Atherosclerotic plaque distribution and characteristics in young patients with stroke/transient ischemic attack: insights from MR vessel wall imaging and comparison with older counterparts

Introduction

High-resolution vessel wall imaging (HRVWI), a well-established three-dimensional (3D) high-resolution black-blood magnetic resonance imaging (MRI) sequence, enables detailed visualization of atherosclerotic plaque morphology. It has been widely adopted in clinical practice for the diagnosis and treatment of cerebrovascular diseases (1-4). Several studies (5-7) have used HRVWI to characterize the distribution and features of intracranial atherosclerotic plaques in both stroke patients and community populations. Prior research has indicated that larger culprit plaques and more intracranial plaques are independently associated with an increased risk of recurrent stroke (8). Moreover, traditional cardiovascular risk factors—particularly advancing age—have been linked to a higher prevalence of intracranial plaque formation (5). Specific regions within the anterior circulation, including the distal intracranial internal carotid artery (ICA), terminal ICA (ICA-T), and the M1 segment of the middle cerebral artery (MCA), have been identified as common predilection sites for plaque development (6,7). These regions are frequently implicated as locations of culprit plaques associated with ischemic stroke (8,9).

However, most existing studies on large artery atherosclerotic stroke (5-7) have primarily focused on middle-aged and older patients (MOP), who account for the majority of cases. In contrast, limited studies have investigated plaque distribution and imaging characteristics in younger patients with stroke or transient ischemic attack (TIA). Emerging evidence suggests that the global incidence of ischemic stroke in young adults is increasing (10), with notable regional and ethnic variations. In particular, large-vessel atherosclerosis has emerged as the leading cause of stroke in young patients in East Asia (11-13). Early identification and characterization of atherosclerotic changes in this population may provide opportunities for intervention and disease prevention. Accordingly, a better understanding of the age-related patterns of intracranial atherosclerosis in patients with stroke is essential for optimizing diagnostic and therapeutic strategies across age groups.

The aim of this study was to characterize the distribution of intracranial atherosclerotic plaques and the imaging features of culprit plaques in young patients with stroke or TIA, and to compare these findings with those observed in MOP group. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2145/rc).

Methods

Patients

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (reference No. 2021-SRFA-111), and the informed consent was waived due to the retrospective design. We reviewed data from young patients (aged 18–45 years) with large-vessel atherosclerotic stroke or TIA who underwent HRVWI at The First Affiliated Hospital of Nanjing Medical University between February 2017 and January 2022, as part of a previously published study (14). The inclusion criteria were as follows: (I) age between 18 and 45 years; (II) presence of culprit plaques on HRVWI; (III) HRVWI performed within 8 weeks of symptom onset; (IV) availability of clinical and laboratory data from medical records; and (V) adequate image quality for analysis. The exclusion criteria included: (I) evidence of cardioembolism or other determined etiologies such as moyamoya disease, arterial dissection, or stroke of undetermined cause; (II) negative HRVWI findings, insufficient clinical data for evaluation, or multiple (>2 potential stroke etiologies; and (III) poor image quality due to significant motion artifacts.

To complement this study, we retrospectively reviewed consecutive MOP with large-vessel atherosclerotic stroke or TIA who underwent HRVWI at our hospital between July 2021 and January 2022, prior to the initiation of treatment. The inclusion and exclusion criteria were identical to those applied to the younger cohort, with two exceptions: (I) age >45 years; and (II) HRVWI performed within 4 weeks of symptom onset.

To better characterize plaque evolution patterns, we stratified young patients into two subgroups (18–35 and 36–45 years), given the marked increase in the prevalence of traditional vascular risk factors after the age of 35 years (15-17).

Clinical data collected included age, sex, history of hypertension, diabetes mellitus, coronary heart disease (CHD), smoking and alcohol use status, and blood lipid levels. Hypertension was defined as a blood pressure level higher than 140/90 mmHg, or current use of antihypertensive medication. Diabetes was defined as a fasting glucose level >7.0 mmol/L and/or a postprandial glucose level >11.1 mmol/L. Smoking and alcohol use were categorized as current or non-current; individuals who had abstained for more than six months were classified as non-current users. Blood lipid testing was performed within one week before or after the HRVWI examination.

MR imaging acquisition

Imaging was conducted on a 3.0 T MR scanner (Skyra; Siemens Healthineers, Erlangen, Germany) with a 20-channel head/neck coil. The acquisition sequences and parameters were identical to those used in our previous study (13) and included the following sequences: (I) 3D time-of-flight magnetic resonance angiography; (II) two-dimensional (2D) black-blood T2-weighted imaging; (III) 3D T1-weighted sampling perfection with application-optimized contrast using different angle evolutions (SPACE) sequence, performed pre- and post-contrast (encompassing the carotid bifurcation and the entire intracranial arterial tree); and (IV) axial diffusion-weighted imaging.

