Hayley Pye
- Molecular Diagnostics and Therapeutics Group, University College London, London WC1E 6BT, UK; (H.P.); (H.W.)
| | - Alistair Grey
- Department of Urology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK; (A.G.); (C.M.)
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK;
| | - Caroline Moore
- Department of Urology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK; (A.G.); (C.M.)
| | - Hayley Whitaker
- Molecular Diagnostics and Therapeutics Group, University College London, London WC1E 6BT, UK; (H.P.); (H.W.)
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London WC1E 6BT, UK; (S.P.); (S.S.)
| | - Saurabh Singh
- Centre for Medical Imaging, University College London, London WC1E 6BT, UK; (S.P.); (S.S.)
| | - Eleftheria Panagiotaki
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
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Lundholm L, Montelius M, Jalnefjord O, Forssell-Aronsson E, Ljungberg M. VERDICT MRI for radiation treatment response assessment in neuroendocrine tumors. NMR IN BIOMEDICINE 2022; 35:e4680. [PMID: 34957637 DOI: 10.1002/nbm.4680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 12/09/2021] [Accepted: 12/10/2021] [Indexed: 06/14/2023]
Abstract
Noninvasive methods to study changes in tumor microstructure enable early assessment of treatment response and thus facilitate personalized treatment. The aim of this study was to evaluate the diffusion MRI model, Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT), for early response assessment to external radiation treatment and to compare the results with those of more studied sets of parameters derived from diffusion-weighted MRI data. Mice xenografted with human small intestine tumors were treated with external radiation treatment, and diffusion MRI experiments were performed on the day before and up to 2 weeks after treatment. The diffusion models VERDICT, ADC, IVIM, and DKI were fitted to MRI data, and the treatment response of each tumor was calculated based on pretreatment tumor growth and post-treatment tumor volume regression. Linear regression and correlation analysis were used to evaluate each model and their respective parameters for explaining the treatment response. VERDICT analysis showed significant changes from day -1 to day 3 for the intracellular and extracellular volume fraction, as well as the cell radius index (p < 0.05; Wilcoxon signed-rank test). The strongest correlation between the diffusion model parameters and the tumor treatment response was seen for the ADC, kurtosis-corrected diffusion coefficient, and intracellular volume fraction on day 3 (τ = 0.47, 0.52, and -0.49, respectively, p < 0.05; Kendall rank correlation coefficient). Of all the tested models, VERDICT held the strongest explanatory value for the tumor treatment response on day 3 (R2 = 0.75, p < 0.01; linear regression). In conclusion, VERDICT has potential for early assessment of external radiation treatment and may provide further insights into the underlying biological effects of radiation on tumor tissue. In addition, the results suggest that the time window for assessment of treatment response using dMRI may be narrow.
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Affiliation(s)
- Lukas Lundholm
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Mikael Montelius
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Oscar Jalnefjord
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, MRI Center, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Eva Forssell-Aronsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, MRI Center, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Maria Ljungberg
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, MRI Center, Sahlgrenska University Hospital, Gothenburg, Sweden
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Differentiation of Prostate Cancer and Stromal Hyperplasia in the Transition Zone With Monoexponential, Stretched-Exponential Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging in a Reduced Number of b Values: Correlation With Whole-Mount Pathology. J Comput Assist Tomogr 2022; 46:545-550. [PMID: 35405685 DOI: 10.1097/rct.0000000000001314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVES The aims of the study were to explore the feasibility of generating a monoexponential model (MEM), stretched-exponential model (SEM) based diffusion-weighted imaging (DWI), and diffusion kurtosis imaging (DKI) by applying the same set of reduced b values and to compare their effectiveness in distinguishing prostate cancer from stromal hyperplasia (SH) in the transition zone (TZ) area. METHODS An analysis of 75 patients who underwent preoperative DWI (b values of 0, 700, 1400, 2000 s/mm2) was performed. All lesions were localized on magnetic resonance images according to whole-mount histopathological correlations. The apparent diffusion coefficient (ADC), water molecular diffusion heterogeneity index (α), distributed diffusion coefficient (DDC), mean diffusivity (MD), and mean kurtosis (MK) values were calculated and compared between the TZ cancer and SH groups. Receiver operating characteristic analysis and areas under the receiver operating characteristic curve (AUCs) were carried out for all parameters. RESULTS Compared with the SH group, the ADC, DDC, α, and MD values of the TZ cancer group were significantly reduced, while the MK value was significantly increased (all P < 0.05). The AUCs of the ADC, DDC, α, MD, and MK were 0.828, 0.801, 0.813, 0.822, and 0.882, respectively. The AUC of MK was significantly higher than that of the other parameters (all P < 0.05). CONCLUSIONS When using the reduced b-value set, all parameters from MEM, SEM, based DWI, and DKI can effectively distinguish TZ cancer from SH. Among them, DKI demonstrated potential clinical superiority over the others in TZ cancer diagnosis.
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Van Booven DJ, Kuchakulla M, Pai R, Frech FS, Ramasahayam R, Reddy P, Parmar M, Ramasamy R, Arora H. A Systematic Review of Artificial Intelligence in Prostate Cancer. Res Rep Urol 2021; 13:31-39. [PMID: 33520879 PMCID: PMC7837533 DOI: 10.2147/rru.s268596] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 01/11/2021] [Indexed: 12/12/2022] Open
Abstract
The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making. Tools like PSA levels, MRI guided biopsies, genomic biomarkers, and Gleason grading are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Nevertheless, diagnosis tracking and subsequent risk stratification often lend itself to significant subjectivity. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.
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Affiliation(s)
- Derek J Van Booven
- John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Manish Kuchakulla
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Raghav Pai
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Fabio S Frech
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Reshna Ramasahayam
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Pritika Reddy
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Madhumita Parmar
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Ranjith Ramasamy
- Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA.,The Interdisciplinary Stem Cell Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Himanshu Arora
- John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA.,Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA.,The Interdisciplinary Stem Cell Institute, Miller School of Medicine, University of Miami, Miami, FL, USA
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9
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Mayer R, Simone CB, Turkbey B, Choyke P. Algorithms applied to spatially registered multi-parametric MRI for prostate tumor volume measurement. Quant Imaging Med Surg 2021; 11:119-132. [PMID: 33392016 DOI: 10.21037/qims-20-137a] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Prostate tumor volume correlates with critical components of cancer staging such as Gleason score (GS) grade, predicted disease progression, and metastasis. Therefore, non-invasive tumor volume measurement may elevate clinical management. Radiology assessments of multi-parametric MRI (MP-MRI) commonly visually examine individual images to determine possible tumor presence. This study combines registered MP-MRI into a single image that display normal tissue and possible lesions. This study tests and exploits the vector nature of spatially registered MP-MRI by using supervised target detection algorithms (STDA) and color display and psychovisual analysis (CIELAB) to non-invasively estimate prostate tumor volume. Methods MRI, including T1, T2, diffusion [apparent diffusion coefficient (ADC)], dynamic contrast enhanced (DCE) images, were resampled, rescaled, translated, and stitched to form spatially registered Multi-parametric cubes. The multi-parametric or multi-spectral signatures (7-component or T1, T2, ADC, etc.) that characterize the prostate tumors were inserted into target detection algorithms with conical decision surfaces (adaptive cosine estimator, ACE). Various detection thresholds were applied to discriminate tumor from normal tissue. In addition, tumor appeared as yellow in color images that were created by assigning red to washout from DCE, green to high B from diffusion, and blue to autonomous diffusion image. The yellow voxels in the three-channel hypercube were visually identified by a reader and recording voxels that exceed a threshold in the b* component of the CIELAB algorithm. The number of reported tumor voxels were converted to volume based on spatial resolution and slice separation. The tumor volume measurements were quantitatively validated by comparing the tumor volume computations to the pathologist's assessment of the histology of sectioned whole mount prostates from 26 consecutive patients with prostate adenocarcinoma who underwent radical prostatectomy. This study analyzed tumors exceeding 1 cc and that also took up contrast material (18 patients). Results High correlation coefficients for tumor volume measurements using supervised target detection and color analysis vs. histology from wholemount prostatectomy were computed (R=0.83 and 0.91, respectively). A linear fit for tumor volume measurements using for supervised target detection and color analysis vs. tumor measurements from radical prostatectomy (after correcting for shrinkage from the radical prostatectomy) results in a slope of 1.02 and 3.02, respectively. A polynomial fit for the color analysis to the histology found (R=0.95). Voxels exceeding a threshold in the b* part of the CIELAB algorithm yielded correlation coefficients (0.71, 0.80) offsets (0.01 cc, -0.63 cc) and slopes (1.99, 0.89) against the wholemount prostatectomy and color analysis, respectively. Conclusions Supervised target detection and color display and analysis applied to registered MP-MRI non-invasively estimates prostate tumor volumes >1 cc and displaying angiogenesis.
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Affiliation(s)
- Rulon Mayer
- Oncoscore, Garrett Park, MD, USA.,University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Peter Choyke
- National Institutes of Health, Bethesda, MD, USA
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10
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Palumbo P, Manetta R, Izzo A, Bruno F, Arrigoni F, De Filippo M, Splendiani A, Di Cesare E, Masciocchi C, Barile A. Biparametric (bp) and multiparametric (mp) magnetic resonance imaging (MRI) approach to prostate cancer disease: a narrative review of current debate on dynamic contrast enhancement. Gland Surg 2020; 9:2235-2247. [PMID: 33447576 DOI: 10.21037/gs-20-547] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Prostate cancer is the most common malignancy in male population. Over the last few years, magnetic resonance imaging (MRI) has proved to be a robust clinical tool for identification and staging of clinically significant prostate cancer. Though suggestions by the European Society of Urogenital Radiology to use complete multiparametric (mp) T2-weighted/diffusion weighted imaging (DWI)/dynamic contrast enhancement (DCE) acquisition for all prostate MRI examinations, the real advantage of functional DCE remains a matter of debate. Recent studies demonstrate that biparametric (bp) and mp approaches have similar accuracy, but controversial evidences remain, and the specific potential benefits of contrast medium administration are still poorly discussed in literature. The bp approach is in fact sufficient in most cases to adequately identify a negative test, or to accurately define the degree of aggressiveness of a lesion, especially if larger or with major characteristics of malignancy. This feature would give the DCE a secondary role, probably limited to a second evaluation of the lesion location, for detecting small cancer or in case of controversy. However, DCE has proved to increase the sensitivity of prostate MRI, though a less specificity. Therefore, an appropriate decision algorithm is needed to standardize the MRI approach. Aim of this review study was to provide a schematic description of bpMRI and mpMRI approaches in the study of prostatic anatomy, focusing on comparative validity and current DCE application. Additional theoretical considerations on prostate MRI are provided.
