从 CT 成像特征和影像组学模型鉴别肾上皮样血管平滑肌脂肪瘤与透明细胞癌
Differentiating renal epithelioid angiomyolipoma from clear cell carcinoma: using a radiomics model combined with CT imaging characteristics.
机构信息
Department of Radiology, Seoul National University Hospital, Seoul, Korea.
Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
出版信息
Abdom Radiol (NY). 2022 Aug;47(8):2867-2880. doi: 10.1007/s00261-022-03571-9. Epub 2022 Jun 13.
PURPOSE
This study aims to assess the computed tomography (CT) findings of renal epithelioid angiomyolipoma (EAML) and develop a radiomics-based model for differentiating EAMLs and clear cell renal cell carcinomas (RCCs).
METHOD
This two-center retrospective study included 28 histologically confirmed EAMLs and 56 size-matched clear cell RCCs with preoperative three-phase kidney CTs. We conducted subjective image analysis to determine the CT parameters that can distinguish EAMLs from clear cell RCCs. Training and test sets were divided by chronological order of CT scans, and radiomics model was built using ten selected features among radiomics and CT features. The diagnostic performance of the radiomics model was compared with that of the three radiologists using the area under the receiver-operating characteristic curve (AUC).
RESULTS
The mean size of the EAMLs was 6.2 ± 5.0 cm. On multivariate analysis, a snowman or ice cream cone tumor shape (OR 16.3; 95% CI 1.7-156.9, P = 0.02) and lower tumor-to-cortex (TOC) enhancement ratio in the corticomedullary phase (OR 33.4; 95% CI 5.7-197, P < 0.001) were significant independent factors for identifying EAMLs. The diagnostic performance of the radiomics model (AUC 0.89) was similar to those of genitourinary radiologists (AUC 0.78 and 0.81, P > 0.05) and superior to that of a third-year resident (AUC 0.63, P = 0.04).
CONCLUSIONS
A snowman or ice cream cone shape and lower TOC ratio were more closely associated with EAMLs than with clear cell RCCs. A CT radiomics model was useful for differentiating EAMLs from clear cell RCCs with better diagnostic performance than an inexperienced radiologist.
目的
本研究旨在评估肾脏上皮样血管平滑肌脂肪瘤(EAML)的计算机断层扫描(CT)表现,并建立基于放射组学的模型以区分 EAML 和透明细胞肾细胞癌(RCC)。
方法
本项两中心回顾性研究纳入了 28 例经组织学证实的 EAML 和 56 例大小匹配的透明细胞 RCC,均行术前三期肾脏 CT。我们进行了主观图像分析,以确定可以区分 EAML 和透明细胞 RCC 的 CT 参数。根据 CT 扫描的时间顺序将训练集和测试集进行划分,并使用放射组学和 CT 特征中选择的 10 个特征构建放射组学模型。使用受试者工作特征曲线(AUC)下面积比较放射组学模型与三位放射科医生的诊断性能。
结果
EAML 的平均大小为 6.2±5.0cm。多变量分析显示,雪人或冰淇淋锥形状(OR 16.3;95%CI 1.7-156.9,P=0.02)和皮质期肿瘤与皮质比值(OR 33.4;95%CI 5.7-197,P<0.001)较低是识别 EAML 的独立显著因素。放射组学模型的诊断性能(AUC 0.89)与泌尿生殖系统放射科医生(AUC 0.78 和 0.81,P>0.05)相当,优于三年级住院医师(AUC 0.63,P=0.04)。
结论
雪人或冰淇淋锥形状和较低的 TOC 比值与 EAML 的相关性强于与透明细胞 RCC 的相关性。CT 放射组学模型有助于区分 EAML 和透明细胞 RCC,诊断性能优于经验不足的放射科医生。