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Liu X, Ji Z, Zhang L, Li L, Xu W, Su Q. Prediction of pathological complete response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer using 18F-FDG PET radiomics features of primary tumour and lymph nodes. BMC Cancer 2025; 25:520. [PMID: 40119358 PMCID: PMC11929329 DOI: 10.1186/s12885-025-13905-7] [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: 12/05/2024] [Accepted: 03/10/2025] [Indexed: 03/24/2025] Open
Abstract
BACKGROUND Predicting the response to neoadjuvant chemoimmunotherapy in patients with resectable non-small cell lung cancer (NSCLC) facilitates clinical treatment decisions. Our study aimed to establish a machine learning model that accurately predicts the pathological complete response (pCR) using 18F-FDG PET radiomics features. METHODS We retrospectively included 210 patients with NSCLC who completed neoadjuvant chemoimmunotherapy and subsequently underwent surgery with pathological results, categorising them into a training set of 147 patients and a test set of 63 patients. Radiomic features were extracted from the primary tumour and lymph nodes. Using 10-fold cross-validation with the least absolute shrinkage and selection operator method, we identified the most impactful radiomic features. The clinical features were screened using univariate and multivariate analyses. Machine learning models were developed using the random forest method, leading to the establishment of one clinical feature model, one primary tumour radiomics model, and two fusion radiomics models. The performance of these models was evaluated based on the area under the curve (AUC). RESULTS In the training set, the three radiomic models showed comparable AUC values, ranging from 0.901 to 0.925. The clinical model underperformed, with an AUC of 0.677. In the test set, the Fusion_LN1LN2 model achieved the highest AUC (0.823), closely followed by the Fusion_Lnall model with an AUC of 0.729. The primary tumour model achieved a moderate AUC of 0.666, whereas the clinical model had the lowest AUC at 0.631. Additionally, the Fusion_LN1LN2 model demonstrated positive net reclassification improvement and integrated discrimination improvement values compared with the other models, and we employed the SHapley Additive exPlanations methodology to interpret the results of our optimal model. CONCLUSIONS Our fusion radiomics model, based on 18F-FDG-PET, will assist clinicians in predicting pCR before neoadjuvant chemoimmunotherapy for patients with resectable NSCLC.
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Affiliation(s)
- Xingbiao Liu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Huanhuxi Road, Hexi Distinct, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Zhilin Ji
- Department of Radiology, Tianjin Hospital, Jiefangnan Road, Hexi District, Tianjin, 300211, China
| | - Libo Zhang
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Huanhuxi Road, Hexi Distinct, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Linlin Li
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Huanhuxi Road, Hexi Distinct, Tianjin, 300060, China
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Wengui Xu
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Huanhuxi Road, Hexi Distinct, Tianjin, 300060, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
| | - Qian Su
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Huanhuxi Road, Hexi Distinct, Tianjin, 300060, China.
- Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
- Key Laboratory of Cancer Prevention and Therapy, Tianjin, China.
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Ozkul O, Sever IH, Ozkul B. Assessment of Apparent Diffusion Coefficient Parameters and Coefficient of Variance in Discrimination of Receptor Status and Molecular Subtypes of Breast Cancer. Curr Med Imaging 2024; 20:e060923220760. [PMID: 37691204 DOI: 10.2174/1573405620666230906092253] [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: 02/13/2023] [Revised: 07/02/2023] [Accepted: 07/26/2023] [Indexed: 09/12/2023]
Abstract
OBJECTIVE The objective of this study was to investigate the diagnostic power of apparent diffusion coefficient/coefficient of variance (ADCcV) as well as ADC parameters formed based on magnetic resonance images (MRI) in the distinction of molecular breast cancer subtypes. METHODS The study involved 205 patients who had breast cancer at stages 1-3. Estrogen receptor (EsR), progesterone receptor (PrR), human epidermal growth factor receptor 2 (Her2), and proliferation index (Ki-67) were histologically analyzed in the tumor. The correlations between the immunohistochemistry and intrinsic subtypes were analyzed using ADC and ADCcV. RESULTS The maximum whole tumor (WTu) ADC (p=0.004), minimum WTu ADC (p<0.001), and mean WTu ADC (p<0.001) values were significantly smaller in the EsR-positive tumors than those in the EsR-negative tumors. Compared to the PrR-negative tumors, the PrR-positive tumors showed significantly smaller maximum, minimum, and mean WTu ADC values (p=0.005, p=0.001, and p<0.001, respectively). In the comparisons of the molecular subtypes in terms of ADCcV, the p-values indicated statistically significant differences between the luminal A (lumA) group and the triple negative (TN) group, between the luminal B (lumB) group and the TN group, and between the Her2-enriched and TN groups (p<0.001, p=0.011, and p=0.004, respectively). Considering the luminal and non-luminal groups, while a significant difference was observed between the groups considering their minimum, maximum, and mean WTu ADC values, their ADCcV values were similar (p<0.001, p=0.004, and p<0.001, respectively). CONCLUSION Using ADCcV in addition to ADC parameters increased the diagnostic power of diffusion weighted-MRI (DW-MRI) in the distinction of molecular subtypes of breast cancer.
