Ma Yanqing, Xu Xiren, Pang Peipei, Wen Yang
Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, 310000, People's Republic of China.
Department of Pharmaceuticals Diagnosis, GE Healthcare, Hangzhou, 310000, People's Republic of China.
Cancer Manag Res. 2021 Feb 12;13:1417-1425. doi: 10.2147/CMAR.S297094. eCollection 2021.
This study aimed to evaluate the role of tumor and mini-peritumor in the context of CT-based radiomics analysis to differentiate fat-poor angiomyolipoma (fp-AML) from clear cell renal cell carcinoma (ccRCC).
A total of 58 fp-AMLs and 172 ccRCCs were enrolled. The volume of interest (VOI) was manually delineated in the standardized CT images and radiomics features were automatically calculated with software. After methods of feature selection, the CT-based logistic models including tumoral model (Ra-tumor), mini-peritumoral model (Ra-peritumor), perirenal model (Ra-Pr), perifat model (Ra-Pf), and tumoral+perirenal model (Ra-tumor+Pr) were constructed. The area under curves (AUCs) were calculated by DeLong test to evaluate the efficiency of logistic models.
The AUCs of Ra-peritumor of nephrographic phase (NP) were slightly higher than those of corticomedullary phase (CMP). Furthermore, the Ra-Pr showed significant higher efficiency than the Ra-Pf, and relative more optimal radiomics features were selected in the Ra-Pr than Ra-Pf. The Ra-tumor+Pr combined tumoral and perirenal radiomics analysis was of most significant in distinction compared with Ra-tumor and Ra-peritumor.
The validity of NP to differentiate fp-AML from ccRCC was slightly higher than that of CMP. To the NP analysis, the Ra-Pr was superior to the Ra-Pf in distinction, and the lesions invaded to the perirenal tissue more severely than to the perifat tissue. It is important to the individual therapeutic surgeries according to the different lesion location. The pooled tumoral and perirenal radiomics analysis was the most promising approach in distinguishing fp-AML and ccRCC.
本研究旨在评估肿瘤及肿瘤周围微小区域在基于CT的放射组学分析中对乏脂性肾血管平滑肌脂肪瘤（fp-AML）与透明细胞肾细胞癌（ccRCC）进行鉴别诊断的作用。
共纳入58例fp-AML和172例ccRCC。在标准化CT图像上手动勾勒感兴趣体积（VOI），并使用软件自动计算放射组学特征。经过特征选择方法后，构建基于CT的逻辑模型，包括肿瘤模型（Ra-肿瘤）、肿瘤周围微小区域模型（Ra-肿瘤周围）、肾周模型（Ra-Pr）、脂肪周围模型（Ra-Pf）以及肿瘤+肾周模型（Ra-肿瘤+Pr）。通过DeLong检验计算曲线下面积（AUC）以评估逻辑模型的效能。
肾实质期（NP）的Ra-肿瘤周围的AUC略高于皮质髓质期（CMP）。此外，Ra-Pr的效能显著高于Ra-Pf，且与Ra-Pf相比，Ra-Pr中选择的放射组学特征相对更优。与Ra-肿瘤和Ra-肿瘤周围相比，Ra-肿瘤+Pr结合肿瘤和肾周放射组学分析在鉴别诊断中最为显著。
NP鉴别fp-AML与ccRCC的有效性略高于CMP。对于NP分析，Ra-Pr在鉴别诊断方面优于Ra-Pf，且病变侵犯肾周组织比侵犯脂肪周围组织更严重。根据不同病变位置进行个体化治疗手术很重要。汇总的肿瘤和肾周放射组学分析是鉴别fp-AML和ccRCC最有前景的方法。
