TY - JOUR
T1 - Renal Mass Imaging with MRI Clear Cell Likelihood Score
T2 - A User’s Guide
AU - Shetty, Anup
AU - Fraum, Tyler J.
AU - Ballard, David
AU - Hoegger, Mark J.
AU - Itani, Malak
AU - Rajput, Mohamed
AU - Lanier, Michael H.
AU - Cusworth, Brian M.
AU - Mehrsheikh, Amanda L.
AU - Cabrera-Lebron, Jorge A.
AU - Chu, Jia
AU - Cunningham, Christopher R.
AU - Hirschi, Ryan S.
AU - Mokkarala, Mahati
AU - Unteriner, Jackson G.
AU - Kim, Eric
AU - Siegel, Cary
AU - Ludwig, Daniel
N1 - Funding Information:
Disclosures of conflicts of interest.—T.J.F. Research grant from Siemens AG, consulting fees from Arterys, payment for honoraria from PrecisCa Oncology, payment for expert witness testimony from the State of Florida Ross Feller Casey LLP. M.I. Grant from American College of Radiology. All other authors, the editor, and the reviewers have disclosed no relevant relationships.
Publisher Copyright:
© RSNA, 2023.
PY - 2023/7
Y1 - 2023/7
N2 - Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician.
AB - Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician.
UR - http://www.scopus.com/inward/record.url?scp=85163903314&partnerID=8YFLogxK
U2 - 10.1148/rg.220209
DO - 10.1148/rg.220209
M3 - Article
C2 - 37319026
AN - SCOPUS:85163903314
SN - 0271-5333
VL - 43
JO - Radiographics
JF - Radiographics
IS - 7
M1 - e220209
ER -