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Affiliation(s)
- Ozlem Ozkul
- Istanbul Aydin University, Medicalpark Hospital, Department of Oncology, Akasya sok. No:4 Kucukcekmece/Istanbul, Turkey
| | - Ibrahim Halil Sever
- Demiroglu Bilim University, Department of Radiology, İzzetpasa mah. Abide-i Hurriyet cad. No:166 Sisli/Istanbul, Turkey
| | - Bahattin Ozkul
- Istanbul Atlas University Medicine Hospital, Department of Radiology, Hamidiye mah. Anadolu cad. No:40 Kagithane/Istanbul-Turkey
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Sokmen BK, Inan N. 18 F-FDG PET/MRI of Primary Hepatic Malignancies: Differential Diagnosis and Histologic Grading. Curr Med Imaging 2024; 20:e080523216636. [PMID: 37157218 DOI: 10.2174/1573405620666230508105758] [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: 09/28/2022] [Revised: 03/02/2023] [Accepted: 03/10/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Distinguishing between IHCC and HCC is important because of their differences in treatment and prognosis. The hybrid Positron Emission Tomography/magnetic Resonance Imaging (PET/MRI) system has become more widely accessible, with oncological imaging becoming one of its most promising applications. OBJECTIVE The objective of this study was to see how well 18F-fluorodeoxyglucose (18F-FDG) PET/MRI could be used for differential diagnosis and histologic grading of primary hepatic malignancies. METHODS We retrospectively evaluated 64 patients (53 patients with HCC, 11 patients with IHCC) with histologically proven primary hepatic malignancies using 18F-FDG/MRI. The Apparent Diffusion Coefficient (ADC), Coefficient of Variance (CV) of the ADC, and standardized uptake value (SUV) were calculated. RESULTS The mean SUVmax value was higher for IHCC (7.7 ± 3.4) than for HCC (5.2 ± 3.1) (p = 0.019). The area under the curve (AUC) was 0.737, an optimal 6.98 cut-off value providing 72% sensitivity and 79% specificity. The ADCcv value in IHCC was statistically significantly higher than in HCC (p=0.014). ADC mean values in HCCs were significantly higher in low-grade tumors than in high-grade tumors. The AUC value was 0.73, and the optimal cut-off point was 1.20x10-6 mm2/s, giving 62% sensitivity and 72% specificity. The SUVmax value was also found to be statistically significantly higher in the high-grade group. The ADCcv value in the HCC low-grade group was found to be lower than in the highgrade group (p=0.036). CONCLUSION 18F FDG PET/MRI is a novel imaging technique that can aid in the differentiation of primary hepatic neoplasms as well as tumor-grade estimation.
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Affiliation(s)
| | - Nagihan Inan
- Department of Radiology, Demiroglu Bilim University, Istanbul Florence Nightingale Hospital, Istanbul, Turkey
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Falahatpour Z, Geramifar P, Mahdavi SR, Abdollahi H, Salimi Y, Nikoofar A, Ay MR. Potential advantages of FDG-PET radiomic feature map for target volume delineation in lung cancer radiotherapy. J Appl Clin Med Phys 2022; 23:e13696. [PMID: 35699200 PMCID: PMC9512354 DOI: 10.1002/acm2.13696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 04/20/2022] [Accepted: 05/27/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To investigate the potential benefits of FDG PET radiomic feature maps (RFMs) for target delineation in non-small cell lung cancer (NSCLC) radiotherapy. METHODS Thirty-two NSCLC patients undergoing FDG PET/CT imaging were included. For each patient, nine grey-level co-occurrence matrix (GLCM) RFMs were generated. gross target volume (GTV) and clinical target volume (CTV) were contoured on CT (GTVCT , CTVCT ), PET (GTVPET40 , CTVPET40 ), and RFMs (GTVRFM , CTVRFM ,). Intratumoral heterogeneity areas were segmented as GTVPET50-Boost and radiomic boost target volume (RTVBoost ) on PET and RFMs, respectively. GTVCT in homogenous tumors and GTVPET40 in heterogeneous tumors were considered as GTVgold standard (GTVGS ). One-way analysis of variance was conducted to determine the threshold that finds the best conformity for GTVRFM with GTVGS . Dice similarity coefficient (DSC) and mean absolute percent error (MAPE) were calculated. Linear regression analysis was employed to report the correlations between the gold standard and RFM-derived target volumes. RESULTS Entropy, contrast, and Haralick correlation (H-correlation) were selected for tumor segmentation. The threshold values of 80%, 50%, and 10% have the best conformity of GTVRFM-entropy , GTVRFM-contrast , and GTVRFM-H-correlation with GTVGS , respectively. The linear regression results showed a positive correlation between GTVGS and GTVRFM-entropy (r = 0.98, p < 0.001), between GTVGS and GTVRFM-contrast (r = 0.93, p < 0.001), and between GTVGS and GTVRFM-H-correlation (r = 0.91, p < 0.001). The average threshold values of 45% and 15% were resulted in the best segmentation matching between CTVRFM-entropy and CTVRFM-contrast with CTVGS , respectively. Moreover, we used RFM to determine RTVBoost in the heterogeneous tumors. Comparison of RTVBoost with GTVPET50-Boost MAPE showed the volume error differences of 31.7%, 36%, and 34.7% in RTVBoost-entropy , RTVBoost-contrast , and RTVBoost-H-correlation , respectively. CONCLUSIONS FDG PET-based radiomics features in NSCLC demonstrated a promising potential for decision support in radiotherapy, helping radiation oncologists delineate tumors and generate accurate segmentation for heterogeneous region of tumors.
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Affiliation(s)
- Zahra Falahatpour
- Department of Medical Physics, Tehran University of Medical Sciences, Tehran, Iran
| | - Parham Geramifar
- Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Rabie Mahdavi
- Department of Medical Physics, Faculty of Medical Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Abdollahi
- Department of Radiology Technology, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran
| | - Yazdan Salimi
- Department of Biomedical Engineering and Medical Physics, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Alireza Nikoofar
- Department of Radiation Oncology, Faculty of Medical Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Ay
- Department of Medical Physics, Tehran University of Medical Sciences, Tehran, Iran
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Nardone V, Boldrini L, Grassi R, Franceschini D, Morelli I, Becherini C, Loi M, Greto D, Desideri I. Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment. Cancers (Basel) 2021; 13:3590. [PMID: 34298803 PMCID: PMC8303203 DOI: 10.3390/cancers13143590] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 07/12/2021] [Accepted: 07/14/2021] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION Neoadjuvant radiotherapy is currently used mainly in locally advanced rectal cancer and sarcoma and in a subset of non-small cell lung cancer and esophageal cancer, whereas in other diseases it is under investigation. The evaluation of the efficacy of the induction strategy is made possible by performing imaging investigations before and after the neoadjuvant therapy and is usually challenging. In the last decade, texture analysis (TA) has been developed to help the radiologist to quantify and identify the parameters related to tumor heterogeneity, which cannot be appreciated by the naked eye. The aim of this narrative is to review the impact of TA on the prediction of response to neoadjuvant radiotherapy and or chemoradiotherapy. MATERIALS AND METHODS Key references were derived from a PubMed query. Hand searching and ClinicalTrials.gov were also used. RESULTS This paper contains a narrative report and a critical discussion of radiomics approaches in different fields of neoadjuvant radiotherapy, including esophageal cancer, lung cancer, sarcoma, and rectal cancer. CONCLUSIONS Radiomics can shed a light on the setting of neoadjuvant therapies that can be used to tailor subsequent approaches or even to avoid surgery in the future. At the same, these results need to be validated in prospective and multicenter trials.
