Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jun 1.
Published in final edited form as: Neuroradiology. 2020 Oct 7:10.1007/s00234-020-02575-w. doi: 10.1007/s00234-020-02575-w

Imaging Endpoints of Intracranial Atherosclerosis using Vessel Wall MR imaging: A Systematic Review

Jae W Song 1, Athanasios Pavlou 2, Morgan P Burke 2, Haochang Shou 3, Kofi-Buaku Atsina 2, Jiayu Xiao 4, Laurie A Loevner 2, David Mankoff 2, Zhaoyang Fan 4, Scott E Kasner 5
PMCID: PMC8024415  NIHMSID: NIHMS1670313  PMID: 33029735

Abstract

Purpose:

The vessel wall MR imaging (VWI) literature was systematically reviewed to assess the criteria and measurement methods of VWI-related imaging endpoints for symptomatic intracranial plaque in patients with ischemic events.

Methods:

PubMed, Scopus, Web of Science, EMBASE and Cochrane databases were searched up to October 2019. Two independent reviewers extracted data from 47 studies. A modified Guideline for Reporting Reliability and Agreement Studies was used to assess completeness of reporting.

Results:

The specific VWI-pulse sequence used to identify plaque was reported in 51% of studies. A VWI-based criterion to define plaque was reported in 38% of studies. A definition for culprit plaque was reported in 40% of studies. Frequently scored qualitative imaging endpoints were plaque quadrant (21%) and enhancement (21%). Frequently measured quantitative imaging endpoints were stenosis (19%), lumen area (15%), and remodeling index (14%). Reproducibility for all endpoints ranged from good to excellent (range: ICCT1 hyperintensity= 0.451 to ICCstenosis= 0.983). However, rater specialty and years of experience varied among studies.

Conclusions:

Investigators are using different criteria to identify and measure VWI-imaging endpoints for symptomatic intracranial plaque. Early awareness of these differences to address methods of acquisition and measurement will help focus research resources and efforts in technique optimization and measurement reproducibility. Consensual definitions to detect plaque will be important to develop automatic lesion detection tools particularly in the era of radiomics.

Keywords: vessel wall MR imaging, atherosclerosis, reproducibility, biomarker

Introduction

Intracranial atherosclerotic disease is one of the leading causes of ischemic stroke worldwide. Vessel wall MRI (VWI) is increasingly being used to study intracranial arteries as it may be a more sensitive technique to image vessel wall pathology. Despite a recent exponential increase in publications using VWI to study intracranial atherosclerosis [1], the diagnostic accuracy of specific imaging endpoints as a surrogate imaging biomarker of symptomatic intracranial plaque is not well established. One challenge is the technical variability in VWI protocols used across institutions [2], which may lead to characterization of different plaque imaging features. Lack of consensus on selection of key imaging endpoints to investigate has resulted in diverse research efforts, particularly in the area of testing reproducibility. While some reproducibility investigations evaluate enhancement characteristics [3], others report stenosis or measures of plaque burden [4]. Measurement reliability is a critical aspect of validating an imaging biomarker and efforts can be costly. Furthermore, in the era of radiomics and generating massive amounts of data with automated tools, clear and consensual definitions for data extraction are critical.

We draw insight about the need for methodological rigor from how carotid stenosis measurement investigations unfolded over the years after the North American Symptomatic Carotid Endarterectomy Trial and European Carotid Surgery Trial, which led to numerous studies and parallel efforts on stenosis measurement and reproducibility [5]. It is critical to understand wherein the variability lies in defining and measuring endpoints to raise early awareness and initiate steps towards consensus.

Assessing analytic validity includes evaluating the extent of agreement on the definition of imaging endpoints, data acquisition methods and reproducibility. In this systematic review, we examine the analytic validity of the different imaging endpoints measured for symptomatic atherosclerotic plaque using intracranial VWI.

Methods

Search Strategy

The systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Scopus, EMBASE, Web of Science and Cochrane were searched on October 31, 2019. Search strategy is shown in Supplemental Table 1. Manual review of the citations was performed. No foreign language restrictions were placed.

Study selection

Inclusion criteria were (a) intracranial atherosclerosis; (b) study of culprit/symptomatic plaque associated with an ischemic event; (c) adult humans; (d) 1.5 or 3 Tesla (T) vessel wall MR imaging; (e) clinical research studies. Exclusion criteria were (a) insufficient exclusion of other sources of ischemic stroke; (b) conference abstracts and case reports/series with insufficient methodological data; (c) animal studies; (d) histology studies.

Data extraction

Two independent reviewers (JWS, AP) extracted data with discrepancies resolved by consensus. Data were collected about study design (e.g., subject inclusion criteria, blinding, rater characteristics), MR technology (e.g., magnet strength, vessel wall MR protocols and pulse sequence parameters, and use of intravenous contrast), imaging data (e.g., artery, imaging endpoints, definitions and measurement technique), and reproducibility methods and results.

Imaging endpoints were categorized as qualitative or quantitative/semi-quantitative. Assessment for enhancement with a binary outcome was categorized as qualitative. Outcomes of enhancement grades, percent contrast enhancement, enhancement area or volume were categorized as semi-quantitative or quantitative.

Reporting was assessed using a modified version of the Guidelines for Reporting Reliability and Agreement Studies (Supplemental Table 2) [6]. Rater characteristics measuring VWI-imaging endpoints of plaque were extracted. Raters who reviewed clinical data to determine infarct location or determine likelihood of culprit plaque without measuring VWI-imaging biomarkers were excluded from this analysis. When the rater was identified by author initials only, the author’s departmental affiliation was used to infer specialty.

