{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T19:52:22Z","timestamp":1788551542337,"version":"build-2803163510"},"reference-count":35,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T00:00:00Z","timestamp":1748390400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health &amp; Welfare, Republic of Korea, Ministry of Food and Drug Safety)","award":["KMDF_PR_20200901_0096"],"award-info":[{"award-number":["KMDF_PR_20200901_0096"]}]},{"name":"Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health &amp; Welfare, Republic of Korea, Ministry of Food and Drug Safety)","award":["RS-2024-00460263"],"award-info":[{"award-number":["RS-2024-00460263"]}]},{"name":"Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health &amp; Welfare, Republic of Korea, Ministry of Food and Drug Safety)","award":["200-20240057"],"award-info":[{"award-number":["200-20240057"]}]},{"name":"Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health &amp; Welfare, Republic of Korea, Ministry of Food and Drug Safety)","award":["200-20240135"],"award-info":[{"award-number":["200-20240135"]}]},{"name":"Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health &amp; Welfare, Republic of Korea, Ministry of Food and Drug Safety)","award":["RS-2021-II211343"],"award-info":[{"award-number":["RS-2021-II211343"]}]},{"name":"Technology development Program","award":["KMDF_PR_20200901_0096"],"award-info":[{"award-number":["KMDF_PR_20200901_0096"]}]},{"name":"Technology development Program","award":["RS-2024-00460263"],"award-info":[{"award-number":["RS-2024-00460263"]}]},{"name":"Technology development Program","award":["200-20240057"],"award-info":[{"award-number":["200-20240057"]}]},{"name":"Technology development Program","award":["200-20240135"],"award-info":[{"award-number":["200-20240135"]}]},{"name":"Technology development Program","award":["RS-2021-II211343"],"award-info":[{"award-number":["RS-2021-II211343"]}]},{"name":"Creative-Pioneering Researchers Program through Seoul National University","award":["KMDF_PR_20200901_0096"],"award-info":[{"award-number":["KMDF_PR_20200901_0096"]}]},{"name":"Creative-Pioneering Researchers Program through Seoul National University","award":["RS-2024-00460263"],"award-info":[{"award-number":["RS-2024-00460263"]}]},{"name":"Creative-Pioneering Researchers Program through Seoul National University","award":["200-20240057"],"award-info":[{"award-number":["200-20240057"]}]},{"name":"Creative-Pioneering Researchers Program through Seoul National University","award":["200-20240135"],"award-info":[{"award-number":["200-20240135"]}]},{"name":"Creative-Pioneering Researchers Program through Seoul National University","award":["RS-2021-II211343"],"award-info":[{"award-number":["RS-2021-II211343"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["KMDF_PR_20200901_0096"],"award-info":[{"award-number":["KMDF_PR_20200901_0096"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["RS-2024-00460263"],"award-info":[{"award-number":["RS-2024-00460263"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["200-20240057"],"award-info":[{"award-number":["200-20240057"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["200-20240135"],"award-info":[{"award-number":["200-20240135"]}]},{"name":"Institute of Information &amp; communications Technology Planning &amp; Evaluation (IITP)","award":["RS-2021-II211343"],"award-info":[{"award-number":["RS-2021-II211343"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Differentiating histologic subtypes of fat-poor small renal masses using conventional imaging remains difficult due to their overlapping radiologic characteristics. We aimed to develop a machine learning-based diagnostic model using CT-derived radiomic features to classify the five most common renal tumor subtypes: clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chRCC), angiomyolipoma (AML), and oncocytoma. Methods: A total of 499 patients with pathologically confirmed renal tumors who underwent preoperative contrast-enhanced CT and nephrectomy were retrospectively analyzed. Results: We extracted and analyzed radiomic features from 1548 multi-phase CT scans from 499 patients, focusing on fat-poor tumors. Five machine learning classifiers including Linear SVM, Rbf SVM, Random Forest, and XGBoost were involved. Among the models, XGBoost showed the best classification performance, with an average AU-PRC: mean = 0.757, standard error = 0.033 and a renal angiomyolipoma-specific AU-ROC: mean = 0.824, standard error = 0.023. These results outperformed other single-phase CT radiomic feature-based machine learning models trained with 20% of principal components. Conclusions: This study demonstrates the effectiveness of radiomics-based machine learning in classifying renal tumor subtypes and highlights the potential of AI in medical imaging. The findings, particularly the utility of single-phase CT and feature optimization, offer valuable insights for future precision medicine approaches. Such methods may support more personalized diagnosis and treatment planning in renal oncology.<\/jats:p>","DOI":"10.3390\/diagnostics15111365","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T12:28:42Z","timestamp":1748435322000},"page":"1365","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Computed Tomography-Based Radiomics Diagnostic Model for Fat-Poor Small Renal Tumor Subtypes"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0450-8763","authenticated-orcid":false,"given":"Seokhwan","family":"Bang","sequence":"first","affiliation":[{"name":"Department of Urology, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heehwan","family":"Wang","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul 08826, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hoyoung","family":"Bae","sequence":"additional","affiliation":[{"name":"Department of Urology, Seoul Metropolitan Government, Seoul National University Boramae Medical Center, Seoul 07061, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sung-Hoo","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Urology, Seoul St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiook","family":"Cha","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul 08826, Republic of Korea"},{"name":"Department of Phychology, Seoul National University, Seoul 08826, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moon Hyung","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Radiology, Eunpyung St. Mary\u2019s Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.eururo.2016.02.029","article-title":"The 2016 WHO classification of tumours of the urinary system and male genital organs\u2014Part A: Renal, penile, and testicular tumours","volume":"70","author":"Moch","year":"2016","journal-title":"Eur. 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