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Affiliation(s)
- Valerio Nardone
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (V.N.); (R.G.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Luca Boldrini
- Radiation Oncology Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy;
| | - Roberta Grassi
- Department of Precision Medicine, University of Campania “L. Vanvitelli”, 80138 Naples, Italy; (V.N.); (R.G.)
- Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy
| | - Davide Franceschini
- Radiotherapy and Radiosurgery Department, IRCCS Humanitas Research Hospital, via Manzoni 56, 20089 Milan, Italy;
| | - Ilaria Morelli
- Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy;
| | - Carlotta Becherini
- Department of Biomedical, Experimental and Clinical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy;
| | - Mauro Loi
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
| | - Daniela Greto
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
| | - Isacco Desideri
- Radiation Oncology Unit, Azienda Ospedaliero Universitaria Careggi, 50139 Florence, Italy; (M.L.); (D.G.); (I.D.)
- Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, 50134 Florence, Italy
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A Systematic Review of PET Textural Analysis and Radiomics in Cancer. Diagnostics (Basel) 2021; 11:diagnostics11020380. [PMID: 33672285 PMCID: PMC7926413 DOI: 10.3390/diagnostics11020380] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 02/10/2021] [Accepted: 02/19/2021] [Indexed: 12/12/2022] Open
Abstract
Background: Although many works have supported the utility of PET radiomics, several authors have raised concerns over the robustness and replicability of the results. This study aimed to perform a systematic review on the topic of PET radiomics and the used methodologies. Methods: PubMed was searched up to 15 October 2020. Original research articles based on human data specifying at least one tumor type and PET image were included, excluding those that apply only first-order statistics and those including fewer than 20 patients. Each publication, cancer type, objective and several methodological parameters (number of patients and features, validation approach, among other things) were extracted. Results: A total of 290 studies were included. Lung (28%) and head and neck (24%) were the most studied cancers. The most common objective was prognosis/treatment response (46%), followed by diagnosis/staging (21%), tumor characterization (18%) and technical evaluations (15%). The average number of patients included was 114 (median = 71; range 20–1419), and the average number of high-order features calculated per study was 31 (median = 26, range 1–286). Conclusions: PET radiomics is a promising field, but the number of patients in most publications is insufficient, and very few papers perform in-depth validations. The role of standardization initiatives will be crucial in the upcoming years.
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Gopal A, Xi Y, Subramaniam RM, Pinho DF. Intratumoral Metabolic Heterogeneity and Other Quantitative 18F-FDG PET/CT Parameters for Prognosis Prediction in Esophageal Cancer. Radiol Imaging Cancer 2021; 3:e200022. [PMID: 33778756 PMCID: PMC7983774 DOI: 10.1148/rycan.2020200022] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 09/04/2020] [Accepted: 09/16/2020] [Indexed: 06/12/2023]
Abstract
PURPOSE To evaluate the impact of intratumoral metabolic heterogeneity (IMH) and other quantitative fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT parameters for predicting progression-free survival (PFS) and overall survival (OS) in patients with esophageal cancer. MATERIALS AND METHODS In this retrospective study, an automated gradient-based segmentation method was used to assess the maximum standardized uptake value, mean standardized uptake value, metabolic tumor volume (MTV), and IMH index of the primary tumor in patients with biopsy-proven adenocarcinoma or squamous cell carcinoma of the esophagus with an initial staging 18F-FDG PET/CT. Data were collected between July 2006 and February 2016. OS and PFS were calculated using multivariable Cox proportional hazards regression with the adjustment (as covariates) of age, sex, weight, stage, tumor type, tumor grade, and treatment. All PET parameters were standardized before analysis. Log-rank tests were performed, and corresponding Kaplan-Meier survival plots were generated. RESULTS A total of 71 patients (mean age, 64 years ± 10 [standard deviation], 62:9 men:women) were included. Median follow-up time was 28.2 months (range, 4-38 months), and median survival was 16.1 months (range, 0.1-60.3 months). Higher MTV was associated with reduced PFS for every standard deviation increase (hazard ratio [HR], 0.193; 95% CI: 0.052, 0.711; P = .01). Higher IMH was associated with reduced PFS for every standard deviation decrease in the area under the curve (HR, 10.78; 95% CI: 1.31, 88.96; P = .03). CONCLUSION PFS for patients with esophageal cancer was associated with MTV and with IMH.Keywords: Esophagus, Neoplasms-Primary, PET/CT, Tumor Response © RSNA, 2020.
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Guan Y, Wang J, Cao F, Chen X, Wang Y, Jiang S, Zhang D, Zhang W, Guo Z, Wang P, Pang Q. Role of clip markers placed by endoscopic ultrasonography in contouring gross tumor volume for thoracic esophageal squamous cell carcinoma: one prospective study. ANNALS OF TRANSLATIONAL MEDICINE 2020; 8:1144. [PMID: 33240993 PMCID: PMC7576083 DOI: 10.21037/atm-20-4030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background We aimed to analyze the value of metal clip markers guided and placed by endoscopic ultrasonography (EUS) in the delineation of gross tumor volume (GTV) for thoracic esophageal squamous cell carcinoma. Methods From September 2016 to September 2018, patients with thoracic esophageal squamous cell carcinoma in Tianjin Medical University Cancer Institute and Hospital were recruited in the prospective trial, NCT02959385. They underwent titanium clips placement on tumor superior and inferior boundaries under EUS by a single expert endosonographer before radiotherapy computed tomography (CT) simulation. According to the clip markers, the reference GTVs were contoured by one experienced radiation oncologist. With the help of the Eclipse treatment planning system, clip markers on CT were concealed. Afterward, two other radiation oncologists with expertise in esophageal cancer delineated GTVs, defined as conventional GTVs, based on endoscopy and barium radiography findings. The two GTVs were compared and analyzed. Subgroup analysis was conducted in different T stage [early (T1 + T2) vs. advanced (T3 + T4)], focus location (upper vs. middle vs. lower segment), and tumor length (<5 vs. >5 cm) groups. Results The trial recruited 55 patients with 60 thoracic esophageal cancer foci. A total of 111 titanium clips were guided and implanted by EUS. Before CT simulation, two titanium clips at two foci fell off. After the procedure, no case of intolerable esophageal pain, hemorrhage, or perforation occurred. Compared to reference GTVs’, discrepancies of conventional GTVs’ superior borders were 0.91±0.82 cm (P<0.001), while differences of inferior borders were 0.74±0.63 cm (P<0.001). On the contrary, conventional GTVs’ lengths were not significantly different from reference GTVs’ with discrepancies 0.08±1.30 cm (P=0.64). Regardless of T stage, tumor location, and tumor length, conventional GTVs’ superior and inferior borders were significantly different from reference GTVs’, while GTVs’ lengths differed insignificantly. Conclusions This study confirmed that EUS-placed titanium clips could correct contouring of GTVs in thoracic esophageal cancer in different T stages, tumor locations, and lengths.