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Affiliation(s)
- Pierpaolo Palumbo
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Rosa Manetta
- Radiology Unit, San Salvatore Hospital, L'Aquila, Italy
| | - Antonio Izzo
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Federico Bruno
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Francesco Arrigoni
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Massimo De Filippo
- Department of Medicine and Surgery (DiMec), Section of Radiology, University of Parma, Maggiore Hospital, Parma, Italy
| | - Alessandra Splendiani
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Ernesto Di Cesare
- Department of Life, Health and Environmental Sciences, University of L'Aquila, L'Aquila, Italy
| | - Carlo Masciocchi
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Antonio Barile
- Department of Biotechnology and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
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11
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Prostatitis, the Great Mimicker of Prostate Cancer: Can We Differentiate Them Quantitatively With Multiparametric MRI? AJR Am J Roentgenol 2020; 215:1104-1112. [PMID: 32901562 DOI: 10.2214/ajr.20.22843] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE. The purpose of this study was to investigate the diagnostic performance of semiquantitative and quantitative pharmacokinetic parameters and quantitative apparent diffusion coefficient (ADC) values obtained from prostate multiparametric MRI (mpMRI) to differentiate prostate cancer (PCa) and prostatitis objectively. MATERIALS AND METHODS. We conducted a retrospective review of patients with biopsy-proven PCa or prostatitis who underwent mpMRI study between January 2015 and February 2018. Mean ADC, forward volume transfer constant (Ktrans), reverse volume transfer constant (kep), plasma volume fraction (Vp), extravascular extracellular space volume fraction (Ve), and time to peak (TTP) values were calculated for both lesions and contralateral normal prostate tissue. Signal intensity-time curves were analyzed. Lesion-to-normal prostate tissue ratios of pharmacokinetic parameters were also calculated. The diagnostic accuracy and cutoff points of all parameters were analyzed to differentiate PCa from prostatitis. RESULTS. A total of 138 patients (94 with PCa and 44 with prostatitis) were included in the study. Statistically, ADC, quantitative pharmacokinetic parameters (Ktrans, kep, Ve, and Vp), their lesion-to-normal prostate tissue ratios, and TTP values successfully differentiated PCa and prostatitis. Surprisingly, we found that Ve values were significantly higher in prostatitis lesions. The combination of these parameters had 92.7% overall diagnostic accuracy. ADC, kep, and TTP made up the most successful combination for differential diagnosis. Analysis of the signal intensity-time curves showed mostly type 2 and type 3 enhancement curve patterns for patients with PCa. Type 3 curves were not seen in any prostatitis cases. CONCLUSION. Quantitative analysis of mpMRI differentiates PCa from prostatitis with high sensitivity and specificity, appears to have significant potential, and may improve diagnostic accuracy. In addition, evaluating these parameters does not cause any extra burden to the patients.
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12
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Klingebiel M, Ullrich T, Quentin M, Bonekamp D, Aissa J, Mally D, Arsov C, Albers P, Antoch G, Schimmöller L. Advanced diffusion weighted imaging of the prostate: Comparison of readout-segmented multi-shot, parallel-transmit and single-shot echo-planar imaging. Eur J Radiol 2020; 130:109161. [DOI: 10.1016/j.ejrad.2020.109161] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 06/30/2020] [Indexed: 01/21/2023]
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13
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Gong L, Xu M, Fang M, Zou J, Yang S, Yu X, Xu D, Zhou L, Li H, He B, Wang Y, Fang X, Dong D, Tian J. Noninvasive Prediction of High-Grade Prostate Cancer via Biparametric MRI Radiomics. J Magn Reson Imaging 2020; 52:1102-1109. [PMID: 32212356 DOI: 10.1002/jmri.27132] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Revised: 03/03/2020] [Accepted: 03/03/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Gleason score (GS) is a histologic prognostic factor and the basis of treatment decision-making for prostate cancer (PCa). Treatment regimens between lower-grade (GS ≤7) and high-grade (GS >7) PCa differ largely and have great effects on cancer progression. PURPOSE To investigate the use of different sequences in biparametric MRI (bpMRI) of the prostate gland for noninvasively distinguishing high-grade PCa. STUDY TYPE Retrospective. POPULATION In all, 489 patients (training cohort: N = 326; test cohort: N = 163) with PCa between June 2008 and January 2018. FIELD STRENGTH/SEQUENCE 3.0T, pelvic phased-array coils, bpMRI including T2 -weighted imaging (T2 WI) and diffusion-weighted imaging (DWI); apparent diffusion coefficient map extracted from DWI. ASSESSMENT The whole prostate gland was delineated. Radiomic features were extracted and selected using the Kruskal-Wallis test, the minimum redundancy-maximum relevance, and the sequential backward elimination algorithm. Two single-sequence radiomic (T2 WI, DWI) and two combined (T2 WI-DWI, T2 WI-DWI-Clinic) models were respectively constructed and validated via logistic regression. STATISTICAL TESTS The Kruskal-Wallis test and chi-squared test were utilized to evaluate the differences among variable groups. P < 0.05 determined statistical significance. The area under the receiver operating characteristic curve (AUC), specificity, sensitivity, and accuracy were used to evaluate model performance. The Delong test was conducted to compare the differences between the AUCs of all models. RESULT All radiomic models showed significant (P < 0.001) predictive performances. Between the single-sequence radiomic models, the DWI model achieved the most encouraging results, with AUCs of 0.801 and 0.787 in the training and test cohorts, respectively. For the combined models, the T2 WI-DWI models acquired an AUC of 0.788, which was almost the same with DWI in the test cohort, and no significant difference was found between them (training cohort: P = 0.199; test cohort: P = 0.924). DATA CONCLUSION Radiomics based on bpMRI can noninvasively identify high-grade PCa before the operation, which is helpful for individualized diagnosis of PCa. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:1102-1109.
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Affiliation(s)
- Lixin Gong
- College of Medicine and Biological Information Engineering School, Northeastern University, Shenyang, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Mengjie Fang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Jian Zou
- Center of Clinical Research, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Shudong Yang
- Department of Pathology, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Xinyi Yu
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Dandan Xu
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Lijuan Zhou
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Hailin Li
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Bingxi He
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Yan Wang
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Xiangming Fang
- Imaging Center, Wuxi People's Hospital, Nanjing Medical University, Wuxi, China
| | - Di Dong
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Jie Tian
- College of Medicine and Biological Information Engineering School, Northeastern University, Shenyang, China.,CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China
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14
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van Schie MA, van Houdt PJ, Ghobadi G, Pos FJ, Walraven I, de Boer HCJ, van den Berg CAT, Smeenk RJ, Kerkmeijer LGW, van der Heide UA. Quantitative MRI Changes During Weekly Ultra-Hypofractionated Prostate Cancer Radiotherapy With Integrated Boost. Front Oncol 2019; 9:1264. [PMID: 31867266 PMCID: PMC6904955 DOI: 10.3389/fonc.2019.01264] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 10/31/2019] [Indexed: 01/29/2023] Open
Abstract
Purpose: Quantitative MRI reflects tissue characteristics. As possible changes during radiotherapy may lead to treatment adaptation based on response, we here assessed if such changes during treatment can be detected. Methods and Materials: In the hypoFLAME trial patients received ultra-hypofractionated prostate radiotherapy with an integrated boost to the tumor in 5 weekly fractions. We analyzed T2 and ADC maps of 47 patients that were acquired in MRI exams prior to and during radiotherapy, and performed rigid registrations based on the prostate contour on anatomical T2-weighted images. We analyzed median T2 and ADC values in three regions of interest (ROIs): the central gland (CG), peripheral zone (PZ), and tumor. We analyzed T2 and ADC changes during treatment and compared patients with and without hormonal therapy. We tested changes during treatment for statistical significance with Wilcoxon signed rank tests. Using confidence intervals as recommended from test-retest measurements, we identified persistent T2 and ADC changes during treatment. Results: In the CG, median T2 and ADC values significantly decreased 12 and 8%, respectively, in patients that received hormonal therapy, while in the PZ these values decreased 17 and 18%. In the tumor no statistically significant change was observed. In patients that did not receive hormonal therapy, median ADC values in the tumor increased with 20%, while in the CG and PZ no changes were observed. Persistent T2 changes in the tumor were found in 2 out of 24 patients, while none of the 47 patients had persistent ADC changes. Conclusions: Weekly quantitative MRI could identify statistically significant ADC changes in the tumor in patients without hormonal therapy. On a patient level few persistent T2 changes in the tumor were observed. Long-term follow-up is required to relate the persistent T2 and ADC changes to outcome and evaluate the applicability of quantitative MRI for response based treatment adaptation.
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Affiliation(s)
- Marcel A van Schie
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Ghazaleh Ghobadi
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Iris Walraven
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Hans C J de Boer
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Robert Jan Smeenk
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Linda G W Kerkmeijer
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands.,Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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15
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Brancato V, Cavaliere C, Salvatore M, Monti S. Non-Gaussian models of diffusion weighted imaging for detection and characterization of prostate cancer: a systematic review and meta-analysis. Sci Rep 2019; 9:16837. [PMID: 31728007 PMCID: PMC6856159 DOI: 10.1038/s41598-019-53350-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 10/28/2019] [Indexed: 12/24/2022] Open
Abstract
The importance of Diffusion Weighted Imaging (DWI) in prostate cancer (PCa) diagnosis have been widely handled in literature. In the last decade, due to the mono-exponential model limitations, several studies investigated non-Gaussian DWI models and their utility in PCa diagnosis. Since their results were often inconsistent and conflicting, we performed a systematic review of studies from 2012 examining the most commonly used Non-Gaussian DWI models for PCa detection and characterization. A meta-analysis was conducted to assess the ability of each Non-Gaussian model to detect PCa lesions and distinguish between low and intermediate/high grade lesions. Weighted mean differences and 95% confidence intervals were calculated and the heterogeneity was estimated using the I2 statistic. 29 studies were selected for the systematic review, whose results showed inconsistence and an unclear idea about the actual usefulness and the added value of the Non-Gaussian model parameters. 12 studies were considered in the meta-analyses, which showed statistical significance for several non-Gaussian parameters for PCa detection, and to a lesser extent for PCa characterization. Our findings showed that Non-Gaussian model parameters may potentially play a role in the detection and characterization of PCa but further studies are required to identify a standardized DWI acquisition protocol for PCa diagnosis.
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16
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Revisiting quantitative multi-parametric MRI of benign prostatic hyperplasia and its differentiation from transition zone cancer. Abdom Radiol (NY) 2019; 44:2233-2243. [PMID: 30955071 DOI: 10.1007/s00261-019-01936-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
PURPOSE This study investigates the multiparametric MRI (mpMRI) appearance of different types of benign prostatic hyperplasia (BPH) and whether quantitative mpMRI is effective in differentiating between prostate cancer (PCa) and BPH. MATERIALS AND METHODS Patients (n = 60) with confirmed PCa underwent preoperative 3T MRI. T2-weighted, multi-echo T2-weighted, diffusion weighted and dynamic contrast enhanced images (DCE) were obtained prior to undergoing prostatectomy. PCa and BPH (cystic, glandular or stromal) were identified in the transition zone and matched with MRI. Quantitative mpMRI metrics: T2, ADC and DCE-MRI parameters using an empirical mathematical model were measured. RESULTS ADC values were significantly lower (p < 0.001) in PCa compared to all BPH types and can differentiate between PCa and BPH with high accuracy (AUC = 0.87, p < 0.001). T2 values were significantly lower (p < 0.001) in PCa compared to cystic BPH only, while glandular (p = 0.27) and stromal BPH (p = 0.99) showed no significant difference from PCa. BPH mimics PCa in the transition zone on DCE-MRI evidenced by no significant difference between them. mpMRI values of glandular (ADC = 1.31 ± 0.22 µm2/ms, T2 = 115.7 ± 37.3 ms) and cystic BPH (ADC = 1.92 ± 0.43 µm2/ms, T2 = 242.8 ± 117.9 ms) are significantly different. There was no significant difference in ADC (p = 0.72) and T2 (p = 0.46) between glandular and stromal BPH. CONCLUSIONS Multiparametric MRI and specifically quantitative ADC values can be used for differentiating PCa and BPH, improving PCa diagnosis in the transition zone. However, DCE-MRI metrics are not effective in distinguishing PCa and BPH. Glandular BPH are not hyperintense on ADC and T2 as previously thought and have similar quantitative mpMRI measurements to stromal BPH. Glandular and cystic BPH appear differently on mpMRI and are histologically different.
