Quantitative characterization of carotid plaque components using MR apparent diffusion coefficients and longitudinal relaxation rates at 3T: A comparison with histology

Diagnostics Accuracy of Magnetic Resonance Imaging in Detection of Atherosclerotic Plaque Characteristics in Carotid Arteries Compared to Histology: A Systematic Review

Carotid plaque composition represents one of the main risk factors of future ischemic stroke. MRI provides excellent soft tissue contrast that can distinguish plaque characteristics. Our objective was to analyze the diagnostic accuracy of MRI imaging in the detection of carotid plaque characteristics compared to histology in patients with symptomatic and asymptomatic carotid atherosclerosis through a systematic review. After prospective registration in PROSPERO (ID CRD42022329690), Medline Ovid, Embase.com, Cochrane Library, and Web of Science Core were searched without any search limitation up to May 27, 2022 to identify eligible articles. Of the 8168 studies, 53 (37 × 1.5 T MRI, 17 × 3 T MRI) evaluated MRI accuracy in the detection of 13 specific carotid plaque characteristics in 169 comparisons. MRI demonstrated high diagnostic accuracy for detection of calcification (3 T MRI: mean sensitivity 92%/mean specificity 90%; 1.5 T MRI: mean sensitivity 81%/mean specificity 91%), fibrous cap (1.5 T: 89%/87%), unstable plaque (1.5 T: 89%/87%), intraplaque hemorrhage (1.5 T: 86%/88%), and lipid-rich necrotic core (1.5 T: 89%/79%). MRI also proved to have a high level of tissue discrimination for the carotid plaque characteristics investigated, allowing potentially for a better risk assessment and follow-up of patients who may benefit from more aggressive treatments. These results emphasize the role of MRI as the first-line imaging modality for comprehensive assessment of carotid plaque morphology, particularly for unstable plaque. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Simultaneous T1, T2, and T2* Mapping of Carotid Plaque: The SIMPLE* Technique

Background Quantitative T1, T2, and T2* measurements of carotid atherosclerotic plaque are important in evaluating plaque vulnerability and monitoring its progression. Purpose To develop a sequence to simultaneously quantify T1, T2, and T2* of carotid plaque. Materials and Methods The simultaneous T1, T2, and T2* mapping of carotid plaque (SIMPLE*) sequence is composed of three modules with different T2 preparation pulses, inversion-recovery pulses, and acquisition schemas. Single-echo data were used for T1 and T2 quantification, while the multiecho (ME) data were used for T2* quantification. The quantitative accuracy of SIMPLE* was tested in a phantom study by comparing its measurements with those of reference standard sequences. In vivo feasibility of the technique was prospectively evaluated between November 2020 and February 2022 in healthy volunteers and participants with carotid atherosclerotic plaque. The Pearson or Spearman correlation test, Student t test, and Wilcoxon rank-sum test were used. Results T1, T2, and T2* estimated with SIMPLE* strongly correlated with inversion-recovery spin-echo (SE) (correlation coefficient [r] = 0.99), ME-SE (r = 0.99), and ME gradient-echo (r = 0.99) sequences in the phantom study. In five healthy volunteers (mean age, 25 years ± 3 [SD]; three women), measurements were similar between SIMPLE* and modified Look-Locker inversion recovery, or MOLLI (1151 msec ± 71 vs 1098 msec ± 64; P = .14), ME turbo SE (31 msec ± 1 vs 31 msec ± 1; P = .32), and ME turbo field echo (24 msec ± 2 vs 25 msec ± 2; P = .19). In 18 participants with carotid plaque (mean age, 65 years ± 9; 16 men), quantitative T1, T2, and T2* of plaque components were consistent with their signal characteristics on multicontrast images. Conclusion A quantitative technique for simultaneous T1, T2, and T2* mapping of carotid plaque with 100-mm³ coverage and 0.8-mm³ resolution was developed using the proposed SIMPLE* sequence and demonstrated high accuracy and in vivo feasibility. © RSNA, 2023 Supplemental material is available for this article.