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Affiliation(s)
- Yong Guan
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Jing Wang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Fuliang Cao
- Department of Endoscopy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Xi Chen
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Yuwen Wang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Shengpeng Jiang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Daguang Zhang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Wencheng Zhang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Zhoubo Guo
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Ping Wang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
| | - Qingsong Pang
- Department of Radiotherapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Preventing and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
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[F18] FDG-PET/CT for manual or semiautomated GTV delineation of the primary tumor for radiation therapy planning in patients with esophageal cancer: is it useful? Strahlenther Onkol 2020; 197:780-790. [PMID: 33104815 PMCID: PMC8397654 DOI: 10.1007/s00066-020-01701-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 09/29/2020] [Indexed: 11/15/2022]
Abstract
Background Target volume definition of the primary tumor in esophageal cancer is usually based on computed tomography (CT) supported by endoscopy and/or endoscopic ultrasound and can be difficult given the low soft-tissue contrast of CT resulting in large interobserver variability. We evaluated the value of a dedicated planning [F18] FDG-Positron emission tomography/computer tomography (PET/CT) for harmonization of gross tumor volume (GTV) delineation and the feasibility of semiautomated structures for planning purposes in a large cohort. Methods Patients receiving a dedicated planning [F18] FDG-PET/CT (06/2011–03/2016) were included. GTV was delineated on CT and on PET/CT (GTVCT and GTVPET/CT, respectively) by three independent radiation oncologists. Interobserver variability was evaluated by comparison of mean GTV and mean tumor lengths, and via Sørensen–Dice coefficients (DSC) for spatial overlap. Semiautomated volumes were constructed based on PET/CT using fixed standardized uptake values (SUV) thresholds (SUV30, 35, and 40) or background- and metabolically corrected PERCIST-TLG and Schaefer algorithms, and compared to manually delineated volumes. Results 45 cases were evaluated. Mean GTVCT and GTVPET/CT were 59.2/58.0 ml, 65.4/64.1 ml, and 60.4/59.2 ml for observers A–C. No significant difference between CT- and PET/CT-based delineation was found comparing the mean volumes or lengths. Mean Dice coefficients on CT and PET/CT were 0.79/0.77, 0.81/0.78, and 0.8/0.78 for observer pairs AB, AC, and BC, respectively, with no significant differences. Mean GTV volumes delineated semiautomatically with SUV30/SUV35/SUV40/Schaefer’s and PERCIST-TLG threshold were 69.1/23.9/18.8/18.6 and 70.9 ml. The best concordance of a semiautomatically delineated structure with the manually delineated GTVCT/GTVPET/CT was observed for PERCIST-TLG. Conclusion We were not able to show that the integration of PET/CT for GTV delineation of the primary tumor resulted in reduced interobserver variability. The PERCIST-TLG algorithm seemed most promising compared to other thresholds for further evaluation of semiautomated delineation of esophageal cancer.
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Zhang Q, Lou Y, Bai XL, Liang TB. Intratumoral heterogeneity of hepatocellular carcinoma: From single-cell to population-based studies. World J Gastroenterol 2020; 26:3720-3736. [PMID: 32774053 PMCID: PMC7383842 DOI: 10.3748/wjg.v26.i26.3720] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 06/02/2020] [Accepted: 06/18/2020] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is characterized by high heterogeneity in both intratumoral and interpatient manners. While interpatient heterogeneity is related to personalized therapy, intratumoral heterogeneity (ITH) largely influences the efficacy of therapies in individuals. ITH contributes to tumor growth, metastasis, recurrence, and drug resistance and consequently limits the prognosis of patients with HCC. There is an urgent need to understand the causes, characteristics, and consequences of tumor heterogeneity in HCC for the purposes of guiding clinical practice and improving survival. Here, we summarize the studies and technologies that describe ITH in HCC to gain insight into the origin and evolutionary process of heterogeneity. In parallel, evidence is collected to delineate the dynamic relationship between ITH and the tumor ecosystem. We suggest that conducting comprehensive studies of ITH using single-cell approaches in temporal and spatial dimensions, combined with population-based clinical trials, will help to clarify the clinical implications of ITH, develop novel intervention strategies, and improve patient prognosis.