The 3D T1-weighted SPACE sequence was acquired with the following parameters: TR/TE, 700/10 ms; FOV, 230×196 mm²; turbo-spin factor, 52 echoes; acquired resolution, 0.6×0.6×0.6 mm³, reconstructed resolution, 0.3×0.3×0.6 mm³. Contrast-enhanced 3D SPACE imaging was initiated approximately 5 minutes after intravenous injection of 0.1 mmol/kg gadodiamide (GE Healthcare, Dublin, Ireland) at a rate of 4 mL/s. Detailed parameters for other protocols, including 3D time-of-flight magnetic resonance angiography, 2D black-blood T2WI, and diffusion-weighted imaging are provided in Appendix 1.

Imaging analysis

Two experienced neuroradiologists—one with 11 years and the other with 13 years of experience—independently reviewed the HRVWI images using a Vue PACS workstation (Carestream). The 3D volumetric SPACE data were reformatted into multiple 2D planes as needed for analysis. Discrepancies between readers were resolved by consensus.

Assessment for affected vessel segment

Twenty-three arterial segments from the head and neck were evaluated, including the bilateral common carotid artery (CCA) bifurcations, extracranial (EICA) and intracranial carotid arteries (IICA), ICA-Ts, A1 and A2 segments of the anterior cerebral artery (ACA), M1 and M2 segments of MCA, P1 and P2 segments of the posterior cerebral artery (PCA), basilar artery (BA), and V4 segments of the vertebral artery. Atherosclerotic plaques were defined as focal wall thickening relative to adjacent or contralateral segments, with or without luminal stenosis (8). A segment was classified as “affected” if a plaque was present. Segments outside the scanning range, hypoplastic, or not visible were excluded from analysis.

For each patient, the affected vessel segment ratio (AVSR) was calculated by dividing the number of affected segments by the total number of evaluable segments.

Culprit plaque characterization

Culprit plaques were identified based on both clinical data and HRVWI findings, defined as the only lesion in the symptomatic territory, or the most stenotic lesion when multiple plaques coexisted within the same vascular territory (18).

Plaque characteristics were analyzed using dedicated vessel wall analysis software (uOmnispace, MR Plaque Analysis, United Imaging Healthcare Co., Ltd., Shanghai, China). Quantitative parameters—including degree of stenosis, plaque area, plaque burden, remodeling index, eccentric index, plaque volume, and plaque length—were automatically obtained based on manual outlining of the plaque. Additional features, including intraplaque hemorrhage, enhancement ratio, and circular involvement, were also assessed manually. Plaque and wall characteristics were defined and quantified as follows:

• Lumen area (LA) is defined as the cross-sectional area enclosed by the luminal border (the blood-intima interface).
• Vessel area (VA) was defined as the cross-sectional area enclosed by the outer border of the vessel wall.
• Plaque area: measured at the maximal stenosis site, calculated as VA-LA.
• Stenosis ratio: calculated as [1 − LA at the most narrowed lumen (MNL) / reference LA] ×100%. Reference site was the nearest proximal plaque-free segment, or the distal site if proximal reference was unavailable.
• Plaque burden: measured on the maximal stenosis site, calculated as (1 − LA / VA) ×100%, which is also termed the normalized wall index in some studies (19,20).
• Remodeling index: VA at MNL divided by VA at the reference site.
• Eccentricity index (EI): (maximum plaque thickness − minimum plaque thickness) / maximum plaque thickness.
• Intraplaque hemorrhage: defined as plaque signal intensity on unenhanced SPACE >150% that of adjacent normal reference wall.
• Enhancement ratio: calculated as the ratio of plaque signal intensity to that of the pituitary stalk (2). The final value was obtained by averaging two measurements.
• Circular involvement: defined as plaque involvement of all four arterial wall quadrants—superior, inferior wall, ventral, and dorsal (21).

Statistical analysis

Continuous variables were presented as mean ± standard deviation or median with interquartile range (IQR), and categorical variables as frequencies and percentages. Inter-reader agreement for plaque assessment was evaluated using intraclass correlation coefficient (ICC) for continuous variables and Cohen’s kappa for categorical variables. An ICC or kappa values <0.4 were considered poor, 0.4–0.75 indicated fair to good agreement, and >0.75 indicated excellent agreement.

