MRI Predicts Residual Disease and Outcomes in Watch-and-Wait Patients with Rectal Cancer

作者：Hannah Williams, Dana Mohamed Rashid Omer, H Thompson, Sabrina T. Lin, Floris S. Verheij, João Miranda, Jonathan Benjamin Yuval, James G. Buckley, Michael R. Marco, Li‐Xuan Qin, David A. Dombroski, R P Kedar, Aytekin Oto, Elena K. Korngold, Joseph C. Veniero, Sunil N. Gandhi, Arun Krishnaraj, Minal Jagtiani Sangwaiya, Kirk Ohanian, Dan Quoc Vu, Thomas A. Hope, Sonia Lee, Ashish P. Wasnik, Nikhil Madhuripan, Marc Jeffrey Gollub, Julio García‐Aguilar, Sujata N Patil, Jin K. Kim, Meghan D. Lee, Richard Francis Dunne, Jorge E. Marcet, Peter A. Cataldo, Blasé N. Polite, Daniel O. Herzig, David Liska, Samuel C. Oommen, Charles M. Friel, Charles A. Ternent, Andrew L. Coveler, Steven R. Hunt, Anita Gregory, Madhulika G. Varma, Brian L. Bello, Joseph C. Carmichael, John C. Krauss, Ana Gleisner, Philip B. Paty, Martin R. Weiser, Garrett Michael Nash, Emmanouil P. Pappou, José G. Guillem, Larissa K. F. Temple, Iris H. Wei, Maria Widmar, Neil Howard Segal, Andrea Cercek, Rona D. Yaeger, Jesse Joshua Smith, Karyn A. Goodman, Abraham Jing-Ching Wu, Leonard B. Saltz · 发表于：Radiology · 年份：2024 · DOI：10.1148/radiol.232748 · 被引用次数：28 · 研究领域：Colorectal Cancer Surgical Treatments、Gastric Cancer Management and Outcomes、Radiomics and Machine Learning in Medical Imaging

Restaging MRI can stratify patients treated with total neoadjuvant therapy into clinical response categories predictive of organ preservation, local regrowth, and survival.