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Affiliation(s)
- Qi Zhang
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
- Key Laboratory of Pancreatic Disease of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Innovation Center for the Study of Pancreatic Diseases of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou 310003, Zhejiang Province, China
| | - Yu Lou
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
- Key Laboratory of Pancreatic Disease of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
| | - Xue-Li Bai
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
- Key Laboratory of Pancreatic Disease of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Innovation Center for the Study of Pancreatic Diseases of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou 310003, Zhejiang Province, China
| | - Ting-Bo Liang
- Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang Province, China
- Key Laboratory of Pancreatic Disease of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Innovation Center for the Study of Pancreatic Diseases of Zhejiang Province, Hangzhou 310003, Zhejiang Province, China
- Zhejiang Clinical Research Center of Hepatobiliary and Pancreatic Diseases, Hangzhou 310003, Zhejiang Province, China
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11
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Krarup MMK, Nygård L, Vogelius IR, Andersen FL, Cook G, Goh V, Fischer BM. Heterogeneity in tumours: Validating the use of radiomic features on 18F-FDG PET/CT scans of lung cancer patients as a prognostic tool. Radiother Oncol 2020; 144:72-78. [PMID: 31733491 DOI: 10.1016/j.radonc.2019.10.012] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 10/01/2019] [Accepted: 10/17/2019] [Indexed: 02/06/2023]
Abstract
AIM The aim was to validate promising radiomic features (RFs)1 on 18F-flourodeoxyglucose positron emission tomography/computed tomography-scans (18F-FDG PET/CT) of non-small cell lung cancer (NSCLC) patients undergoing definitive chemo-radiotherapy. METHODS 18F-FDG PET/CT scans performed for radiotherapy (RT) planning were retrieved. Auto-segmentation with visual adaption was used to define the primary tumour on PET images. Six pre-selected prognostic and reproducible PET texture -and shape-features were calculated using texture respectively shape analysis. The correlation between these RFs and metabolic active tumour volume (MTV)3, gross tumour volume (GTV)4 and maximum and mean of standardized uptake value (SUV)5 was tested with a Spearman's Rank test. The prognostic value of RFs was tested in a univariate cox regression analysis and a multivariate cox regression analysis with GTV, clinical stage and histology. P-value ≤ 0.05 were considered significant. RESULTS Image analysis was performed for 233 patients: 145 males and 88 females, mean age of 65.7 and clinical stage II-IV. Mean GTV was 129.87 cm3 (SD 130.30 cm3). Texture and shape-features correlated more strongly to MTV and GTV compared to SUV-measurements. Four RFs predicted PFS in the univariate analysis. No RFs predicted PFS in the multivariate analysis, whereas GTV and clinical stage predicted PFS (p = 0.001 and p = 0.008 respectively). CONCLUSION The pre-selected RFs were insignificant in predicting PFS in combination with GTV, clinical stage and histology. These results might be due to variations in technical parameters. However, it is relevant to question whether RFs are stable enough to provide clinically useful information.
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Affiliation(s)
- Marie Manon Krebs Krarup
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Lotte Nygård
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Ivan Richter Vogelius
- Department of Oncology, Rigshospitalet, Copenhagen University Hospital, Denmark; Faculty of Health and Medical Sciences, Copenhagen University, Denmark.
| | - Flemming Littrup Andersen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark.
| | - Gary Cook
- PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
| | - Vicky Goh
- PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
| | - Barbara Malene Fischer
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Denmark; PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, United Kingdom.
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12
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Li Z, Han C, Wang L, Zhu J, Yin Y, Li B. Prognostic Value of Texture Analysis Based on Pretreatment DWI-Weighted MRI for Esophageal Squamous Cell Carcinoma Patients Treated With Concurrent Chemo-Radiotherapy. Front Oncol 2019; 9:1057. [PMID: 31681593 PMCID: PMC6811607 DOI: 10.3389/fonc.2019.01057] [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] [Received: 02/25/2019] [Accepted: 09/27/2019] [Indexed: 01/08/2023] Open
Abstract
Purpose: The purpose of the research was to assess the prognostic value of three-dimensional (3D) texture features based on diffusion-weighted magnetic resonance imaging (DWI) for esophageal squamous cell carcinoma (ESCC) patients undergoing concurrent chemo-radiotherapy (CRT). Methods: We prospectively enrolled 82 patients with ESCC into a cohort study. Two DWI sequences (b = 0 and b = 600 s/mm2) were acquired along with axial T2WI and T1WI before CRT. Two groups of features were examined: (1) clinical and demographic features (e.g., TNM stage, age and sex) and (2) changes in spatial texture characteristics of the apparent diffusion coefficient (ADC), which characterizes gray intensity changes in tumor areas, spatial pattern and distribution, and related changes caused by CRT. Reproducible feature sets without redundancy were statistically filtered and validated. The prognostic values associated with overall survival (OS) for each parameter were studied using Kaplan-Meier and Cox regression models for univariate and multivariate analyses, respectively. Results: Both univariate and multivariate Cox model analyses showed that the energy of intensity histogram texture (IHIST_energy), radiation dose, mean of the contrast in distance 1 of 26 directions (m_contrast_1), extreme difference of the homogeneity in distance 2 of 26 directions (Diff_homogeneity_2), mean of the inverse variance in distance 2 of 26 directions (m_lnversevariance_2), high-intensity small zone emphasis (HISE), and low-intensity large zone emphasis (LILE) were significantly associated with survival. The results showed that 6 texture parameters extracted from the ADC images before treatment could distinguish among high-, medium-, and low-risk groups (log-rank χ2 = 9.7; P = 0.00773). The biased C-index value was 0.715 (95% CI: 0.708 to 0.732) based on bootstrapping validation. Conclusions: The ADC 3D texture feature can be used as a useful biomarker to predict the survival of ESCC patients undergoing CRT. Combining ADC 3D texture features with conventional prognostic factors can generate reliable survival prediction models.
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Affiliation(s)
- Zhenjiang Li
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China
| | - Chun Han
- Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Lan Wang
- Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jian Zhu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China
| | - Yong Yin
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China
| | - Baosheng Li
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Shandong Cancer Hospital, Jinan, China
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13
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Khurshid Z, Ahmadzadehfar H, Gaertner FC, Papp L, Zsóter N, Essler M, Bundschuh RA. Role of textural heterogeneity parameters in patient selection for 177Lu-PSMA therapy via response prediction. Oncotarget 2018; 9:33312-33321. [PMID: 30279962 PMCID: PMC6161784 DOI: 10.18632/oncotarget.26051] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Accepted: 08/06/2018] [Indexed: 11/25/2022] Open
Abstract
Purpose Prostate cancer is most common tumor in men causing significant patient mortality and morbidity. In newer diagnostic/therapeutic agents PSMA linked ones are specifically important. Analysis of textural heterogeneity parameters is associated with determination of innately aggressive and therapy resistant cell lines thus emphasizing their importance in therapy planning. The objective of current study was to assess predictive ability of tumor textural heterogeneity parameters from baseline 68Ga-PSMA PET prior to 177Lu-PSMA therapy. Results Entropy showed a negative correlation (rs = −0.327, p = 0.006, AUC = 0.695) and homogeneity showed a positive correlation (rs = 0.315, p = 0.008, AUC = 0.683) with change in pre and post therapy PSA levels. Conclusions Study showed potential for response prediction through baseline PET scan using textural features. It suggested that increase in heterogeneity of PSMA expression seems to be associated with an increased response to PSMA radionuclide therapy. Materials and Methods Retrospective analysis of 70 patients was performed. All patients had metastatic prostate cancer and were planned to undergo 177Lu-PSMA therapy. Pre-therapeutic 68Ga- PSMA PET scans were used for analysis. 3D volumes (VOIs) of 3 lesions each in bones and lymph nodes were manually delineated in static PET images. Five PET based textural heterogeneity parameters (COV, entropy, homogeneity, contrast, size variation) were determined. Results obtained were then compared with clinical parameters including pre and post therapy PSA, alkaline phosphate, bone specific alkaline phosphate levels and ECOG criteria. Spearman correlation was used to determine statistical dependence among variables. ROC analysis was performed to estimate the optimal cutoff value and AUC.
