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Abstract Background and aims Carotid calcification features are readily quantifiable by CTA, yet their relationship with plaque vulnerability and rupture remains controversial. We investigated whether calcium score, volume, density, and residual (volume-normalized) calcium density are associated with carotid plaque vulnerability, symptomatic status, and recurrent ipsilateral ischemic stroke and transient ischemic attack (TIA). Methods Patients with recent TIA or ischemic stroke and ≥2mm carotid plaque with <70% stenosis underwent baseline CTA and MRI. Carotid calcifications were segmented on CTA (≥130 Hounsfield units), yielding calcium score, volume, and density. Volume-normalized residual calcium density was calculated as the standardized residuals from a log-transformed calcium density-volume model (Figure 1). Vulnerable plaque features (intraplaque hemorrhage, thin-or-ruptured fibrous cap, and lipid-rich necrotic core, and ulceration) were linked to calcium metrics. Associations between calcium metrics and recurrent ipsilateral TIA or ischemic stroke were assessed using Cox regression and adjusted for age, sex, stenosis. Results Among 193 patients (mean age 67.8±8.5 years, 144 (75%) men), 26 experienced ipsilateral ischemic stroke or TIA over median 5-year follow-up. Lower calcium density and residual calcium density were independently associated with vulnerable plaques (adjusted ORs: 0.40-0.60; Figure 2). Residual calcium density remained independently associated with symptomatic side (adjusted OR: 0.64, 95%CI: 0.47-0.88) and with recurrent TIA/stroke (adjusted HR: 0.53, 95%CI: 0.29-0.95). Calcium score, volume, and density were not independently associated with symptomatic side or recurrent events (Figure 3). Conclusions Residual calcium density is a robust, independent marker of carotid plaque vulnerability and ipsilateral ischemic stroke and TIA risk in patients with symptomatic carotid artery disease. Conflict of interest Juul Bierens: nothing to disclose; Daniel Bos: nothing to disclose; Paul J. Nederkoorn: nothing to disclose; Pim A. de Jong: nothing to disclose; Robert J. van Oostenbrugge: nothing to disclose; Luc J.M. Smits: nothing to disclose; Jae W. Song: nothing to disclose; Giuseppe Lanzino: nothing to disclose; M. Eline Kooi: nothing to disclose; Luca Saba: nothing to disclose. Figure 1 - belongs to Methods Figure 2 - belongs to Results Figure 3 - belongs to Conclusions

Background Carotid artery calcification represents a common feature of atherosclerotic plaques. However, the geometric relationships of calcific clusters have not been systematically investigated. This study aimed to develop a geometry-based atlas, independent of symptom status, characterizing the three-dimensional properties of calcium clusters within carotid plaques and quantifying population-level distributions and data-driven couplings between size, shape, and density. Methods Standardized three-dimensional calcium masks of clinical CT scans were analyzed using connected-component labeling. Extracted features included cluster volume, aspect ratio, eccentricity, compactness, and CT attenuation values (mean μ, standard deviation σ). Associations between cluster features were assessed using Spearman correlations with Benjamini–Hochberg false discovery rate correction. Independent associations were determined using partial Spearman correlation and restricted cubic spline regression. Results Among 107 plaques, 149 distinct clusters were identified, most frequently presenting as a single elongated cluster (aspect ratio = 2.23). Independent associations (all p < 0.001) were identified for: eccentricity with μ (ρ = −0.39), volume with μ (ρ = 0.47), compactness with μ (ρ = 0.39), and volume with eccentricity (ρ = 0.82). Multi-cluster plaques exhibited smaller mean cluster volume (76.1 vs 359.5 mm 3 ; p < 0.001) and lower eccentricity (0.5 vs 1.6; p < 0.001) compared with single-cluster plaques. Conclusion Carotid calcification most frequently manifests as a single elongated cluster, with robust couplings between cluster size, shape, and density. These geometric archetypes provide a quantifiable framework for future biomechanical and biological studies of plaque vulnerability.