Comparisons between groups were performed using Chi-squared tests for categorical variables, and independent two-sample t-tests or nonparametric tests for continuous variables, as appropriate. Binary logistic regression analysis was performed to explore factors independently associated with young patients. Variables with P<0.05 in univariate analyses were subsequently entered into the multivariate logistic regression model. A two-sided P<0.05 was considered statistically significant. All analyses were performed using SPSS software (version 22.0, IBM Corp., Armonk, New York, USA) and MedCalc (version 19.1.2, MedCalc Inc., Mariakerke, Belgium).

Results

Patient demographics and vascular risk factors

A total of 244 patients were enrolled in this study, including 145 young patients and 99 MOP, as illustrated in the flowchart (Figure 1). The young group comprised 116 males and 29 females, with a median age of 40.0 years (IQR, 33.5–43.0 years), while the MOP group included 76 males and 23 females, with a mean age of 63.7±9.0 years (Table 1). No significant intergroup difference was noted in gender distribution (P=0.545).

Figure 1 Flowchart of patient selection. HRVWI, high-resolution vessel wall imaging; LAA, large artery atherosclerosis; TIA, transient ischemic attack.

The young cohort was further stratified into two subgroups: 45 patients aged 18–35 years and 100 patients aged 36–45 years. A significant difference in sex distribution was observed between the two subgroups (P=0.025), with males comprising 41 (91%) of patients in the 18–35–year group and 75 (75%) in the 36–45-year group. The prevalence of hypertension, diabetes, and coronary heart disease was significantly lower in the young group compared to the MOP group (Table 1). No significant differences were observed between the groups in terms of smoking history and alcohol abuse.

Notably, young patients exhibited higher low-density lipoprotein levels than the MOP group (2.10 vs. 2.05 mmol/L; P=0.020). However, no significant differences were found in levels of high-density lipoprotein, total cholesterol, triglycerides, or apolipoproteins. Among young patients, vascular risk factors did not differ significantly between the 18–35 and 36–45 years age subgroups (Table 1).

Interobserver reproducibility for imaging assessment

The interobserver agreement for evaluating both plaque-affected vessel segments and plaque characteristics was excellent. ICCs ranged from 0.750 to 0.882, while kappa values ranged from 0.886 to 0.996. Detailed results are summarized in Tables S1,S2.

Plaque distribution

Plaques were more prevalent in 18 (78.3%) vessel segments in the MOP group compared to the young group, detailed in Table S3. The bilateral M1 segments of the MCA were the most frequently affected sites across all age groups. Within the young group, patients aged 36–45 years were more likely to exhibit plaques in the bilateral IICAs (right: 69.0% vs. 31.1%, P<0.001; left: 63.0% vs. 44.4%, P=0.037), bilateral ICA‑Ts (right: 63.5% vs. 38.6%, P=0.006; left: 63.3% vs. 45.5%, P=0.047), and BA (47.0% vs. 22.2%, P=0.005) than those aged 18–35 years, as detailed in the table motioned above.

Compared to the MOP group, young patients exhibited significantly lower proportions of affected vessel segments in the anterior circulation, posterior circulation, and the entire cerebral vasculature (Table 2). These differences remained statistically significant after adjustment for vascular risk factors (Table S4): total AVSR (adjusted OR 0.002, P<0.001), anterior AVSR (adjusted OR 0.002, P<0.001), and posterior AVSR (adjusted OR 0.052, P<0.001). Within the young cohort, patients aged 36–45 years had a greater number of affected vessel segments in the anterior circulation and in the overall vasculature compared with those aged 18–35 years (all P<0.01), whereas no significant difference was observed in the posterior circulation (Table 2).

Culprit plaque characteristics

Given that certain characteristics of culprit plaques may change over time, young patients who presented more than four weeks after symptom onset were excluded from further analysis to ensure alignment of imaging time with that of the MOP group. As a result, a total of 204 culprit plaques were evaluated, comprising 105 plaques in young patients (median age, 39.0 years; IQR, 33.5–43.0 years; 83 males and 22 females) and 99 plaques in MOP patients.

Culprit plaques were primarily located in the MCA (137 plaques, 67.2%), followed by BA (20 plaques, 9.8%), and ICA (15 plaques, 7.4%). Notably, young patients had a lower proportion of culprit plaques in the BA compared to the MOP group (5.7% vs. 14.1%, P=0.043, Table 3). As summarized in Table 4, culprit lesions in young patients exhibited distinct imaging features compared to those in the MOP group. Specifically, young patients demonstrated lower degrees of luminal stenosis, smaller plaque area, lower plaque burden, higher eccentricity index, and a lower incidence of intraplaque hemorrhage (all P<0.05). Figure 2 provides comparative imaging of the culprit lesions from the young adult and MOP groups.