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Affiliation(s)
- Zain Khurshid
- Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany
| | | | | | - László Papp
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | | | - Markus Essler
- Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany
| | - Ralph A Bundschuh
- Department of Nuclear Medicine, University Hospital Bonn, Bonn, Germany
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14
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Wang X, Cui H, Gong G, Fu Z, Zhou J, Gu J, Yin Y, Feng D. Computational delineation and quantitative heterogeneity analysis of lung tumor on 18F-FDG PET for radiation dose-escalation. Sci Rep 2018; 8:10649. [PMID: 30006600 PMCID: PMC6045640 DOI: 10.1038/s41598-018-28818-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 06/18/2018] [Indexed: 12/13/2022] Open
Abstract
Quantitative measurement and analysis of tumor metabolic activities could provide a more optimal solution to personalized accurate dose painting. We collected PET images of 58 lung cancer patients, in which the tumor exhibits heterogeneous FDG uptake. We design an automated delineation and quantitative heterogeneity measurement of the lung tumor for dose-escalation. For tumor delineation, our algorithm firstly separates the tumor from its adjacent high-uptake tissues using 3D projection masks; then the tumor boundary is delineated with our stopping criterion of joint gradient and intensity affinities. For dose-escalation, tumor sub-volumes with low, moderate and high metabolic activities are extracted and measured. Based on our quantitative heterogeneity measurement, a sub-volume oriented dose-escalation plan is implemented in intensity modulated radiation therapy (IMRT) planning system. With respect to manual tumor delineations by two radiation oncologists, the paired t-test demonstrated our model outperformed the other computational methods in comparison (p < 0.05) and reduced the variability between inter-observers. Compared to standard uniform dose prescription, the dosimetry results demonstrated that the dose-escalation plan statistically boosted the dose delivered to high metabolic tumor sub-volumes (p < 0.05). Meanwhile, the doses received by organs-at-risk (OAR) including the heart, ipsilateral lung and contralateral lung were not statistically different (p > 0.05).
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Affiliation(s)
- Xiuying Wang
- BMIT research group, School of Information Technologies, The University of Sydney, Sydney, Australia.
| | - Hui Cui
- BMIT research group, School of Information Technologies, The University of Sydney, Sydney, Australia
| | - Guanzhong Gong
- The Radiation Oncology Department of Shandong Cancer Hospital, Affiliated to Shandong University, Jinan, China
| | - Zheng Fu
- PET/CT center, Shandong Tumor Hospital and Institute, Shandong Academy of Medical Sciences, Jinan, China
| | | | - Jiabing Gu
- The Radiation Oncology Department of Shandong Cancer Hospital, Affiliated to Shandong University, Jinan, China
| | - Yong Yin
- The Radiation Oncology Department of Shandong Cancer Hospital, Affiliated to Shandong University, Jinan, China.
| | - Dagan Feng
- BMIT research group, School of Information Technologies, The University of Sydney, Sydney, Australia.,Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, China
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15
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Lee JW, Lee SM. Radiomics in Oncological PET/CT: Clinical Applications. Nucl Med Mol Imaging 2018; 52:170-189. [PMID: 29942396 PMCID: PMC5995782 DOI: 10.1007/s13139-017-0500-y] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 09/22/2017] [Accepted: 09/29/2017] [Indexed: 12/11/2022] Open
Abstract
18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is widely used for staging, evaluating treatment response, and predicting prognosis in malignant diseases. FDG uptake and volumetric PET parameters such as metabolic tumor volume have been used and are still used as conventional PET parameters to assess biological characteristics of tumors. However, in recent years, additional features derived from PET images by computational processing have been found to reflect intratumoral heterogeneity, which is related to biological tumor features, and to provide additional predictive and prognostic information, which leads to the concept of radiomics. In this review, we focus on recent clinical studies of malignant diseases that investigated intratumoral heterogeneity on PET/CT, and we discuss its clinical role in various cancers.
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Affiliation(s)
- Jeong Won Lee
- Department of Nuclear Medicine, International St. Mary’s Hospital, Catholic Kwandong University College of Medicine, 25, Simgok-ro 100 Gil 25, Seo-gu, Incheon, 22711 South Korea
- Institute for Integrative Medicine, International St. Mary’s Hospital, Catholic Kwandong University College of Medicine, Incheon, South Korea
| | - Sang Mi Lee
- Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, South Korea
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16
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Stein D, Goldberg N, Domachevsky L, Bernstine H, Nidam M, Abadi-Korek I, Guindy M, Sosna J, Groshar D. Quantitative biomarkers for liver metastases: comparison of MRI diffusion-weighted imaging heterogeneity index and fluorine-18-fluoro-deoxyglucose standardised uptake value in hybrid PET/MR. Clin Radiol 2018; 73:832.e17-832.e22. [PMID: 29859634 DOI: 10.1016/j.crad.2018.04.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 04/18/2018] [Indexed: 01/24/2023]
Abstract
AIM To investigate the ability of apparent diffusion coefficient (ADC) heterogeneity index to discriminate liver metastases (LM) from normal-appearing liver (NAL) tissue as compared to common magnetic resonance imaging (MRI) metrics, and to investigate its correlation with 2-[18F]-fluoro-2-deoxy-d-glucose (18F-FDG) positron-emission tomography (PET) standardised uptake value (SUV). MATERIALS AND METHODS Thirty-nine liver metastases in 24 oncology patients (13 women, 11 men; mean age 56±13 years) with proven LM from heterogeneous sources were evaluated on a PET/MRI system. Abdominal sequences included Dixon and diffusion-weighted imaging (DWI) protocols with simultaneous PET. Tissue heterogeneity was calculated using the coefficient of variance (CV) of the ADC, and compared in LM and in NAL tissue of the same volume in an adjacent portion of the liver. The correlations between various ADC measures and PET SUV in distinguishing LM from NAL were evaluated. RESULTS A good correlation was found between ADCcv and SUVpeak (r=0.712). Moderate inverse correlation was found between ADCmin and SUVpeak (r=-0.536), and a weak inverse correlation between ADCmean and SUVpeak (r=-0.273). There was a significant difference between LM and NAL when ADCcv (p<0.0001) and ADCmin (p=0.001) were used. Receiver operating characteristic (ROC) analysis of SUV, ADCcv, ADCmin, and ADCmean produced an AUC of 0.989, 0.900, 0.742, and 0.623 respectively. CONCLUSIONS The ADCcv index is a potential biomarker of LM with better correlation to 18F-FDG PET SUVpeak than conventional MRI metrics, and may serve to quantitatively discriminate between LM and NAL.
