Noninvasive Differentiation of Indolent from Aggressive Renal Neoplasms with MR Fingerprinting Combined with Diffusion/Perfusion MRI

Sep 23, 2026

Accurate grading and aggressiveness assessment for renal neoplasms is essential for patient management. This prospective proof-of-concept study evaluates kidney MR fingerprinting (MRF) alone and combined with diffusion-weighted imaging and arterial spin labeling (ASL) MRI to distinguish indolent from aggressive tumors. Adults with suspected renal cell carcinoma underwent noncontrast coronal T1/T2 MRF at 3.0T plus ADC and renal blood flow measurements. Histopathology served as the reference standard, and multivariable analysis showed complementary MRF-derived T1 and T2 performance for differentiation.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages22

Reading Time55 min

AccessFree to download

Background

Purpose

Materials and Methods

Participants and reference standard

Imaging and analysis

Results

Conclusion

Author Manuscript Author Manuscript Author Manuscript Author Manuscript | | HHS Public Access
Author manuscript
Radiology. Author manuscript; available in PMC 2026 July 06. | | --- | --- | Published in final edited form as: Radiology. 2026 March ; 318(3): e251404 . doi:10.1148/radiol.251404 . Noninvasive Differentiation of Indolent from Aggressive Renal Neoplasms with MR Fingerprinting Combined with Diffusion/ Perfusion MRI Sree Harsha Tirumani, MD 1,2 , Christina J. MacAskill, BS3 , Yilun Sun, PhD4 , Dheeman Futela, MD 1 , Holly Harper, MD5,6 , Adam Calaway, MD7,8 , Bernd Kuehn, PhD9 , Ke Cheng Liu, PhD 10 , Lee Ponsky, MD7,8 , Mark Griswold, PhD 1,2 , Chris A. Flask, PhD 1,2,3,11,12 , Yong Chen, PhD 1,2 1 Department of Radiology, Case Western Reserve University, 11100 Euclid Ave, Bolwell Bldg, Room B120, Cleveland, OH 44106 2 Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio 3 Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 4 Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio 5 Department of Pathology, Case Western Reserve University, Cleveland, Ohio 6 Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, Ohio 7 Department of Urology, Case Western Reserve University, Cleveland, Ohio 8 Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, Ohio 9MR Application Predevelopment, Siemens Healthineers, Erlangen, Germany 10Siemens Medical Solutions USA, Malvern, Pa 11 Department of Pediatrics, Case Western Reserve University, Cleveland, Ohio 12 Department of Pediatrics, University Hospitals Cleveland Medical Center, Cleveland, Ohio Abstract Published by the Radiological Society of North America under a CC BY 4.0 license. Address correspondence to: Y.C. ([yxc235@case.edu](yxc235@case.edu)). Author contributions: Sree Harsha Tirumani: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing-original draft, Writing-review & editing; Christina J. MacAskill: Data curation, Investigation, Methodology, Software; Yilun Sun: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review & editing; Dheeman Futela: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization; Holly Harper: Data curation, Formal analysis, Investigation, Visualization; Adam Calaway: Conceptualization, Data curation, Investigation; Bernd Kuehn: Methodology; Ke Cheng Liu: Methodology; Lee Ponsky: Data curation, Investigation; Mark Griswold: Funding acquisition, Investigation, Methodology, Resources, Software; Chris A. Flask: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing-original draft, Writing-review & editing; and Yong Chen: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing-original draft, Writing-review & editing. Disclosures of conflicts of interest: Please see ICMJE form(s) for author conflicts of interest. These have been provided as supplemental materials. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Tirumani et al. Page 2 Background: Accurate characterization of tumor grade and aggressiveness for renal neoplasms with noninvasive imaging methods is critical for patient management and outcome. Purpose: To evaluate kidney MR fingerprinting (MRF) alone and in combination with diffusionweighted imaging and arterial spin labeling (ASL) MRI for the diagnosis and characterization of renal neoplasms by assessing its performance in differentiating indolent from aggressive t

FAQs

What imaging approach does the study evaluate for differentiating renal tumors?

It evaluates kidney MR fingerprinting (MRF) alone and combined with diffusion-weighted imaging and arterial spin labeling (ASL) MRI, using ADC and renal blood flow measures for characterization.

How were tumors classified in this research?

Histopathologic grading served as the reference standard, classifying renal masses as indolent (low-grade or benign) versus aggressive (high-grade or unclassified RCC) based on biologic behavior.

What were the key findings on diagnostic performance?

While between-group differences were observed in T2, no evidence of differences was seen in T1, ADC, or renal blood flow alone. Multivariable analysis combining MRF-derived T1 and T2 achieved an AUC of 0.89 in this exploratory setting.

Sep 23, 2026

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