Disparate trends of atherosclerotic plaque evolution in stroke patients under 18-month follow-up: a 3D whole-brain magnetic resonance vessel wall imaging study

Plaque Evolution and Vessel Wall Remodeling of Intracranial Arteries: A Prospective, Longitudinal Vessel Wall MRI Study

BACKGROUND

Progression of intracranial atherosclerotic disease (ICAD) is associated with ischemic stroke events and can be quantified with three-dimensional (3D) intracranial vessel wall (IVW) MRI. However, longitudinal 3D IVW studies are limited and ICAD evolution remains relatively unknown.

PURPOSE

To evaluate ICAD changes longitudinally and to characterize the imaging patterns of atherosclerotic plaque evolution.

STUDY TYPE

Prospective.

POPULATION

37 patients (69 ± 12 years old, 12 females) with angiography confirmed ICAD.

FIELD STRENGTH/SEQUENCE

3.0T/3D time-of-flight gradient echo sequence and T1- and proton density-weighted fast spin echo sequences.

ASSESSMENT

Each patient underwent baseline and 1-year follow-up IVW. Then, IVW data from both time points were jointly preprocessed using a multitime point, multicontrast, and multiplanar viewing workflow (known as MOCHA). Lumen and outer wall of plaques were traced and measured, and plaques were then categorized into progression, stable, and regression groups based on changes in plaque wall thickness. Patient demographic and clinical data were collected. Culprit plaques were identified based on cerebral ischemic infarcts.

STATISTICAL TESTS

Generalized estimating equations-based linear and logistic regressions were used to assess associations between vascular risk factors, medications, luminal stenosis, IVW plaque imaging features, and longitudinal changes. A two-sided P-value<0.05 was considered statistically significant.

RESULTS

Diabetes was significantly associated with ICAD progression, resulting in 6.6% decrease in lumen area and 6.7% increase in wall thickness at 1-year follow-up. After accounting for arterial segments, baseline contrast enhancement predicted plaque progression (odds ratio = 3.61). Culprit plaques experienced an average luminal expansion of 10.9% after 1 year. 74% of the plaques remained stable during follow-up. The regression group (18 plaques) showed significant increase in minimum lumen area (from 7.4 to 8.3 mm2), while the progression group (13 plaques) showed significant decrease in minimum lumen area (from 5.4 to 4.3 mm2).

DATA CONCLUSION

Longitudinal 3D IVW showed ICAD remodeling on the lumen side. Culprit plaques demonstrated longitudinal luminal expansion compared with their non-culprit counterparts. Baseline plaque contrast enhancement and diabetes mellitus were found to be significantly associated with ICAD changes.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

HR-MRI-based nomogram network calculator to predict stroke recurrence in high-risk non-disabling ischemic cerebrovascular events patients

Background and objective

To investigate the use of high-resolution magnetic resonance imaging (HR-MRI) to identify the characteristics of culprit plaques in intracranial arteries, and to evaluate the predictive value of the characteristics of culprit plaques combined with the modified Essen score for the recurrence risk of high-risk non-disabling ischemic cerebrovascular events (HR-NICE) patients.

Methods

A retrospective analysis was conducted on 180 patients with HR-NICE at the First Affiliated Hospital of Xinxiang Medical University, including 128 patients with no recurrence (non-recurrence group) and 52 patients with recurrence (recurrence group). A total of 65 patients with HR-NICE were collected from the Sixth Affiliated Hospital of Shanghai Jiaotong University as a validation group, and their modified Essen scores, high-resolution magnetic resonance vessel wall images, and clinical data were collected. The culprit plaques were analyzed using VesselExplorer2 software. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for recurrence, and a nomogram was constructed using R software to evaluate the discrimination of the model. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) was used to evaluate the model performance. Calibration curves and Decision Curve Analysis (DCA) were used to evaluate the model efficacy.