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17
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Raeside M, Low A, Cohen P, Sutherland P, Gormly K. Prostate MRI evolution in clinical practice: Audit of tumour detection and staging versus prostatectomy with staged introduction of multiparametric MRI and Prostate Imaging Reporting and Data System v2 reporting. J Med Imaging Radiat Oncol 2019; 63:487-494. [DOI: 10.1111/1754-9485.12878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 03/02/2019] [Indexed: 12/12/2022]
Affiliation(s)
- Mitchell Raeside
- Dr Jones & Partners Medical Imaging Eastwood South Australia Australia
| | - Andrew Low
- Royal Adelaide Hospital Adelaide South Australia Australia
| | | | | | - Kirsten Gormly
- Dr Jones & Partners Medical Imaging Eastwood South Australia Australia
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18
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Tomita H, Soga S, Suyama Y, Ito K, Asano T, Shinmoto H. Analysis of Diffusion-weighted MR Images Based on a Gamma Distribution Model to Differentiate Prostate Cancers with Different Gleason Score. Magn Reson Med Sci 2019; 19:40-47. [PMID: 30918223 PMCID: PMC7067910 DOI: 10.2463/mrms.mp.2018-0124] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Purpose: Prostate cancer management includes identification of clinically significant cancers that may require curative treatment. Statistical models based on gamma distribution can describe diffusion signal decay curves of prostate cancer. The purpose of this study was to evaluate the ability of parameters obtained with the gamma model in differentiating prostate cancers with different Gleason score values. Methods: This study included 155 patients with prostate cancer who underwent multiparametric magnetic resonance imaging prior to prostate biopsy (127 patients) or radical prostatectomy (28 patients) between January 2015 and June 2017; 159 foci of prostate cancer were included in our study. We compared cases scored as Gleason score (GS) 3 + 3 and GS ≥ 3 + 4, and analyzed cases scored as GS ≤ 3+ 4 and GS ≥ 4 + 3 based on the gamma model (Frac < 1.0, Frac < 0.8, Frac < 0.5, Frac < 0.3, and Frac > 3.0), and apparent diffusion coefficient (ADC). Results: Among 159 cancerous lesions in 155 patients, 13 (8.2%) were GS 3 + 3 prostate cancers, 51 (32.0%) were GS 3 + 4 prostate cancers, 30 (18.2%) were GS 4 + 3 cancers, and 65 (40.9%) were GS ≥ 4 + 4 cancers. Frac < 0.3, Frac < 0.5, Frac < 0.8, and Frac < 1.0 were significantly higher and ADC values were significantly lower in GS ≥ 4 + 3 cancers than in GS ≤ 3 + 4 cancers (P < 0.01, P < 0.01, P < 0.01, P = 0.01, and P < 0.01, respectively). With receiver operating characteristic (ROC) analysis, Frac < 0.3 and Frac < 0.5 had significantly greater area under the ROC curve for discriminating GS ≥ 4 + 3 cancers from GS ≤ 3 + 4 cancers than ADC (P = 0.03, P < 0.01, respectively). Conclusion: Frac < 0.3 and Frac < 0.5 showed higher diagnostic performance than ADC for differentiating GS ≥ 4 + 3 from GS ≤ 3 + 4 cancers. The gamma model may add additional value in discrimination of tumor grades.
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Affiliation(s)
- Hiroko Tomita
- Department of Radiology, National Defense Medical College
| | | | - Yohsuke Suyama
- Department of Radiology, National Defense Medical College
| | - Keiichi Ito
- Department of Urology, National Defense Medical College
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19
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Koori N, Kato T, Kurata K. [Influence of Inversion Time of Fat Suppression Methods on Measurement of Apparent Diffusion Coefficient]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2019; 75:1173-1176. [PMID: 31631111 DOI: 10.6009/jjrt.2019_jsrt_75.10.1173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Recently, tumor differentiation in various tissues has been performed by using the apparent diffusion coefficient (ADC) value. However, the influence of ADC value due to the different inversion time (TI) of fat suppression methods has not been reported yet. Therefore, the purpose of our study was to verify the influence of the different TI of fat suppression methods on the ADC value. ADC values were compared for diffusion-weighted imaging (DWI), using the short-TI inversion recovery (STIR) method and the spectral attenuated inversion recovery (SPAIR) method. For the STIR method, when TI was closed to the null point of each phantom, signal intensity decreased, and the ADC value thereby decreased. However, by the SPAIR method, signal intensity and ADC value were not affected by the inversion time. When using the STIR method, signal intensity decreased when the null point for each phantom was approached, which was thought to decrease the ADC value. In conclusion, when using STIR-DWI after contrast agent administration, the ADC value might have been affected by the TI.
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Affiliation(s)
- Norikazu Koori
- Department of Radiology, Komaki City Hospital
- Graduate School of Medical Science, Kanazawa University
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20
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Dinis Fernandes C, van Houdt PJ, Heijmink SWTPJ, Walraven I, Keesman R, Smolic M, Ghobadi G, van der Poel HG, Schoots IG, Pos FJ, van der Heide UA. Quantitative 3T multiparametric MRI of benign and malignant prostatic tissue in patients with and without local recurrent prostate cancer after external-beam radiation therapy. J Magn Reson Imaging 2018; 50:269-278. [PMID: 30585368 PMCID: PMC6618021 DOI: 10.1002/jmri.26581] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 10/31/2018] [Accepted: 11/01/2018] [Indexed: 12/27/2022] Open
Abstract
Background Post‐radiotherapy locally recurrent prostate cancer (PCa) patients are candidates for focal salvage treatment. Multiparametric MRI (mp‐MRI) is attractive for tumor localization. However, radiotherapy‐induced tissue changes complicate image interpretation. To develop focal salvage strategies, accurate tumor localization and distinction from benign tissue is necessary. Purpose To quantitatively characterize radio‐recurrent tumor and benign radiation‐induced changes using mp‐MRI, and investigate which sequences optimize the distinction between tumor and benign surroundings. Study Type Prospective case–control. Subjects Thirty‐three patients with biochemical failure after external‐beam radiotherapy (cases), 35 patients without post‐radiotherapy recurrent disease (controls), and 13 patients with primary PCa (untreated). Field Strength/Sequences 3T; quantitative mp‐MRI: T2‐mapping, ADC, and Ktrans and kep maps. Assessment Quantitative image‐analysis of prostatic regions, within and between cases, controls, and untreated patients. Statistical Tests Within‐groups: nonparametric Friedman analysis of variance with post‐hoc Wilcoxon signed‐rank tests; between‐groups: Mann–Whitney tests. All with Bonferroni corrections. Generalized linear mixed modeling to ascertain the contribution of each map and location to tumor likelihood. Results Benign imaging values were comparable between cases and controls (P = 0.15 for ADC in the central gland up to 0.91 for kep in the peripheral zone), both with similarly high peri‐urethral Ktrans and kep values (min−1) (median [range]: Ktrans = 0.22 [0.14–0.43] and 0.22 [0.14–0.36], P = 0.60, kep = 0.43 [0.24–0.57] and 0.48 [0.32–0.67], P = 0.05). After radiotherapy, benign central gland values were significantly decreased for all maps (P ≤ 0.001) as well as T2, Ktrans, and kep of benign peripheral zone (all with P ≤ 0.002). All imaging maps distinguished recurrent tumor from benign peripheral zone, but only ADC, Ktrans, and kep were able to distinguish it from benign central gland. Recurrent tumor and peri‐urethral Ktrans values were not significantly different (P = 0.81), but kep values were (P < 0.001). Combining all quantitative maps and voxel location resulted in an optimal distinction between tumor and benign voxels. Data Conclusion Mp‐MRI can distinguish recurrent tumor from benign tissue. Level of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:269–278.
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Affiliation(s)
| | - Petra J van Houdt
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Iris Walraven
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Rick Keesman
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Milena Smolic
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ghazaleh Ghobadi
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Henk G van der Poel
- Department of Urology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Ivo G Schoots
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Uulke A van der Heide
- Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands
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21
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Salvaggio G, Calamia M, Purpura P, Bartolotta TV, Picone D, Dispensa N, Lunetta C, Bruno A, Raso L, Salvaggio L, Lo Re G, Galia M, Simonato A, Midiri M, Lagalla R. Role of apparent diffusion coefficient values in prostate diseases characterization on diffusion-weighted magnetic resonance imaging. MINERVA UROL NEFROL 2018; 71:154-160. [PMID: 30421590 DOI: 10.23736/s0393-2249.18.03065-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND To evaluate if normal and pathological prostate tissue can be distinguished by using apparent diffusion coefficient (ADC) values on magnetic resonance imaging (MRI) and to understand if it is possible to differentiate among pathological prostate tissues using ADC values. METHODS Our population consisted in 81 patients (mean age 65.4 years) in which 84 suspicious areas were identified. Regions of interest were placed over suspicious areas, detected on MRI, and over areas with normal appearance, and ADC values were recorded. Statistical differences between ADC values of suspicious and normal areas were evaluated. Histopathological diagnosis, obtained from targeted biopsy using MRI-US fusion biopsies in 39 patients and from prostatectomy in 42 patients, were correlated to ADC values. RESULTS Histopathological diagnosis revealed 58 cases of prostate cancer (PCa), 19 patients with indolent PCa (Gleason Score ≤6) and 39 patients with clinically significant PCa (Gleason Score ≥7), 16 of high-grade prostatic intraepithelial neoplasia (HG-PIN) and 10 of atypical small acinar proliferation (ASAP). Significant statistical differences between mean ADC values of normal prostate tissue versus PCa (P<0.00001), HG-PIN (P<0.00001) and ASAP (P<0.00001) were found. Significant differences were observed between mean ADC values of PCa versus HG-PIN (P<0.00001) and ASAP (P<0.00001) with many overlapping values. Differences between mean ADC values of HG-PIN versus ASAP (P=0.015) were not significant. Significant differences of ADC values were also observed between patients with indolent and clinically significant PCa (P<0.00001). CONCLUSIONS ADC values allow differentiation between normal and pathological prostate tissue and between indolent and clinically significant PCa but do not allow a definite differentiation between PCa, HG-PIN, and ASAP.
