@article{QIMS19518,
author = {Daniel Jeong and Natarajan Raghunand and Diego Hernando and Michael Poch and Katherine Jeong and Brendan Eck and Jasreman Dhillon},
title = {Quantification of sarcomatoid differentiation in renal cell carcinoma on magnetic resonance imaging},
journal = {Quantitative Imaging in Medicine and Surgery},
volume = {8},
number = {4},
year = {2018},
keywords = {},
abstract = {Background: Sarcomatoid differentiation in renal cell carcinoma (sRCC) is histologically characterized by anaplastic changes of renal cell carcinoma (RCC) subtypes, which has been associated with a poor prognosis. sRCC is managed more aggressively than RCC without sarcomatoid components, so pre-operative detection of sarcomatoid differentiation would significantly affect surgical management. The purpose of this study is to compare the quantification of sarcomatoid features in RCCs on pre-operative magnetic resonance imaging (MRI) to standard histological examination.
Methods: Patients who had nephrectomy at our institution between 2000 and 2015 with pathology proven RCC and pre-operative contrast enhanced MRI abdominal scans were retrospectively reviewed. A custom MATLAB routine calculated the portion of each manually segmented whole tumor with MRI signal suggestive of sarcomatoid involvement based on prior research (MRI%SARC). The primary endpoint compared MRI%SARC to percent sarcomatoid involvement estimated by histological examination (HIST%SARC) using Pearson correlation and Bland Altman analysis.
Results: A total of 17 patients with sRCC (10 males, age 60.3±11.1 years) and 17 consecutive control patients with clear cell RCC (ccRCC) without sarcomatoid components (10 males, age 64.5±7.6 years) were evaluated. Pearson correlation analysis revealed a strong association between MRI%SARC and HIST%SARC (r=0.782, P},
issn = {2223-4306}, url = {https://qims.amegroups.org/article/view/19518}
}