Intratumoral and peritumoral radiomics using multi-phase contrast-enhanced CT for diagnosis of renal oncocytoma and chromophobe renal cell carcinoma: a multicenter retrospective study.

IF 3.5 3区 医学 Q2 ONCOLOGY Frontiers in Oncology Pub Date : 2025-02-05 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1501084
Yongsong Ye, Bei Weng, Yan Guo, Lesheng Huang, Shanghuang Xie, Guimian Zhong, Wenhui Feng, Wenxiang Lin, Zhixuan Song, Huanjun Wang, Tianzhu Liu
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Abstract

Purpose: To construct diagnostic models that distinguish renal oncocytoma (RO) from chromophobe renal cell carcinoma (CRCC) using intratumoral and peritumoral radiomic features from the corticomedullary phase (CMP) and nephrographic phase (NP) of computed tomography, and compare model results with manual and radiological results.

Methods: The RO and CRCC cases from five centers were split into a training set (70%) and a validation set (30%). CMP and NP intratumoral and peritumoral (1-3 mm) radiomic features were extracted. Segmentation was performed by radiologists and software. Features with high intraclass correlation coefficients (ICC>0.75) were selected through univariate analysis, followed by the LASSO method to determine the final features for the SVM model. All images were assessed by two radiologists, and radiological reports were also examined. The diagnostic performances of the different methods were compared using several statistical methods.

Results: The training set had 65 cases (29 RO, 36 CRCC) and the validation set had 27 cases (12 RO, 15 CRCC). All the training models had excellent performance (area under the curve [AUC]: 0.828-0.942); the AUC values of the validation models ranged from 0.900 (Model 4) to 0.600 (Model 2). CMP models (AUC: 0.811-0.900) generally outperformed NP and fusion models (AUC: 0.728-0.756). SVM models (sensitivity: 62.50-88.89%; specificity: 63.16-77.78%; accuracy: 62.96-81.48%) outperformed manual diagnosis (sensitivity: 46.74-70.59%; specificity: 41.67-46.34%; accuracy: 52.27-59.78%). The clinical reports alone had no diagnostic value.

Conclusion: CMP intratumoral and peritumoral radiomics models reliably distinguished RO from CRCC.

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瘤内和瘤周放射组学应用多期增强CT诊断肾嗜瘤细胞瘤和嫌色肾细胞癌:一项多中心回顾性研究。
目的:利用计算机断层扫描皮质髓质期(CMP)和肾图期(NP)的瘤内和瘤周放射学特征,建立肾嗜铬细胞瘤(RO)和嗜色肾细胞癌(CRCC)的诊断模型,并将模型结果与手工和放射学结果进行比较。方法:将5个中心的RO和CRCC病例分为训练集(70%)和验证集(30%)。提取肿瘤内和肿瘤周围(1-3 mm)的CMP和NP放射学特征。分割由放射科医生和软件完成。通过单变量分析选择类内相关系数高(ICC>0.75)的特征,然后采用LASSO方法确定SVM模型的最终特征。所有图像由两名放射科医生评估,并检查放射报告。采用几种统计方法对不同方法的诊断性能进行比较。结果:训练集65例(RO 29例,CRCC 36例),验证集27例(RO 12例,CRCC 15例)。所有训练模型均表现优异(曲线下面积[AUC]: 0.828-0.942);验证模型的AUC值在0.900(模型4)~ 0.600(模型2)之间,CMP模型(AUC: 0.811-0.900)总体优于NP模型和融合模型(AUC: 0.728-0.756)。SVM模型(灵敏度:62.50-88.89%;特异性:63.16 - -77.78%;准确率:62.96 ~ 81.48%)优于人工诊断(灵敏度:46.74 ~ 70.59%;特异性:41.67 - -46.34%;准确性:52.27 - -59.78%)。单独的临床报告没有诊断价值。结论:CMP瘤内和瘤周放射组学模型可靠地区分了RO和CRCC。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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