本研究旨在评估来自瘤内和瘤周区域的放射组学的预测价值，并开发放射组学列线图来预测透明细胞肾细胞癌 (ccRCC) 患者的术前核分级和总生存期 (OS)。该研究包括 395 名患者与我们机构的 ccRCC 合作。 A中心（匿名）机构的患者被随机分为训练队列（n = 284）和内部验证队列（n = 71）。还包括由来自 B 中心的 40 名患者组成的外部验证队列。从肿瘤内部区域 (IAT) 和 IAT 组合肿瘤周围区域 3mm (PAT 3mm) 和 5mm (PAT 5mm) 提取计算机断层扫描 (CT) 放射组学特征。来自临床和放射组学评分 (Radscore) 的独立预测因子用于构建放射组学列线图。采用对数秩检验进行 Kaplan-Meier 分析，以评估因素与 OS 之间的相关性。PAT 5-mm 放射组学模型 (RM) 表现出出色的分级预测能力，曲线下面积分别为 0.80、0.80 和 0.80。训练、内部验证和外部验证队列中为 0.90。从 PAT 5 mm 区域获得的列线图和 RM 比临床模型在临床上更有用。 OS 与根据 PAT 5-mm Radscore 和列线图预测评分得出的预测核分级之间的关联具有统计显着性 (p< 0.05)。基于 CT 的放射组学和列线图为世界卫生组织/国际协会显示了宝贵的预测能力瘤内和瘤周放射组学对于预测透明细胞肾细胞癌患者的核分级和总生存期是可行的，有前景的，这有助于制定个性化的术前治疗策略。 -区域放射组学特征与透明细胞肾细胞癌（ccRCC）分级和预后相关。瘤内和瘤周 5mm 区域特征的组合证明了分级的卓越预测性能。列线图和放射组学模型具有广泛的临床应用。© 2024。作者。

This study aimed to assess the predictive value of radiomics derived from intratumoral and peritumoral regions and to develop a radiomics nomogram to predict preoperative nuclear grade and overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC).The study included 395 patients with ccRCC from our institution. The patients in Center A (anonymous) institution were randomly divided into a training cohort (n = 284) and an internal validation cohort (n = 71). An external validation cohort comprising 40 patients from Center B also was included. Computed tomography (CT) radiomics features were extracted from the internal area of the tumor (IAT) and IAT combined peritumoral areas of the tumor at 3 mm (PAT 3 mm) and 5 mm (PAT 5 mm). Independent predictors from both clinical and radiomics scores (Radscore) were used to construct a radiomics nomogram. Kaplan-Meier analysis with a log-rank test was performed to evaluate the correlation between factors and OS.The PAT 5-mm radiomics model (RM) exhibited exceptional predictive capability for grading, achieving an area under the curves of 0.80, 0.80, and 0.90 in the training, internal validation, and external validation cohorts. The nomogram and RM gained from the PAT 5-mm region were more clinically useful than the clinical model. The association between OS and predicted nuclear grade derived from the PAT 5-mm Radscore and the nomogram-predicted score was statistically significant (p < 0.05).The CT-based radiomics and nomograms showed valuable predictive capabilities for the World Health Organization/International Society of Urological Pathology grade and OS in patients with ccRCC.The intratumoral and peritumoral radiomics are feasible and promising to predict nuclear grade and overall survival in patients with clear cell renal cell carcinoma, which can contribute to the development of personalized preoperative treatment strategies.The multi-regional radiomics features are associated with clear cell renal cell carcinoma (ccRCC) grading and prognosis. The combination of intratumoral and peritumoral 5 mm regional features demonstrated superior predictive performance for grading. The nomogram and radiomics models have a broad range of clinical applications.© 2024. The Author(s).