Hao Yu-Wei, Ning Xue-Yi, Wang He, Bai Xu, Zhao Jian, Xu Wei, Zhang Xiao-Jing, Yang Da-Wei, Jiang Jia-Hui, Ding Xiao-Hui, Cui Meng-Qiu, Liu Bai-Chuan, Guo Hui-Ping, Ye Hui-Yi, Wang Hai-Yi
Department of Radiology, First Medical Center, Chinese PLA General Hospital, Beijing, China.
Department of Radiology, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
J Magn Reson Imaging. 2025 Jan;61(1):97-110. doi: 10.1002/jmri.29392. Epub 2024 May 13.
Clear cell likelihood score (ccLS) is reliable for diagnosing small renal masses (SRMs). However, the diagnostic value of Clear cell likelihood score version 1.0 (ccLS v1.0) and v2.0 for common subtypes of SRMs might be a potential score extension.
To compare the diagnostic performance and interobserver agreement of ccLS v1.0 and v2.0 for characterizing five common subtypes of SRMs.
Retrospective.
797 patients (563 males, 234 females; mean age, 53 ± 12 years) with 867 histologically proven renal masses.
FIELD STRENGTH/SEQUENCES: 3.0 and 1.5 T/T2 weighted imaging, T1 weighted imaging, diffusion-weighted imaging, a dual-echo chemical shift (in- and opposed-phase) T1 weighted imaging, multiphase dynamic contrast-enhanced imaging.
Six abdominal radiologists were trained in the ccLS algorithm and independently scored each SRM using ccLS v1.0 and v2.0, respectively. All SRMs had definite pathological results. The pooled area under curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate the diagnostic performance of ccLS v1.0 and v2.0 for characterizing common subtypes of SRMs. The average κ values were calculated to evaluate the interobserver agreement of the two scoring versions.
Random-effects logistic regression; Receiver operating characteristic analysis; DeLong test; Weighted Kappa test; Z test. The statistical significance level was P < 0.05.
The pooled AUCs of clear cell likelihood score version 2.0 (ccLS v2.0) were statistically superior to those of ccLS v1.0 for diagnosing clear cell renal cell carcinoma (ccRCC) (0.907 vs. 0.851), papillary renal cell carcinoma (pRCC) (0.926 vs. 0.888), renal oncocytoma (RO) (0.745 vs. 0.679), and angiomyolipoma without visible fat (AMLwvf) (0.826 vs. 0.766). Interobserver agreement for SRMs between ccLS v1.0 and v2.0 is comparable and was not statistically significant (P = 0.993).
The diagnostic performance of ccLS v2.0 surpasses that of ccLS v1.0 for characterizing ccRCC, pRCC, RO, and AMLwvf. Especially, the standardized algorithm has optimal performance for ccRCC and pRCC. ccLS has potential as a supportive clinical tool.
Stage 2.
透明细胞可能性评分（ccLS）在诊断小肾肿块（SRMs）方面是可靠的。然而，透明细胞可能性评分1.0版（ccLS v1.0）和2.0版（ccLS v2.0）对SRMs常见亚型的诊断价值可能是一个潜在的评分扩展。
比较ccLS v1.0和v2.0对SRMs五种常见亚型进行特征描述的诊断性能和观察者间一致性。
回顾性研究。
797例患者（563例男性，234例女性；平均年龄53±12岁），共867个经组织学证实的肾肿块。
场强/序列：3.0和1.5T/T2加权成像、T1加权成像、扩散加权成像、双回波化学位移（同相和反相）T1加权成像、多期动态对比增强成像。
6名腹部放射科医生接受了ccLS算法培训，并分别使用ccLS v1.0和v2.0对每个SRM进行独立评分。所有SRMs均有明确的病理结果。计算汇总曲线下面积（AUC）、准确性、敏感性和特异性，以评估ccLS v1.0和v2.0对SRMs常见亚型进行特征描述的诊断性能。计算平均κ值以评估两种评分版本的观察者间一致性。
随机效应逻辑回归；受试者操作特征分析；德龙检验；加权卡方检验；Z检验。统计学显著性水平为P<0.05。
在诊断透明细胞肾细胞癌（ccRCC）（0.907对0.851）、乳头状肾细胞癌（pRCC）（0.926对0.888）、肾嗜酸细胞瘤（RO）（0.745对0.679）和无可见脂肪的血管平滑肌脂肪瘤（AMLwvf）（0.826对0.766）方面，透明细胞可能性评分2.0版（ccLS v2.0）的汇总AUC在统计学上优于ccLS v1.0。ccLS v1.0和v2.0之间SRMs的观察者间一致性相当，且无统计学显著性（P=0.993）。
在对ccRCC、pRCC、RO和AMLwvf进行特征描述方面，ccLS v2.0的诊断性能优于ccLS v1.0。特别是，标准化算法在ccRCC和pRCC方面具有最佳性能。ccLS有潜力作为一种辅助临床工具。
4级。
2级。