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Affiliation(s)
- Giuseppe Salvaggio
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy -
| | - Mauro Calamia
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Pierpaolo Purpura
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Tommaso V Bartolotta
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Dario Picone
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Nino Dispensa
- Unit of Urology, Department of Surgery, Oncology, and Stomatology, University of Palermo, Palermo, Italy
| | - Claudio Lunetta
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Alberto Bruno
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Ludovica Raso
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | | | - Giuseppe Lo Re
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Massimo Galia
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Alchiede Simonato
- Unit of Urology, Department of Surgery, Oncology, and Stomatology, University of Palermo, Palermo, Italy
| | - Massimo Midiri
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
| | - Roberto Lagalla
- Section of Radiological Sciences, Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy
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Dynamic Contrast-Enhanced Imaging as a Prognostic Tool in Early Diagnosis of Prostate Cancer: Correlation with PSA and Clinical Stage. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:3181258. [PMID: 30327584 PMCID: PMC6169212 DOI: 10.1155/2018/3181258] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 07/22/2018] [Indexed: 02/08/2023]
Abstract
Background and Purpose Although several methods have been developed to predict the outcome of patients with prostate cancer, early diagnosis of individual patient remains challenging. The aim of the present study was to correlate tumor perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical prognostic factors and further to explore the diagnostic value of DCE-MRI parameters in early stage prostate cancer. Patients and Methods Sixty-two newly diagnosed patients with histologically proven prostate adenocarcinoma were enrolled in our prospective study. Transrectal ultrasound-guided biopsy (12 cores, 6 on each lobe) was performed in each patient. Pathology was reviewed and graded according to the Gleason system. DCE-MRI was performed and analyzed using a two-compartmental model; quantitative parameters including volume transfer constant (Ktrans), reflux constant (Kep), and initial area under curve (iAUC) were calculated from the tumors and correlated with prostate-specific antigen (PSA), Gleason score, and clinical stage. Results Ktrans (0.11 ± 0.02 min−1 versus 0.16 ± 0.06 min−1; p < 0.05), Kep (0.38 ± 0.08 min−1 versus 0.60 ± 0.23 min−1; p < 0.01), and iAUC (14.33 ± 2.66 mmoL/L/min versus 17.40 ± 5.97 mmoL/L/min; p < 0.05) were all lower in the clinical stage T1c tumors (tumor number, n=11) than that of tumors in clinical stage T2 (n=58). Serum PSA correlated with both tumor Ktrans (r=0.304, p < 0.05) and iAUC (r=0.258, p < 0.05). Conclusions Our study has confirmed that DCE-MRI is a promising biomarker that reflects the microcirculation of prostate cancer. DCE-MRI in combination with clinical prognostic factors may provide an effective new tool for the basis of early diagnosis and treatment decisions.
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Steensma BR, Voogt I, van der Werf AJ, van den Berg CA, Luijten PR, Klomp DW, Raaijmakers AJ. Design of a forward view antenna for prostate imaging at 7 T. NMR IN BIOMEDICINE 2018; 31:e3993. [PMID: 30022543 PMCID: PMC6175442 DOI: 10.1002/nbm.3993] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 06/07/2018] [Accepted: 06/08/2018] [Indexed: 05/19/2023]
Abstract
PURPOSE To design a forward view antenna for prostate imaging at 7 T, which is placed between the legs of the subject in addition to a dipole array. MATERIALS AND METHODS The forward view antenna is realized by placing a cross-dipole antenna at the end of a small rectangular waveguide. Quadrature drive of the cross-dipole can excite a circularly polarized wave propagating along the axial direction to and from the prostate region. Functioning of the forward view antenna is validated by comparing measurements and simulations. Antenna performance is evaluated by numerical simulations and measurements at 7 T. RESULTS Simulations of B1+ on a phantom are in good correspondence with measurements. Simulations on a human model indicate that the signal-to-noise ratio (SNR), specific absorption rate (SAR) efficiency and SAR increase when adding the forward view antenna to a previously published dipole array. The SNR increases by up to 18% when adding the forward view antenna as a receive antenna to an eight-channel dipole array in vivo. CONCLUSIONS A design for a forward view antenna is presented and evaluated. SNR improvements up to 18% are demonstrated when adding the forward view antenna to a dipole array.
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Affiliation(s)
| | - Ingmar Voogt
- University Medical Center UtrechtUtrechtthe Netherlands
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Lahoti AM, Lakhotiya AR, Ingole SM, Dhok AP, Mudaliar PN. Role and Application of Diffusion-weighted Imaging in Evaluation of Prostate Cancer. Indian J Med Paediatr Oncol 2018. [DOI: 10.4103/ijmpo.ijmpo_41_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Abstract
Introduction: Diffusion-weighted imaging (DWI) is an important part of magnetic resonance imaging (MRI) in the evaluation of specific organs, including the breast, kidney, liver, and prostate. Prostate cancer lesions are composed of tightly packed cells with reduced extracellular space, which can be visualized on DWIs as areas of restricted diffusion (i.e., high-signal intensity), with corresponding low-signal intensity on apparent diffusion coefficient (ADC) maps and low mean ADC value. Objective: The objective of this study is to identify the appropriate cutoff and mean ADC value to diagnose neoplastic prostatic lesions in central India. Materials and Methods: Sixty-six patients with suspected prostatic pathology were included in this study. All patients underwent MRI on a 1.5-T scanner with a phased-array body coil. MRIs were evaluated compared with the histopathological staging. Results:: The diagnostic accuracy of DWI in predicting malignancy was 39/41, i.e., 95.12%, which is the positive predicted value. The mean ADC for benign category was 1.14 with standard deviation (SD) of 0.14 while mean for prostatitis was 0.91 with SD of 0.26 and for carcinoma was 0.75 with SD of 0.19. The difference in the means was statistically highly significant. Conclusion: DWI demonstrates the restriction of diffusion and the reduction of ADC values in neoplastic tissue and improves the diagnostic accuracy in lesion characterization. This technique allows short acquisition time and provides high-contrast resolution between neoplastic and normal tissue. This technique can be a useful adjunct to the established dynamic contrast-enhanced-MRI.
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Affiliation(s)
- Amol Madanlal Lahoti
- Department of Radiology, NKP Sims and Lata Mangeshkar Hospital, Nagpur, Maharashtra, India
| | | | - Sarang Manohar Ingole
- Department of Radiology, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India
| | - Avinash Parshuram Dhok
- Department of Radiology, NKP Sims and Lata Mangeshkar Hospital, Nagpur, Maharashtra, India
| | - Prashant N Mudaliar
- Department of Radiology, NKP Sims and Lata Mangeshkar Hospital, Nagpur, Maharashtra, India
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An JY, Sidana A, Choyke PL, Wood BJ, Pinto PA, Türkbey İB. Multiparametric Magnetic Resonance Imaging for Active Surveillance of Prostate Cancer. Balkan Med J 2018; 34:388-396. [PMID: 28990929 PMCID: PMC5635625 DOI: 10.4274/balkanmedj.2017.0708] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Active surveillance has gained popularity as an acceptable management option for men with low-risk prostate cancer. Successful utilization of this strategy can delay or prevent unnecessary interventions - thereby reducing morbidity associated with overtreatment. The usefulness of active surveillance primarily depends on correct identification of patients with low-risk disease. However, current population-wide algorithms and tools do not adequately exclude high-risk disease, thereby limiting the confidence of clinicians and patients to go on active surveillance. Novel imaging tools such as mpMRI provide information about the size and location of potential cancers enabling more informed treatment decisions. The term “multiparametric” in prostate mpMRI refers to the summation of several MRI series into one examination whose initial goal is to identify potential clinically-significant lesions suitable for targeted biopsy. The main advantages of MRI are its superior anatomic resolution and the lack of ionizing radiation. Recently, the Prostate Imaging-Reporting and Data System has been instituted as an international standard for unifying mpMRI results. The imaging sequences in mpMRI defined by Prostate Imaging Reporting and Data System version 2 includes: T2-weighted MRI, diffusion-weighted MRI, derived apparent-diffusion coefficient from diffusion-weighted MRI, and dynamic contrast-enhanced MRI. The use of mpMRI prior to starting active surveillance could prevent those with missed, high-grade lesions from going on active surveillance, and reassure those with minimal disease who may be hesitant to take part in active surveillance. Although larger validation studies are still necessary, preliminary results suggest mpMRI has a role in selecting patients for active surveillance. Less certain is the role of mpMRI in monitoring patients on active surveillance, as data on this will take a long time to mature. The biggest obstacles to routine use of prostate MRI are quality control, cost, reproducibility, and access. Nevertheless, there is great a potential for mpMRI to improve outcomes and quality of treatment. The major roles of MRI will continue to expand and its emerging use in standard of care approaches becomes more clearly defined and supported by increasing levels of data.
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Affiliation(s)
- Julie Y An
- Center for Interventional Oncology, NIH Clinical Center and National Cancer Institute, National Institutes of Health, Maryland, USA
| | - Abhinav Sidana
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Maryland, USA
| | - Peter L Choyke
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Maryland, USA
| | - Bradford J. Wood
- Center for Interventional Oncology, NIH Clinical Center and National Cancer Institute, National Institutes of Health, Maryland, USA
| | - Peter A Pinto
- Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Maryland, USA
| | - İsmail Barış Türkbey
- Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Maryland, USA
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Abdelsalam EM, EL Adalany MA, Fouda MEA. Value of diffusion weighted magnetic resonance imaging in grading of urinary bladder carcinoma. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2018.01.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
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Zhang XQ, Yu XR, Du ZL, Miao XF, Lu J, Zhou Q. Three-dimensional proton magnetic resonance spectroscopy and diffusion-weighted imaging in the differentiation of incidental prostate carcinoma from benign prostate hyperplasia. Oncol Lett 2018; 15:6541-6546. [PMID: 29616121 DOI: 10.3892/ol.2018.8131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2016] [Accepted: 01/17/2018] [Indexed: 11/06/2022] Open
Abstract
The present study evaluated three-dimensional proton magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) features in differentiating incidental prostate carcinoma (IPCa) and benign prostate hyperplasia (BPH) in the central gland of the prostate. The clinical and imaging data of 9 patients with IPCa, 118 patients with BPH [including those with glandular hyperplasia (GH), stromal hyperplasia (SH) and mixed hyperplasia (MH)], were retrospectively analyzed. The mean (choline + creatine)/citrate (CC/C) value of 3D MRS, the apparent diffusion coefficient (ADC) value and the minimal ADC value of DWI were compared between carcinoma and non-carcinoma tissues. The mean CC/C values were 1.04±0.28, and 1.09±0.58 in IPCa and BPH, respectively (t=-0.205, P=0.838). No significant difference in CC/C values (χ2=2.595, P=0.458) could be detected between IPCa, GH, SH and MH groups. The ADC values of the central gland only differed between IPCa (1.48±0.18) ×10-3 and GH (1.60±0.16) ×10-3 mm2/sec (P=0.037). The minimal ADC values were similar between IPCa (1.15±0.10) ×10-3 and BPH (1.14±0.11) ×10-3 mm2/sec, no significant differences could be detected between IPCa and GH (P=0.930), IPCa and SH (P=0.192), and IPCa and MH (P=0.544). Although the ADC values of the central gland of the prostate differed between IPCa and GH, the findings of the present study therefore indicate that combining 3D MRS with DWI cannot potentially improve the detection of IPCa.