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Affiliation(s)
- D Stein
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - N Goldberg
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - L Domachevsky
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - H Bernstine
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - M Nidam
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - I Abadi-Korek
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - M Guindy
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - J Sosna
- Department of Radiology, Hadassah Hebrew University Medical Center, Jerusalem, Israel
| | - D Groshar
- Department of Nuclear Medicine, Assuta Medical Centers, Tel-Aviv, Israel and Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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17
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Calandriello L, Larici AR, Leccisotti L, del Ciello A, Sica G, Infante A, Congedo MT, Poscia A, Giordano A, Bonomo L. Multifunctional Assessment of Non–Small Cell Lung Cancer. Clin Nucl Med 2018; 43:e18-e24. [DOI: 10.1097/rlu.0000000000001888] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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18
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Sollini M, Cozzi L, Antunovic L, Chiti A, Kirienko M. PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology. Sci Rep 2017; 7:358. [PMID: 28336974 PMCID: PMC5428425 DOI: 10.1038/s41598-017-00426-y] [Citation(s) in RCA: 115] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 02/23/2017] [Indexed: 12/21/2022] Open
Abstract
Imaging with positron emission tomography (PET)/computed tomography (CT) is crucial in the management of cancer because of its value in tumor staging, response assessment, restaging, prognosis and treatment responsiveness prediction. In the last years, interest has grown in texture analysis which provides an "in-vivo" lesion characterization, and predictive information in several malignances including NSCLC; however several drawbacks and limitations affect these studies, especially because of lack of standardization in features calculation, definitions and methodology reporting. The present paper provides a comprehensive review of literature describing the state-of-the-art of FDG-PET/CT texture analysis in NSCLC, suggesting a proposal for harmonization of methodology.
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Affiliation(s)
- M Sollini
- Department of Biomedical Sciences, Humanitas University, via Manzoni, 113-20089, Rozzano, (Milan), Italy.
| | - L Cozzi
- Department of Biomedical Sciences, Humanitas University, via Manzoni, 113-20089, Rozzano, (Milan), Italy
- Radiotherapy and Radiosurgery Unit, Humanitas Clinical and Research Center, via Manzoni, 56-20089, Rozzano, (Milan), Italy
| | - L Antunovic
- Nuclear Medicine Unit, Humanitas Clinical and Research Center, via Manzoni, 56-20089, Rozzano, (Milan), Italy
| | - A Chiti
- Department of Biomedical Sciences, Humanitas University, via Manzoni, 113-20089, Rozzano, (Milan), Italy
- Nuclear Medicine Unit, Humanitas Clinical and Research Center, via Manzoni, 56-20089, Rozzano, (Milan), Italy
| | - M Kirienko
- Department of Biomedical Sciences, Humanitas University, via Manzoni, 113-20089, Rozzano, (Milan), Italy
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19
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Dong X, Sun X, Zhao X, Zhu W, Sun L, Huang Y, Li W, Wan H, Xing L, Yu J. The impact of intratumoral metabolic heterogeneity on postoperative recurrence and survival in resectable esophageal squamous cell carcinoma. Oncotarget 2017; 8:14969-14977. [PMID: 28122340 PMCID: PMC5362458 DOI: 10.18632/oncotarget.14743] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Accepted: 01/10/2017] [Indexed: 01/18/2023] Open
Abstract
OBJECTIVE To evaluate the impact of intratumoral metabolic heterogeneity measured by 18F-FDG PET imaging on postoperative recurrence and survival for patients with esophageal squamous cell carcinoma (ESCC). RESULTS AUC-CSH, metabolic tumor volume and pN-stage were significant prognostic factors for RFS. Additionally, tumor recurrence of the low AUC-CSH group (≤ 0.478) was 3 times higher than high group (P = 0.015). The median OS of patients with advanced AJCC stage or low AUC-CSH was also significantly shorter than that of patients with stage I & II or high AUC-CSH (P = 0.021, 0.009). Multivariate analysis identified the AUC-CSH to be the only significant risk factor for postoperative recurrence and overall survival in whole-group and stage III patients. MATERIALS AND METHODS 116 ESCC patients who underwent staging 18F-FDG PET-CT scan and surgical resection were reviewed. The metabolic parameters were assessed as follows: maximum standardized uptake value (SUVmax), metabolic tumor volume, and the area under the curve of the cumulative SUV-volume histogram (AUC-CSH), which is known to reflect the intratumoral metabolic heterogeneity. Regression analyses were used to identify clinicopathological and imaging variables associated with relapse-free survival (RFS) and overall survival (OS). CONCLUSIONS Intratumoral metabolic heterogeneity characterized by AUC-CSH can predict postoperative recurrence and survival in patients with resectable ESCC.
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Affiliation(s)
- Xinzhe Dong
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xiaorong Sun
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Xianguang Zhao
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
| | - Wanqi Zhu
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
| | - Lu Sun
- Jinan University, Jinan, Shandong, China
| | - Yong Huang
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Wenwu Li
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Honglin Wan
- College of Physics and Electronic Science, Shandong Normal University, Jinan, Shandong, China
| | - Ligang Xing
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Jinming Yu
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Academy of Medical Sciences, Jinan, Shandong, China
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20
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Hatt M, Tixier F, Pierce L, Kinahan PE, Le Rest CC, Visvikis D. Characterization of PET/CT images using texture analysis: the past, the present… any future? Eur J Nucl Med Mol Imaging 2017; 44:151-165. [PMID: 27271051 PMCID: PMC5283691 DOI: 10.1007/s00259-016-3427-0] [Citation(s) in RCA: 338] [Impact Index Per Article: 42.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/18/2016] [Indexed: 02/07/2023]
Abstract
After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach.
