Differential associations of intracranial large artery phenotypes (calcification vs. stenosis) with topographical white matter hyperintensity patterns in minor stroke/transient ischemic attack (TIA)

Introduction

White matter hyperintensity (WMH) is commonly observed on brain magnetic resonance imaging (MRI) in older population. WMH are often perceived as a clinical surrogate for cerebral small-vessel disease and are associated with increased risks for stroke and dementia (1-4). The prevalence of WMH rises significantly with age, ranging from 68–87% in individuals aged 60–70 years, and surpassing 95% in those aged 80–90 years (5,6). Insight into the pathophysiological mechanisms of WMH is crucial for optimizing prevention and treatment strategies.

The precise pathophysiological mechanisms of WMH remain largely unknown. First, variable lesions in the major intracranial arteries, including stiffness, intima-media thickness, stenosis, and calcification, are associated with increased WMH burden (7-10). Although these features frequently coexist, their pathophysiological mechanisms differ. Intracranial arterial stenosis (ICAS) may contribute by reducing cerebral perfusion, while intracranial artery calcification (IAC) might do so by impairing arteriolar diastolic function. Moreover, distinguishing IAC subtypes—medial versus intimal—is critical, as they likely influence the topographic distribution of WMH through distinct pathways (11). Posing additional challenges, ICAS and IAC frequently coexist in the same patient, or even the identical vessel in clinical practice (12). Previous studies have investigated the impact of intracranial arterial diseases, such as atherosclerotic stenosis, vessel wall calcification, dolichoectasia, on WMH (13,14). However, inadequate consideration of confounding effects from atherosclerotic stenosis and calcification led to conflicting and inconclusive results. Furthermore, recent studies indicate that different regions of WMH, specifically periventricular-WMH (P-WMH) and deep-WMH (D-WMH), exhibit distinct genetic backgrounds and pathological feature (15-17). The impact of intracranial artery lesions on distinctive WMH regions need to be elucidated.

In this study, we aimed to investigate the relationship between ICAS and IAC and their impacts on WMH. First, we quantified the intracranial artery stenosis burden (ICASB), discriminated the patterns of IAC and quantify the extent of IAC involvement of intracranial arteries, then examined the potential correlation between ICASB and IAC. We further explored their association with WMH severity. Given the distinct pathophysiological mechanisms across WMH regions, we also evaluated the effects of ICASB and IAC on P-WMH and D-WMH, respectively. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1810/rc).

Methods

Participants

This study included consecutive patients with minor stroke or transient ischemic attack (TIA) admitted to the Department of Neurology at the 10th Affiliate Hospital of Southern Medical University between November 2021 and August 2023. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Dongguan People’s Hospital (No. KYKT 20210062). Informed consents were waived because of the retrospective observational nature. The inclusion criteria were: (I) patients above 45 years of age; (II) admission National Institutes of Health Stroke Scale (NIHSS) ≤5; (III) patients had at least one atherosclerotic risk factor, including hypertension, diabetes mellitus, hyperlipidemia, and smoking; and (IV) having performed brain MRI and computed tomography angiography (CTA) with 0.625- mm slice thickness as measurement of calcification. The exclusion criteria were as follows: (I) coexist ≥50% stenosis in cervical segment of ICA; (II) extensive cerebral infarction affecting over 50% of the MCA territory impacts WMH assessment; (III) other potential etiologies of WMH including vasculitis, demyelinating diseases, and radiation-induced encephalopathy; (IV) poor MRI or CTA quality; (V) insufficient clinical data for analysis (Figure 1).

Figure 1 Flowchart of study population. CT, computed tomography; D-WMH, deep white matter hyperintensity; IAC, intracranial artery calcification; ICASB, intracranial artery stenosis burden; MCA, middle cerebral artery; MR, magnetic resonance; P-WMH, periventricular white matter hyperintensity; TIA, transient ischemic attack; WMH, white matter hyperintensity.

Clinical information, including age, sex, atherosclerotic risk factors, history of hypertension, hyperlipidemia, diabetes and smoking was collected from the electronic medical records. Laboratory tests were routinely performed six hours after admission on a fasting basis included measurements of total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), homocysteine, uric acid.