Clinical Evaluation of High-Resolution MRI Combined With DWI in Identifying Vulnerable Carotid Plaque

BACKGROUND

High-resolution magnetic resonance imaging combined with diffusion weighted imaging is used to identify vulnerable plaques (VP) and their characteristic components, and apparent diffusion coefficient (ADC) correlation analysis with serum inflammatory markers to assess plaque vulnerability.

METHODS

In this study, 60 eligible patients were included, including 29 patients in VP group and 31 patients in non-VP group (N group). The average ADC value, serum inflammatory marker levels (high-sensitivity C-reactive protein, myeloperoxidase, and erythrocyte sedimentation rate) of the 2 groups were measured, and the characteristics of different plaque components and ADC levels of vascular wall in VP group were compared, to evaluate the correlation between serum inflammatory markers and the mean value of plaque ADC.

RESULTS

The results showed that the ADC mean value of the plaques in the VP group was significantly lower than that in the N group, and the levels of hypersensitive C-reactive protein and myeloperoxidase were correlated with the ADC mean value of the plaques.

CONCLUSION

The ADC value of plaque measured by high-resolution magnetic resonance imaging combined with diffusion weighted imaging sequence can quantify the identification of VP and its characteristic components, reflect the inflammation of plaque to a certain extent, and thus prevent and treat stroke and other adverse outcomes more effectively.

Role of diffusion-weighted imaging in carotid plaque vulnerability assessment

Background

MR plaque imaging is a valuable tool in characterizing carotid atherosclerotic plaque and identifying high-risk features. There are limited data on the role of the widely available single-shot diffusion-weighted imaging (DWI) in plaque characterization along with histological correlation. This study aimed to correlate the plaque characteristics identified by MR imaging in vivo at the level of maximum stenosis with histological plaque characteristics in the postoperative specimen.

Methods

Patients who underwent carotid endarterectomy in a tertiary care center during one and half years were prospectively recruited for non-contrast MR carotid plaque imaging (including single-shot EPI-DWI sequence) in a 3 Tesla MRI using a dedicated carotid coil. An experienced radiologist correlated DWI sequence findings with histopathology of postsurgical sections to confirm the high-risk features.

Results

Twenty-three patients (mean age 66.1 years ± SD 6.25) were evaluated, of which 65% were males and 96% were symptomatic. Apparent diffusion coefficient (ADC) values in location of plaques could differentiate histopathological unstable from stable plaques (0.83 × 10–3 mm2/s vs 1.7 × 10–3 mm2/s; p 0.001), with a sensitivity and specificity of 75% and 79%, respectively, at an ADC cutoff of 1.24 × 10–3 mm2/s. Plaques with and without lipid-rich necrotic core (0.86 × 10–3 mm2/s vs 1.44 × 10–3 mm2/s; p = 0.042) as well as intraplaque hemorrhage could be differentiated (0.751 × 10–3 mm2/s vs 1.352 × 10–3 mm2/s; p 0.037) using the apparent diffusion coefficients.

Conclusion

The widely available single-shot EPI-DWI in assessing plaque characteristics in carotid stenosis is promising and correlated with histopathological features. Diffusion-weighted imaging will be a helpful adjunct in patients when contrast administration is intolerable.

Reliability and Value of 3D Sequential QUantitative T1 -T2 -T2 * MAppings (SQUMA) MR Multi-Parametric Imaging in Characterizing Carotid Artery Atherosclerosis

BACKGROUND

T₁ , T₂ , and T₂ * mappings are seldom performed in a single examination, and their values in evaluating symptomatic atherosclerosis are lacking.

PURPOSE

To perform three-dimensional (3D) quantitative T₁ , T₂ , and T₂ * mappings (SQUMA) multi-parametric imaging for carotid vessel wall and evaluate its reliability and value in assessing carotid atherosclerosis.

STUDY TYPE

Prospective.

SUBJECTS

Eight healthy subjects and 20 patients with symptomatic carotid atherosclerosis.

FIELD STRENGTH/SEQUENCE

3 T, SQUMA imaging T₁ -, T₂ -, and T₂ *-mapping, multi-contrast vessel wall imaging including T₁ - and T₂ -weighted, time-of-flight, and SNAP sequences.

