Liu Jian, Zhang Xunlan, Lv Rui, Zhang Xiaoyong, Wang Rongpin, Zeng Xianchun
Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province, Engineering Research Center of Text Computing & Cognitive Intelligence, State Key Laboratory of Public Big Data, College of Computer Science and Technology, Ministry of Education, Guizhou University, No. 2708, Huaxi Avenue, Guiyang, 550025, Guizhou, China.
Department of nuclear medicine, Guizhou Provincial People's Hospital, No. 83, Zhongshan Dong Road, Guiyang, 550002, Guizhou, China.
Cancer Imaging. 2025 Apr 4;25(1):49. doi: 10.1186/s40644-025-00866-0.
To explore the potential of using the extracellular volume fraction (ECV), measured through enhanced computed tomography (CT), as a tool for determining the pathological grade of clear cell renal cell carcinoma (ccRCC).
This retrospective study, approved by the institutional review board, included 65 patients (median age: 58.40 ± 10.84 years) who were diagnosed with ccRCC based on the nucleolar grading of the International Society of Urological Pathology (ISUP). All patients underwent preoperative abdominal enhanced CT between January 2022 and August 2024. CT features from the unenhanced, corticomedullary, nephrographic, and delayed phases were analyzed, and the extracellular volume fraction (ECV) of ccRCC was calculated by measuring CT values from regions of interest in both the unenhanced and nephrographic phases. Statistical significance was evaluated for differences in these parameters across the four ISUP grades. Additionally, diagnostic efficiency was assessed using receiver operating characteristic (ROC) curve analysis.
The ECV showed significant differences across the four ISUP grades of ccRCC, its potential as an important predictor of high-grade ccRCC (P = 0.035). The ROC curve analysis indicated that ECV exhibited the highest diagnostic efficacy for assessing the lower- and higher- pathological grade of ccRCC, with an area under the ROC curve of 0.976. The optimal diagnostic threshold for ECV was determined to be 41.64%, with a sensitivity of 91.31% and a specificity of 97.62%.
ECV derived from enhanced CT has the potential to function as an in vivo biomarker for distinguishing between lower- and higher-grade ccRCC. This quantitative measure provides diagnostic value that extends beyond traditional qualitative CT features, offering a more precise and objective assessment of tumor grade.
探讨通过增强计算机断层扫描（CT）测量的细胞外体积分数（ECV）作为确定透明细胞肾细胞癌（ccRCC）病理分级工具的潜力。
这项回顾性研究经机构审查委员会批准，纳入了65例患者（中位年龄：58.40±10.84岁），这些患者根据国际泌尿病理学会（ISUP）的核仁分级被诊断为ccRCC。所有患者在2022年1月至2024年8月期间接受了术前腹部增强CT检查。分析了平扫期、皮质髓质期、肾实质期和延迟期的CT特征，并通过测量平扫期和肾实质期感兴趣区域的CT值来计算ccRCC的细胞外体积分数（ECV）。评估了这四个ISUP分级中这些参数差异具有的统计学意义。此外，使用受试者操作特征（ROC）曲线分析评估诊断效率。
ECV在ccRCC的四个ISUP分级中显示出显著差异，其作为高级别ccRCC重要预测指标的潜力（P = 0.035）。ROC曲线分析表明，ECV在评估ccRCC的低级别和高级别病理分级方面具有最高的诊断效能，ROC曲线下面积为0.976。确定ECV的最佳诊断阈值为41.64%，灵敏度为91.31%，特异性为97.62%。
增强CT得出的ECV有潜力作为区分低级别和高级别ccRCC的体内生物标志物。这种定量测量提供了超越传统定性CT特征的诊断价值，为肿瘤分级提供了更精确和客观的评估。