Introduction: Carotid artery intraplaque hemorrhage (IPH) is increasingly recognized as a predictive marker of cerebrovascular events. Despite widespread utilization of contrast-enhanced CT angiography (CTA) for the evaluation of carotid atherosclerosis, diagnosis of IPH on CTA is challenging, limiting risk stratification capabilities. We evaluated convolutional neural networks (CNN) for detection of histology-proven IPH in carotid CTA. Methods: The study included carotid endarterectomy patients from our center who had preoperative CTA and available plaque specimens from the Mayo Clinic Carotid Artery Atherosclerosis Trial (MCAT) Biobank. A validated segmentation model localized common and internal carotid arteries (CCA/ICA). CCA bifurcation served as landmark after a large language model, Llama3.0-70B, verified culprit plaque proximity to the bifurcation from CTA reports. A 3×3×4cm box around ipsilateral CCA bifurcation was sampled from CTA volumes and images were labeled IPH by histology study of carotid specimen (Fig 1). Given limited cases with concurrent imaging and histology, we employed a robust cross-validation strategy: 22 cases (20%) held-out for testing, with remaining data 86 cases used for 5-fold cross-validation (stratified by IPH presence). The five resulting models independently generated IPH probability scores, and ensembled predictions calculated by three methods to enhance generalizability: Majority and weighted voting based on binary IPH class and soft voting based on IPH probability scores. Results: Of 418 patients with histological analysis, 130 had CTA studies available. After excluding 22 cases lacking histological consensus, 108 cases were analyzed. In the 22 test cases the mean age was 68.1±8.5 years and 59% were male; In the cross-validation folds age ranged from 67.1±6.9 to 75.3±7.6 years 56-82% were male. Individual models' performance on the test set showed mean ROC-AUC of 0.79 (95% CI: ±0.05) and average precision of 0.85 (±0.05) (Fig 2). The ensemble approach achieved superior performance with soft voting demonstrated 82% ROC-AUC, 77% accuracy, 79% precision, 85% sensitivity, and 82% F1-score for IPH detection, outperforming majority voting and weighted voting (Fig 3). Conclusion: Automated IPH detection in widely available CTA imaging can turn it to a powerful stroke risk assessment tool, supporting personalized prevention strategies and surgical decision-making, ultimately reducing cerebrovascular morbidity and mortality.

Background: Little is known about the association between intraplaque hemorrhage (IPH) and other features of high-risk carotid atherosclerotic plaques, such as the presence of plaque ulceration, plaque enhancement, and lipid-rich necrotic core (LRNC). This study set out to assess the relationship between IPH and other vulnerable plaque features. Materials and Methods: A retrospective review was done of 102 patients with IPH in one or both of the internal carotid arteries (ICA) on neck MRA between 1/1/2016 and 3/31/2021. IPH was defined as a ≥200% signal intensity of the adjacent sternocleidomastoid muscle on MPRAGE images. All ICA plaques were assessed for the presence or absence of IPH, plaque ulceration, plaque enhancement, and LRNC, as well as IPH volume. IPH volume was measured manually by outlining the region of interest. Results: A total of 102 patients were included, with 88 (86.3%) being male. The average age was 73.5 years (SD = 9.0). Both IPH and LRNC were more commonly seen in the left carotid artery ( p = .018 and p = .047, respectively). For right-sided ICAs, there was a significant association between IPH and LRNC ( p < .0001). Lesions without IPH were more likely to have plaque enhancement than lesions with IPH ( p = .04). For left-sided ICAs, there was also a significant association between the presence of IPH and LRNC ( p < .0001). Conclusions: There is a significant association between the presence of IPH and LRNC. An inverse relationship was found between the presence of IPH and plaque enhancement for right-sided plaques. No associations were found between IPH and plaque ulceration.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.

Background: Previous studies have linked pericoronary artery adipose tissue attenuation to major adverse cardiac event (MACE). However, the association between pericarotid artery fat and prognosis remains underexplored. This study aimed to investigate the association between preoperative pericarotid fat characteristics and the subsequent prognosis in patients undergoing carotid endarterectomy (CEA). Methods: This study included patients with preoperative computed tomography angiography (CTA) followed by CEA. Preoperative neck CTA images were obtained and analyzed with novel methods using 3D Slicer software. We segmented the common and internal carotid arteries. The segment was horizontally trimmed, isolating the region around the bifurcation, extending 15 mm above and 10 mm below. Pericarotid fat was defined as adipose tissue within a 5 mm radial distance from the outer vessel wall, with Hounsfield units (HU) between -190 and -30 (Figure 1, carotid segmentation [green] and pericarotid fat [yellow]) . For each patient, we calculated the HU average and the volume (mm3) of the pericarotid fat. MACE was defined as a composite of all-cause mortality, myocardial infarction, and cerebrovascular events. The relationship between both pericarotid fat characteristics and MACE was investigated. Results: Of the 43 patients initially included, one was excluded due to an inability to perform segmentation caused by chronic total occlusion, leaving 42 patients (age 73 [67-78] years, 33 [76.7%] male). The comparison of mean pericarotid fat HU between the ipsilateral and contralateral sides showed no significant difference (-60.3±11.0 HU vs. -60.9 ±11.3 HU, p=0.437). However, the median ipsilateral fat volume was significantly higher than the contralateral volume (528 [248, 1100] mm3 vs. 328 [184, 697] mm3, p=0.020). When comparing patients with and without MACE, those with MACE had a significantly lower ipsilateral fat density (-59.4±10.2 HU vs. -66.8 ±11.1 HU, p=0.022) and a higher fat volume (468 [233, 746] mm3 vs. 845 [458, 1451] mm3, p=0.044). Kaplan-Meier analysis revealed that higher volume and lower fat density than the median were significant predictors of MACE (log-rank p=0.015 and p=0.042, respectively) (Figure 2). Conclusions: Assessment of pericarotid fat using a novel CTA analytic method in patients undergoing CEA identified ipsilateral lower fat density and higher fat volume as predictors of adverse outcomes.

