Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, The Air Force Medical University, 569 Xinsi Road, Xi'an, 710038, Shaanxi Province, China.
Department of Radiology, The 987th Hospital of Joint Logistic Support Force, People's Liberation Army, 45# Dongfeng Road, Jintai District, Baoji, 721004, Shaanxi Province, China.
Cancer Imaging. 2024 Aug 18;24(1):109. doi: 10.1186/s40644-024-00754-z.
This study aimed to investigate the intra- and inter-observer consistency of the Visually Accessible Rembrandt Images (VASARI) feature set before and after dichotomization, and the association between dichotomous VASARI features and the overall survival (OS) in glioblastoma (GBM) patients.
This retrospective study included 351 patients with pathologically confirmed IDH1 wild-type GBM between January 2016 and June 2022. Firstly, VASARI features were assessed by four radiologists with varying levels of experience before and after dichotomization. Cohen's kappa coefficient (κ) was calculated to measure the intra- and inter-observer consistency. Then, after adjustment for confounders using propensity score matching, Kaplan-Meier curves were used to compare OS differences for each dichotomous VASARI feature. Next, patients were randomly stratified into a training set (n = 211) and a test set (n = 140) in a 3:2 ratio. Based on the training set, Cox proportional hazards regression analysis was adopted to develop combined and clinical models to predict OS, and the performance of the models was evaluated with the test set.
Eleven VASARI features with κ value of 0.61-0.8 demonstrated almost perfect agreement after dichotomization, with the range of κ values across all readers being 0.874-1.000. Seven VASARI features were correlated with GBM patient OS. For OS prediction, the combined model outperformed the clinical model in both training set (C-index, 0.762 vs. 0.723) and test set (C-index, 0.812 vs. 0.702).
The dichotomous VASARI features exhibited excellent inter- and intra-observer consistency. The combined model outperformed the clinical model for OS prediction.
本研究旨在探讨 Visually Accessible Rembrandt Images（VASARI）特征集在二分法前后的观察者内和观察者间一致性，以及二分 VASARI 特征与胶质母细胞瘤（GBM）患者总生存期（OS）之间的关联。
本回顾性研究纳入了 2016 年 1 月至 2022 年 6 月期间经病理证实为 IDH1 野生型 GBM 的 351 例患者。首先，由 4 名具有不同经验水平的放射科医生在二分法前后评估 VASARI 特征。采用 Cohen's kappa 系数（κ）来衡量观察者内和观察者间的一致性。然后，通过倾向评分匹配调整混杂因素后，采用 Kaplan-Meier 曲线比较每个二分 VASARI 特征的 OS 差异。接下来，将患者按 3:2 的比例随机分为训练集（n=211）和测试集（n=140）。基于训练集，采用 Cox 比例风险回归分析建立联合和临床模型来预测 OS，并采用测试集评估模型的性能。
11 个 VASARI 特征在二分法后具有 κ 值为 0.61-0.8，表现出几乎完美的一致性，所有读者的 κ 值范围为 0.874-1.000。7 个 VASARI 特征与 GBM 患者 OS 相关。对于 OS 预测，在训练集（C 指数，0.762 与 0.723）和测试集（C 指数，0.812 与 0.702）中，联合模型均优于临床模型。
二分 VASARI 特征表现出极好的观察者内和观察者间一致性。联合模型在 OS 预测方面优于临床模型。
