MRI has become an increasingly important modality for evaluating the upper urinary tract. Although CT urography remains the standard imaging modality for assessing hematuria, MRI offers distinct advantages, including superior soft-tissue contrast, functional imaging capability, and a radiation-free evaluation, making it particularly valuable in certain clinical scenarios. This review provides a comprehensive overview of MRI of the upper urinary tract, with a focus on upper tract urothelial carcinoma (UTUC). Optimized MRI techniques, including T2-weighted imaging, MR urography, diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted imaging, are discussed with respect to their complementary roles in tumor detection, characterization, and local staging. MRI findings of UTUC are summarized, emphasizing the role of DWI in improving tumor detection and assessing renal parenchymal invasion. Beyond UTUC, the review addresses MRI features of non-UTUC neoplastic lesions, infectious and inflammatory diseases, and congenital anomalies of the upper urinary tract, underscoring the value of MRI in differential diagnosis. We discuss the potential role of MRI-derived imaging biomarkers, focusing on apparent diffusion coefficient measurements as noninvasive indicators of tumor aggressiveness and invasiveness. We also introduce emerging radiomics approaches as promising, albeit investigational, tools. As technical innovations continue and clinical evidence grows, the role of MRI in the personalized evaluation and management of upper urinary tract diseases is expected to expand.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine. 2026 Jan [Epub]
Atsushi Nakamoto, Takashi Ota, Hideyuki Fukui, Toru Honda, Kengo Kiso, Koki Kaketaka, Takumi Tanigaki, Eriko Yoshidome, Feier Ding, Ryo Hirooka, Hiromitsu Onishi, Masatoshi Hori, Noriyuki Tomiyama
Department of Future Diagnostic Radiology, The University of Osaka Graduate School of Medicine, Suita, Osaka, Japan., Department of Diagnostic and Interventional Radiology, The University of Osaka Graduate School of Medicine, Suita, Osaka, Japan., Department of Artificial Intelligence in Diagnostic Radiology, The University of Osaka Graduate School of Medicine, Suita, Osaka, Japan.