ASSESSMENT

SQUMA was acquired in all subjects and multi-contrast images were acquired in healthy subjects. T₁ , T₂ , and T₂ * values and lumen area (LA), wall area (WA), mean wall thickness (MeanWT), and normalized wall index (NWI) of carotid arteries were measured. SQUMA and multi-contrast measurements were compared in healthy subjects and differences in SQUMA measurements between healthy subjects and patients were assessed. The discriminative value of SQUMA measurements for symptomatic vessel was determined.

STATISTICAL TESTS

Paired t or Wilcoxon signed-rank test, independent t or Mann-Whitney U test, area under the receiver operating characteristic curve (AUC), intraclass correlation coefficients, and Bland-Altman plots. Statistically significant level, P < 0.05.

RESULTS

There were no significant differences in LA (P = 0.340), WA (P = 0.317), MeanWT (P = 0.088), and NWI (P = 0.091) of carotid arteries between SQUMA and multi-contrast vessel wall images. The values of T₂ (50.9 ± 2.9 msec vs. 44.5 ± 4.2 msec), T₂ * (28.2 ± 4.3 msec vs. 24.7 ± 2.6 msec), WA (23.7 ± 4.6 mm² vs. 36.2 ± 7.7 mm² ), MeanWT (0.99 ± 0.05 mm vs. 1.50 ± 0.28 mm), and NWI (40.7 ± 3.0% vs. 53.8 ± 5.4%) of carotid arteries in healthy subjects were significantly different from those in atherosclerotic patients. The combination of quantitative T₁ , T₂ , and T₂ * values and MeanWT showed greatest AUC (0.81; 95% CI: 0.65-0.92) in discriminating symptomatic vessels.

DATA CONCLUSION

Carotid MR 3D quantitative multi-parametric imaging of SQUMA enables acquisition of T₁ , T₂ , and T₂ * maps, reliably measuring carotid morphology and discriminating carotid symptomatic atherosclerosis.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Differentiation of symptomatic and asymptomatic carotid intraplaque hemorrhage using 3D high-resolution diffusion-weighted stack of stars imaging

Ischemic events related to carotid disease are far more strongly associated with plaque instability than stenosis. 3D high-resolution diffusion-weighted (DW) imaging can provide quantitative diffusion measurements on carotid atherosclerosis and may improve detection of vulnerable intraplaque hemorrhage (IPH). The 3D DW-stack of stars (SOS) sequence was implemented with 3D SOS acquisition combined with DW preparation. After simulation of signals created from 3D DW-SOS, phantom studies were performed. Three healthy subjects and 20 patients with carotid disease were recruited. Apparent diffusion coefficient (ADC) values were statistically analyzed on three subgroups by using a two-group comparison Wilcoxon-Mann-Whitney U test with p values less than 0.05: symptomatic versus asymptomatic; IPH-positive versus IPH-negative; and IPH-positive symptomatic versus asymptomatic plaques to determine the relationship with plaque vulnerability. ADC values calculated by 3D DW-SOS provided values similar to those calculated from other techniques. Mean ADC of symptomatic plaque was significantly lower than asymptomatic plaque (0.68 ± 0.18 vs. 0.98 ± 0.16 x 10-3  mm2 /s, p < 0.001). ADC was also significantly lower in IPH-positive versus IPH-negative plaque (0.68 ± 0.13 vs. 1.04 ± 0.11 x 10-3  mm2 /s, p < 0.001). Additionally, ADC was significantly lower in symptomatic versus asymptomatic IPH-positive plaque (0.57 ± 0.09 vs. 0.75 ± 0.11 x 10-3  mm2 /s, p < 0.001). Our results provide strong evidence that ADC measurements from 3D DW-SOS correlate with the symptomatic status of extracranial internal carotid artery plaque. Further, ADC improved discrimination of symptomatic plaque in IPH. These data suggest that diffusion characteristics may improve detection of destabilized plaque leading to elevated stroke risk.

Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application

Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the United States of America and globally. Carotid arterial plaque, a cause and also a marker of such CVD, can be detected by various non-invasive imaging modalities such as magnetic resonance imaging (MRI), computer tomography (CT), and ultrasound (US). Characterization and classification of carotid plaque-type in these imaging modalities, especially into symptomatic and asymptomatic plaque, helps in the planning of carotid endarterectomy or stenting. It can be challenging to characterize plaque components due to (I) partial volume effect in magnetic resonance imaging (MRI) or (II) varying Hausdorff values in plaque regions in CT, and (III) attenuation of echoes reflected by the plaque during US causing acoustic shadowing. Artificial intelligence (AI) methods have become an indispensable part of healthcare and their applications to the non-invasive imaging technologies such as MRI, CT, and the US. In this narrative review, three main types of AI models (machine learning, deep learning, and transfer learning) are analyzed when applied to MRI, CT, and the US. A link between carotid plaque characteristics and the risk of coronary artery disease is presented. With regard to characterization, we review tools and techniques that use AI models to distinguish carotid plaque types based on signal processing and feature strengths. We conclude that AI-based solutions offer an accurate and robust path for tissue characterization and classification for carotid artery plaque imaging in all three imaging modalities. Due to cost, user-friendliness, and clinical effectiveness, AI in the US has dominated the most.

Improvement in the contrast-to-noise ratio and quantitative measurement of T1 and T2* values for carotid atherosclerotic plaque using multi-echo phase-sensitive inversion recovery

Quantitative magnetic resonance imaging is required to accurately evaluate carotid plaque vulnerability. We prospectively evaluated the potential for fast quantitative black-blood carotid vessel wall imaging using a three-dimensional (3D) multi-echo phase-sensitive inversion recovery (mPSIR) sequence. Forty-nine patients with carotid atherosclerotic plaques were examined. Two-dimensional (2D) turbo spin-echo (TSE), 3D volumetric isotropic turbo spin-echo, and 3D mPSIR imaging were performed. The contrast-to-noise ratios (CNRs) between the carotid plaque and adjacent muscle were compared for the three imaging methods. The T₁ and T₂* values of the carotid plaques were measured using 3D mPSIR images. These values were compared with those of symptomatic and asymptomatic plaques. For carotid plaques with a signal intensity ratio ≥ 1.55, between the carotid plaque and adjacent muscle in 2D TSE images, the CNR of the mPSIR images was significantly higher than that of the other sequences. T₁ values for symptomatic and asymptomatic plaques were 544.0 ± 258.0 and 569.1 ± 301.7, respectively. T₂* values for symptomatic and asymptomatic plaques were 34.0 ± 33.0 and 21.8 ± 20.3 ms, respectively. There were no significant differences in the T₁ and T₂* values between the symptomatic and asymptomatic plaques. 3D mPSIR improves the CNR of T₁-weighted images for carotid plaques and the adjacent muscle while simultaneously providing the T₁ and T₂* values of the carotid plaque. This improved CNR may be useful for assessing the vulnerability of carotid plaques.