Statistical Analysis

Categorical variables are expressed in counts and percentages; continuous variables are expressed in means. Agreement was calculated with an unweighted Cohen’s κ. Statistical significance was set at p<0.05. SPSS v19 (IBM, Chicago, IL) was used for statistical analysis.

Results

Literature Search

Initial search yielded 883 studies among which 666 were screened by 2 independent reviewers with moderate agreement (κ=0.62, 95% CI 0.55-0.70, p<0.001). Full-text screen was performed on 136 articles, from which 47 articles published from 2010 to 2019 were qualitatively reviewed (Fig. 1).

Fig. 1: Literature Search.

Fig. 1:

Open in a new tab

From 5 databases, 883 articles were identified. After excluding duplicate articles, 666 articles were screened by predetermined inclusion/exclusion criteria leaving 97 articles for full-text review. An additional 39 articles were identified from a manual citation search of the 97 articles. A total of 136 articles underwent full-text review, from which 47 met the inclusion/exclusion criteria and are included in this systematic review.

Technique: VWI Protocols and Pulse Sequences

All included studies that met the inclusion criteria were performed at 3T field strength. Dedicated intracranial VWI protocols varied between single contrast (e.g., T1-weighting [T1w, n=13], T2-weighted [T2w, n=3], proton density-weighted [PDw, n=5]) and multi-contrast protocols (Supplemental Fig. 1). Pre- and post-contrast imaging was performed in most studies (60%), among which one study performed only post-contrast VWI imaging [7]. One protocol included 2 different planes of postcontrast acquisitions to exclude flow artifact [8]. When reported, intravenous contrast injection-to-scan intervals ranged from 1.3 minutes [41] to 5 minutes [10, 11, 16–18, 21, 29–31]. Among the studies using post-contrast imaging, 24% used three-dimensional sequences with either blood or cerebrospinal fluid (CSF) suppression techniques.

The specific VWI-sequence used to identify plaque was reported in 51% of studies (Fig. 2A). Among these, T1w was most frequently used (n=12) [9–20], followed by T2w (n=8) [4, 8, 21–26] and PDw (n=4) [27–30]. Four studies did not specify which VWI-sequence was used to identify plaque but was inferred based on the single-contrast VWI protocol (PDw, n=2 [31, 32]; T1w, n=2 [7, 33]). Fourteen studies reported a multi-contrast VWI protocol but did not report which sequence was used to identify plaque.

Fig. 2: VWI Pulse Sequence and Definition for Plaque Detection.

Fig. 2:

Open in a new tab

(A) Frequencies of studies that report which VWI pulse sequence is used to identify plaque, and which contrast weighting (e.g., T1w, T2w, or PDw), are shown.

(B) Frequencies of studies that report a VWI-plaque definition, and description type, are shown.

(C) Frequencies of studies that define a culprit plaque, and specific culprit lesion characteristics, are shown. The stenosis degree inclusion criterion is also shown as a sub-analysis.

In-plane spatial resolution is an important consideration when making quantitative measurements. Among the 27 studies that identified which VWI sequence was used to identify plaque, 37% and 48% acquired sequences with in-plane spatial resolutions of ≤0.50 mm2 (n=10) and 0.51-0.63 mm2 (n=14), respectively. The lowest in-plane spatial resolution was 0.75 mm2 [11]. Two studies reported the VWI sequence in-plane spatial resolution to range between 0.50-0.70 mm2 [12, 27].

VWI-Definition of Intracranial Plaque Detection

A VWI-definition of how plaque was identified was reported in 38% of studies (Fig. 2B). The most common definition was focal/eccentric vessel wall thickening (n=10) [11, 18, 19, 22–24, 31, 34–36], focal/eccentric wall thickening with or without stenosis (n=3) [10, 29, 30], or focal/eccentric signal intensity (n=1) [37]. Other VWI-plaque definitions included both eccentric or concentric vessel wall thickening (n=3) [13, 17, 25], wall thickening (n=1) [16], or used a threshold derivation of plaque burden (n=1) [38]. Among studies that did not report a VWI-definition of plaque, 86% used angiographically measured or velocity-based measure of stenosis as a subject inclusion criterion, thus using stenosis as a surrogate marker of plaque.

The definition of a culprit plaque, the plaque thought to be the cause of an ischemic event, was reported in 40% of the studies (Fig. 2C). The vessel supplying the hemisphere with the ischemic event was evaluated in all studies for a culprit lesion. The most common culprit lesion criterion was stenosis in the relevant artery supplying the vascular territory with ischemia (n=13) [8, 11, 16–18, 23, 29–31, 39–42]. Nine of these studies accounted for the possibility of multiple or tandem lesions and specified selecting the lesion with maximal stenosis [16–18, 29–31, 39, 40, 42]. Most of these studies (37%) used ≥50% stenosis as a subject inclusion criterion. Three studies incorporated VWI-plaque characteristics as part of the culprit plaque definition (e.g., presence of intraplaque T1/T2 signal and enhancement [37] or wall thickening of a plaque quadrant blocking a perforator ostium [35, 36]). Two of these studies specified low grade (<50%) stenosis [36] and no stenosis [35] as subject inclusion criteria and used VWI to add diagnostic information beyond the lumen.

