Background: The purpose of this research is to evaluate the predictive capabilities of a radiomics model for the Ki67 index and its correlation with prognosis in advanced gastric tubular adenocarcinoma patients.

Methods: Clinical data from 213 patients were analyzed, categorizing patients into high and low Ki67 index groups. The radiomic features of 192 patients were selected by lasso method and the model was constructed, which was validated using the TCIA dataset. Univariate and multivariate Cox regression analyses were used to further analyze clinical features associated with the prognosis of gastric cancer, radiomic models are also used to assess patient outcomes.

Results: The radiomics model demonstrated moderate accuracy, with AUC values of 0.634, 0.666, and 0.602 for the training, validation 1, and validation 2 sets, respectively. Additionally, a significant correlation was found between the Ki67 index and radiomics scores, a higher Ki67 index was associated with improved outcomes. Kaplan-Meier analysis showed distinct survival differences between patients with high and low radiomics scores, indicating that higher scores predict better prognosis.

Conclusions: The radiomics model accurately predicts the Ki67 index and correlates with prognosis in advanced gastric tubular adenocarcinoma, offering valuable insights for clinical decision-making and personalized treatment strategies.

Keywords: Advanced gastric tubular adenocarcinoma; Ki67; Prognosis; Radiomics.

© 2025. The Author(s).

背景：本研究的目的是评估预测胃管状腺癌患者Ki67指数的影像组学模型的能力及其与预后的相关性。

方法：分析了213名患者的临床数据，并将患者分为高Ki67指数组和低Ki67指数组。通过Lasso方法选择了192名患者的影像组学特征，构建了模型并使用TCIA数据集进行了验证。采用单因素和多因素Cox回归分析进一步分析与胃癌预后相关的临床特征，并且也利用影像组学模型来评估患者的结果。

结果：该影像组学模型表现出中等的准确性，训练集、验证1集和验证2集的AUC值分别为0.634、0.666和0.602。此外，发现Ki67指数与影像组学评分之间存在显著相关性，较高的Ki67指数与更好的结果相关。Kaplan-Meier分析显示高分组患者与低分组患者的生存差异明显，表明较高得分预示着较好的预后。

结论：该影像组学模型能够准确预测胃管状腺癌的Ki67指数，并且与预后相关，为临床决策和个性化治疗策略提供了有价值的见解。

关键词：晚期胃管状腺癌；Ki67；预后；影像组学。

© 2025. The Author(s).