Results

Intra-plaque hemorrhage (OR = 3.592, 95% CI = 1.474-9.104, p = 0.006), homocysteine (OR = 1.098, 95% CI = 1.025-1.179, p = 0.007), and normalized wall index (OR = 1.114, 95% CI = 1.027-1.222, p = 0.015) were significantly higher in the recurrent stroke group than in the non-recurrent stroke group, and were independent risk factors for recurrent stroke. The performance of the nomogram model (AUC = 0.830, 95% CI: 0.769-0.891; PR-AUC = 0.628) was better than that of the modified Essen scoring model (AUC = 0.660, 95% CI: 0.583-0.738) and the independent risk factor combination model (AUC = 0.827, 95% CI: 0.765-0.889). The nomogram model still had good model performance in the validation group (AUC = 0.785, 95% CI: 0.671-0.899), with a well-fitting calibration curve and a DCA curve indicating good net benefit efficacy for patients.

Conclusion

High-resolution vessel wall imaging combined with a modified Essen score can effectively assess the recurrence risk of HR-NICE patients, and the nomogram model can provide a reference for identifying high-risk populations with good clinical application prospects.

Emerging Concept of Intracranial Arterial Diseases: The Role of High Resolution Vessel Wall MRI

Intracranial arterial disease (ICAD) is a heterogeneous condition characterized by distinct pathologies, including atherosclerosis. Advances in magnetic resonance technology have enabled the visualization of intracranial arteries using high-resolution vessel wall imaging (HR-VWI). This review summarizes the anatomical, embryological, and histological differences between the intracranial and extracranial arteries. Next, we review the heterogeneous pathophysiology of ICAD, including atherosclerosis, moyamoya or RNF213 spectrum disease, intracranial dissection, and vasculitis. We also discuss how advances in HR-VWI can be used to differentiate ICAD etiologies. We emphasize that one should consider clinical presentation and timing of imaging in the absence of pathology-radiology correlation data. Future research should focus on understanding the temporal profile of HR-VWI findings and developing quantitative interpretative approaches to improve the decision-making and management of ICAD.

Intracranial atherosclerotic plaque enhancement and long-term risk of future strokes: A prospective, longitudinal study

BACKGROUND AND PURPOSE

The prognostic significance of postcontrast enhancement of intracranial atheromatous plaque is uncertain. Prospective, long-term follow-up studies in Caucasians, using a multicenter design, are lacking. We aimed to evaluate whether this radiological sign predicts long-term new stroke in symptomatic and asymptomatic intracranial atherosclerotic disease (ICAD) patients.

METHODS

This was a prospective, observational, longitudinal, multicenter study. We included a symptomatic and an asymptomatic cohort of ICAD patients that underwent 3T MRI including high-resolution sequences focused on the atheromatous plaque. We evaluated grade of stenosis, plaque characteristics, and gadolinium enhancement ratio (postcontrast plaque signal/postcontrast corpus callosum signal). The occurrence of new events was evaluated at 3, 6, 9, and 12 months and annually thereafter. The association between plaque characteristics and new stroke was studied using Cox multiple regression survival analysis and Kaplan-Meier curves.

RESULTS

Forty-eight symptomatic and 13 asymptomatic patients were included. During 56.3 ± 16.9 months, 11 patients (18%) suffered a new event (seven ischemic, two hemorrhagic, and two transient ischemic attacks). A receiver operating characteristic curve identified an enhancement ratio of >1.77 to predict a new event. In a multivariable Cox regression, postcontrast enhancement ratio >1.77 (hazard ratio [HR]= 3.632; 95% confidence interval [CI], 1.082-12.101) and cerebral microbleeds (HR = 5.244; 95% CI, 1.476-18.629) were independent predictors of future strokes. Patients with a plaque enhancement ratio >1.77 had a lower survival free of events (p < .05).