Imaging Endpoints and Measurement Criteria of Symptomatic Plaque

Fig. 3 shows the reported qualitative and quantitative plaque imaging endpoints in the literature. The most frequently scored qualitative imaging endpoints were plaque quadrant (21%) [11–13, 15, 19–22, 28, 34–36, 43, 44] and presence/absence of plaque enhancement (21%) [9, 10, 19, 21, 29, 34, 37–39, 42, 45–48]. Plaque quadrant was most frequently scored on T1w (40%) followed by T2w (27%) sequences (Fig. 4). Intraplaque T2w signal intensity (15%) [23, 26, 27, 34, 37, 38, 41, 43–45, 48, 49] and T1 signal intensity (15%) [8, 13, 17, 18, 20, 26, 37, 38, 40, 41, 49, 50] were frequently measured. Two studies used T1w signal intensity to calculate percent contrast ratios [16, 29]. T1w signal hyperintensity was used as a surrogate marker for intraplaque hemorrhage in 5 studies; all 5 studies used a threshold of >150% increase in T1w signal intensity to describe intraplaque hemorrhage but different tissues were referenced (n=4, muscle (e.g., auricularis anterior muscles [40], medial pterygoid muscle [8], adjacent muscle such as extraocular muscle [20], and “adjacent muscle” without further specification [50]; n=1, gray matter [13]). Examples of imaging endpoints are shown in Fig. 5.

Fig. 3: Imaging Endpoints for Intracranial Atherosclerosis by VWI Pulse Sequence Type.

Fig. 3:

Open in a new tab

Frequencies of qualitative and quantitative/semi-quantitative imaging endpoints measured on dedicated VWI-sequences are shown.

Abbreviation: NR, not reported

Fig. 4: Qualitative and Quantitative/Semi-quantitative Plaque Imaging Endpoints.

Fig. 4:

Open in a new tab

Frequencies of reported qualitative and quantitative imaging endpoints for intracranial plaque are shown.

Abbreviations: PD, proton density; SI, signal intensity

Fig. 5: MR Examples of VWI Imaging Endpoints.

Fig. 5:

Open in a new tab

(A) Axial T2w VWI sequence of the left intradural vertebral artery shows eccentric T2 hyperintense signal (arrowhead) and narrowing of the lumen.

(B) Axial postcontrast T1w sequence of the basilar artery shows eccentric wall thickening and enhancement without appreciable narrowing of the lumen (arrowhead). Inset shows a sagittal plane of the basilar artery with wall thickening and enhancement (arrow).

(C) Axial-oblique precontrast T1w sequence of the proximal left M1 middle cerebral artery shows T1 hyperintense signal in the vessel walls (arrowhead). Inset shows an orthogonal plane of the same artery.

(D) Sagittal precontrast T1w sequence shows a short-axis view of the right M1 middle cerebral artery with eccentric wall thickening and plaque surface irregularity.

Stenosis was the most frequently measured quantitative imaging endpoint using a VWI sequence (19%) (Figure 3). Derivation of stenosis degree was most commonly measured as a lumen area-based percent stenosis (n=21) followed by diameter-based percent luminal stenosis (n=5; (1-(Diameterstenosis/Diameternormal segment)x100%)) [8–10, 13, 20] according to the Warfarin-Aspirin Symptomatic Intracranial Disease study criteria. Three studies used 2 sequences to confirm presence of stenosis; these studies used TOF-MRA and contrast-enhanced MRA [35]; VWI-PDw and TOF-MRA [30]; and VWI (specific sequence not specified) and TOF-MRA [51]. Stenosis was most frequently measured on T1w (37%) or PDw (27%) sequences (Fig. 4).

Other frequently measured quantitative endpoints included vessel area (13%) and lumen area (15%), which were commonly used to calculate wall area (11%) or remodeling index (14%) (Fig. 3). Only two studies reported correcting for vessel tapering when calculating the remodeling index [28, 30] and one addressed it in the limitations [52]. Enhancement was measured frequently (12%) and methods included measuring percent contrast enhancement (n=5) [8, 9, 29, 33, 40], contrast enhancement ratio (n=7) [7, 9, 10, 17, 18, 26, 40], enhancement index (n=1) [16], enhancement volume (n=3) [16, 42, 47], enhancement area (n=3) [16, 46, 47], and grades of enhancement (n=10) [11, 12, 17, 18, 20, 26, 29, 31, 33, 41].

Reproducibility Assessment

Characteristics of raters who measured VWI-imaging endpoints varied by number, years of training, and specialty. The rater specialty or departmental affiliation was reported in 77% of studies. At least one radiologist was a rater in 64% of studies and a neurologist in 23% of studies. The specialty or author initials were not identified in 23% of studies. Most studies (81%) reported at least 2 raters who measured imaging endpoints. Among these studies, 34% reported the raters conducted the measurements independently [8, 9, 17, 19, 21, 27–30, 40, 41, 48, 53]. The raters were blinded to clinical information in 40% of studies, to conventional imaging in 2% of studies, and to both clinical information and other imaging data in 30% of studies.

Both inter-rater and intra-rater reproducibility were calculated in 21% of studies [17, 22, 23, 25, 28, 39, 42, 43, 46, 48]. Only intra-rater reproducibility was reported in 2 studies [4, 47]. Only inter-rater reproducibility was reported in 10 studies [8, 9, 12, 19, 29, 30, 35, 40, 41, 53]. Percent agreement was reported in 2 studies for plaque identification [23] and intraplaque hemorrhage detection [8]. Measures of statistical uncertainty for reproducibility were reported in 54% of studies. Among studies with at least 2 raters for measuring VWI imaging endpoints, discrepancies were most frequently resolved by consensus (65%) followed by a third arbitrator (25%).

Supplemental Table 3 shows a summary of the reported inter-rater reliability for VWI-plaque imaging endpoints. Reported measures showed moderate to strong reliability for qualitative (range: ICCT1 hyperintensity=0.451 to ICCplaque quadrant=0.953) [9, 43] and quantitative (range: ICCwall area index=0.579 to ICCstenosis=0.983) [46] imaging endpoints. When assessed by rater specialty (with or without a radiologist) and years of experience (e.g., ≥5 years versus less than 5 years), inter-rater reliability measures were mostly higher when the rater included a radiologist or a rater with ≥ 5 years of experience (Supplemental Table 4). The average number of years of experience of non-radiology raters was not reported, limiting insight about the need for training.