Evaluation of ICASB

First, the degree of ICAS was assessed in each patient using CTA, following the WASID study methodology (18,19). We examined the seven major intracranial arterial segments, including the internal carotid artery (ICA) segments C3 to C7, the middle cerebral artery (MCA) segment M1, the vertebral artery (VA) segment V4, and the basilar artery (BA). Stenosis was scored as 1 point for <50%, 2 points for 50–99%, and 3 points for >99% occlusion. The total ICASB score was obtained by summing the stenosis grades (0–3 points) for each affected vessel, based on prior reports (20).

Evaluation of IAC

IAC was detected by non-contrast computed tomography (NCCT) scanning (Philips Healthcare, Best, The Netherlands) in axial plane using a fixed bone window setting (center: 300 Hounsfield units (HU); width: 1,600 HU), slice thickness (0.7 mm). Image quality was assessed, and all images were of adequate quality with no significant artifacts (beam hardening, photon starvation, noise) that might influence evaluation. Seven major intracranial arteries, including bilateral ICA (C3–C7), MCA, VA (V4) and BA as described above, were used for IAC volume measurement and pattern discrimination. When hyperdense foci were identified, a region of interest was delineated over the vessel to quantify HU; IAC was defined as hyperdense foci over 130 HU as previously reported (21).

Original CT source images underwent three-dimensional (3D) reconstruction using MATLAB (R2024a; MathWorks, MA, USA). Subsequent IAC segmentation was performed in Analyze (v12.0; AnalyzeDirect, KS, USA) employing a semi-automated “seeding method” with manual refinement. Final IAC volumes were quantified automatically in ITK-SNAP (v3.4.0; www.itk-snap.org).

The IAC pattern was classified into intimal- and medial-IAC based on the method (22) previously validated against histology that evaluates thickness (1 point for ≥1.5 mm, 3 for <1.5 mm), circularity (1 point for dot, 2 for <90°, 3 for 90–270°, and 4 for 270–360°), and morphology along the long axis of the artery (0 points for indistinguishable, 1 for irregular/patchy and 4 for continuous). Intimal-IAC was designated with scores of 1–6, while medial-IAC was indicated by scores of 7–11. The visual scoring method for distinguishing intimal and medial patterns of IAC is detailed and illustrated in Figure S1. Accordingly, the number of vessels affected by intimal-IAC and medial-IAC was enumerated. IAC pattern was assessed by Y.L. and K.C. who were blinded to the clinical information and any disagreements were resolved through negotiation with a third senior neurologist (Z.S.). The inter-observer agreement for the classification of IAC patterns was found to be significant [Cohen’s Kappa 0.86, 95% confidence interval (CI): 0.75–0.94, P=0.012].

Evaluation of WMH

All participants underwent multimodal brain MRI as protocol, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), magnetic resonance angiography (MRA), fluid attenuated inversion recovery (FLAIR). Magnetic resonance (MR) images were acquired using a 3T Siemens Prisma MR scanner (Siemens Healthcare, Germany) with a 32-channel head coil for reception. The following parameters were used for the FLAIR images: axial slice thickness, 2 mm; no gap, repetition time (TR) of 11,000 ms; echo time (TE), 125 ms; flip angle, 90°; and matrix size, 512×512 pixels. Brain MRI was acquired within seven days of the index stroke [median time: 3 d; interquartile range (IQR), 2–5 d]. The assessment of WMH severity was performed on FLAIR sequences, with careful exclusion of any areas that corresponded to acute infarction as confirmed on diffusion-weighted imaging (DWI). Lesions displaying high signal intensity within 10 mm of the ventricle were classified as P-WMH, whereas WMH surrounded by brain tissue were designated as D-WMH. According to the Fazekas scale, both deep and periventricular WMH were coded from 0 to 3, for a total score of 0 to 6. P-WMH grading: Grade 0 = no lesion, Grade 1 = thin cap-like or pencil-like lesion, Grade 2 = smooth halo, Grade 3 = irregular hyperintensity extending into deep white matter. D-WMH grading: Grade 0 = no lesion, Grade 1 = punctate lesion, Grade 2 = merging lesions, Grade 3 = extensive merging. Fazekas score combined P-WMH and D-WMH grades, with none =0, mild WMH =1–2 points, moderate WMH =3–4 points, severe WMH =5–6 points. Fazekas score was assessed by Y.L. and K.C. who were blinded to the clinical information. Any disagreements were resolved through negotiation with a third senior neuroradiologist (X.F.). The inter-observer agreement for the WMH grading was found to be significant (Cohen’s Kappa 0.80, 95% CI: 0.68–0.88, P=0.018).