CONCLUSIONS

High intracranial postcontrast enhancement is a long-term predictor of new stroke in ICAD patients. Further studies are needed to elucidate whether postcontrast enhancement reflects inflammatory activity of intracranial atheromatous plaque.

Intracranial vessel wall segmentation with deep learning using a novel tiered loss function incorporating class inclusion

PURPOSE

To develop an automated vessel wall segmentation method on T1-weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall.

METHODS

We propose a novel method that estimates the inner and outer vessel wall boundaries simultaneously, using a network with a single output channel resembling the level-set function height. The network is driven by a unique tiered loss that accounts for data fidelity of the lumen and vessel wall classes and a length regularization to encourage boundary smoothness.

RESULTS

Implemented with a 2.5D UNet with a ResNet backbone, the proposed method achieved Dice similarity coefficients (DSC) in 2D of 0.925 ± 0.048, 0.786 ± 0.084, Hausdorff distance (HD) of 0.286 ± 0.436, 0.345 ± 0.419 mm, and mean surface distance (MSD) of 0.083 ± 0.037 and 0.103 ± 0.032 mm for the lumen and vessel wall, respectively, on a test set; compared favorably to a baseline UNet model that achieved DSC 0.924 ± 0.047, 0.794 ± 0.082, HD 0.298 ± 0.477, 0.394 ± 0.431 mm, and MSD 0.087 ± 0.056, 0.119 ± 0.059 mm. Our vessel wall segmentation method achieved substantial improvement in morphological integrity and accuracy compared to benchmark methods.

CONCLUSIONS

The proposed method provides a systematic approach to model the inclusion morphology and incorporate it into an optimization infrastructure. It can be applied to any application where inclusion exists among a (sub)set of classes to be segmented. Improved feasibility in result morphology promises better support for clinical quantification and decision.

3D Enhancement Color Maps in the Characterization of Intracranial Atherosclerotic Plaques

BACKGROUND AND PURPOSE

High-resolution MR imaging allows the identification of culprit symptomatic plaques after the administration of gadolinium. Current high-resolution MR imaging methods are limited by 2D multiplanar views and manual sampling of ROIs. We analyzed a new 3D method to objectively quantify gadolinium plaque enhancement.

MATERIALS AND METHODS

Patients with stroke due to intracranial atherosclerotic disease underwent 7T high-resolution MR imaging. 3D segmentations of the plaque and its parent vessel were generated. Signal intensity probes were automatically extended from the lumen into the plaque and the vessel wall to generate 3D enhancement color maps. Plaque gadolinium (Gd) uptake was quantified from 3D color maps as gadolinium uptake = (µPlaque T1 + Gd -µPlaque T1/SDPlaque T1). Additional metrics of enhancement such as enhancement ratio, variance, and plaque-versus-parent vessel enhancement were also calculated. Conventional 2D measures of enhancement were collected for comparison.

RESULTS

Thirty-six culprit and 44 nonculprit plaques from 36 patients were analyzed. Culprit plaques had higher gadolinium uptake than nonculprit plaques (P < .001). Gadolinium uptake was the most accurate metric for identifying culprit plaques (OR, 3.9; 95% CI 2.1-8.3). Gadolinium uptake was more sensitive (86% versus 70%) and specific (71% versus 68%) in identifying culprit plaques than conventional 2D measurements. A multivariate model, including gadolinium uptake and plaque burden, identified culprit plaques with an 83% sensitivity and 86% specificity.

CONCLUSIONS

The new 3D color map method of plaque-enhancement analysis is more accurate for identifying culprit plaques than conventional 2D methods. This new method generates a new set of metrics that could potentially be used to assess disease progression.

Radiomics Nomogram for Predicting Stroke Recurrence in Symptomatic Intracranial Atherosclerotic Stenosis

Objective

To develop and validate a radiomics nomogram for predicting stroke recurrence in symptomatic intracranial atherosclerotic stenosis (SICAS).

