Liu Ping, Zeng Yu-Ping, Qu Hong, Zheng Wan-Yi, Zhou Tian-Xing, Hang Li-Feng, Jiang Gui-Hua
Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital, Jinan University, Guangzhou, China.
Department of Medical Imaging, Ganzhou People's Hospital, Ganzhou, China.
Quant Imaging Med Surg. 2024 Aug 1;14(8):5665-5681. doi: 10.21037/qims-24-280. Epub 2024 Jun 11.
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 F-fluorodeoxyglucose (F-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 F-FDG PET, arterial spin labelling (ASL), and diffusion-weighted imaging (DWI) with hybrid PET/MRI were retrospectively enrolled. The relative maximum standardized uptake value (rSUV), relative cerebral blood flow (rCBF), and relative minimum apparent diffusion coefficient (rADC) 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 rSUV and rCBF but lower rADC in the solid component and 5 mm-adjacent PTR, lower rADC in 10 mm-adjacent PTR, and higher rCBF in 15- and 20-mm-adjacent PTR. rSUV in solid component performed best [area under the curve (AUC) =0.865] as a single parameter for grading. Combination of rSUV 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 rSUV, rCBF, and rADC in the solid component and 5-mm-adjacent PTR predicted HGG with a concordance index (C-index) of 0.906.
Multiparametric F-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.
术前对胶质瘤进行分级对于临床治疗决策至关重要。目前用于胶质瘤分级的非侵入性成像方式主要集中在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所获得的生物学信息。因此，我们旨在将实体成分和PTR的混合氟代脱氧葡萄糖（F-FDG）PET/MRI的多参数结合起来，以区分高级别胶质瘤（HGG）和低级别胶质瘤（LGG）。
回顾性纳入76例经病理证实的胶质瘤患者（41例HGG和35例LGG），这些患者同时接受了F-FDG PET、动脉自旋标记（ASL）和混合PET/MRI的扩散加权成像（DWI）。比较了实体成分和肿瘤边界外不同距离处PTR的相对最大标准化摄取值（rSUV）、相对脑血流量（rCBF）和相对最小表观扩散系数（rADC）。应用受试者工作特征（ROC）曲线评估分级性能。构建了HGG预测列线图。
HGG在实体成分和距肿瘤边界5mm的相邻PTR中显示出较高的rSUV和rCBF，但rADC较低；在距肿瘤边界10mm的相邻PTR中rADC较低，在距肿瘤边界15mm和20mm的相邻PTR中rCBF较高。实体成分中的rSUV作为分级的单一参数表现最佳[曲线下面积（AUC）=0.865]。实体成分和相邻20mm处的rSUV联合使用表现更好（AUC =0.881）。实体成分和相邻20mm处的所有3个指标联合使用表现最佳（AUC =0.928）。包含实体成分和距肿瘤边界5mm的相邻PTR中的rSUV、rCBF和rADC的列线图预测HGG的一致性指数（C指数）为0.906。
实体成分和PTR的多参数F-FDG PET/MRI在区分HGG和LGG方面表现出色。它可作为胶质瘤患者术前分级分层的一种非侵入性有效工具，可在临床实践中予以考虑。
