Dier Carlos, Sanchez Sebastian, Sagues Elena, Gudino Andres, Jaramillo Rodrigo, Wendt Linder, Samaniego Edgar A
Neurology, University of Iowa, Iowa City, Iowa, USA.
Department of Neurology, Yale University, New Haven, Connecticut, USA.
J Neurointerv Surg. 2025 Sep 12;17(10):1096-1101. doi: 10.1136/jnis-2024-022133.
Blebs significantly increase rupture risk of intracranial aneurysms. Radiomic analysis offers a robust characterization of the aneurysm wall. However, the unique radiomic profile of various compartments, including blebs, remains unexplored. Likewise, the correlation between these imaging markers and fluid/mechanical metrics is yet to be investigated. To address this, we analyzed the radiomic features (RFs) of bleb-containing aneurysms and their relationship with wall tension and shear stress metrics, aiming to enhance risk assessment.
Aneurysms were imaged using high-resolution magnetic resonance imaging (MRI). A T1 and a T1 after contrast (T1+Gd) sequences were acquired. 3D models of aneurysm bodies and blebs were generated, and RFs were extracted. Aneurysms with and without blebs were matched based on location and size for analysis. Univariate regression models and Spearman's correlations were used to establish associations between bleb-dependent RFs and mechanical/fluid dynamics metrics.
Eighteen aneurysms with blebs were identified. Fifty-five RFs were significantly different between blebs and body within the same aneurysms. Of these RFs, 9% (5/55) were first-order, and 91% (50/55) were second-order features. After aneurysms with and without blebs were matched for location and size, five RFs 5% (5/93) were significantly different. Forty-one out of the 55 RFs different between bleb and body sac of the primary aneurysm were moderately and strongly correlated with mechanical and fluid dynamics metrics.
Aneurysm blebs exhibit distinct radiomic profiles compared with the main body of the aneurysm sac. The variability in bleb wall characteristics may arise from differing mechanical stresses and localized hemodynamics. Leveraging radiomic profiling could help identify regions with a heightened risk of rupture.
脑膨出显著增加颅内动脉瘤破裂风险。放射组学分析能够对动脉瘤壁进行有力表征。然而，包括脑膨出在内的各个腔室独特的放射组学特征仍未得到探索。同样，这些成像标志物与流体/力学指标之间的相关性也有待研究。为解决这一问题，我们分析了含脑膨出的动脉瘤的放射组学特征（RFs）及其与壁张力和剪应力指标的关系，旨在加强风险评估。
使用高分辨率磁共振成像（MRI）对动脉瘤进行成像。采集T1序列和对比剂增强后的T1（T1+Gd）序列。生成动脉瘤主体和脑膨出的三维模型，并提取RFs。根据位置和大小对有脑膨出和无脑膨出的动脉瘤进行匹配分析。使用单变量回归模型和Spearman相关性分析来确定与脑膨出相关的RFs与力学/流体动力学指标之间的关联。
共识别出18个有脑膨出的动脉瘤。在同一动脉瘤内，脑膨出和主体之间有55个RFs存在显著差异。其中，9%（5/55）为一阶特征，91%（50/55）为二阶特征。在根据位置和大小对有脑膨出和无脑膨出的动脉瘤进行匹配后，有5个RFs（5/93）存在显著差异。在原发性动脉瘤的脑膨出和瘤囊主体之间不同的55个RFs中，有41个与力学和流体动力学指标呈中度和强相关性。
与动脉瘤瘤囊主体相比，动脉瘤脑膨出表现出独特的放射组学特征。脑膨出壁特征的变异性可能源于不同的机械应力和局部血流动力学。利用放射组学分析有助于识别破裂风险较高的区域。
