OBJECTIVE: To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer. METHODS: This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A maximum of eight most important features were selected for model development using support vector machines and fivefold cross-validation to predict each outcome parameter via elastic net regularization. Diagnostic metrics of the final models were calculated, including sensitivity, specificity, PPV, NPV, accuracy, and AUC. RESULTS: The study included 236 patients (54 ± 12 years, 135 men). The AUC, sensitivity, specificity, PPV, NPV, and accuracy for each clinical outcome were as follows: for pCR, 0.89, 78.0%, 85.1%, 52.5%, 94.9%, 83.9%; for local recurrence, 0.79, 68.3%, 80.7%, 46.7%, 91.2%, 78.3%; for distant recurrence, 0.87, 80.0%, 88.4%, 58.3%, 95.6%, 87.0%; for cT, 0.80, 85.8%, 56.5%, 89.1%, 49.1%, 80.1%; for ypN, 0.74, 65.0%, 80.1%, 52.7%, 87.0%, 76.3%; and for ypT, 0.86, 81.3%, 84.2%, 96.4%, 46.4%, 81.8%. CONCLUSION: Radiomics features of mesorectal fat can predict pathological complete response and local and distant recurrence, as well as post-treatment T and N categories. KEY POINTS: • Mesorectal fat contains important prognostic information in patients with locally advanced rectal cancer (LARC). • Radiomics features of mesorectal fat were significantly different between those who achieved complete vs incomplete pathologic response (accuracy 83.9%, 95% CI: 78.6-88.4%). • Radiomics features of mesorectal fat were significantly different between those who did vs did not develop local or distant recurrence (accuracy 78.3%, 95% CI: 72.0-83.7% and 87.0%, 95% CI: 81.6-91.2% respectively).
OBJECTIVE: To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer. METHODS: This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A maximum of eight most important features were selected for model development using support vector machines and fivefold cross-validation to predict each outcome parameter via elastic net regularization. Diagnostic metrics of the final models were calculated, including sensitivity, specificity, PPV, NPV, accuracy, and AUC. RESULTS: The study included 236 patients (54 ± 12 years, 135 men). The AUC, sensitivity, specificity, PPV, NPV, and accuracy for each clinical outcome were as follows: for pCR, 0.89, 78.0%, 85.1%, 52.5%, 94.9%, 83.9%; for local recurrence, 0.79, 68.3%, 80.7%, 46.7%, 91.2%, 78.3%; for distant recurrence, 0.87, 80.0%, 88.4%, 58.3%, 95.6%, 87.0%; for cT, 0.80, 85.8%, 56.5%, 89.1%, 49.1%, 80.1%; for ypN, 0.74, 65.0%, 80.1%, 52.7%, 87.0%, 76.3%; and for ypT, 0.86, 81.3%, 84.2%, 96.4%, 46.4%, 81.8%. CONCLUSION: Radiomics features of mesorectal fat can predict pathological complete response and local and distant recurrence, as well as post-treatment T and N categories. KEY POINTS: • Mesorectal fat contains important prognostic information in patients with locally advanced rectal cancer (LARC). • Radiomics features of mesorectal fat were significantly different between those who achieved complete vs incomplete pathologic response (accuracy 83.9%, 95% CI: 78.6-88.4%). • Radiomics features of mesorectal fat were significantly different between those who did vs did not develop local or distant recurrence (accuracy 78.3%, 95% CI: 72.0-83.7% and 87.0%, 95% CI: 81.6-91.2% respectively).
Authors: Hiram Shaish; Andrew Aukerman; Rami Vanguri; Antonino Spinelli; Paul Armenta; Sachin Jambawalikar; Jasnit Makkar; Stuart Bentley-Hibbert; Armando Del Portillo; Ravi Kiran; Lara Monti; Christiana Bonifacio; Margarita Kirienko; Kevin L Gardner; Lawrence Schwartz; Deborah Keller Journal: Eur Radiol Date: 2020-07-14 Impact factor: 5.315
Authors: S Amor; M C Iglesias-de la Cruz; E Ferrero; O García-Villar; V Barrios; N Fernandez; L Monge; A L García-Villalón; M Granado Journal: Int J Colorectal Dis Date: 2015-10-22 Impact factor: 2.571
Authors: Alex Zwanenburg; Martin Vallières; Mahmoud A Abdalah; Hugo J W L Aerts; Vincent Andrearczyk; Aditya Apte; Saeed Ashrafinia; Spyridon Bakas; Roelof J Beukinga; Ronald Boellaard; Marta Bogowicz; Luca Boldrini; Irène Buvat; Gary J R Cook; Christos Davatzikos; Adrien Depeursinge; Marie-Charlotte Desseroit; Nicola Dinapoli; Cuong Viet Dinh; Sebastian Echegaray; Issam El Naqa; Andriy Y Fedorov; Roberto Gatta; Robert J Gillies; Vicky Goh; Michael Götz; Matthias Guckenberger; Sung Min Ha; Mathieu Hatt; Fabian Isensee; Philippe Lambin; Stefan Leger; Ralph T H Leijenaar; Jacopo Lenkowicz; Fiona Lippert; Are Losnegård; Klaus H Maier-Hein; Olivier Morin; Henning Müller; Sandy Napel; Christophe Nioche; Fanny Orlhac; Sarthak Pati; Elisabeth A G Pfaehler; Arman Rahmim; Arvind U K Rao; Jonas Scherer; Muhammad Musib Siddique; Nanna M Sijtsema; Jairo Socarras Fernandez; Emiliano Spezi; Roel J H M Steenbakkers; Stephanie Tanadini-Lang; Daniela Thorwarth; Esther G C Troost; Taman Upadhaya; Vincenzo Valentini; Lisanne V van Dijk; Joost van Griethuysen; Floris H P van Velden; Philip Whybra; Christian Richter; Steffen Löck Journal: Radiology Date: 2020-03-10 Impact factor: 29.146