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Affiliation(s)
- Xue-Qin Zhang
- Department of Radiology, The Third People's Hospital of Nantong, Nantong, Jiangsu 226006, P.R. China
| | - Xiang-Rong Yu
- Department of Radiology, Zhuhai Hospital of Jinan University, Zhuhai People's Hospital, Zhuhai, Guangdong 519000, P.R. China
| | - Zhong-Li Du
- Department of Radiology, Zhuhai Hospital of Jinan University, Zhuhai People's Hospital, Zhuhai, Guangdong 519000, P.R. China
| | - Xiao-Fen Miao
- Department of Radiology, The Third People's Hospital of Nantong, Nantong, Jiangsu 226006, P.R. China
| | - Jian Lu
- Department of Radiology, The Third People's Hospital of Nantong, Nantong, Jiangsu 226006, P.R. China
| | - Quan Zhou
- Department of Radiology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510000, P.R. China
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Wang X, Zhao Y, Hu Y, Zhou Y, Ye X, Liu K, Bai G, Guo A, Du M, Jiang L, Wang J, Yan Z. Evaluation and validation of the diagnostic value of the apparent diffusion coefficient for differentiating early-stage endometrial carcinomas from benign mimickers at 3T MRI. Oncotarget 2018. [PMID: 28634318 PMCID: PMC5542275 DOI: 10.18632/oncotarget.18553] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Previous researchers obtained various apparent diffusion coefficient (ADC) cutoff values to differentiate endometrial carcinoma from benign mimickers with 1.5T magnetic resonance imaging (MRI). Few studies have used 3T MRI or validated the effectiveness of these cutoff ADC values prospectively. This study was designed in two stages to obtain a cutoff ADC value at 3T MRI and to validate prospectively the role of the ADC value. First, we conducted a retrospective study of 60 patients to evaluate the diagnostic value of ADC by obtain a theoretical cutoff ADC value for differentiating between benign and malignant endometrial lesions. Student's t test revealed that ADC values for stage I endometrial carcinomas were significantly lower than those for benign lesions. The area under the curve value of the receiver operating characteristic curve was 0.993, and the cutoff ADC value was 0.98 × 10-3 mm2/s. The sensitivity, specificity, and overall accuracy of diagnosing stage I endometrial carcinoma were 100%, 97.1%, and 98.3%, respectively. Second, we conducted a prospective study of 26 patients to validate the use of the cutoff ADC value obtained in the study's first stage. The sensitivity, specificity, and overall accuracy for differentiating malignant from benign endometrial lesions based on the cutoff ADC value obtained earlier were as follows: radiologist 1 attained 86.67%, 100.0%, and 92.31%, respectively; radiologist 2 attained 86.67%, 91.0%, and 88.5%, respectively. Our results suggest that ADC values could be a potential biomarker for use as a quantitative and qualitative tool for differentiating between early-stage endometrial carcinomas and benign mimickers.
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Affiliation(s)
- Xue Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Yu Zhao
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Yumin Hu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Yongjin Zhou
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Xinjian Ye
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Kun Liu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Guanghui Bai
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Anna Guo
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Meimei Du
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Lezhen Jiang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Jinhong Wang
- Department of Medical Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou 325027, China
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Taha Ali TF, ElHariri MA, Riad MM. Diffusion-weighted MRI in prostatic lesions: Diagnostic performance of normalized ADC using normal peripheral prostatic zone as a reference. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2017.09.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
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30
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MRI and 11C Acetate PET/CT for Prediction of Regional Lymph Node Metastasis in Newly Diagnosed Prostate Cancer. Radiol Oncol 2018. [PMID: 29520210 PMCID: PMC5839086 DOI: 10.2478/raon-2018-0001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Background The aim of the study was to examine the value of quantitative and qualitative MRI and 11C acetate PET/CT parameters in predicting regional lymph node (LN) metastasis of newly diagnosed prostate cancer (PCa). Patients and methods Patients with intermediate (n = 6) and high risk (n = 47) PCa underwent 3T MRI (40 patients) and 11C acetate PET/CT (53 patients) before extended pelvic LN dissection. For each patient the visually most suspicious LN was assessed for mean apparent diffusion coefficient (ADCmean), maximal standardized uptake value (SUVmax), size and shape and the primary tumour for T stage on MRI and ADCmean and SUVmax in the index lesion. The variables were analysed in simple and multiple logistic regression analysis. Results All variables, except ADCmean and SUVmax of the primary tumor, were independent predictors of LN metastasis. In multiple logistic regression analysis the best model was ADCmean in combintion with MRI T-stage where both were independent predictors of LN metastasis, this combination had an AUC of 0.81 which was higher than the AUC of 0.65 for LN ADCmean alone and the AUC of 0.69 for MRI T-stage alone. Conclusions Several quantitative and qualitative imaging parameters are predictive of regional LN metastasis in PCa. The combination of ADCmean in lymph nodes and T-stage on MRI was the best model in multiple logistic regression with increased predictive value compared to lymph node ADCmean and T-stage on MRI alone.
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Asai A, Ogura A, Sotome H, Fuju A. [Effect of Slice Thickness for Apparent Diffusion Coefficient Measurement of Mass]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2018; 74:805-809. [PMID: 30122745 DOI: 10.6009/jjrt.2018_jsrt_74.8.805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Apparent diffusion coefficient (ADC) values calculated from diffusion-weighted magnetic resonance imaging (DW-MRI) can be used for differentiation of tumors. Clinically, ADC values are used for monitoring treatment response after chemotherapy or radiation. However, it is reported that the threshold of the ADC value differs among institutions. In addition, there are reports regarding the change factor of the ADC value. Slice thickness may induce error in the ADC value by the influence of the partial volume effect in thicker objects, and by the influence of signal-to-noise ratio (SNR) in thinner objects. Therefore, in this study, the effect of slice thickness was examined. The signal body of spherical high-diffusion coefficients of 6, 7.9, and 9.3 mm in diameter was fixed in the low-circumference material of the diffusion coefficient. These phantoms were imaged using DW imaging (DWI) of 1, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 15, and 20 mm slice thickness using the multi-b values. In addition, different SNR were imaged by changing field-of-view and the number of additions. ADC was calculated by DWI of the different b values. As a result, slice thickness showed a peak at 50-65% of the diameter of the signal body. Furthermore, ADC values fluctuated in the slice thickness in front of the peak with a change in SNR. In conclusion, the ADC value was most accurate at a setting of 50-65% of slice thickness for the object diameter.
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Affiliation(s)
- Ayumi Asai
- School of Radiological Technology, Gunma Prefectural College of Health Sciences (Current address: Department of Radiology, Shizuoka City Shizuoka Hospital)
| | - Akio Ogura
- Graduate School of Radiological Technology, Gunma Prefectural College of Health Sciences
| | - Hana Sotome
- School of Radiological Technology, Gunma Prefectural College of Health Sciences (Current address: Department of Radiology, Fujioka General Hospital)
| | - Atsuya Fuju
- School of Radiological Technology, Gunma Prefectural College of Health Sciences (Current address: Department of Radiology, Kiryu Kosei General Hospital)
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Scialpi M, D'Andrea A, Martorana E, Malaspina CM, Aisa MC, Napoletano M, Orlandi E, Rondoni V, Scialpi P, Pacchiarini D, Palladino D, Dragone M, Di Renzo G, Simeone A, Bianchi G, Brunese L. Biparametric MRI of the prostate. Turk J Urol 2017; 43:401-409. [PMID: 29201499 DOI: 10.5152/tud.2017.06978] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 10/27/2017] [Indexed: 12/13/2022]
Abstract
Biparametric Magnetic Resonance Imaging (bpMRI) of the prostate combining both morphologic T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) is emerging as an alternative to multiparametric MRI (mpMRI) to detect, to localize and to guide prostatic targeted biopsy in patients with suspicious prostate cancer (PCa). BpMRI overcomes some limitations of mpMRI such as the costs, the time required to perform the study, the use of gadolinium-based contrast agents and the lack of a guidance for management of score 3 lesions equivocal for significant PCa. In our experience the optimal and similar clinical results of the bpMRI in comparison to mpMRI are essentially related to the DWI that we consider the dominant sequence for detection suspicious PCa both in transition and in peripheral zone. In clinical practice, the adoption of bpMRI standardized scoring system, indicating the likelihood to diagnose a clinically significant PCa and establishing the management of each suspicious category (from 1 to 4), could represent the rationale to simplify and to improve the current interpretation of mpMRI based on Prostate Imaging and Reporting Archiving Data System version 2 (PI-RADS v2). In this review article we report and describe the current knowledge about bpMRI in the detection of suspicious PCa and a simplified PI-RADS based on bpMRI for management of each suspicious PCa categories to facilitate the communication between radiologists and urologists.
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Affiliation(s)
- Michele Scialpi
- Department of Surgical and Biomedical Sciences, Division of Radiology 2, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Alfredo D'Andrea
- Department of Experimental Medicine, Magrassi Lanzara, Luigi Vanvitelli, Second University of Naples, Naples, Italy
| | | | - Corrado Maria Malaspina
- Department of Surgical and Biomedical Sciences, Division of Radiology 2, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Maria Cristina Aisa
- Department of Surgical and Biomedical Sciences, Division of Gynaecology, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Maria Napoletano
- Department of Surgical and Biomedical Sciences, Division of Radiology 2, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Emanuele Orlandi
- Department of Surgical and Biomedical Sciences, Division of Radiology 2, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Valeria Rondoni
- Department of Surgical and Biomedical Sciences, Division of Radiology 2, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy
| | - Pietro Scialpi
- Division of Urology, Portogruaro Hospital, Venice, Italy
| | - Diamante Pacchiarini
- Health Management, S. Maria della Misericordia Hospital, Sant' Andrea delle Fratte, Perugia, Italy
| | - Diego Palladino
- Department of Radiology, Casa Sollievo della Sofferenza Hospital, Foggia, Italy
| | - Michele Dragone
- Department of Radiology, Casa Sollievo della Sofferenza Hospital, Foggia, Italy
| | - Giancarlo Di Renzo
- Department of Surgical and Biomedical Sciences, Division of Gynaecology, Santa Maria della Misericordia Hospital, Perugia University, Sant' Andrea delle Fratte, Perugia, Italy.,3DIFIC, Medical Area, University of Perugia, Perugia, Italy
| | - Annalisa Simeone
- Department of Radiology, Casa Sollievo della Sofferenza Hospital, Foggia, Italy
| | | | - Luca Brunese
- Department of Radiology, Campobasso University, C.da Tappino, Campobasso, Italy
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Fusco R, Sansone M, Granata V, Setola SV, Petrillo A. A systematic review on multiparametric MR imaging in prostate cancer detection. Infect Agent Cancer 2017; 12:57. [PMID: 29093748 PMCID: PMC5663098 DOI: 10.1186/s13027-017-0168-z] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Accepted: 10/23/2017] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Literature data suggest that multi-parametric Magnetic Resonance Imaging (MRI), including morphologic T2-weigthed images (T2-MRI) and functional approaches such as Dynamic Contrast Enhanced-MRI (DCE-MRI), Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopic Imaging (MRSI), give an added value in the prostate cancer localization and local staging. METHODS We performed a systematic review of literature about the role and the potentiality of morphological and functional MRI in prostate cancer, also in a multimodal / multiparametric approach, and we reported the diagnostic accuracy results for different imaging modalities and for different MR coil settings: endorectal coil (ERC) and phased array coil (PAC). Forest plots and receiver operating characteristic curves were performed. Risk of bias and the applicability at study level were calculated. RESULTS Thirty three papers were identified for the systematic review. Sensitivity and specificity values were, respectively, for T2-MRI of 75% and of 60%, for DCE-MRI of 80% and of 72%, for MRSI of 89% and of 69%, for combined T2-MRI and DCE-MRI of 87% and of 46%, for combined T2-MRI and MRSI of 79% and of 57%, for combined T2-MRI, DWI and DCE-MRI of 81% and of 84%, and for combined MRSI and DCE-MRI of 83% and of 83%. For MRI studies performed with ERC we obtained a pooled sensitivity and specificity of 81% and of 66% while the pooled values for MRI studies performed with PAC were of 78% and of 64%, respectively (p>0.05 at McNemar test). No studies were excluded from the analysis based on the quality assessment. CONCLUSIONS ERC use yielded no additional benefit in terms of prostate cancer detection accuracy compared to multi-channel PAC use (71% versus 68%) while the use of additional functional imaging techniques (DCE-MRI, DWI and MRSI) in a multiparametric MRI protocol improves the accuracy of prostate cancer detection allowing both the early cure and the guidance of biopsy.
