Predictive Value of CT-Based Radiomics in Distinguishing Renal Angiomyolipomas with Minimal Fat from Other Renal Tumors

• Published in: Disease markers Vol. 2022; pp. 1 - 8
• Main Authors: Han, Zhiwei, Zhu, Yuanqiang, Xu, Jingji, Wen, Didi, Xia, Yuwei, Zheng, Minwen, Yan, Tao, Wei, Mengqi
• Format: Journal Article
• Language: English
• Published: United States Hindawi 2022; John Wiley & Sons, Inc
• Subjects: Accuracy; Adipocytes; Angiomyolipoma - diagnostic imaging; Artificial intelligence; Classifiers; Diagnostic systems; Feature extraction; Humans; Kidney Neoplasms - diagnostic imaging; Kidney Neoplasms - pathology; Kidneys; Machine learning; Medical imaging; Multilayer perceptrons; Patients; Prediction models; Radiomics; Regression; Retrospective Studies; Sensitivity; Support vector machines; Tomography; Tomography, X-Ray Computed; Tumors

Objectives. This study is aimed at determining whether CT-based radiomics models can help differentiate renal angiomyolipomas with minimal fat (AMLmf) from other solid renal tumors. Methods. This retrospective study included 58 patients with a postoperative pathologically confirmed AMLmf (observatio...