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Affiliation(s)
- Mathieu Hatt
- INSERM, UMR 1101, LaTIM, University of Brest IBSAM, Brest, France.
| | - Florent Tixier
- Nuclear Medicine, University Hospital, Poitiers, France
- Medical school, EE DACTIM, University of Poitiers, Poitiers, France
| | - Larry Pierce
- Imaging Research Laboratory, University of Washington, Seattle, WA, USA
| | - Paul E Kinahan
- Imaging Research Laboratory, University of Washington, Seattle, WA, USA
| | - Catherine Cheze Le Rest
- Nuclear Medicine, University Hospital, Poitiers, France
- Medical school, EE DACTIM, University of Poitiers, Poitiers, France
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van Rossum PSN, Xu C, Fried DV, Goense L, Court LE, Lin SH. The emerging field of radiomics in esophageal cancer: current evidence and future potential. Transl Cancer Res 2016; 5:410-423. [PMID: 30687593 DOI: 10.21037/tcr.2016.06.19] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
'Radiomics' is the name given to the emerging field of extracting additional information from standard medical images using advanced feature analysis. This innovative form of quantitative image analysis appears to have future potential for clinical practice in patients with esophageal cancer by providing an additional layer of information to the standard imaging assessment. There is a growing body of evidence suggesting that radiomics may provide incremental value for staging, predicting treatment response, and predicting survival in esophageal cancer, for which the current work-up has substantial limitations. This review outlines the available evidence and future potential for the application of radiomics in the management of patients with esophageal cancer. In addition, an overview of the current evidence on the importance of reproducibility of image features and the substantial influence of varying smoothing scales, quantization levels, and segmentation methods is provided.
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Affiliation(s)
- Peter S N van Rossum
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston (Texas), USA.,Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cai Xu
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston (Texas), USA.,Department of Radiation Oncology, Cancer Hospital & Institute, Chinese Academy of Medical Science, Beijing 100021, China
| | - David V Fried
- Department of Radiation Oncology, University of North Carolina, Chapel Hill (North Carolina), USA
| | - Lucas Goense
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Laurence E Court
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston (Texas), USA
| | - Steven H Lin
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston (Texas), USA
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22
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Dong X, Sun X, Sun L, Maxim PG, Xing L, Huang Y, Li W, Wan H, Zhao X, Xing L, Yu J. Early Change in Metabolic Tumor Heterogeneity during Chemoradiotherapy and Its Prognostic Value for Patients with Locally Advanced Non-Small Cell Lung Cancer. PLoS One 2016; 11:e0157836. [PMID: 27322376 PMCID: PMC4913903 DOI: 10.1371/journal.pone.0157836] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2016] [Accepted: 06/06/2016] [Indexed: 12/25/2022] Open
Abstract
Introduction To observe the early change of metabolic tumor heterogeneity during chemoradiotherapy and to determine its prognostic value for patients with locally advanced non-small cell lung cancer (NSCLC). Methods From January 2007 to March 2010, 58 patients with NSCLC were included who were received 18F-fluorodeoxyglucose (18F-FDG) PET/CT before and following 40 Gy radiotherapy with the concurrent cisplatin-based chemotherapy (CCRT). Primary tumor FDG uptake heterogeneity was determined using global and local scale textural features extracted from standardized uptake value (SUV) histogram analysis (coefficient of variation [COV], skewness, kurtosis, area under the curve of the cumulative SUV histogram [AUC-CSH]) and normalized gray-level co-occurrence matrix (contrast, dissimilarity, entropy, homogeneity). SUVmax and metabolic tumor volume (MTV) were also evaluated. Correlations were analyzed between parameters on baseline or during treatments with tumor response, progression-free survival (PFS), and overall survival (OS). Results Compared with non-responders, responders showed significantly greater pre-treatment COV, contrast and MTV (AUC = 0.781, 0.804, 0.686, respectively). Receiver-operating-characteristic curve analysis showed that early change of tumor textural analysis serves as a response predictor with higher sensitivity (73.2%~92.1%) and specificity (80.0%~83.6%) than baseline parameters. Change in AUC-CSH and dissimilarity during CCRT could also predict response with optimal cut-off values (33.0% and 28.7%, respectively). The patients with greater changes in contrast and AUC-CSH had significantly higher 5-year OS (P = 0.008, P = 0.034) and PFS (P = 0.007, P = 0.039). In multivariate analysis, only change in contrast was found as the independent prognostic factor of PFS (HR 0.476, P = 0.021) and OS (HR 0.519, P = 0.015). Conclusions The metabolic tumor heterogeneity change during CCRT characterized by global and local scale textural features may be valuable for predicting treatment response and survival for patients with locally advanced NSCLC.
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Affiliation(s)
- Xinzhe Dong
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Xiaorong Sun
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Lu Sun
- Jinan University, Jinan, Shandong, China
| | - Peter G. Maxim
- Department of Radiation Oncology and Cancer Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Lei Xing
- Department of Radiation Oncology and Cancer Institute, Stanford University School of Medicine, Stanford, California, United States of America
| | - Yong Huang
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Wenwu Li
- Department of Radiology, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
| | - Honglin Wan
- College of Physics and Electronic Science, Shandong Normal University, Jinan, Shandong, China
| | - Xianguang Zhao
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
- * E-mail: (XZ); (LX)
| | - Ligang Xing
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
- * E-mail: (XZ); (LX)
| | - Jinming Yu
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, Shandong, China
- Key Laboratory of Radiation Oncology of Shandong Province, Shandong Cancer Hospital and Institute, Jinan, Shandong, China
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23
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Yip SSF, Coroller TP, Sanford NN, Huynh E, Mamon H, Aerts HJWL, Berbeco RI. Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction. Phys Med Biol 2016; 61:906-22. [PMID: 26738433 DOI: 10.1088/0031-9155/61/2/906] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI = 58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI = 69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC = 0.58, q-value = 0.33), while the differentiation was significant with other textures (AUC = 0.71-0.73, p < 0.009). Among the deformable algorithms, fast-demons (AUC = 0.68-0.70, q-value < 0.03) and fast-free-form (AUC = 0.69-0.74, q-value < 0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC = 0.72-0.78, q-value < 0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.
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Affiliation(s)
- Stephen S F Yip
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115, USA
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