Fu Sunya, Chen Dawei, Zhang Yuqin, Wei Yuguo, Pan Yuning
Department of Radiology, Ningbo Medical Center LiHuiLi Hospital, 1111 Jiangnan road, Ningbo, 315040, Zhejiang, People's Republic of China.
Department of Gastroenterology, Ningbo Medical Center LiHuiLi Hospital, 1111 Jiangnan road, Ningbo, 315040, Zhejiang, People's Republic of China.
Sci Rep. 2025 Jan 21;15(1):2736. doi: 10.1038/s41598-025-86932-w.
Eosinophilic solid and cystic renal cell carcinoma (ESC-RCC) is rare and often misdiagnosed as clear cell renal cell carcinoma (ccRCC). Therefore, a CT-based scoring system was developed to improve differential diagnosis. Retrospectively, 25 ESC-RCC and 176 ccRCC cases, were collected. The two groups were matched on a 1:2 basis using the propensity-score-matching (PSM) method, with matching factors including sex and age. Finally, 25 ESC-RCC and 50 ccRCC cases were included and randomly divided into a training cohort (52 cases) and a validation cohort (23 cases). Logistic regression identified significant factors, constructed the primary model, and assigned weights for the scoring model. Diagnostic performance was compared using receiver operating characteristic curves, dividing points into three intervals. Multifactorial logistic regression identified three independent factors: intra-tumour necrosis (3 points), degree of corticomedullary phase (CMP) enhancement (3 points), and pseudocapsule (2 points). The primary model's area under the curve (AUC) value was 0.954 (95% confidence interval [CI]: 0.857-0.993, P < 0.001), with 85.7% sensitivity and 94.1% specificity. The scoring model's AUC value for the training cohort was 0.950 (95% CI: 0.852-0.991, P < 0.001), with 77.1% sensitivity and 100% specificity at a cut-off of 4 points. The validation cohort's AUC was 0.942 (95% CI: 0.759-0.997, P < 0.001). The scoring system intervals were: ≥0 to < 2 points, ≥ 2 to ≤ 3 points, and > 3 to ≤ 8 points. Higher scores correlated with increased ccRCC incidence and decreased ESC-RCC incidence.The limitation of this study is the small sample size. A CT-based scoring system effectively differentiates ESC-RCC from ccRCC.
嗜酸性实性和囊性肾细胞癌（ESC-RCC）较为罕见，常被误诊为透明细胞肾细胞癌（ccRCC）。因此，开发了一种基于CT的评分系统以改善鉴别诊断。回顾性收集了25例ESC-RCC和176例ccRCC病例。采用倾向评分匹配（PSM）方法按1:2的比例对两组进行匹配，匹配因素包括性别和年龄。最终，纳入了25例ESC-RCC和50例ccRCC病例，并随机分为训练队列（52例）和验证队列（23例）。逻辑回归确定显著因素，构建初级模型，并为评分模型分配权重。使用受试者操作特征曲线比较诊断性能，将分界点分为三个区间。多因素逻辑回归确定了三个独立因素：肿瘤内坏死（3分）、皮髓质期（CMP）强化程度（3分）和假包膜（2分）。初级模型的曲线下面积（AUC）值为0.954（95%置信区间[CI]：0.857-0.993，P < 0.001），敏感性为85.7%，特异性为94.1%。训练队列评分模型的AUC值为0.950（95%CI：0.852-0.991，P < 0.001），在截断值为4分时，敏感性为77.1%，特异性为100%。验证队列的AUC为0.942（95%CI：0.759-0.997，P < 0.001）。评分系统区间为：≥0至<2分、≥2至≤3分和>3至≤8分。得分越高，ccRCC发病率增加，ESC-RCC发病率降低。本研究的局限性在于样本量小。一种基于CT的评分系统能有效区分ESC-RCC和ccRCC。