Statistical analysis

Continuous variables are presented as mean ± standard deviation or median with IQR, and categorical data are reported as frequencies and percentages. Comparisons for continuous variables were conducted using Student’s t-test or Mann-Whitney U-test, while the chi-square test was used for categorical variables. Spearman correlation analysis was employed to assess correlations between visual ICASB, calcium volume, and the number of arteries affected by IAC.

Given its skewed distribution and to enhance clinical interpretability, WMH severity was dichotomized into none/mild (total Fazekas score 0–1) and moderate/severe (total Fazekas score 2–6). Based on prior literature, we a priori specified age, sex, hypertension, diabetes, and hyperhomocysteinemia as covariates for adjustment in multivariable logistic regression models. In these analyses, ICASB and IAC subtypes (intimal and medial) were simultaneously entered to investigate their independent associations with WMH burden. To assess potential multicollinearity among predictors, variance inflation factors (VIFs) were calculated; all VIF values were <2.5. We subsequently performed stratified binary logistic regression analyses to examine the specific associations of IAC and ICASB with severe P-WMH and D-WMH, respectively, adjusting for the same a priori-defined set of covariates. A two-sided P value <0.05 was considered statistically significant. All analyses were performed using IBM SPSS Statistics software, version 26.

Results

Baseline characteristics

A total of 626 consecutive patients were enrolled. Among the participants, 72 had ≥50% stenosis in the extracranial segment of the cervical ICA, 23 were excluded due to infarct exceeding 1/2 MCA territory, 2 were diagnosed with inflammatory demyelinating encephalopathies, and 18 were excluded due to suboptimal MRI quality and 8 due to incomplete clinical data. Five hundred and three eligible patients were included in the final analysis, with a median age of 71 years (IQR, 68–76 years) and 204 (40.6%) females. Among them, 58.1% (292 cases) presented with hypertension, 38.0% (191 cases) with mellitus diabetes, and 26.0% (131 cases) with previous stroke. No IAC subtype was detected in 107 (21.3%), intimal IAC subtype in 286 (56.9%), medial IAC subtype in 207 (41.2%), and mixed IAC subtype in 86 (17.1%) (Table 1).

Distribution of intimal vs. medial calcification in intracranial arteries

Among 503 minor stroke/TIA patients, medial-IAC predominated in the left ICA (n=165), exceeding the right ICA (n=141), vertebral arteries (left: 39; right: 43), and BA (n=13). No MCA involvement occurred. Similarly, intimal-IAC peaked in the left ICA (n=170), followed by the right ICA (n=141). Vertebral arteries showed balanced intimal involvement (left: 51; right: 50), while the BA (n=9) and MCA (n=4) demonstrated minimal involvement. All MCA intimal-IAC co-occurred with other vessel lesions (Figure 2).

Figure 2 Distribution patterns of intimal-IAC (upper panel, blue) and medial-IAC (lower panel, red) across seven major intracranial arterial segments in patients with minor stroke/TIA. Vertical bars indicate intersection size (n), and horizontal bars indicate vessel frequency (n). IAC, intracranial artery calcification. IAC, intracranial artery calcification.

Higher ICASB tertiles correlated with increased prevalence of hypertension, diabetes, and hyperhomocysteinemia. Both intimal- and medial-IAC affected arteries, along with total IAC volumes, rose progressively with ICASB (Table 2). Spearman analysis demonstrated significant correlation between intimal-IAC affected arteries and ICASB scores (ρ=0.73, 95% CI: 0.65–0.81; P<0.001), whereas medial-IAC affected arteries showed no association (ρ=0.12, P=0.18). In multivariable linear regression adjusted for age, hypertension, and diabetes, a 1-mm³ increase in intimal-IAC volume was significantly associated with a 0.4 unit increase in ICASB (β=0.399, SE =0.07; P<0.001) (Figure S2).