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Affiliation(s)
- Roberta Fusco
- Radiology Unit, “Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale”, Via Mariano Semmola, Naples, Italy
| | - Mario Sansone
- Department of Electrical Engineering and Information Technologies, University “Federico II” of Naples, Via Claudio, Naples, Italy
| | - Vincenza Granata
- Radiology Unit, “Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale”, Via Mariano Semmola, Naples, Italy
| | - Sergio Venanzio Setola
- Radiology Unit, “Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale”, Via Mariano Semmola, Naples, Italy
| | - Antonella Petrillo
- Radiology Unit, “Dipartimento di supporto ai percorsi oncologici Area Diagnostica, Istituto Nazionale Tumori - IRCCS - Fondazione G. Pascale”, Via Mariano Semmola, Naples, Italy
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Maurer MH, Heverhagen JT. Diffusion weighted imaging of the prostate-principles, application, and advances. Transl Androl Urol 2017; 6:490-498. [PMID: 28725591 PMCID: PMC5503962 DOI: 10.21037/tau.2017.05.06] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
This review article aims to provide an overview on the principles of diffusion-weighted magnetic resonance imaging (DW-MRI) and its applications in the imaging of the prostate. DW-MRI with regards to different applications for prostate cancer (PCa) detection and characterization, local staging as well as for active surveillance (AS) and tumor recurrence after radical prostatectomy (RP) will be discussed. Furthermore, advances in DW-MRI techniques like diffusion kurtosis imaging (DKI) will be presented.
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Affiliation(s)
- Martin H Maurer
- Department of Radiology, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland
| | - Johannes T Heverhagen
- Department of Radiology, Inselspital, Bern University Hospital, University of Bern, Bern 3010, Switzerland
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Wysock JS, Lepor H. Multi-parametric MRI imaging of the prostate-implications for focal therapy. Transl Androl Urol 2017; 6:453-463. [PMID: 28725587 PMCID: PMC5503978 DOI: 10.21037/tau.2017.04.29] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The primary goal of a focal therapy treatment paradigm is to achieve cancer control through targeted tissue destruction while simultaneously limiting deleterious effects on peri-prostatic structures. Focal therapy approaches are employed in several oncologic treatment protocols, and have been shown to provide equivalent cancer control for malignancies such as breast cancer and renal cell carcinoma. Efforts to develop a focal therapy approach for prostate cancer have been challenged by several concepts including the multifocal nature of the disease and limited capability of prostate ultrasound and systematic biopsy to reliably localize the site(s) and aggressiveness of disease. Multi-parametric MRI (mpMRI) of the prostate has significantly improved disease localization, spatial demarcation and risk stratification of cancer detected within the prostate. The accuracy of this imaging modality has further enabled the urologist to improve biopsy approaches using targeted biopsy via MRI-ultrasound fusion. From this foundation, an improved delineation of the location of disease has become possible, providing a critical foundation to the development of a focal therapy strategy. This chapter reviews the accuracy of mpMRI for detection of “aggressive“ disease, the accuracy of mpMRI in determining the tumor volume, and the ability of mpMRI to accurately identify the index lesion. While mpMRI provides a critical, first step in developing a strategy for focal therapy, considerable questions remain regarding the relationship between MR identified tumor volume and pathologic tumor volume, the accuracy and utility of mpMRI for treatment surveillance and the optimal role and timing of follow-up mpMRI.
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Affiliation(s)
- James S Wysock
- Department of Urology, NYU Langone Medical Center, New York University School of Medicine, New York, NY, USA
| | - Herbert Lepor
- Department of Urology, NYU Langone Medical Center, New York University School of Medicine, New York, NY, USA
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Gupta PK, Awasthi R, Singh S, Behari S, Maria Das KJ, Gupta RK, Kumar S. Value of Minimum Apparent Diffusion Coefficient on Magnetic Resonance Imaging as a Biomarker for Predicting Progression of Disease Following Surgery and Radiotherapy in Glial Tumors from a Tertiary Care Center in Northern India. J Neurosci Rural Pract 2017; 8:185-193. [PMID: 28479790 PMCID: PMC5402482 DOI: 10.4103/0976-3147.203823] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Purpose: Studies have shown that cellularity of glial tumors are inversely correlated to minimum apparent diffusion coefficient (ADC) values derived on diffusion-weighted imaging (DWI). The purpose of this prospective exploratory study was to evaluate whether temporal change in “minimum ADC” values during follow-up predict progressive disease in glial tumors post radiotherapy and surgery. Materials and Methods: Adult patients of glial tumors, subjected to surgery followed by Radiotherapy (RT), were included in the study. Serial conventional magnetic resonance imaging with DWI at the following time points – presurgery, pre-RT, post-RT imaging at 3, 7, and 15 months were done. For “minimum ADC” values, multiple regions of interest (ROI) were identified on ADC maps derived from DWI. A mean of 5 minimum ADC values was chosen as “minimum ADC” value. The correlation was drawn between histology and minimum ADC values and time trends were studied. Results: Fourteen patients were included in this study. Histologies were low-grade glioma (LGG) – 5, anaplastic oligodendroglioma (ODG) -5, and glioblastoma multiforme (GBM) – 4. Minimum ADC values were significantly higher in LGG and GBM than ODG. Presurgery, the values were 0.812, 0.633, and 0.787 × 10−3 mm2/s for LGG, ODG, and GBM, respectively. DWI done at the time of RT planning showed values of 0.786, 0.636, 0.869 × 10−3 mm2/s, respectively. During follow-up, the increasing trend of minimum ADC was observed in LGG (P = 0.02). All these patients were clinically and radiologically stable. Anaplastic ODGs, however, showed an initial increase followed by the fall of minimum ADC in all the 5 cases (P = 0.00). Four of the five cases developed progressive disease subsequently. In all the 4 GBM cases, a consistent fall of minimum ADC values was observed (P = 0.00), and they all progressed in spite of RT. Conclusions: The DWI-derived minimum ADC values are an important yet simple quantitative tool to assess the treatment response and disease progression before they are evident on conventional imaging during the follow-up of glial tumors.
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Affiliation(s)
- Pramod Kumar Gupta
- Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - Rishi Awasthi
- Department of Radio Diagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - Shalini Singh
- Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - Sanjay Behari
- Department of Neurosurgery, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - K J Maria Das
- Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - Rakesh Kumar Gupta
- Department of Radio Diagnosis, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
| | - Shaleen Kumar
- Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
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Johnston E, Pye H, Bonet-Carne E, Panagiotaki E, Patel D, Galazi M, Heavey S, Carmona L, Freeman A, Trevisan G, Allen C, Kirkham A, Burling K, Stevens N, Hawkes D, Emberton M, Moore C, Ahmed HU, Atkinson D, Rodriguez-Justo M, Ng T, Alexander D, Whitaker H, Punwani S. INNOVATE: A prospective cohort study combining serum and urinary biomarkers with novel diffusion-weighted magnetic resonance imaging for the prediction and characterization of prostate cancer. BMC Cancer 2016; 16:816. [PMID: 27769214 PMCID: PMC5073433 DOI: 10.1186/s12885-016-2856-2] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Accepted: 10/12/2016] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Whilst multi-parametric magnetic resonance imaging (mp-MRI) has been a significant advance in the diagnosis of prostate cancer, scanning all patients with elevated prostate specific antigen (PSA) levels is considered too costly for widespread National Health Service (NHS) use, as the predictive value of PSA levels for significant disease is poor. Despite the fact that novel blood and urine tests are available which may predict aggressive disease better than PSA, they are not routinely employed due to a lack of clinical validity studies. Furthermore approximately 40 % of mp-MRI studies are reported as indeterminate, which can lead to repeat examinations or unnecessary biopsy with associated patient anxiety, discomfort, risk and additional costs. METHODS/DESIGN We aim to clinically validate a panel of minimally invasive promising blood and urine biomarkers, to better select patients that will benefit from a multiparametric prostate MRI. We will then test whether the performance of the mp-MRI can be improved by the addition of an advanced diffusion-weighted MRI technique, which uses a biophysical model to characterise tissue microstructure called VERDICT; Vascular and Extracellular Restricted Diffusion for Cytometry in Tumours. INNOVATE is a prospective single centre cohort study in 365 patients. mp-MRI will act as the reference standard for the biomarker panel. A clinical outcome based reference standard based on biopsy, mp-MRI and follow-up will be used for VERDICT MRI. DISCUSSION We expect the combined effect of biomarkers and VERDICT MRI will improve care by better detecting aggressive prostate cancer early and make mp-MRI before biopsy economically viable for universal NHS adoption. TRIAL REGISTRATION INNOVATE is registered on ClinicalTrials.gov, with reference NCT02689271 .
