The role of radiomics analysis in the assessment of renal nodules on CT

期刊论文
出版模式：

开放获取
发表日期：

2024年9月4日

查看全文

Alice Zannotti,
Alessandra Borgheresi,
Francesco Mariotti,
Gloria Giacomelli,
Elisabetta Tola,
Elisa Cesari,
Marzia Marchegiani,
Francesca Sternardi,
Alessia Cimadamore,
Andrea Agostini,
Andrea Benedetto Galosi,
Andrea Giovagnoni

摘要

Purpose

To develop a radiomics model for the characterization of renal nodules on CT.

Methods

Patients who underwent surgical resection of renal nodules, with preoperative CT (LightSpeed VCT, GE) with contrast agent (Iopamidol 370; 1.5 ml/kg) and availability of a histopathological report, were retrospectively included. Renal lesions were segmented by two radiologists in consensus, in the arterial phase on the axial section with greater diameter. The radiomics analysis was performed with validated software (PyRadiomics on Syngo.via Frontier, Siemens) by applying normalization, resampling (1,1,1), setting bin width (15), and applying padding (2). The extracted features were used for training and testing machine learning models (random forest and support vector machine (end point: clear cell carcinoma, ccRCC).

Results

45 patients were included (mean age 56 years; 34/45 ccRCC). SVM e RF models obtained an AUC of 0.84 and accuracy of 0.87 and 0.80, respectively, in the testing phase.

Conclusion

Radiomics analysis is feasible and effective in the characterization of renal lesions on CT.