Analysis of Cerebral Aneurysm Wall Tension and Enhancement Using Finite Element Analysis and High-Resolution Vessel Wall Imaging

Biomechanical computational simulation of intracranial aneurysms has become a promising method for predicting features of instability leading to aneurysm growth and rupture. Hemodynamic analysis of aneurysm behavior has helped investigate the complex relationship between features of aneurysm shape, morphology, flow patterns, and the proliferation or degradation of the aneurysm wall. Finite element analysis paired with high-resolution vessel wall imaging can provide more insight into how exactly aneurysm morphology relates to wall behavior, and whether wall enhancement can describe this phenomenon. In a retrospective analysis of 23 unruptured aneurysms, finite element analysis was conducted using an isotropic, homogenous third order polynomial material model. Aneurysm wall enhancement was quantified on 2D multiplanar views, with 14 aneurysms classified as enhancing (CRstalk≥0.6) and nine classified as non-enhancing. Enhancing aneurysms had a significantly higher 95th percentile wall tension (μ = 0.77 N/cm) compared to non-enhancing aneurysms (μ = 0.42 N/cm, p < 0.001). Wall enhancement remained a significant predictor of wall tension while accounting for the effects of aneurysm size (p = 0.046). In a qualitative comparison, low wall tension areas concentrated around aneurysm blebs. Aneurysms with irregular morphologies may show increased areas of low wall tension. The biological implications of finite element analysis in intracranial aneurysms are still unclear but may provide further insights into the complex process of bleb formation and aneurysm rupture.

High-resolution magnetic resonance vessel wall imaging–guided endovascular recanalization for nonacute intracranial artery occlusion

OBJECTIVE On the basis of the characteristics of occluded segments on high-resolution magnetic resonance vessel wall imaging (MR-VWI), the authors evaluated the role of high-resolution MR-VWI–guided endovascular recanalization for patients with symptomatic nonacute intracranial artery occlusion (ICAO). METHODS Consecutive patients with symptomatic nonacute ICAO that was refractory to aggressive medical treatment were prospectively enrolled and underwent endovascular recanalization. High-resolution MR-VWI was performed before the recanalization intervention. The characteristics of the occluded segments on MR-VWI, including signal intensity, occlusion morphology, occlusion angle, and occlusion length, were evaluated. Technical success was defined as arterial recanalization with modified Thrombolysis in Cerebral Infarction grade 2b or 3 and residual stenosis < 50%. Perioperative complications were recorded. The characteristics of the occluded segments on MR-VWI were compared between the recanalized group and the failure group. RESULTS Twenty-five patients with symptomatic nonacute ICAO that was refractory to aggressive medical treatment were consecutively enrolled from April 2020 to February 2021. Technical success was achieved in 19 patients (76.0%). One patient (4.0%) had a nondisabling ischemic stroke during the perioperative period. Multivariable logistic analysis showed that successful recanalization of nonacute ICAO was associated with occlusion with residual lumen (OR 0.057, 95% CI 0.004–0.735, p = 0.028) and shorter occlusion length (OR 0.853, 95% CI 0.737–0.989, p = 0.035). CONCLUSIONS The high-resolution MR-VWI modality could be used to guide endovascular recanalization for nonacute ICAO. Occlusion with residual lumen and shorter occlusion length on high-resolution MR-VWI were identified as predictors of technical success of endovascular recanalization for nonacute ICAO.

Abstract 1122‐000172: High Resolution Vessel Wall Imaging and Cerebrovascular Plaques: Comparison with DSA, MRA, and CTA

Introduction : Current imaging modalities might underestimate the presence and severity of intracranial atherosclerosis (ICAD). High resolution vessel wall imaging (HR‐VWI) MRI emerged as a powerful tool to diagnose plaques not detected on routine imaging. We aim to compare different imaging modalities (HR‐VWI MRI; digital subtraction angiogram (DSA); Time‐of‐flight (TOF) MRA; and CTA) in the identification and characterization of intracranial atherosclerotic culprit plaques. Methods : Patients diagnosed with ICAD were prospectively imaged with HR‐VWI MRI. Culprit plaques were identified based on the likelihood of causing the stroke. Using cross‐sectional images of intracranial vessels, regions of interest (ROI) were delineated. Then, diameters and ROI areas were measured for the purpose of calculating the following variables: degree of stenosis (DS) at the plaque level, plaque burden (PB), and remodeling index (RI). Additional imaging modalities (DSA, TOF MRA, and CTA) were identified retrospectively for each patient. The sensitivity of detecting a culprit plaque as well as the correlations between the different variables were analyzed for each modality. Linear regression analysis was used to determine the association of DS with PB and RI. Interobserver agreement on the determination of a culprit plaque on every imaging modality was evaluated. Results : A total of 44 patients who underwent HR‐VWI had ICAD and were included in the final analysis. Of those, 34 had CTA, 18 had TOF‐MRA, and 18 had DSA. Using HR‐VWI as gold standard, the sensitivity for culprit plaque detection was 88% for DSA, 78% for TOF MRA, and 76% for CTA. We found no difference between the DS in all four modalities using measured cross‐sectional diameters, but difference was found when measuring ROI areas to calculate DS. There was a significant positive correlation between PB and DS on HR‐VWI MRI (p<0.001), but not on the DSA (p = 0.168), MRA (p = 0.144), or CTA (p = 0.253), and a significant negative correlation between RI and DS on HR‐VWI MRI (p = 0.003), but not on DSA (p = 0.783), MRA (p = 0.405), or CTA (p = 0.751). PB and RI predicted the degrees of stenosis on HR‐VWI, but not on the other modalities. There was good inter‐rater agreement for culprit plaque detection on HR‐VWI (k = 0.48, p = 0.001), but no agreement was found on the other modalities. Conclusions : HR‐VWI MRI can locate otherwise undetectable plaques on conventional imaging through the ability to measure plaque burden, an essential component for characterization of plaques severity and a strong predictor of stenosis. HR‐VWI also showed more accurate measurements of degree of stenosis through measurement of ROI areas, and had good inter‐rater agreement for accurate plaque detection, compared to DSA, MRA, and CTA.