Schmitz-Abecassis Bárbara, Dirven Linda, Jiang Janey, Keller Jasmin A, Croese Robert J I, van Dorth Daniëlle, Ghaznawi Rashid, Kant Ilse M J, Taphoorn Martin J B, van Osch Matthias J P, Koekkoek Johan A F, de Bresser Jeroen
C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Medical Delta, South-Holland, The Netherlands.
Neurooncol Adv. 2023 Oct 12;5(1):vdad133. doi: 10.1093/noajnl/vdad133. eCollection 2023 Jan-Dec.
Distinguishing true tumor progression (TP) from treatment-induced abnormalities (eg, pseudo-progression (PP) after radiotherapy) on conventional MRI scans remains challenging in patients with a glioblastoma. We aimed to establish brain MRI phenotypes of glioblastomas early after treatment by combined analysis of structural and perfusion tumor characteristics and assessed the relation with recurrence rate and overall survival time.
Structural and perfusion MR images of 67 patients at 3 months post-radiotherapy were visually scored by a neuroradiologist. In total 23 parameters were predefined and used for hierarchical clustering analysis. Progression status was assessed based on the clinical course of each patient 9 months after radiotherapy (or latest available). Multivariable Cox regression models were used to determine the association between the phenotypes, recurrence rate, and overall survival.
We established 4 subgroups with significantly different tumor MRI characteristics, representing distinct MRI phenotypes of glioblastomas: TP and PP rates did not differ significantly between subgroups. Regression analysis showed that patients in subgroup 1 (characterized by having mostly small and ellipsoid nodular enhancing lesions with some hyper-perfusion) had a significant association with increased mortality at 9 months (HR: 2.6 (CI: 1.1-6.3); = .03) with a median survival time of 13 months (compared to 22 months of subgroup 2).
Our study suggests that distinct MRI phenotypes of glioblastomas at 3 months post-radiotherapy can be indicative of overall survival, but does not aid in differentiating TP from PP. The early prognostic information our method provides might in the future be informative for prognostication of glioblastoma patients.
在胶质母细胞瘤患者中,在传统MRI扫描上区分真正的肿瘤进展(TP)与治疗引起的异常(例如放疗后的假性进展(PP))仍然具有挑战性。我们旨在通过对结构和灌注肿瘤特征的联合分析来建立胶质母细胞瘤治疗后早期的脑MRI表型,并评估其与复发率和总生存时间的关系。
由一名神经放射科医生对67例患者放疗后3个月的结构和灌注MR图像进行视觉评分。总共预定义了23个参数,并用于层次聚类分析。根据每位患者放疗后9个月(或最新可得时间)的临床病程评估进展状态。使用多变量Cox回归模型来确定表型、复发率和总生存之间的关联。
我们建立了4个具有显著不同肿瘤MRI特征的亚组,代表了胶质母细胞瘤不同的MRI表型:亚组之间的TP和PP率没有显著差异。回归分析显示,亚组1(其特征为大多是小的椭圆形结节状强化病变且有一些高灌注)的患者在9个月时死亡率显著增加(HR:2.6(CI:1.1 - 6.3);P = 0.03),中位生存时间为13个月(相比之下,亚组2为22个月)。
我们的研究表明,放疗后3个月胶质母细胞瘤不同的MRI表型可指示总生存,但无助于区分TP与PP。我们的方法提供的早期预后信息未来可能对胶质母细胞瘤患者的预后有指导意义。