Effects of ICASB and IAC pattern on WMH severity

Fazekas scores indicated 212 patients (42.1%) with no/mild WMH, 250 patients (49.7%) with moderate WMH, and 41 patients (8.2%) with severe WMH. In three groups, a trend towards higher age [no/mild vs. moderate vs. severe: 70 (67–74) vs.73 (69–77) vs.78 (73–81) years, P<0.001], hypertension rate (no/mild vs. moderate vs. severe: 46.3% vs. 64.0% vs. 82.9%, P<0.001) was detected with increasing WMH burden. Furthermore, a consistent tendency for the medial-IAC affected arteries [no/mild vs. moderate vs. severe: 0 (0–0) vs. 1 (0–2) vs. 2 (0–2), P<0.001] and IAC volumes [no/mild vs. moderate vs. severe: 9.68 (0.00–36.27) vs. 39.83 (19.00–59.29) vs. 58.34 (36.27–69.85) mL, P<0.001] was observed. No significant differences were observed for intimal-IAC pattern and ICASB among three groups (Table 3).

In multivariable logistic regression for moderate/severe WMH, age [adjusted odds ratio (aOR) =1.08 per year; 95% CI: 1.03–1.12; P=0.029], total calcification volume (aOR=1.13 per mm³; 95% CI: 1.01–2.94; P=0.011) and ICASB demonstrated significant associations (aOR =1.47; 95% CI:1.31–1.66; P<0.001) with moderate/severe WMH. Additionally, medial-IAC affected arteries (aOR =1.34; 95% CI: 1.05–1.71; P=0.021) emerged as independent predictors, whereas the effect of intimal-IAC affected arteries diminished after adjustment (Table 4).

Disparities in risk factors for P-WMH versus D-WMH

To investigate the impact of medial-IAC and ICAS burdens on WMH in specific regions, binary logistic regression was conducted with severe P-WMH (Grade 3) and D-WMH (Grade 3) as outcome variables. After multivariate adjustment, older age (aOR =1.11 per year; 95% CI: 1.06–1.16; P<0.001), higher ICASB (aOR =1.08 per unit; 95% CI: 1.07–1.30; P<0.001) and increased burden of medial-IAC affected arteries (aOR =1.42 per vessel; 95% CI: 1.21–3.83; P=0.012) were associated with severe P-WMH. In contrast, higher ICASB (aOR =1.86; 95% CI: 1.31–2.73; P=0.007 and increased burden of intimal-IAC affected arteries (aOR =1.11 per vessel; 95% CI: 1.09–2.76; P=0.014) were significantly associated with severe D-WMH (Table 5).

Discussion

In this cohort of minor stroke/TIA patients with multiple atherosclerotic risk factors, 56.9% exhibited intimal-IAC, while 41.2% demonstrated medial-IAC. The C3–C7 segments of ICA, particularly the left ICA, constituted the predominant site for both IAC patterns. Our study found significant associations between ICASB and WMH, as well as between medial-IAC and WMH. Moreover, the effect of ICASB on D-WMH was more pronounced than that on P-WMH. After adjusting for ICASB, intimal-IAC showed a significant association specifically with D-WMH, whereas medial-IAC was linked to P-WMH.

Stenosis and calcification frequently coexist in major intracranial arteries, yet manifest distinct pathophysiological processes and clinical outcomes (23). Previous studies suggested that intracranial artery stenosis was associated with WMH (13,24,25). However, some follow-up studies do not support the association between them (26,27). A major limitation is the reliance on localized plaque characteristics of a single stenotic vessel, which fails to reflect the overall status of multiple significant arterial stenoses in the brain. In our study, we implemented a CTA-based scoring system for assessing intracranial major arterial stenosis, referred to as the ICASB (20,28,29). In univariate analysis, there was no significant linear trend between ICASB and WMH severity, which might be due to confounding by strong covariates such as age and hypertension. After adjusting for age, hypertension, and IAC, we observed significant associations between ICASB and both P-WMH and D-WMH, with a more pronounced effect on D-WMH. A plausible explanation for this discrepancy is the differential distribution of supplying vessels across various white matter regions. The periventricular white matter is supplied by the choroidal and lenticulostriate arteries, while the deep white matter, relying solely on the medullary arteries, is more susceptible to low perfusion risk associated with ICASB (9,30).

