Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer

Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer

Abstract Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in man...

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Bibliographic Details
Main Authors: Yuki Arita, Thomas C. Kwee, Oguz Akin, Keisuke Shigeta, Ramesh Paudyal, Christian Roest, Ryo Ueda, Alfonso Lema-Dopico, Sunny Nalavenkata, Lisa Ruby, Noam Nissan, Hiromi Edo, Soichiro Yoshida, Amita Shukla-Dave, Lawrence H. Schwartz
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Insights into Imaging
Subjects:
Artificial intelligence
Biomarker
Multiparametric magnetic resonance imaging
Treatment response
Urinary bladder neoplasm
Online Access:https://doi.org/10.1186/s13244-024-01884-5
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