Figure 2 Culprit plaque characteristics in young versus older stroke patients. A 31-year-old male presented with acute cerebral infarction (A-D). He had no traditional vascular risk factors. DWI revealed an acute infarction in the right frontal lobe and periventricular region. Correspondingly, MRA demonstrated severe stenosis (thin arrow) in the right M1 segment of the MCA. CPR of HRVWI, both pre- and post-contrast (C and D, respectively), clearly demonstrated significant plaque enhancement (thick arrows) at the corresponding site. A 73-year-old male with a history of hypertension, hyperlipidemia, and chronic alcohol use presented with stroke (E-H). DWI confirmed an acute infarction in the left periventricular region (E). MRA revealed severe stenosis of the left M1 segment of the MCA (F, thin arrow). CPR of pre- and post-contrast HRVWI (G,H) demonstrated a significantly enhanced plaque at the stenotic site (thick arrows). Notably, the culprit plaque in this case exhibited higher burden compared to that in the younger patient (Case a). Furthermore, it was surrounded by more additional plaques (arrowheads). CPR, curve planar reformation; DWI, diffusion-weighted imaging; HRVWI, high-resolution vessel wall imaging; MCA, middle cerebral artery; MRA, magnetic resonance angiography.

Multivariate logistic regression revealed that plaque burden was independently associated with age (OR, 0.092; 95% confidence interval: 0.009–0.950, P=0.045; Table 5). When comparing the 18–35- and 36–45-year-old subgroups, no significant differences were observed in the characteristics of culprit lesions, except for plaque area, which was smaller in the 18–35 years subgroup (5.60 mm²; IQR, 4.20–7.56 mm²) than in the 36–45 years subgroup (6.81 mm²; IQR, 5.62–8.76 mm²) (P=0.045). However, this difference was no longer statistically significant after adjustment for gender (OR, 1.127; 95% confidence interval: 0.983–1.292, P=0.086).

Discussion

This study investigated the distribution and characteristics of intracranial atherosclerotic plaques across age groups in symptomatic patients, yielding several key findings. First, a distinct age-related pattern of plaque distribution was identified, both between young and MOP patients and within the younger subgroup (18–35 vs. 36–45 years). Second, overall AVSR increased with age, particularly in the anterior circulation, while posterior circulation involvement was significantly more pronounced only in the MOP group. Third, compared to MOP patients, young patients exhibited culprit plaques with lower degrees of luminal stenosis, smaller plaque area, lower plaque burden higher eccentricity index, and less frequent intraplaque hemorrhage. Among these features, plaque burden was independently associated with age.

Atherosclerotic plaques are known to have site-specific predilections. Consistent with previous studies (5,8,22-24), we found that the most commonly involved intracranial sites were the M1 segment of the MCA and the IICA, followed by the BA, the V4 segment of the vertebral artery, the PCA, and the ACA, while extracranial plaques were relatively rare. Two mechanisms may explain this distribution. First, larger arteries are more susceptible to plaque development due to higher blood pressure gradients (23). For example, BA pressure can reach up to 80% of systemic pressure, whereas pial arteries experience lower pressures (24). Chronic hypertension may impair endothelium function, initiating and promoting atherosclerosis. Second, plaque formation frequently occurs at sites of vascular curvature and bifurcation (25,26) due to disturbed flow and low oscillatory shear stress (27). Although M1 segments are typically regarded as straight, 3D imaging has shown they are often curved, with plaques preferentially forming along the inner curvature where shear stress is lower and oscillatory shear index is higher.

Our findings also support the well-established relationship between aging and plaque development (22,28). With advancing age, arteries become more tortuous and elongated, which may reduce shear stress and promote turbulent flow. Plaque development at arterial curves and bifurcations appears to progress gradually throughout adulthood, whereas progression in smaller vessels becomes more significant in later life. In addition, several age-related molecular mechanisms identified in recent years—including clonal hematopoiesis of indeterminate potential driven by somatic mutations, cellular senescence, and chronic inflammation—have been shown to contribute to the development and progression of atherosclerotic lesions (29). We also observed increased plaque accumulation in the posterior circulation in MOP, likely due to aging-related changes in vessel geometry and flow dynamics.

Meanwhile, the above discussion does not diminish the importance of vascular risk factors. As shown in Table 1, the prevalence of hypertension, diabetes, coronary heart disease, and elevated low-density lipoprotein was significantly higher in the MOP group. These risk factors are well known to have complex interactions with the formation and development of atherosclerosis (29-31). A plausible interpretation is that age and these vascular risk factors likely exert synergistic or cumulative effects at the individual level: prolonged exposure to risk factors, acting on a vasculature that becomes increasingly susceptible with aging, may jointly accelerate and exacerbate atherogenesis. The high prevalence of these risk factors, together with the persistent “age effect” after adjustment, reflects a complex and multi-layered cardiovascular risk profile in the MOP population.