A modified version of the Guideline for Reporting Reliability and Agreement Studies was used to assess completeness of reporting (Supplemental Fig. 2–3) [6].

Discussion

Current efforts toward precision medicine and radiomics have resulted in data-driven methods and the development of automated segmentation tools for intracranial atherosclerosis [14, 40]. The crux of developing such tools relies on clear definitions and measurement methods with strong reproducibility. The intracranial VWI literature for atherosclerosis shows a need for agreement on the selection of imaging endpoints and methods of acquiring and measuring endpoints. The results show most studies do not clearly define how a plaque is identified on a VWI sequence or, if a multicontrast VWI protocol is used, which sequence is used. Definitions of culprit plaque were also lacking in 60% of studies. Taking advantage of VWI’s ability to image the vessel wall itself, identifying plaque quadrant to identify blockage of a perforator ostium, and plaque components such as plaque enhancement and T1/T2 signal intensities were most commonly reported. Surprisingly, stenosis degree was a common measure alongside quantitative measures of plaque burden. Reported reproducibility measures across studies ranged from good to excellent. However, rater characteristics were variable and methods incompletely reported giving rise to possible sources of bias.

No consensual definition for VWI-defined plaque emerged. Although focal/eccentric wall thickening on VWI was the most common definition, studies using this strict criterion may underestimate plaque prevalence. Histology shows intracranial plaques are associated with both eccentric and concentric wall thickening. For example, one histology study reported that while 69% of middle cerebral artery plaques were eccentric, 75% of vertebral artery and 62% of basilar artery plaques were concentric [54]. Eccentricity alone may not be a specific marker of intracranial plaque. Additionally, technical pitfalls such as incomplete blood or CSF suppression may lead to artifactual wall thickening and overestimate quantitative measures. Ways to mitigate this artifact include modifying sequences to optimize flow suppression, confirming wall thickening in multiple planes or using additional VWI-imaging features to increase diagnostic confidence.

Stenosis degree was a common quantitative imaging endpoint. Concordance studies comparing VWI and angiographic techniques suggest measures from VWI strongly correlate with digital subtraction angiography [55] and are superior to computed tomography angiography [56] and TOF-MRA [57]. Yet, measurement techniques to measure stenosis varied among studies with some investigators using diameter, area, or visual criteria. Given degree of stenosis can be an important guide to treatment decisions, agreement on measurement technique should be an early consideration and established for future studies.

Other quantitative measures such as lumen area and vessel area were primarily measured to calculate wall area, plaque burden, and remodeling index. Reproducibility estimates for these quantitative features ranged from good to excellent. However, it is important to recognize that technique may limit accuracy of these measurements. Mean vessel wall thickness of ex vivo imaged circle of Willis specimens on 7T VWI reportedly range from 0.45 to 0.66 mm [58]. Given the in-plane resolution of VWI-sequences for some studies exceeded these wall thickness measures, investigators should be wary of partial volume effects when reporting precise quantitative measures.

Many methods to measure plaque enhancement were identified. Both the degree and persistence of plaque enhancement are hypothesized to be promising imaging biomarkers of culprit plaque [31] and recurrent ischemic stroke [45]. Enhancement is also promising as a biomarker as it may be less susceptible to technical aspects such as spatial resolution. In fact partial volume effects could be considered advantageous to detect enhancement of small distal arteries [59]. Our results show while it is a common imaging endpoint, measurement methods and techniques vary widely. Several studies have addressed how imaging technique and measurement methods may impact enhancement and report enhancement degree is influenced by contrast injection-to-scan time intervals [60] and quantitative methods are more objective than qualitative methods [9]. Indeed, reported reproducibility measures for quantitative/semi-quantitative methods for enhancement (ICC=0.64 to 0.92) were higher than qualitative methods (κ=0.75 to 0.83) but also ranged wider. Moreover, the contrast-to-scan interval durations ranged from 1.3 to 5 minutes among the included studies in this systematic review.

In addition to the inherent black-blood effect in turbo spin-echo or variable flip angle-turbo spin-echo acquisitions, there are different types of blood suppression techniques being adopted to further improve the performance. Global blood suppression approaches such as delay alternating with nutation for tailored excitation and motion-sensitizing preparation module are more suitable for 3D VWI, although the vessel wall signal and desired vessel wall contrast weighting (e.g. T1 weighting) may be slightly reduced. Inflow presaturation by slab-selective radiofrequency pulses is a relatively localized blood suppression approach, which potentially results in flow-related enhancement in segments with recirculating or stagnant blood flow. Future studies should be aware of these technical considerations when designing protocols and measurement methods that include evaluating enhancement.

Imaging biomarkers are likely to have clinical utility only if they have strong reproducibility. Yet, reproducibility studies are often a sub-study of diagnostic accuracy studies in which reproducibility is reported as a measure of quality control. Presently, few dedicated VWI investigations on reproducibility have been published and while some align with the identified common imaging endpoints, others focus on less commonly used metrics [3, 4, 61–64]. Additionally, the investigations use different pulse sequences and techniques. A key factor in clinically translating new technologies is the likelihood that the technique is available at different sites. Equally important is the likelihood that the interpretive expertise exists at each clinical site. Imaging biomarkers with putative use in general populations require evidence of reproducibility across expert and non-expert centers before they are considered clinically valid. This critical aspect generated numerous studies investigating generalizability [65] and precision for NASCET and ECST techniques [66, 67] for measuring carotid stenosis. From the surveyed VWI literature, data for rater characteristics measuring plaque features were limited and insufficient to draw convincing conclusions. For example, while some raters were identified as neuroradiologists in the text, others reported the rater’s initials and were categorized by the author’s departmental affiliation. We acknowledge that affiliation may not equate to practicing a medical specialty. Future studies to comprehensively evaluate years of experience and specialty are warranted to better understand what type learning curve or experience is needed to address generalizability.

