An Image-Based Workflow for Objective Vessel Wall Enhancement Quantification in Intracranial Aneurysms

Imaging of Intracranial Aneurysms: A Review of Standard and Advanced Imaging Techniques

The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several clinical and radiological risk factors for aneurysm rupture have been described and incorporated into prediction models. Despite the recent technological advancements in aneurysm imaging, linear length and visible irregularity with a bleb are the only radiological measure used in clinical prediction models. The purpose of this article is to summarize both the standard imaging techniques, including their limitations, and the advanced techniques being used experimentally to image aneurysms. It is expected that as our understanding of advanced techniques improves, and their ability to predict clinical events is demonstrated, they become an increasingly routine part of aneurysm assessment. It is important that neurovascular specialists understand the spectrum of imaging techniques available.

Statins may Decrease Aneurysm wall Enhancement of Unruptured Fusiform Intracranial Aneurysms: A high-resolution 3T MRI Study

Inflammation plays an integral role in the formation, growth, and progression to rupture of unruptured intracranial aneurysms. Aneurysm wall enhancement (AWE) in high-resolution magnetic resonance imaging (HR-MRI) has emerged as a surrogate biomarker of vessel wall inflammation and unruptured intracranial aneurysm instability. We investigated the correlation between anti-inflammatory drug use and three-dimensional AWE of fusiform intracranial aneurysms (FIAs). We retrospectively analyzed consecutive patients with FIAs in our database who underwent 3T HR-MRI at three Chinese centers. FIAs were classified as fusiform-type, dolichoectatic-type, or transitional-type. AWE was objectively defined using the aneurysm-to-pituitary stalk contrast ratio in three-dimensional space by determining the contrast ratio of the average signal intensity in the aneurysmal wall and pituitary stalk on post-contrast T1-weighted images. Data on aneurysm size, morphology, and location, as well as patient demographics and comorbidities, were collected. Univariate and multivariate logistic regression analyses were performed to determine factors independently associated with AWE of FIAs on HR-MRI. In total, 127 FIAs were included. In multivariate analysis, statin use (β = -0.236, P = 0.007) was the only independent factor significantly associated with decreased AWE. In the analysis of three FIA subtypes, the fusiform and transitional types were significantly associated with statin use (rs = -0.230, P = 0.035; and rs = -0.551, P = 0.010; respectively). It establishes an incidental correlation between the use of statins daily for ≥ 6 months and decreased AWE of FIAs. The findings also indicate that the pathophysiology may differ among the three FIA subtypes.

3D aneurysm wall enhancement is associated with symptomatic presentation

BACKGROUND

Aneurysm wall enhancement (AWE) is a potential surrogate biomarker for aneurysm instability. Previous studies have assessed AWE using 2D multiplanar methods, most of which were conducted qualitatively.

OBJECTIVE

To use a new quantitative tool to analyze a large cohort of saccular aneurysms with 3D-AWE maps METHODS: Saccular aneurysms were imaged prospectively with 3T high resolution MRI. 3D-AWE maps of symptomatic (defined as ruptured or presentation with sentinel headache/cranial nerve neuropathy) and asymptomatic aneurysms were created by extending orthogonal probes from the aneurysm lumen into the wall. Three metrics were used to characterize enhancement: 3D circumferential AWE (3D-CAWE), aneurysm-specific contrast uptake (SAWE), and focal AWE (FAWE). Aneurysms with a circumferential AWE higher than the corpus callosum (3D-CAWE ≥1) were classified as 3D-CAWE+. Symptomatic presentation was analyzed with univariate and multivariate logistic models. Aneurysm size, size ratio, aspect ratio, irregular morphology, and PHASES and ELAPSS scores were compared with the new AWE metrics. Bleb and microhemorrhage analyses were also performed.