Some researchers proposed that WMH was linked not only to decreased cerebral perfusion due to ICAS (31,32), but also to the damage caused by ICAS that disrupts cerebral blood flow autoregulation (33-35). Our research included a population of minor stroke/TIA patients with multiple risk factors for atherosclerosis, revealing a significant positive relationship between ICASB and IAC. As the research participants were not derived from a healthy community cohort, careful consideration is warranted when interpreting this association. While IAC and ICASB are regarded as representative of two different pathological processes—arteriosclerosis and atherosclerosis—considering the mechanisms underlying WMH, which involve hypoperfusion and compromised autoregulation (36,37), we posited that IAC, which frequently coexists with ICAS, might play an additional significant role in the association between ICASB and WMH.

After adjusting for ICASB factors, we observed a dose-response relationship between the number of medial-IAC affected arteries and the severity of WMH. The correlation between medial-IAC and WMH has been validated in earlier studies (38). The correlation between medial-IAC and WMH in our cohort was consistent with previous studies. Medial-IAC promotes large-artery stiffness, which amplifies pulsatile energy transmission into the cerebral microcirculation. This elevated pulsatile stress is thought to contribute to blood-brain barrier disruption and WMH, as these watershed regions are particularly susceptible to hemodynamic fluctuations (39-41).

In the study population, we found a significant association between aging and severe P-WMH; however, after adjusting for hypertension, ICASB, and IAC, the association with D-WMH did not reach statistical significance. ICASB was a shared risk factor for both P-WMH and D-WMH, demonstrating a stronger correlation with D-WMH. Even after adjusting for ICASB, intimal-IAC retained a significant association with D-WMH. Conversely, medial-type IAC was strongly correlated with P-WMH, but did not show a significant relationship with D-WMH. This disparity may be explained by the higher sensitivity of P-WMH to vascular dysfunction resulting from medial-IAC, in contrast to D-WMH. These findings corroborate recent evidence that the pathological mechanisms associated with P-WMH are not fully aligned with those of D-WMH, and there may be a subtle heterogeneity between P-WMH and D-WMH in the context of intracranial artery disease (12,42,43).

There were some limitations to this study. First, as a single-center retrospective study, we included patients with minor strokes/TIA, which resulted in significant differences in the prevalence of intimal- and medial-IAC compared to community populations. However, patients at high risk for symptomatic strokes also represents a high-risk for WMH, highlighting for increased vigilance. Second, our assessment of ICASB, IAC phenotypes, and WMH using visual scoring may lack sufficient accuracy, potentially concealing minor changes in these variables. Third, our study did not differentiate ICAS lesions by symptomatic status and it limited the ability to ascertain whether recently symptomatic plaques have a stronger association with WMH than chronic, asymptomatic stenoses. Moreover, the observed differences in the associations for P-WMH versus D-WMH should be interpreted with caution. While they may reflect genuine differences in underlying pathophysiology, they could also be influenced, in part, by methodological variation in scoring sensitivity. Finally, since routine computed tomography perfusion (CTP) evaluations were not conducted for stroke/TIA patients at our center, we were unable to provide direct evidence regarding ICASB induced hypoperfusion, necessitating further investigation in future research.

Conclusions

Stenosis and calcification of major intracranial arteries are common in stroke patients and appear to contribute collectively to the burden of WMH. Our findings suggest a differential association between distinct vascular phenotypes and topographic WMH patterns: medial-IAC shows a stronger association with P-WMH, whereas intimal-IAC exhibits a relatively stronger link with D-WMH. These observations support the notion that P-WMH and D-WMH may, at least in part, arise from partially distinct underlying pathophysiological mechanisms.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1810/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1810/dss

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1810/coif). The authors have no 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 Ethics Committee of Dongguan People’s Hospital (No. KYKT 20210062). Informed consents were waived because of the retrospective observational nature.

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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