There are several limitations to this study. First, some studies may have been missed from the literature search despite efforts to be comprehensive by searching 5 databases, including foreign language articles and performing a manual citation search. Second, the included studies are drawn from the past decade, a period during which the technology continuously evolved [2]. Thus variability in defining the endpoints may also reflect a learning curve in image acquisition and interpretation. Third, reliability measures were not quantitatively pooled in this review. Reliability is subject to many caveats and is a factor of the subjects, rater characteristics, the setting, as well as sample size. Hence, some authors have suggested statistically pooling reliability measures is not recommended [68]. Finally, this review summarizes the most commonly used techniques and methods rather than provide data on recommendations for specific techniques or measurement methods. Methodological studies to compare measurement methods of the common imaging endpoints and assess diagnostic accuracy are a future direction. There is presently an unmet need in the field to establish the analytic validity of VWI-imaging biomarkers for ICAD. It may be of value in the future to form an international expert panel to establish a consensus for methodological recommendations.

Summary

The variability in the definitions of imaging endpoints for plaque and the methods of acquisition and measurement may be sources of bias. Early awareness and efforts to address standardization is important in the process of validating an imaging biomarker and is critical for allocating resources. As the field evolves to amass radiomics data by the development of automated tools, agreement on the criteria to detect plaque and culprit plaque by VWI will be a critical step.

Supplementary Material

Supplemental Material

Footnotes

Conflict of interest statement

We declare that we have no conflict of interest.

