本研究的目的是根据 18F-FDG PET/CT 图像获得的定量空间异质性指标构建预测高级别浆液性卵巢癌 (HGSOC) 铂类耐药的模型。对诊断为 HGSOC 的患者进行回顾性研究。使用来自 CT 和 PET 图像的传统特征和 Haralick 纹理特征生成空间异质性的定量指标。建立了三组预测模型（传统模型、异质性模型和集成模型）。每组的最佳模型是曲线下面积 (AUC) 最高的模型。术后对 Ki-67 和 p53 进行免疫组织化学染色。采用Spearman相关系数（ρ）评估异质性指标与Ki-67和p53评分之间的相关性。共纳入286名患者（54.6±9.3岁）。提取了107个空间异质性指标。使用梯度提升机 (GBM) 算法获得每组的最佳模型。验证集的常规模型中的 AUC 为 0.790（95% CI：0.696，0.885），验证集的异质性模型中的 AUC 为 0.904（95% CI：0.842，0.966）。集成模型实现了最高的预测性能，验证集的 AUC 值为 0.928（95% CI：0.872，0.984）。 Spearman 相关性显示 HU_Kurtosis 与 p53 评分的相关性最强，ρ = 0.718，而簇位点熵与 Ki-67 评分的相关性最强，ρ = 0.753。添加源自 PET/CT 图像的定量空间异质性指标可以改善预测HGSOC 患者铂类耐药的影响。空间异质性指标与 Ki-67 和 p53 分数相关。© 2024 作者。约翰·威利出版的癌症医学

The purpose of this study is to construct models for predicting platinum resistance in high-grade serous ovarian cancer (HGSOC) derived from quantitative spatial heterogeneity indicators obtained from 18F-FDG PET/CT images.A retrospective study was conducted on patients diagnosed with HGSOC. Quantitative indicators of spatial heterogeneity were generated using conventional features and Haralick texture features from both CT and PET images. Three groups of predictive models (conventional, heterogeneity, and integrated) were built. Each group's optimal model was the one with the highest area under curve (AUC). Postoperative immunohistochemical staining for Ki-67 and p53 was conducted. The correlation between the heterogeneity indicators and scores for Ki-67 and p53 was assessed by Spearman's correlation coefficient (ρ).A total of 286 patients (54.6 ± 9.3 years) were enrolled. And 107 spatial heterogeneity indicators were extracted. The optimal models for each group were obtained using the Gradient Boosting Machine (GBM) algorithm. There was an AUC of 0.790 (95% CI: 0.696, 0.885) in the conventional model for the validation set, and an AUC of 0.904 (95% CI: 0.842, 0.966) in the heterogeneity model for the validation set. The integrated model achieved the highest predictive performance, with an AUC value of 0.928 (95% CI: 0.872, 0.984) for the validation set. Spearman's correlation showed that HU_Kurtosis had the strongest correlation with p53 scores with ρ = 0.718, while cluster site entropy had the strongest correlation with Ki-67 scores with ρ = 0.753.Adding quantitative spatial heterogeneity indicators derived from PET/CT images can improve the prediction of platinum resistance in patients with HGSOC. Spatial heterogeneity indicators were related to Ki-67 and p53 scores.© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.