Methods

The data of 156 patients with SICAS were obtained from the hospital database. Those with and without stroke recurrence were identified. The 156 patients were separated into a training cohort (n = 110) and a validation cohort (n = 46). Baseline clinical data were collected from our medical records, and plaque radiological features were extracted from vascular wall high-resolution imaging (VW-HRMRI). The imaging sequences included 3D-T1WI-VISTA, T2WI, and 3D-T1WI-VISTA-enhanced imaging. Least absolute shrinkage and selection operator (LASSO) analysis were used to select the radiomics features associated with stroke recurrence. Then, multiple logistic regression analysis of clinical risk factors, radiological features, and radiomics signatures were performed, and a predictive nomogram was constructed to predict the probability of stroke recurrence in SICAS. The performance of the nomogram was evaluated.

Results

Diabetes mellitus, plaque burden, and enhancement ratio were independent risk factors for stroke recurrence [odds ratio (OR) = 1.24, 95% confidence interval (CI): 1.04–3.79, p = 0.018; OR = 1.76, per 10% increase, 95% CI, 1.28–2.41, p < 0.001; and OR = 1.94, 95% CI: 1.27–3.09, p < 0.001]. Five features of 3D-T1WI-VISTA, six features of T2WI, and nine features of 3D-T1WI-VISTA-enhanced images were associated with stroke recurrence. The radiomics signature in 3D-T1WI-VISTA-enhanced images was superior to the radiomics signature of the other two sequences for predicting stroke recurrence in both the training cohort [area under the curve (AUC), 0.790, 95% CI: 0.669–0.894] and the validation cohort (AUC, 0.779, 95% CI: 0.620–0.853). The combination of clinical risk factors, radiological features, and radiomics signature had the best predictive value (AUC, 0.899, 95% CI: 0.844–0.936 in the training cohort; AUC, 0.803, 95% CI: 0.761–0.897 in the validation cohort). The C-index of the nomogram was 0.880 (95% CI: 0.805–0.934) and 0.817 (95% CI: 0.795–0.948), respectively, in the training and validation cohorts. The decision curve analysis further confirmed that the radiomics nomogram had good clinical applicability with a net benefit of 0.458.

Conclusion

The radiomics features were helpful to predict stroke recurrence in patients with SICAS. The nomogram constructed by combining clinical high-risk factors, plaque radiological features, and radiomics features is a reliable tool for the individualized risk assessment of predicting the recurrence of SICAS stroke.

Case Report: Serial MR Vessel Wall Imaging Visualizes the Response of Intracranial Plaques and Assists in Decision-Making

Intracranial atherosclerotic disease (ICAD) is a dynamic process that leads to ischemic stroke. Symptomatic ICAD patients still suffer a high recurrent rate even under standard treatment. In this case report, to better understand the response of intracranial atherosclerotic plaques to medication, serial MR imaging was added to standard clinical workup in a 47-year-old male patient with acute occipital lobe infarction at baseline, 3-month, 6-month, and 12-month post index stroke to directly visualize the morphology and signal change of plaques. We noticed that one of the plaques showed dramatic worsening at 3-month imaging follow-up despite a decrease in low-density lipoprotein level. Early identification of patients who do not respond well to medication is critical to prevent the recurrence of cardiovascular events in ICAD patients.

Current Clinical Applications of Intracranial Vessel Wall MR Imaging

Intracranial vessel wall MR imaging (VWI) is increasingly being used as a valuable adjunct to conventional angiographic imaging techniques. This article will provide an updated review on intracranial VWI protocols and image interpretation. We review VWI technical considerations, describe common VWI imaging features of different intracranial vasculopathies and show illustrative cases. We review the role of VWI for differentiating among steno-occlusive vasculopathies, such as intracranial atherosclerotic plaque, dissections and Moyamoya disease. We also highlight how VWI may be used for the diagnostic work-up and surveillance of patients with vasculitis of the central nervous system and cerebral aneurysms.