References

  • 1.Song JW, Guiry SC, Shou H, et al. (2019) Qualitative Assessment and Reporting Quality of Intracranial Vessel Wall MR Imaging Studies: A Systematic Review. AJNR Am J Neuroradiol 40:2025–2032. doi: 10.3174/ajnr.A6317 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Song JW, Moon BF, Burke MP, et al. (2020) MR Intracranial Vessel Wall Imaging: A Systematic Review. J Neuroimaging 30:428–442. doi: 10.1111/jon.12719 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Mossa-Basha M, Watase H, Sun J, et al. (2019) Inter-rater and scan-rescan reproducibility of the detection of intracranial atherosclerosis on contrast-enhanced 3D vessel wall MRI. Br J Radiol 92:20180973. doi: 10.1259/bjr.20180973 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Zhang X, Zhu C, Peng W, et al. (2015) Scan-rescan reproducibility of high resolution magnetic resonance imaging of atherosclerotic plaque in the middle cerebral artery. PLoS ONE 10:e0134913. doi: 10.1371/journal.pone.0134913 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Rothwell PM, Pendlebury ST, Wardlaw J, et al. (2000) Critical appraisal of the design and reporting of studies of imaging and measurement of carotid stenosis. Stroke 31:1444–1450. doi: 10.1161/01.str.31.6.1444 [DOI] [PubMed] [Google Scholar]
  • 6.Kottner J, Audige L, Brorson S, et al. (2011) Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. J Clin Epidemiol 64:96–106. doi: 10.1016/j.jclinepi.2010.03.002 [DOI] [PubMed] [Google Scholar]
  • 7.Ryu CW, Jahng GH, Shin HS (2014) Gadolinium enhancement of atherosclerotic plaque in the middle cerebral artery: relation to symptoms and degree of stenosis. AJNR Am J Neuroradiol 35:2306–2310. doi: 10.3174/ajnr.A4038 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Zhu C, Tian X, Degnan AJ, et al. (2018) Clinical Significance of Intraplaque Hemorrhage in Low- and High-Grade Basilar Artery Stenosis on High-Resolution MRI. AJNR Am J Neuroradiol 39:1286–1292. doi: 10.3174/ajnr.A5676 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Alexander MD, de Havenon A, Kim SE, et al. (2019) Assessment of quantitative methods for enhancement measurement on vessel wall magnetic resonance imaging evaluation of intracranial atherosclerosis. Neuroradiology 61:643–650. doi: 10.1007/s00234-019-02167-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Huang J, Jiao S, Zhao X, et al. (2019) Characteristics of patients with enhancing intracranial atherosclerosis and association between plaque enhancement and recent cerebrovascular ischemic events: a high-resolution magnetic resonance imaging study. Acta Radiol 60:1301–1307. doi: 10.1177/0284185118822645 [DOI] [PubMed] [Google Scholar]
  • 11.Lu SS, Ge S, Su CQ, et al. (2018) Plaque Distribution and Characteristics in Low-Grade Middle Cerebral Artery Stenosis and Its Clinical Relevance: A 3-Dimensional High-Resolution Magnetic Resonance Imaging Study. J Stroke Cerebrovasc Dis 27:2243–2249. doi: S1052-3057(18)30186-1 [DOI] [PubMed] [Google Scholar]
  • 12.Shan Y, Wang P, Yang J, Liu H, Du J (2018) Evaluation of symptomatic middle cerebral arterial atherosclerotic plaque by three dimensional-sampling perfection with application optimized contrasts using different flip angle evolutions of high-resolution magnetic resonance imaging. Chinese Journal of Neurology 51:28–33. [Google Scholar]
  • 13.Shen M, Gao P, Zhang Q, et al. (2018) Middle Cerebral Artery Atherosclerosis and Deep Subcortical Infarction: A 3T Magnetic Resonance Vessel Wall Imaging Study. J Stroke Cerebrovasc Dis 27:3387–3392. doi: 10.1016/j.jstrokecerebrovasdis.2018.08.013 [DOI] [PubMed] [Google Scholar]
  • 14.Shi F, Yang Q, Guo X, et al. (2019) Vessel Wall Segmentation Using Convolutional Neural Networks. IEEE Trans Biomed Eng 66:2840–2847. doi: 10.1109/TBME.2019.2896972 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Sun L, Li Z, Tang W, et al. (2018) High resolution magnetic resonance imaging in pathogenesis diagnosis of single lenticulostriate infarction with nonstenotic middle cerebral artery, a retrospective study. BMC Neurology 18:51. doi: 10.1186/s12883-018-1054-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Wang M, Wu F, Yang Y, et al. (2018) Quantitative assessment of symptomatic intracranial atherosclerosis and lenticulostriate arteries in recent stroke patients using whole-brain high-resolution cardiovascular magnetic resonance imaging. J Cardiovasc Magn Reson 20:35–8. doi: 10.1186/s12968-018-0465-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Wu F, Ma Q, Song H, et al. (2018) Differential Features of Culprit Intracranial Atherosclerotic Lesions: A Whole-Brain Vessel Wall Imaging Study in Patients With Acute Ischemic Stroke. J Am Heart Assoc 7: 10.1161/JAHA.118.009705.e009705 e009705. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Wu F, Song H, Ma Q, et al. (2018) Hyperintense Plaque on Intracranial Vessel Wall Magnetic Resonance Imaging as a Predictor of Artery-to-Artery Embolic Infarction. Stroke 49:905–911. doi: 10.1161/STROKEAHA.117.020046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Zou X, Chung Y, Zhang L, et al. (2015) Middle Cerebral Artery Atherosclerotic Plaques in Recent Small Subcortical Infarction: A Three-Dimensional High-resolution MR Study. BioMed Research International 2015:540217. doi: 10.1155/2015/540217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Wang W, Yang Q, Li D, et al. (2017) Incremental Value of Plaque Enhancement in Patients with Moderate or Severe Basilar Artery Stenosis: 3.0 T High-Resolution Magnetic Resonance Study. Biomed Res Int 2017:4281629. doi: 10.1155/2017/4281629 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Xu X, Wei Y, Zhang X, et al. (2016) Value of higher-resolution MRI in assessing middle cerebral atherosclerosis and predicting capsular warning syndrome. J Magn Reson Imaging 44:1277–1283. doi: 10.1002/jmri.25265 [DOI] [PubMed] [Google Scholar]
  • 22.Yu YN, Li ML, Xu YY, et al. (2018) Middle cerebral artery geometric features are associated with plaque distribution and stroke. Neurology 91:e1760–e1769. doi: 10.1212/WNL.0000000000006468 [DOI] [PubMed] [Google Scholar]
