Differentiation of Predominantly Solid Enhancing Lipid-Poor Renal Cell Masses by Use of Contrast-Enhanced CT: Evaluating the Role of Texture in Tumor Subtyping

AJR. American Journal of Roentgenology
Bino VargheseVinay Duddalwar

Abstract

The purpose of this study was to assess the accuracy of a panel of texture features extracted from clinical CT in differentiating benign from malignant solid enhancing lipid-poor renal masses. In a retrospective case-control study of 174 patients with predominantly solid nonmacroscopic fat-containing enhancing renal masses, 129 cases of malignant renal cell carcinoma were found, including clear cell, papillary, and chromophobe subtypes. Benign renal masses-oncocytoma and lipid-poor angiomyolipoma-were found in 45 patients. Whole-lesion ROIs were manually segmented and coregistered from the standard-of-care multiphase contrast-enhanced CT (CECT) scans of these patients. Pathologic diagnosis of all tumors was obtained after surgical resection. CECT images of the renal masses were used as inputs to a CECT texture analysis panel comprising 31 texture metrics derived with six texture methods. Stepwise logistic regression analysis was used to select the best predictor among all candidate predictors from each of the texture methods, and their performance was quantified by AUC. Among the texture predictors aiding renal mass subtyping were entropy, entropy of fast-Fourier transform magnitude, mean, uniformity, information measure of cor...Continue Reading

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Citations

Jul 8, 2018·Journal of Digital Imaging·Gautam KunapuliVinay Duddalwar
Jun 22, 2019·Journal of Applied Clinical Medical Physics·Bino A VargheseVinay A Duddalwar
Oct 16, 2019·AJR. American Journal of Roentgenology·Burak KocakOzgur Kilickesmez
Jan 9, 2020·AJR. American Journal of Roentgenology·Takashi TanakaSusumu Kanazawa
Jul 16, 2020·The British Journal of Radiology·Abdul RazikBalaji Ganeshan
Jan 13, 2021·Journal of Applied Clinical Medical Physics·Bino A VargheseVinay A Duddalwar
Jun 29, 2021·Journal of Computer Assisted Tomography·Yuhan ZhangXinquan Gu

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