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Affiliation(s)
- Edward Johnston
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
| | - Hayley Pye
- Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT UK
- Addenbrookes Hospital, Level 4, Pathology Block, Hills Road, Cambridge, CB20QQ UK
| | | | | | - Dominic Patel
- Department of Research Pathology, UCL Cancer Institute, Rockefeller Building, 21 University Street, London, WC1E 6JJ UK
| | - Myria Galazi
- Molecular Oncology group, UCL Cancer Institute, Paul O’Gorman Building, 72 Huntley Street, London, WC1E 6DD UK
| | - Susan Heavey
- Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT UK
- Addenbrookes Hospital, Level 4, Pathology Block, Hills Road, Cambridge, CB20QQ UK
| | - Lina Carmona
- Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT UK
- Addenbrookes Hospital, Level 4, Pathology Block, Hills Road, Cambridge, CB20QQ UK
| | - Alexander Freeman
- Department of Research Pathology, UCL Cancer Institute, Rockefeller Building, 21 University Street, London, WC1E 6JJ UK
| | - Giorgia Trevisan
- Department of Research Pathology, UCL Cancer Institute, Rockefeller Building, 21 University Street, London, WC1E 6JJ UK
| | - Clare Allen
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
| | - Alexander Kirkham
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
| | - Keith Burling
- Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT UK
- Addenbrookes Hospital, Level 4, Pathology Block, Hills Road, Cambridge, CB20QQ UK
| | - Nicola Stevens
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
| | - David Hawkes
- Department of Computer Science, UCL, Gower Street, London, WC1E 6BT UK
| | - Mark Emberton
- Division of Surgery, 4th floor, 21 University Street, London, WC1E UK
| | - Caroline Moore
- Division of Surgery, 4th floor, 21 University Street, London, WC1E UK
| | - Hashim U Ahmed
- Division of Surgery, 4th floor, 21 University Street, London, WC1E UK
| | - David Atkinson
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
| | - Manuel Rodriguez-Justo
- Department of Research Pathology, UCL Cancer Institute, Rockefeller Building, 21 University Street, London, WC1E 6JJ UK
| | - Tony Ng
- Molecular Oncology group, UCL Cancer Institute, Paul O’Gorman Building, 72 Huntley Street, London, WC1E 6DD UK
| | - Daniel Alexander
- Department of Computer Science, UCL, Gower Street, London, WC1E 6BT UK
| | - Hayley Whitaker
- Research Department for Tissue & Energy, Division of Surgery & Interventional Science, Wing 2.4 Cruciform Building, Gower Street, London, WC1E 6BT UK
- Addenbrookes Hospital, Level 4, Pathology Block, Hills Road, Cambridge, CB20QQ UK
| | - Shonit Punwani
- UCL Centre for Medical Imaging, 5th floor, Wolfson House, 4 Stephenson Way, London, NW1 2HE UK
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El-Samei HAEKA, Amin MF, Hassan EE. Assessment of the accuracy of multi-parametric MRI with PI-RADS 2.0 scoring system in the discrimination of suspicious prostatic focal lesions. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2016. [DOI: 10.1016/j.ejrnm.2016.04.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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De Visschere PJL, Vral A, Perletti G, Pattyn E, Praet M, Magri V, Villeirs GM. Multiparametric magnetic resonance imaging characteristics of normal, benign and malignant conditions in the prostate. Eur Radiol 2016; 27:2095-2109. [DOI: 10.1007/s00330-016-4479-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Revised: 06/16/2016] [Accepted: 06/21/2016] [Indexed: 01/21/2023]
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Gilani N, Malcolm P, Johnson G. A model describing diffusion in prostate cancer. Magn Reson Med 2016; 78:316-326. [PMID: 27439379 DOI: 10.1002/mrm.26340] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2016] [Revised: 06/08/2016] [Accepted: 06/20/2016] [Indexed: 12/15/2022]
Abstract
PURPOSE Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill-defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non-Gaussian behavior of tissue diffusion. METHOD The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two-compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10-fold cross-validation. RESULTS Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature. CONCLUSION A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316-326, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Nima Gilani
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Paul Malcolm
- Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Glyn Johnson
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
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Application of an unsupervised multi-characteristic framework for intermediate-high risk prostate cancer localization using diffusion-weighted MRI. Magn Reson Imaging 2016; 34:1227-1234. [PMID: 27451403 DOI: 10.1016/j.mri.2016.06.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Revised: 06/14/2016] [Accepted: 06/26/2016] [Indexed: 12/22/2022]
Abstract
PURPOSE The aim of this proof-of-concept work is to propose an unsupervised framework that combines multiple parameters, in "positive-if-all-positive" manner, from different models to localize tumors. METHODS A voxel-by-voxel analysis of the DW-MRI images of whole prostate was performed to obtain parametric maps for D*, D, f, and K using the IVIM and kurtosis models. Ten patients with moderate or high-risk prostate cancer were included in study. The mean age and serum PSA for these 10 patients were 65years (range 54-78) and 21.9ng/mL (range 4.84-44.81), respectively. These patients were scanned using a DW spin-echo sequence with echo-planar readout with 16 equidistantly spaced b-values in the range of 0-2000s/mm2 (TE=58ms; TR=3990ms; spatial resolution 2.19×2.19×2.73mm3, slices =26, FOV=140×140mm, slice gap =0.27mm, NSA=2). RESULTS The proposed framework detected 24 lesions of which 14 were true positive with 58% tumor detection rate on lesion-based analysis with sensitivity of 100%. The mpMRI evaluation (PIRADSv2) identified 12 of 14 true positive lesions with sensitivity of 86%; positive predictive value of mpMRI was 92%. The index lesions were visible on all framework maps and were coded as the most suspicious in 9 of 10 patients. CONCLUSION Preliminary results of the proposed framework indicate high patient-based sensitivity with 100% detection rate for identifying moderate-high risk aggressive index lesions.
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Selnæs KM, Vettukattil R, Bertilsson H, Wright AJ, Heerschap A, Angelsen A, Tessem MB, Bathen TF. Tissue Microstructure Is Linked to MRI Parameters and Metabolite Levels in Prostate Cancer. Front Oncol 2016; 6:146. [PMID: 27379208 PMCID: PMC4905954 DOI: 10.3389/fonc.2016.00146] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 05/30/2016] [Indexed: 01/09/2023] Open
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) can portray spatial variations in tumor heterogeneity, architecture, and its microenvironment in a non-destructive way. The objective of this study was to assess the relationship between MRI parameters measured on patients in vivo, individual metabolites measured in prostatectomy tissue ex vivo, and quantitative histopathology. MATERIALS AND METHODS Fresh frozen tissue samples (n = 53 from 15 patients) were extracted from transversal prostate slices and linked to in vivo MR images, allowing spatially matching of ex vivo measured metabolites with in vivo MR parameters. Color-based segmentation of cryosections of each tissue sample was used to identify luminal space, stroma, and nuclei. RESULTS Cancer samples have significantly lower area percentage of lumen and higher area percentage of nuclei than non-cancer samples (p ≤ 0.001). Apparent diffusion coefficient is significantly correlated with percentage area of lumen (ρ = 0.6, p < 0.001) and percentage area of nuclei (ρ = -0.35, p = 0.01). There is a positive correlation (ρ = 0.31, p = 0.053) between citrate and percentage area of lumen. Choline is negatively correlated with lumen (ρ = -0.38, p = 0.02) and positively correlated with percentage area of nuclei (ρ = 0.38, p = 0.02). CONCLUSION Microstructures that are observed by histopathology are linked to MR characteristics and metabolite levels observed in prostate cancer.
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Affiliation(s)
- Kirsten Margrete Selnæs
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway; St. Olavs Hospital, Trondheim, Norway
| | - Riyas Vettukattil
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology , Trondheim , Norway
| | - Helena Bertilsson
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway; Department of Urology, St. Olavs Hospital, Trondheim, Norway
| | - Alan J Wright
- Cancer Research UK Cambridge Institute, University of Cambridge , Cambridge , UK
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center , Nijmegen , Netherlands
| | - Anders Angelsen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology , Trondheim , Norway
| | - May-Britt Tessem
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology , Trondheim , Norway
| | - Tone Frost Bathen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology , Trondheim , Norway
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Henderson DR, de Souza NM, Thomas K, Riches SF, Morgan VA, Sohaib SA, Dearnaley DP, Parker CC, van As NJ. Nine-year Follow-up for a Study of Diffusion-weighted Magnetic Resonance Imaging in a Prospective Prostate Cancer Active Surveillance Cohort. Eur Urol 2016; 69:1028-33. [PMID: 26482887 DOI: 10.1016/j.eururo.2015.10.010] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2015] [Accepted: 10/05/2015] [Indexed: 01/06/2023]
Abstract
BACKGROUND In active surveillance (AS) for prostate cancer there are few data on long-term outcomes associated with novel imaging markers. OBJECTIVE To determine long-term outcomes with respect to the apparent diffusion coefficient (ADC) derived from diffusion-weighted magnetic resonance imaging (DW-MRI) in a prospective AS cohort. Early results have already been published; we now present findings with long-term follow-up. DESIGN, SETTING, AND PARTICIPANTS A subset of patients (n=86) underwent pre-enrolment DW-MRI in a prospective AS study between 2002 and 2006. Inclusion criteria were untreated prostate cancer, clinical T1/T2a/N0M0, Gleason ≤ 3+4, and prostate-specific antigen (PSA) <15 ng/ml. Protocol follow-up was by biopsy at 18-24 mo and then every 24 mo, with regular PSA measurement. INTERVENTION Men underwent baseline DW-MRI in addition to standard sequences. ADC was measured from the index lesion on T2-weighted images. To avoid influencing treatment decisions, DW-MRI sequence results were not available to the AS study investigators. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Baseline ADC was analysed with respect to time to radical treatment (TRT) and time to adverse histology (TAH). Kaplan-Meier analysis and univariate and multivariate regression analyses were performed. RESULTS AND LIMITATIONS The median follow-up was 9.5 yr (interquartile range 7.9-10.0 yr). On univariate analysis, ADC below the median was associated with shorter TAH (hazard ratio [HR] 2.13, 95% confidence interval [CI] 1.17-3.89; p<0.014) and TRT (HR 2.54, 95% CI 1.49-4.32; p<0.001). Median TRT was 9.3 yr (95% CI 7.0-11.6 yr) for patients with ADC above the median and only 2.4 yr (95% CI 1.5-6.0 yr) for ADC below the median. For TRT, addition of ADC to a multivariate model of baseline variables resulted in a significant improvement in model fit (HR 1.33, 95% CI 1.14-1.54; p<0.001). Receiver operating characteristic analysis for TRT revealed an area under the curve of 0.80 (95% CI 0.70-0.88). The number of variables included in the multivariate model was limited by sample size. CONCLUSIONS Long-term follow-up for this study provides strong evidence that ADC is a useful marker when selecting patients for AS. Routine DW-MRI is now being evaluated in our ongoing AS study for initial assessment and as an alternative to repeat biopsy. PATIENT SUMMARY Before entering a study of close monitoring for the initial management of prostate cancer, patients had a type of magnetic resonance imaging scan that looks at the movement of water within cancers. These scans may help in predicting whether patients should receive close monitoring or whether immediate treatment should be given.
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Affiliation(s)
- Daniel R Henderson
- Academic Urology Unit, Royal Marsden NHS Foundation Trust, London, UK; Institute of Cancer Research, London, UK
| | - Nandita M de Souza
- Institute of Cancer Research, London, UK; Department of Radiology, Royal Marsden NHS Foundation Trust, London, UK
| | - Karen Thomas
- Academic Urology Unit, Royal Marsden NHS Foundation Trust, London, UK
| | - Sophie F Riches
- Institute of Cancer Research, London, UK; Department of Radiology, Royal Marsden NHS Foundation Trust, London, UK
| | - Veronica A Morgan
- Institute of Cancer Research, London, UK; Department of Radiology, Royal Marsden NHS Foundation Trust, London, UK
| | - Syed A Sohaib
- Institute of Cancer Research, London, UK; Department of Radiology, Royal Marsden NHS Foundation Trust, London, UK
| | - David P Dearnaley
- Academic Urology Unit, Royal Marsden NHS Foundation Trust, London, UK; Institute of Cancer Research, London, UK
| | - Christopher C Parker
- Academic Urology Unit, Royal Marsden NHS Foundation Trust, London, UK; Institute of Cancer Research, London, UK
| | - Nicholas J van As
- Academic Urology Unit, Royal Marsden NHS Foundation Trust, London, UK; Institute of Cancer Research, London, UK.