  • 23.Yu YN, Liu MW, Villablanca JP, et al. (2019) Middle Cerebral Artery Plaque Hyperintensity on T2-Weighted Vessel Wall Imaging Is Associated with Ischemic Stroke. AJNR Am J Neuroradiol 40:1886–1892. doi: 10.3174/ajnr.A6260 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Xu W-, Li M-, Gao S, et al. (2010) In vivo high-resolution MR imaging of symptomatic and asymptomatic middle cerebral artery atherosclerotic stenosis. Atherosclerosis 212:507–511. doi: 10.1016/j.atherosclerosis.2010.06.035 [DOI] [PubMed] [Google Scholar]
  • 25.Meng Y, Li M, Yu Y, et al. (2019) Quantitative score of the vessel morphology in middle cerebral artery atherosclerosis. J Neurol Sci 399:111–117. doi: S0022-510X(19)30086-3 [DOI] [PubMed] [Google Scholar]
  • 26.Peng W, Zhan Q, Jiang Y, et al. (2016) Comparison between culprit plaques and non-culprit plaques in atherosclerotic disease of the middle cerebral artery by high-resolution MRI. Chin J Med Imaging Technol 32:353–357. [Google Scholar]
  • 27.Zhao D, Teng G, Chen X, et al. (2014) Arterial remodeling in middle cerebral artery atherosclerotic stenosis: a high-resolution MRI study. Zhonghua Yi Xue Za Zhi 94:2893–2896. [PubMed] [Google Scholar]
  • 28.Zhu XJ, Du B, Lou X, et al. (2013) Morphologic characteristics of atherosclerotic middle cerebral arteries on 3T high-resolution MRI. AJNR Am J Neuroradiol 34:1717–1722. doi: 10.3174/ajnr.A3573 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Qiao Y, Zeiler SR, Mirbagheri S, et al. (2014) Intracranial plaque enhancement in patients with cerebrovascular events on high-spatial-resolution MR images. Radiology 271:534–542. doi: 10.1148/radiol.13122812 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Qiao Y, Anwar Z, Intrapiromkul J, et al. (2016) Patterns and Implications of Intracranial Arterial Remodeling in Stroke Patients. Stroke 47:434–440. doi: 10.1161/STROKEAHA.115.009955 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Kwee RM, Qiao Y, Liu L, et al. (2019) Temporal course and implications of intracranial atherosclerotic plaque enhancement on high-resolution vessel wall MRI. Neuroradiology 61:651–657. doi: 10.1007/s00234-019-02190-4 [DOI] [PubMed] [Google Scholar]
  • 32.Shi MC, Wang SC, Zhou HW, et al. (2012) Compensatory remodeling in symptomatic middle cerebral artery atherosclerotic stenosis: A high-resolution MRI and microemboli monitoring study. Neurol Res 34:153–158. doi: 10.1179/1743132811Y.0000000065 [DOI] [PubMed] [Google Scholar]
  • 33.Liang J, Guo J, Liu D, et al. (2019) Application of High-Resolution CUBE Sequence in Exploring Stroke Mechanisms of Atherosclerotic Stenosis of Middle Cerebral Artery. J Stroke Cerebrovasc Dis 28:156–162. doi: S1052-3057(18)30524-X [DOI] [PubMed] [Google Scholar]
  • 34.Bae YJ, Choi BS, Jung C, et al. (2017) Differentiation of deep subcortical infarction using high-resolution vessel wall MR imaging of middle cerebral artery. Korean J Radiol 18:964–972. doi: 10.3348/kjr.2017.18.6.964 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Cho HJ, Kim KH, Kim EJ, et al. (2018) Clinical Implications of Basilar Artery Plaques in the Pontine Infarction with Normal Basilar Angiogram: A High-Resolution Magnetic Resonance Imaging Study. J Stroke Cerebrovasc Dis 27:3591–3598. doi: S1052-3057(18)30486-5 [DOI] [PubMed] [Google Scholar]
  • 36.Yu J, Li M-, Xu Y-, et al. (2017) Plaque distribution of low-grade basilar artery atherosclerosis and its clinical relevance. BMC Neurology 17:8. doi: 10.1186/s12883-016-0785-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Kim J-, Jung K-, Sohn C-, et al. (2012) Middle cerebral artery plaque and prediction of the infarction pattern. Arch Neurol 69:1470–1475. doi: 10.1001/archneurol.2012.1018 [DOI] [PubMed] [Google Scholar]
  • 38.Teng Z, Peng W, Zhan Q, et al. (2016) An assessment on the incremental value of high-resolution magnetic resonance imaging to identify culprit plaques in atherosclerotic disease of the middle cerebral artery. Eur Radiol 26:2206–2214. doi: 10.1007/s00330-015-4008-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Choi EH, Lee H, Chung JW, et al. (2019) Ring Finger Protein 213 Variant and Plaque Characteristics, Vascular Remodeling, and Hemodynamics in Patients with Intracranial Atherosclerotic Stroke: A High-Resolution Magnetic Resonance Imaging and Hemodynamic Study. J Am Heart Assoc 8:e011996. doi: 10.1161/JAHA.119.011996 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Shi Z, Zhu C, Degnan AJ, et al. (2018) Identification of high-risk plaque features in intracranial atherosclerosis: initial experience using a radiomic approach. Eur Radiol 28:3912–3921. doi: 10.1007/s00330-018-5395-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Lu SS, Ge S, Su CQ, et al. (2018) MRI of plaque characteristics and relationship with downstream perfusion and cerebral infarction in patients with symptomatic middle cerebral artery stenosis. J Magn Reson Imaging 48:66–73. doi: 10.1002/jmri.25879 [DOI] [PubMed] [Google Scholar]
  • 42.Chung JW, Hwang J, Lee MJ, et al. (2016) Previous Statin Use and High-Resolution Magnetic Resonance Imaging Characteristics of Intracranial Atherosclerotic Plaque: The Intensive Statin Treatment in Acute Ischemic Stroke Patients With Intracranial Atherosclerosis Study. Stroke 47:1789–1796. doi: 10.1161/STROKEAHA.116.013495 [DOI] [PubMed] [Google Scholar]
  • 43.Zhao DL, Deng G, Xie B, et al. (2015) High-resolution MRI of the vessel wall in patients with symptomatic atherosclerotic stenosis of the middle cerebral artery. J Clin Neurosci 22:700–704. doi: 10.1016/j.jocn.2014.10.018 [DOI] [PubMed] [Google Scholar]
  • 44.Zhao DL, Deng G, Xie B, et al. (2016) Wall characteristics and mechanisms of ischaemic stroke in patients with atherosclerotic middle cerebral artery stenosis: a high-resolution MRI study. Neurol Res 38:606–613. doi: 10.1179/1743132815Y.0000000088 [DOI] [PubMed] [Google Scholar]
  • 45.Kim JM, Jung KH, Sohn CH, et al. (2016) Intracranial plaque enhancement from high resolution vessel wall magnetic resonance imaging predicts stroke recurrence. Int J Stroke 11:171–179. doi: 10.1177/1747493015609775 [DOI] [PubMed] [Google Scholar]