RESULTS

Ninety-three aneurysms were analyzed. 3D-CAWE, SAWE, and FAWE were associated with symptomatic status (OR=1.34, 1.25, and 1.08, respectively). A multivariate model including aneurysm size, 3D-CAWE+, age, female gender, and FAWE detected symptomatic status with 80% specificity and 90% sensitivity (area under the curve=0.914, =0.967). FAWE was also associated with irregular morphology and high-risk location (p=0.043 and p=0.001, respectively). In general, blebs enhanced 56% more than the aneurysm body. Areas of microhemorrhage co-localized with areas of increased SAWE (p=0.047).

CONCLUSIONS

3D-AWE mapping provides a new set of metrics that could potentially improve the identification of symptomatic aneurysms.

Tectonic infarct analysis: A computational tool for automated whole-brain infarct analysis from TTC-stained tissue

Background

Infarct volume measured from 2,3,5-triphenyltetrazolium chloride (TTC)-stained brain slices is critical to in vivo stroke models. In this study, we developed an interactive, tunable, software that automatically computes whole-brain infarct metrics from serial TTC-stained brain sections.

Methods

Three rat ischemic stroke cohorts were used in this study (Total n = 91 rats; Cohort 1 n = 21, Cohort 2 n = 40, Cohort 3 n = 30). For each, brains were serially-sliced, stained with TTC and scanned on both anterior and posterior sides. Ground truth annotation and infarct morphometric analysis (e.g., brain-V_brain, infarct-V_infarct, and non-infarct-V_non-infarct volumes) were completed by domain experts. We used Cohort 1 for brain and infarct segmentation model development (n = 3 training cases with 36 slices [18 anterior and posterior faces], n = 18 testing cases with 218 slices [109 anterior and posterior faces]), as well as infarct morphometrics automation. The infarct quantification pipeline and pre-trained model were packaged as a standalone software and applied to Cohort 2, an internal validation dataset. Finally, software and model trainability were tested as a use-case with Cohort 3, a dataset from a separate institute.

Results

Both high segmentation and statistically significant quantification performance (correlation between manual and software) were observed across all datasets. Segmentation performance: Cohort 1 brain accuracy = 0.95/f1-score = 0.90, infarct accuracy = 0.96/f1-score = 0.89; Cohort 2 brain accuracy = 0.97/f1-score = 0.90, infarct accuracy = 0.97/f1-score = 0.80; Cohort 3 brain accuracy = 0.96/f1-score = 0.92, infarct accuracy = 0.95/f1-score = 0.82. Infarct quantification (cohort average): V_brain (ρ = 0.87, p < 0.001), V_infarct (0.92, p < 0.001), V_non-infarct (0.80, p < 0.001), %infarct (0.87, p = 0.001), and infarct:non-infact ratio (ρ = 0.92, p < 0.001).

Conclusion

Tectonic Infarct Analysis software offers a robust and adaptable approach for rapid TTC-based stroke assessment.

Aneurysm risk metrics and hemodynamics are associated with greater vessel wall enhancement in intracranial aneurysms

Vessel wall enhancement (VWE) in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for intracranial aneurysm (IA) risk stratification. In this study, we investigated the relationship between VWE features, risk metrics, morphology and hemodynamics in 41 unruptured aneurysms. We reconstructed the IA geometries from MR angiography and mapped pituitary stalk-normalized MRI intensity on the aneurysm surface using an in-house tool. For each case, we calculated the maximum intensity (CRstalk) and IA risk (via size and the rupture resemblance score (RRS)). We performed correlation analysis to assess relationships between CRstalk and IA risk metrics (size and RRS), as well as each parameter encompassed in RRS, i.e. aneurysmal size ratio (SR), normalized wall shear stress (WSS) and oscillatory shear index. We found that CRstalk had a strong correlation (Pearson correlation coefficient, PCC = 0.630) with size and a moderate correlation (PCC = 0.472) with RRS, indicating an association between VWE and IA risk. Furthermore, CRstalk had a weak negative correlation with normalized WSS (PCC = -0.320) and a weak positive correlation with SR (PCC = 0.390). Local voxel-based analysis showed only a weak negative correlation between normalized WSS and contrast-enhanced MRI signal intensity (PCC = -0.240), suggesting that if low-normalized WSS induces enhancement-associated pathobiology, the effect is not localized.