术前胶质瘤分级对于临床治疗决策至关重要。目前用于神经胶质瘤分级的非侵入性成像方式主要集中于肿瘤区域的磁共振成像（MRI）或正电子发射断层扫描（PET）。然而，这些方法忽略了肿瘤的瘤周区域（PTR），无法充分利用混合成像产生的生物学信息。因此，我们的目的是结合固体成分的混合 18F-氟脱氧葡萄糖 (18F-FDG) PET/MRI 和 PTR 的多参数，以区分高级别胶质瘤 (HGG) 和低级别胶质瘤 (LGG)。 总共 76回顾性纳入经病理证实的神经胶质瘤患者（41 HGG 和 35 LGG），同时接受 18F-FDG PET、动脉自旋标记（ASL）和混合 PET/MRI 弥散加权成像（DWI）。比较肿瘤边界外不同距离处固体成分和PTR的相对最大标准化摄取值（rSUVmax）、相对脑血流量（rCBF）和相对最小表观扩散系数（rADCmin）。应用接受者操作特征（ROC）曲线来评估分级性能。构建了 HGG 预测列线图。HGG 在固体成分和 5 mm 相邻 PTR 中显示较高的 rSUVmax 和 rCBF，但 rADCmin 较低，在 10 mm 相邻 PTR 中较低 rADCmin，在 15 和 20 mm 相邻 PTR 中显示较高 rCBF 。固体成分中的 rSUVmax 作为单一分级参数表现最佳 [曲线下面积 (AUC) =0.865]。实体成分和相邻 20 mm 中 rSUVmax 的组合表现更好（AUC = 0.881）。实体成分和相邻 20 mm 中所有 3 个指标的整合表现最好（AUC =0.928）。列线图包括固体成分中的 rSUVmax、rCBF 和 rADCmin，以及 5 毫米相邻的 PTR 预测 HGG，一致性指数 (C 指数) 为 0.906。来自固体成分和 PTR 的多参数 18F-FDG PET/MRI 在以下方面表现出色区分 HGG 和 LGG。它可以作为胶质瘤患者术前分级分层的无创有效工具，并可以在临床实践中考虑。2024医学和外科定量成像。版权所有。

Preoperative grading gliomas is essential for therapeutic clinical decision-making. Current non-invasive imaging modality for glioma grading were primarily focused on magnetic resonance imaging (MRI) or positron emission tomography (PET) of the tumor region. However, these methods overlook the peritumoral region (PTR) of tumor and cannot take full advantage of the biological information derived from hybrid-imaging. Therefore, we aimed to combine multiparameter from hybrid 18F-fluorodeoxyglucose (18F-FDG) PET/MRI of the solid component and PTR were combined for differentiating high-grade glioma (HGG) from low-grade glioma (LGG).A total of 76 patients with pathologically confirmed glioma (41 HGG and 35 LGG) who underwent simultaneous 18F-FDG PET, arterial spin labelling (ASL), and diffusion-weighted imaging (DWI) with hybrid PET/MRI were retrospectively enrolled. The relative maximum standardized uptake value (rSUVmax), relative cerebral blood flow (rCBF), and relative minimum apparent diffusion coefficient (rADCmin) for the solid component and PTR at different distances outside tumoral border were compared. Receiver operating characteristic (ROC) curves were applied to assess the grading performance. A nomogram for HGG prediction was constructed.HGGs displayed higher rSUVmax and rCBF but lower rADCmin in the solid component and 5 mm-adjacent PTR, lower rADCmin in 10 mm-adjacent PTR, and higher rCBF in 15- and 20-mm-adjacent PTR. rSUVmax in solid component performed best [area under the curve (AUC) =0.865] as a single parameter for grading. Combination of rSUVmax in the solid component and adjacent 20 mm performed better (AUC =0.881). Integration of all 3 indicators in the solid component and adjacent 20 mm performed the best (AUC =0.928). The nomogram including rSUVmax, rCBF, and rADCmin in the solid component and 5-mm-adjacent PTR predicted HGG with a concordance index (C-index) of 0.906.Multiparametric 18F-FDG PET/MRI from the solid component and PTR performed excellently in differentiating HGGs from LGGs. It can be used as a non-invasive and effective tool for preoperative grade stratification of patients with glioma, and can be considered in clinical practice.2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.