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DOI 10.1186/s12885-024-13283-6

Медицинская библиотека · BMC cancer · 2024

Radiomics for differential diagnosis of Bosniak II-IV renal masses via CT imaging.

Zhao Xun, Yan Ye, Xie Wanfang, Qin Zijian, Zhao Litao, Liu Cheng, Zhang Shudong, Liu Jiangang, Ma Lulin

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Аннотация

RATIONALE AND

OBJECTIVES

The management of complex renal cysts is guided by the Bosniak classification system, which may be inadequate for risk stratification of patients to determine the appropriate intervention. Radiomics models based on CT imaging may provide additional useful information.

MATERIALS AND

METHODS

A total of 322 patients with Bosniak II-IV cysts were included in the study from January 2010 to December 2019. Contrast-enhanced CT scans were performed on all patients. ITK-snap was used for segmentation, and the PyRadiomics 3.0.1 package was used for feature extraction. The radiomics features were screened via the least absolute shrinkage and selection operator (LASSO) regression method. After feature selection, a logistic regression (LR) model, support vector machine (SVM) model and random forest (RF) model were constructed.

RESULTS

In the present study, 217 benign renal cysts (67.4%) and 105 cystic renal cell carcinomas (32.6%) were identified. According to the Bosniak classification, the sample included 179 (55.6%) Bosniak II cysts, 38 (11.8%) Bosniak IIF cysts, 44 (13.7%) Bosniak III cysts and 61 (18.9%) Bosniak IV cysts. A total of 1334 radiomics features were extracted from both unenhanced and cortical CT scans. After LASSO regression, all the models (LR, SVM and RF) showed satisfactory discrimination and reliability in both unenhanced and cortical CT scans (AUC > 0.950). In the Bosniak IIF-III subgroup analysis, the diagnostic accuracy of the LR model was very low for both the unenhanced and cortical scans. In contrast, the SVM model and RF model showed excellent and stable performance in classifying Bosniak IIF-III cysts. The AUCs of the models were all > 0.85, with a maximum of 0.941. The sensitivity, specificity, accuracy, and AUC of the RF model were 0.889, 0.913, 0.902, and 0.941, respectively.

CONCLUSION

Our data indicate that radiomics models can effectively distinguish between cystic renal cell carcinoma (cRCC) and complex renal cysts (Bosniak II-IV). Radiomics models may still have high diagnostic accuracy even for Bosniak IIF-III cysts that are clinically difficult to distinguish. However, external validation of these findings is still needed.

Для цитирования: Zhao Xun, Yan Ye, Xie Wanfang, Qin Zijian, Zhao Litao, Liu Cheng, Zhang Shudong, Liu Jiangang, Ma Lulin. Radiomics for differential diagnosis of Bosniak II-IV renal masses via CT imaging.. BMC cancer. 2024. DOI: 10.1186/s12885-024-13283-6.

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