To our knowledge, few studies have assessed age-related differences in culprit plaque characteristics using HRVWI. Compared to MOP patients, young patients exhibited lower luminal stenosis, smaller plaque area, lower plaque burden, greater eccentricity index, and fewer instances of intraplaque hemorrhage. These findings contrast with a previous study focusing on patients with unilateral symptomatic MCA stenosis, which reported longer lesions in young individuals but no differences in plaque burden (21). The discrepancy may be due to differing patient populations or the inclusion of non-atherosclerotic etiologies such as dissection. Future studies with larger and more homogeneous cohorts using standardized imaging protocols are needed to resolve these inconsistencies. Moreover, we found no significant differences in plaque enhancement between young and MOP patients. Given that enhancement reflects inflammation and neovascularization, and that all patients in our study were imaged during the acute or subacute phase of stroke, this similarity is expected.

Our findings could have clinical implications. While age is a known independent risk factor for stroke occurrence and recurrence, younger individuals generally experience better functional recovery and prognosis. Our results may provide imaging-based insights into these age-related differences. Notably, plaque burden—a comprehensive metric reflecting plaque area, lumen stenosis, and arterial remodeling pattern—was independently associated with age. Previous studies have highlighted its prognostic value: one cross-sectional study identified plaque burden as the only independent predictor of recurrent stroke in the MCA territory (20), while a longitudinal study in MOP patients demonstrated that higher plaque burden was an independent risk factor for stroke recurrence (32). The relatively lower plaque burden observed in young patients may therefore contribute to their more favorable outcomes. Nevertheless, the occurrence of stroke despite lower plaque burden and lower degrees of luminal stenosis emphasizes the importance of aggressive secondary prevention strategies, even in younger patients.

This study has several limitations. First, it was a single-center, retrospective, cross-sectional study with a relatively small sample size. Larger, multicenter, longitudinal studies are required to validate these findings. Second, in the present study, two MRI scanners from different vendors with varying parameters were used, which may introduce potential confounding factors. Third, the analysis in this study focused solely on traditional risk factors and did not address emerging risk factors such as inflammation, lifestyle, and mental stress (33,34). These emerging risk factors might provide further insights into our observations.

In addition, several potential sources of inaccuracy exist in the morphological measurement of plaques. First, although a limited number of ex vivo histological studies have supported the accuracy of HRVWI-derived parameters (35), in vivo pathological validation of quantitative vessel wall imaging remains lacking due to technical constraints. Second, measurement variability may arise in the assessment of vascular and wall area. Incomplete suppression of blood flow or adjacent cerebrospinal fluid can mimic vessel wall structures, leading to partial volume effects and consequent overestimation of the true luminal area and wall thickness. Third, clear delineation of the vessel wall may be limited when the vessel caliber is small or the wall is particularly thin. This is especially pertinent for reference segments, where the wall may fall below the spatial resolution threshold and become imperceptible, potentially introducing estimation bias in both area and thickness measurements. Finally, some reference vessels may be subject to early atherosclerotic remodeling, which could lead to underestimation of the true remodeling ratio.

Conclusions

Our study found that intracranial atherosclerosis develops asynchronously across vascular territories. Compared with MOP patients, younger patients with atherosclerotic stroke exhibited distinct plaque characteristics, with plaque burden emerging as an independent imaging marker associated with age. These findings provide new insights into the age-related development of intracranial atherosclerosis and underscore the importance of targeted prevention and long-term management strategies even in young patients.

Acknowledgments

We sincerely thank Dr. Jin Liu from the clinical research institute, The First Affiliated Hospital of Nanjing Medical University, who kindly provided statistical advice for our study.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2145/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2145/dss

Funding: This study was supported by the National Natural Science Foundation of China (grant Nos. 82572186, 82171907, and 82271964), and the Jiangsu Province Capability Improvement Project through Science Technology and Education (No. JSDW202243).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-aw-2145/coif). All authors report that this study was supported by the National Natural Science Foundation of China (grant Nos. 82572186, 82171907, and 82271964) and the Jiangsu Province Capability Improvement Project through Science Technology and Education (No. JSDW202243). X.Y. and Y.F.M. are staff members of Shanghai United Imaging Healthcare Co., Ltd. Shanghai, China. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by The First Affiliated Hospital of Nanjing Medical University (reference No. 2021-SRFA-111) and informed consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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