  • 46.Ryoo S, Lee MJ, Cha J, et al. (2015) Differential Vascular Pathophysiologic Types of Intracranial Atherosclerotic Stroke: A High-Resolution Wall Magnetic Resonance Imaging Study. Stroke 46:2815–2821. doi: 10.1161/STROKEAHA.115.010894 [doi] [DOI] [PubMed] [Google Scholar]
  • 47.Bang OY, Chung JW, Cha J, et al. (2016) A Polymorphism in RNF213 Is a Susceptibility Gene for Intracranial Atherosclerosis. PLoS One 11:e0156607. doi: 10.1371/journal.pone.0156607 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Kim YJ, Lee DH, Kwon JY, et al. (2013) High resolution MRI difference between moyamoya disease and intracranial atherosclerosis. Eur J Neurol 20:1311–1318. doi: 10.1111/ene.12202 [DOI] [PubMed] [Google Scholar]
  • 49.Chung GH, Kwak HS, Hwang SB, et al. (2012) High resolution MR imaging in patients with symptomatic middle cerebral artery stenosis. Eur J Radiol 81:4069–4074. doi: 10.1016/j.ejrad.2012.07.001 [DOI] [PubMed] [Google Scholar]
  • 50.Xu WH, Li ML, Gao S, et al. (2012) Middle cerebral artery intraplaque hemorrhage: prevalence and clinical relevance. Ann Neurol 71:195–198. doi: 10.1002/ana.22626 [DOI] [PubMed] [Google Scholar]
  • 51.Feng C, Xu Y, Bai X, et al. (2013) Basilar artery atherosclerosis and hypertensive small vessel disease in isolated pontine infarctions: a study based on high-resolution MRI. Eur Neurol 70:16–21. doi: 10.1159/000346577 [DOI] [PubMed] [Google Scholar]
  • 52.Zhang DF, Chen YC, Chen H, et al. (2017) A High-Resolution MRI Study of Relationship between Remodeling Patterns and Ischemic Stroke in Patients with Atherosclerotic Middle Cerebral Artery Stenosis. Front Aging Neurosci 9:140. doi: 10.3389/fnagi.2017.00140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Kim JM, Jung KH, Sohn CH, et al. (2016) Intracranial plaque enhancement from high resolution vessel wall magnetic resonance imaging predicts stroke recurrence. Int J Stroke 11:171–179. doi: 10.1177/1747493015609775 [DOI] [PubMed] [Google Scholar]
  • 54.Yang WJ, Fisher M, Zheng L, et al. (2017) Histological Characteristics of Intracranial Atherosclerosis in a Chinese Population: A Postmortem Study. Front Neurol 8:488. doi: 10.3389/fneur.2017.00488 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Lee NJ, Chung MS, Jung SC, et al. (2016) Comparison of High-Resolution MR Imaging and Digital Subtraction Angiography for the Characterization and Diagnosis of Intracranial Artery Disease. AJNR Am J Neuroradiol 37:2245–2250. doi: ajnr.A4950 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Liu Q, Huang J, Degnan AJ, et al. (2013) Comparison of high-resolution MRI with CT angiography and digital subtraction angiography for the evaluation of middle cerebral artery atherosclerotic steno-occlusive disease. Int J Cardiovasc Imaging 29:1491–1498. doi: 10.1007/s10554-013-0237-3 [DOI] [PubMed] [Google Scholar]
  • 57.Bai X, Lv P, Liu K, et al. (2018) 3D Black-Blood Luminal Angiography Derived from High-Resolution MR Vessel Wall Imaging in Detecting MCA Stenosis: A Preliminary Study. AJNR Am J Neuroradiol 39:1827–1832. doi: 10.3174/ajnr.A5770 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Harteveld AA, Denswil NP, van Hecke W, et al. (2018) Ex vivo vessel wall thickness measurements of the human circle of Willis using 7T MRI. Atherosclerosis 273:106–114. doi: 10.1016/j.atherosclerosis.2018.04.023 [DOI] [PubMed] [Google Scholar]
  • 59.Song JW, Shou H, Obusez EC, et al. (2019) Spatial Distribution of Intracranial Vessel Wall Enhancement in Hypertension and Primary Angiitis of the CNS. Sci Rep 9:19270–5. doi: 10.1038/s41598-019-55634-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.de Havenon A, Muhina HJ, Parker DL, et al. (2019) Effect of Time Elapsed since Gadolinium Administration on Atherosclerotic Plaque Enhancement in Clinical Vessel Wall MR Imaging Studies. AJNR Am J Neuroradiol 40:1709–1711. doi: 10.3174/ajnr.A6191 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Yang W, Huang B, Liu X, et al. (2014) Reproducibility of high-resolution MRI for the middle cerebral artery plaque at 3T. Eur J Radiol 83:49. doi: 10.1016/j.ejrad.2013.10.003 [DOI] [PubMed] [Google Scholar]
  • 62.Qiao Y, Guallar E, Suri FK, et al. (2016) MR Imaging Measures of Intracranial Atherosclerosis in a Population-based Study. Radiology 280:860–868. doi: 10.1148/radiol.2016151124 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Ma N, Lou X, Zhao T, et al. (2011) Intraobserver and interobserver variability for measuring the wall area of the basilar artery at the level of the trigeminal ganglion on high-resolution MR images. AJNR Am J Neuroradiol 32:E29–E32. doi: 10.3174/ajnr.A2049 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Zhang N, Zhang F, Deng Z, et al. (2018) 3D whole-brain vessel wall cardiovascular magnetic resonance imaging: a study on the reliability in the quantification of intracranial vessel dimensions. J Cardiovasc Magn Reson 20:39-z. doi: 10.1186/s12968-018-0453-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Gagne PJ, Matchett J, MacFarland D, et al. (1996) Can the NASCET technique for measuring carotid stenosis be reliably applied outside the trial? J Vasc Surg 24:449–6. doi: S0741-5214(96)70201-X [DOI] [PubMed] [Google Scholar]
  • 66.Saba L, Mallarini G (2010) A comparison between NASCET and ECST methods in the study of carotids: evaluation using Multi-Detector-Row CT angiography. Eur J Radiol 76:42–47. doi: 10.1016/j.ejrad.2009.04.064 [DOI] [PubMed] [Google Scholar]
  • 67.Vanninen R, Manninen H, Koivisto K, et al. (1994) Carotid stenosis by digital subtraction angiography: reproducibility of the European Carotid Surgery Trial and the North American Symptomatic Carotid Endarterectomy Trial measurement methods and visual interpretation. AJNR Am J Neuroradiol 15:1635–1641. [PMC free article] [PubMed] [Google Scholar]
  • 68.Duffy L, Gajree S, Langhorne P, et al. (2013) Reliability (inter-rater agreement) of the Barthel Index for assessment of stroke survivors: systematic review and meta-analysis. Stroke 44:462–468. doi: 10.1161/STROKEAHA.112.678615 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material
NIHMS1670313-supplement-Supplemental_Material.pdf (739.8KB, pdf)

RESOURCES