MR imaging of vulnerable carotid plaque

Current risk stratification for stroke is still based upon percentage of carotid stenosis, despite this measure providing minimal patient-specific information on the actual risk of stroke for both symptomatic individuals without significant carotid artery stenosis as well as asymptomatic carotid stenosis patients. A continuously growing body of literature suggests that the identification and quantification of certain carotid plaque characteristics, including lipid-rich necrotic core (LRNC), thin/ruptured fibrous cap (FC), and intraplaque hemorrhage (IPH), provide a superior means of predicting future stroke. These characteristics are identifiable via magnetic resonance imaging (MRI), with most features detectable using commercially available coils and sequences utilized in routine clinical practice in as little as 4 minutes. The presence of LRNC, a thin/ruptured FC, and IPH is associated with increased risk of future stroke or TIA. Plaques with greater than 40% LRNC with a thin overlying FC are prone to rupture. LRNC is T2 hypointense and lacks enhancement on contrast enhanced T1 weighted images. Increasing LRNC size is associated with the development of new ulceration, FC rupture, increasing plaque burden, as well as fatal and nonfatal myocardial infarction, ischemic stroke, hospitalization for acute coronary syndrome (ACS), and symptom-driven revascularization, allowing for MR biomarkers of carotid plaque vulnerability to be utilized for systemic athero-thrombotic risk and not just stroke/TIA. LRNC typically shrinks with appropriate statin therapy, with PCSK9 inhibitors possibly playing a role in patients with inadequate response. Carotid plaques with IPH represent a more advanced stage of atherosclerotic disease. IPH is detectable with field strengths of both 3.0 T and 1.5 T and will demonstrate high signal on all T1 weighted imaging sequences. The presence of IPH increases the risk of future stroke in both symptomatic and asymptomatic patients, with multivariate analysis identifying IPH as a predictor of stroke, independent of percent stenosis, with no statistical difference in men vs. women, demonstrating that simple carotid stenosis measurements and traditional risk factor analysis may be inadequate in identifying patients at the highest risk for adverse cerebrovascular events. In the evaluation for recurrent stroke in recently symptomatic patients with >50% carotid stenosis, the estimated annual stroke risk is 23.2% in IPH+ patients and only 0.6% in IPH- patients, calling into question the current risk-benefit assessment for CEA. Additionally, a recent meta-analysis suggests that IPH+ plaque in patients with symptomatic <50% stenosis may be the etiology of embolic strokes previously labeled as "embolic stroke of undetermined source" (ESUS). There are no prospective drug trials testing the ability of any lipid-lowering therapies to decrease IPH and/or total plaque volume (TPV). Given the continuously increasing evidence of IPH as a significant predictor of carotid plaque progression and future adverse vascular events, trials aimed at targeted therapy for IPH represents a significant need.

Quantitative evaluation of carotid atherosclerotic vulnerable plaques using in vivo T1 mapping cardiovascular magnetic resonaonce: validation by histology

BACKGROUND

It has been proved that multi-contrast cardiovascular magnetic resonance (CMR) vessel wall imaging could be used to characterize carotid vulnerable plaque components according to the signal intensity on different contrast images. The signal intensity of plaque components is mainly dependent on the values of T1 and T2 relaxation. T1 mapping recently showed a potential in identifying plaque components but it is not well validated by histology. This study aimed to validate the usefulness of in vivo T1 mapping in assessing carotid vulnerable plaque components by histology.

METHODS

Thirty-four subjects (mean age, 64.0 ± 8.9 years; 26 males) with carotid plaques referred to carotid endarterectomy were prospectively enrolled and underwent 3 T CMR imaging from May 2017 to October 2017. The T1 values of intraplaque hemorrhage (IPH), necrotic core (NC) and loose matrix (LM) which were identified on multi-contrast vessel wall images or histology were measured on in-vivo T1 mapping. The IPHs were divided into two types based on the proportion of the area of fresh hemorrhage on histology. The T1 values of different plaque components were compared using Mann-Whitney U test and the agreement between T1 mapping and histology in identifying and quantifying IPH was analyzed with Cohen's Kappa and intraclass correlation coefficient (ICC).

RESULTS

Of 34 subjects, 19 had histological specimens matched with CMR imaging. The mean T1 values of IPH (651 ± 253 ms), NC (1161 ± 182 ms) and LM (1447 ± 310 ms) identified by histology were significantly different. The T1 values of Type 1 IPH were significantly shorter than that of Type 2 IPH (456 ± 193 ms vs. 775 ± 205 ms, p < 0.001). Moderate to excellent agreement was found in identification (kappa = 0.51, p < 0.001), classification (kappa = 0.40, p = 0.028) and segmentation (ICC = 0.816, 95% CI 0.679-0.894) of IPHs between T1 mapping and histology.

CONCLUSIONS

The T1 values of carotid plaque components, particularly for intraplaque hemorrhage, are differentiable, and the stage of intraplaque hemorrhage can be classified according to T1 values, suggesting the potential capability of assessment of vulnerable plaque components by T1 mapping.