Background: Previous research has suggested pericarotid fat density to be significantly linked to atherosclerotic plaque components and cerebrovascular events. Inflammatory markers within the plaques are critical in the pathogenesis and progression of carotid artery disease. However, the association between pericarotid fat and inflammatory processes within atherosclerotic plaques remains underexplored. This study hypothesizes that pericarotid fat density is directly associated with the levels of inflammatory markers within atherosclerotic plaques. Methods: Carotid plaques were prospectively collected from patients with carotid artery disease undergoing carotid endarterectomy (CEA). The levels of inflammatory plaque cytokines (MCP-1, IL-8, IFN-γ, IL-10, IL-1β, IL-6, PDGF-AA, PDGF-AB/BB, TNF-α, VEGF) were measured in tissue homogenates using a customized 10-plex Luminex assay. Baseline demographics and clinical data of our population were extracted from electronic health records. We analyzed preoperative neck computed tomography angiography (CTA) images placing regions-of-interest (ROI) in the pericarotid fat on the slice showing maximal stenosis. For each patient, we calculated the average of Hounsfield Units (HU) within the ROI. Spearman correlation test was used to assess the correlation between variables. Results: Among the 43 patients included, the median age was 73 (67, 78) years, and 33 (76.7%) patients were male. Plaque levels of PDGF-AA and VEGF showed significant positive correlations with HU (r=0.330, p=0.030; r=0.380, p=0.011, respectively), as illustrated in Figure 1 . Although plaque levels of IFN-γ demonstrated a significant negative correlation with HU (r=-0.390, p=0.010), the most cases exhibited values close to zero. Conclusions: The assessment of pericarotid fat density on CTA may allow for the estimation of plaque inflammation, suggesting that more fat density is associated with increased inflammatory activity within atherosclerotic plaques.

Background: The bovine aortic arch is a vascular variant in which the left common carotid artery originates from the brachiocephalic trunk rather than directly from the aortic arch. The bovine anatomical variation may alter the blood flow dynamics, potentially contributing to the formation and progression of carotid plaques. In this study, we evaluated the association of the bovine aortic arch and the severity of carotid stenosis. Methods: In this retrospective study, we included patients with carotid artery disease undergoing carotid endarterectomy (CEA) and pre-surgical computed tomography angiography (CTA). CTAs were reviewed to assess the carotid stenosis and the anatomy of the aortic arch. The left carotid artery was classified as normal if it originated from the aortic arch and as bovine if it originated from the brachiocephalic trunk (Figure 1) . Unlimited propensity score matching was performed to balance baseline characteristics between patients with bovine and normal anatomies. The Mann-Whitney U test was applied to compare carotid stenosis between bovine and normal arteries. Results: A total of 203 patients (bovine:23, normal:180) were initially enrolled. Using propensity score matching, 20 patients with bovine anatomy were matched to 45 patients with normal anatomy (Figure 2) . Among the 65 patients included, 47 (74.6%) were male, with a median age of 70 [IQR:65.0-76.0] years. Left-sided carotid artery disease was more prevalent in the bovine compared to normal group (N=12, 66.7% vs. N=16, 36.4%; p=0.030). Additionally, the severity of carotid stenosis in CEA-treated side was higher in patients with bovine arch compared to normal controls (82.5% [76.2-88.7] vs. 70.0% [50.0-95.0]; p=0.030) (Figure 3) . Conclusions: The association of a bovine aortic arch with more severe carotid stenosis suggests that this anatomical variant may be a marker for increased cerebrovascular risk.

Abstract Cardiovascular disease remains a prominent cause of disability and premature death worldwide. Within this spectrum, carotid artery atherosclerosis is a complex and multifaceted condition, and a prominent precursor of acute ischaemic stroke and other cardiovascular events. The intricate interplay among inflammation, oxidative stress, endothelial dysfunction, lipid metabolism, and immune responses participates in the development of lesions, leading to luminal stenosis and potential plaque instability. Even non-stenotic plaques can precipitate a sudden cerebrovascular event, regardless of the degree of luminal encroachment. In this context, carotid imaging modalities have proved their efficacy in providing in vivo characterization of plaque features, contributing substantially to patient risk stratification and clinical management. This review emphasizes the importance of identifying high-risk individuals by use of current imaging modalities, biomarkers, and risk stratification tools. Such approaches inform early intervention and the implementation of personalized therapeutic strategies, ultimately enhancing patient outcomes in the realm of cardiovascular disease management.

Positive remodeling (PR) is an atherosclerotic plaque feature defined as an increase in arterial caliber at the level of an atheroma, in response to increasing plaque burden. The mechanisms that lead to its formation are incompletely understood, but its role in coronary atherosclerosis has major clinical implications. Indeed, plaques with PR have elevated risk of provoking acute cardiac events. Hence, PR figures among the high-risk plaque features that cardiac imaging studies should report. This review aims to provide an overview of the current literature on coronary PR. It outlines the pathophysiology of PR, the different techniques used to assess its presence, and the imaging findings associated to PR, on both noninvasive and invasive studies. This review also summarizes clinical observations, trials, and studies, focused on the impact of PR on clinical outcome.