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Multiparametric MRI of the anterior prostate gland: clinical–radiological–histopathological correlation. Clin Radiol 2016; 71:405-17. [DOI: 10.1016/j.crad.2016.01.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2015] [Revised: 08/19/2015] [Accepted: 01/04/2016] [Indexed: 11/19/2022]
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What can particle therapy add to the treatment of prostate cancer? Phys Med 2016; 32:485-91. [DOI: 10.1016/j.ejmp.2016.03.017] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 03/19/2016] [Accepted: 03/21/2016] [Indexed: 11/19/2022] Open
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De Visschere PJL, Briganti A, Fütterer JJ, Ghadjar P, Isbarn H, Massard C, Ost P, Sooriakumaran P, Surcel CI, Valerio M, van den Bergh RCN, Ploussard G, Giannarini G, Villeirs GM. Role of multiparametric magnetic resonance imaging in early detection of prostate cancer. Insights Imaging 2016; 7:205-14. [PMID: 26847758 PMCID: PMC4805618 DOI: 10.1007/s13244-016-0466-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 01/07/2016] [Accepted: 01/20/2016] [Indexed: 11/30/2022] Open
Abstract
Abstract Most prostate cancers (PC) are currently found on the basis of an elevated PSA, although this biomarker has only moderate accuracy. Histological confirmation is traditionally obtained by random transrectal ultrasound guided biopsy, but this approach may underestimate PC. It is generally accepted that a clinically significant PC requires treatment, but in case of an non-significant PC, deferment of treatment and inclusion in an active surveillance program is a valid option. The implementation of multiparametric magnetic resonance imaging (mpMRI) into a screening program may reduce the risk of overdetection of non-significant PC and improve the early detection of clinically significant PC. A mpMRI consists of T2-weighted images supplemented with diffusion-weighted imaging, dynamic contrast enhanced imaging, and/or magnetic resonance spectroscopic imaging and is preferably performed and reported according to the uniform quality standards of the Prostate Imaging Reporting and Data System (PIRADS). International guidelines currently recommend mpMRI in patients with persistently rising PSA and previous negative biopsies, but mpMRI may also be used before first biopsy to improve the biopsy yield by targeting suspicious lesions or to assist in the selection of low-risk patients in whom consideration could be given for surveillance. Teaching Points • MpMRI may be used to detect or exclude significant prostate cancer. • MpMRI can guide targeted rebiopsy in patients with previous negative biopsies. • In patients with negative mpMRI consideration could be given for surveillance. • MpMRI may add valuable information for the optimal treatment selection.
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Affiliation(s)
| | - Alberto Briganti
- Department of Urology, Urological Research Institute, Vita-Salute University San Raffaele, Milan, Italy
| | - Jurgen J Fütterer
- Department of Radiology and Nuclear Medicine, Radboud UMC, Nijmegen, The Netherlands
| | - Pirus Ghadjar
- Department of Radiation Oncology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Hendrik Isbarn
- Department of Urology, Regio Clinic Wedel, Wedel, Germany.,Department of Urology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Christophe Massard
- Department of Oncology, Institut Gustave Roussy, University of Paris Sud, Villejuif, France
| | - Piet Ost
- Department of Radiation Oncology and Experimental Cancer Research, Ghent University Hospital, Ghent, Belgium
| | - Prasanna Sooriakumaran
- Surgical Intervention Trials Unit, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK.,Department of Molecular Medicine & Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Cristian I Surcel
- Centre of Urological Surgery, Dialysis and Renal Transplantation, Fundeni Clinical Institute, Bucharest, Romania
| | | | | | - Guillaume Ploussard
- Urology Department, Saint Jean Languedoc Hospital, Toulouse, France.,Research Unit INSERM U955, Paris Est University, Team 7, Paris, France
| | - Gianluca Giannarini
- Urology Unit, Academic Medical Centre Hospital «Santa Maria della Misericordia», Udine, Italy
| | - Geert M Villeirs
- Department of Radiology, Ghent University Hospital, De Pintelaan 185, 9000, Ghent, Belgium
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Jafar MM, Parsai A, Miquel ME. Diffusion-weighted magnetic resonance imaging in cancer: Reported apparent diffusion coefficients, in-vitro and in-vivo reproducibility. World J Radiol 2016; 8:21-49. [PMID: 26834942 PMCID: PMC4731347 DOI: 10.4329/wjr.v8.i1.21] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 11/10/2015] [Accepted: 12/07/2015] [Indexed: 02/06/2023] Open
Abstract
There is considerable disparity in the published apparent diffusion coefficient (ADC) values across different anatomies. Institutions are increasingly assessing repeatability and reproducibility of the derived ADC to determine its variation, which could potentially be used as an indicator in determining tumour aggressiveness or assessing tumour response. In this manuscript, a review of selected articles published to date in healthy extra-cranial body diffusion-weighted magnetic resonance imaging is presented, detailing reported ADC values and discussing their variation across different studies. In total 115 studies were selected including 28 for liver parenchyma, 15 for kidney (renal parenchyma), 14 for spleen, 13 for pancreatic body, 6 for gallbladder, 13 for prostate, 13 for uterus (endometrium, myometrium, cervix) and 13 for fibroglandular breast tissue. Median ADC values in selected studies were found to be 1.28 × 10(-3) mm(2)/s in liver, 1.94 × 10(-3) mm(2)/s in kidney, 1.60 × 10(-3) mm(2)/s in pancreatic body, 0.85 × 10(-3) mm(2)/s in spleen, 2.73 × 10(-3) mm(2)/s in gallbladder, 1.64 × 10(-3) mm(2)/s and 1.31 × 10(-3) mm(2)/s in prostate peripheral zone and central gland respectively (combined median value of 1.54×10(-3) mm(2)/s), 1.44 × 10(-3) mm(2)/s in endometrium, 1.53 × 10(-3) mm(2)/s in myometrium, 1.71 × 10(-3) mm(2)/s in cervix and 1.92 × 10(-3) mm(2)/s in breast. In addition, six phantom studies and thirteen in vivo studies were summarized to compare repeatability and reproducibility of the measured ADC. All selected phantom studies demonstrated lower intra-scanner and inter-scanner variation compared to in vivo studies. Based on the findings of this manuscript, it is recommended that protocols need to be optimised for the body part studied and that system-induced variability must be established using a standardized phantom in any clinical study. Reproducibility of the measured ADC must also be assessed in a volunteer population, as variations are far more significant in vivo compared with phantom studies.
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Zidan S, Tantawy HI. Prostate carcinoma: Accuracy of diagnosis and differentiation with Dynamic Contrast-Enhanced MRI and Diffusion Weighted Imaging. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2015. [DOI: 10.1016/j.ejrnm.2015.06.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
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Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images. Proc Natl Acad Sci U S A 2015; 112:E6265-73. [PMID: 26578786 DOI: 10.1073/pnas.1505935112] [Citation(s) in RCA: 273] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification of prostate cancer aggressiveness by combining apparent diffusion coefficient (ADC) and T2-weighted (T2-w) MRI-based texture features. Our approach achieved reasonably accurate classification of Gleason scores (GS) 6(3 + 3) vs. ≥7 and 7(3 + 4) vs. 7(4 + 3) despite the presence of highly unbalanced samples by using two different sample augmentation techniques followed by feature selection-based classification. Our method distinguished between GS 6(3 + 3) and ≥7 cancers with 93% accuracy for cancers occurring in both peripheral (PZ) and transition (TZ) zones and 92% for cancers occurring in the PZ alone. Our approach distinguished the GS 7(3 + 4) from GS 7(4 + 3) with 92% accuracy for cancers occurring in both the PZ and TZ and with 93% for cancers occurring in the PZ alone. In comparison, a classifier using only the ADC mean achieved a top accuracy of 58% for distinguishing GS 6(3 + 3) vs. GS ≥7 for cancers occurring in PZ and TZ and 63% for cancers occurring in PZ alone. The same classifier achieved an accuracy of 59% for distinguishing GS 7(3 + 4) from GS 7(4 + 3) occurring in the PZ and TZ and 60% for cancers occurring in PZ alone. Separate analysis of the cancers occurring in TZ alone was not performed owing to the limited number of samples. Our results suggest that texture features derived from ADC and T2-w MRI together with sample augmentation can help to obtain reasonably accurate classification of Gleason patterns.
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Kobus T, van der Laak JAWM, Maas MC, Hambrock T, Bruggink CC, Hulsbergen-van de Kaa CA, Scheenen TWJ, Heerschap A. Contribution of Histopathologic Tissue Composition to Quantitative MR Spectroscopy and Diffusion-weighted Imaging of the Prostate. Radiology 2015; 278:801-11. [PMID: 26418614 DOI: 10.1148/radiol.2015142889] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE To determine associations of metabolite levels derived from magnetic resonance (MR) spectroscopic imaging (ie, hydrogen 1 [(1)H] MR spectroscopic imaging) and apparent diffusion coefficients (ADCs) from diffusion-weighted imaging with prostate tissue composition assessed by digital image analysis of histologic sections. MATERIALS AND METHODS Institutional ethical review board approved this retrospective study and waived informed consent. Fifty-seven prostate cancer patients underwent an MR examination followed by prostatectomy. One hematoxylin and eosin-stained section of the resected prostate per patient was digitized and computationally segmented into nuclei, lumen, and combination of epithelial cytoplasm and stroma. On each stained section, regions of interest (ROIs) were chosen and matched to the corresponding ADC map and (1)H MR spectroscopic imaging voxels. ADC and two metabolite ratios (citrate [Cit], spermine [Spm], and creatine [Cr] to choline [Cho] and Cho to Cr plus Spm) were correlated with percentage areas of nuclei, lumen, and cytoplasm and stroma for peripheral zone (PZ), transition zone (TZ), and tumor tissue in both zones of the prostate by using a linear mixed-effect model and Spearman correlation coefficient (ρ). RESULTS ADC and (Cit + Spm + Cr)/Cho ratio showed positive correlation with percentage area of lumen (ρ = 0.43 and 0.50, respectively) and negative correlation with percentage area of nuclei (ρ = -0.29 and -0.26, respectively). The Cho/(Cr + Spm) ratio showed negative association with percentage area of lumen (ρ = -0.40) and positive association with area of nuclei (ρ = 0.26). Percentage areas of lumen and nuclei, (Cit + Spm + Cr)/Cho ratio, and ADC were significantly different (P < .001) between benign PZ (23.7 and 7.7, 8.83, and 1.58 × 10(-3) mm(2)/sec, respectively) and tumor PZ tissue (11.4 and 12.5, 5.13, and 1.20 × 10(-3) mm(2)/sec, respectively). These parameters were also significantly different between benign TZ (20.0 and 8.2, 6.50, and 1.26 × 10(-3) mm(2)/sec, respectively) and tumor TZ tissue (9.8 and 11.2, 4.36, and 1.03 × 10(-3) mm(2)/sec, respectively). CONCLUSION The observed correlation of (Cit + Spm + Cr)/Cho ratio and ADC of the prostate with its tissue composition indicates that components of this composition, such as percentage luminal area, contribute to the value of these MR parameters.
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Affiliation(s)
- Thiele Kobus
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Jeroen A W M van der Laak
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Marnix C Maas
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Thomas Hambrock
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Caroline C Bruggink
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Christina A Hulsbergen-van de Kaa
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Tom W J Scheenen
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
| | - Arend Heerschap
- From the Department of Radiology and Nuclear Medicine (T.K., M.C.M., T.H., C.C.B., T.W.J.S., A.H.) and Department of Pathology (J.A.W.M.v.d.L., C.A.H.v.d.K.), Radboud University Medical Center, Geert Grooteplein 10, 6525 GA Nijmegen, the Netherlands
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