Neimantaite Alice, Carstam Louise, Gómez Vecchio Tomás, Häggström Ida, Dunås Tora, Latini Francesco, Zetterling Maria, Blomstrand Malin, Bartek Jiri, Jensdottir Margret, Thurin Erik, Smits Anja, Jakola Asgeir S
Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Department of Neurosurgery, Sahlgrenska University Hospital, Gothenburg, Sweden.
J Neurooncol. 2025 Mar 18. doi: 10.1007/s11060-025-05006-z.
Adult patients with diffuse lower-grade gliomas (dLGG) show heterogeneous survival outcomes, complicating postoperative treatment planning. Treating all patients early increases the risk of long-term side effects, while delayed treatment may lead to impaired survival. Refinement of prognostic models could optimize timing of treatment. Conventional radiological features are prognostic in dLGG, but MRI could carry more prognostic information. This study aimed to investigate MRI-based radiomics survival models and compare them with clinical models.
Two clinical survival models were created: a preoperative model (tumor volume) and a full clinical model (tumor volume, extent of resection, tumor subtype). Radiomics features were extracted from preoperative MRI. The dataset was divided into training set and unseen test set (70:30). Model performance was evaluated on test set with Uno's concordance index (c-index). Risk groups were created by the best performing model's predictions.
207 patients with mutated IDH (mIDH) dLGG were included. The preoperative clinical, full clinical and radiomics models showed c-indexes of 0.70, 0.71 and 0.75 respectively on test set for overall survival. The radiomics model included four features of tumor diameter and tumor heterogeneity. The combined full clinical and radiomics model showed best performance with c-index = 0.79. The survival difference between high- and low-risk patients according to the combined model was both statistically significant and clinically relevant.
Radiomics can capture quantitative prognostic information in patients with dLGG. Combined models show promise of synergetic effects and should be studied further in astrocytoma and oligodendroglioma patients separately for optimal modelling of individual risks.
弥漫性低级别胶质瘤（dLGG）成年患者的生存结果存在异质性，这使得术后治疗计划变得复杂。对所有患者进行早期治疗会增加长期副作用的风险，而延迟治疗可能会导致生存受损。完善预后模型可以优化治疗时机。传统的放射学特征在dLGG中具有预后价值，但MRI可能携带更多的预后信息。本研究旨在探讨基于MRI的放射组学生存模型，并将其与临床模型进行比较。
创建了两个临床生存模型：术前模型（肿瘤体积）和完整临床模型（肿瘤体积、切除范围、肿瘤亚型）。从术前MRI中提取放射组学特征。将数据集分为训练集和未见过的测试集（70:30）。使用Uno一致性指数（c指数）在测试集上评估模型性能。通过表现最佳模型的预测创建风险组。
纳入了207例异柠檬酸脱氢酶（IDH）突变（mIDH）的dLGG患者。术前临床模型、完整临床模型和放射组学模型在测试集上的总生存c指数分别为0.70、0.71和0.75。放射组学模型包括肿瘤直径和肿瘤异质性的四个特征。完整临床模型与放射组学模型相结合表现最佳，c指数 = 0.79。根据联合模型，高风险和低风险患者之间的生存差异在统计学上具有显著性且具有临床相关性。
放射组学可以获取dLGG患者的定量预后信息。联合模型显示出协同效应的前景，应分别在星形细胞瘤和少突胶质细胞瘤患者中进一步研究，以实现个体风险的最佳建模。
