Intracranial atherosclerotic disease (ICAD) is a common cause of ischemic stroke in individuals of Asian descent (1), accounting for approximately 50% of strokes in China and Southeastern Asia (2). ICAD is a chronic and progressive disease that can affect multiple intracranial arteries simultaneously. Although patients may exhibit no clinical symptoms in the early stages of the disease, there is a risk of developing neurological deficits. As the disease progresses, transient ischemic attacks (TIAs) or even acute ischemic strokes (AISs) may occur. TIA and AIS can be considered successive manifestations of acute cerebrovascular events. Patients with TIA experience transient and sudden onset of focal neurological symptoms, which are usually quickly and completely relieved (3). TIA represents brain tissue hypoperfusion, and severe hypoperfusion can eventually result in irreversible ischemic necrosis of brain tissue, significantly increasing the disability and mortality risk for patients with ICAD (4). TIA is considered the most valuable early warning sign prior to the onset of stroke. Studies have shown that the proportion of TIA patients who experience a stroke within 90 days is as high as 20% (5, 6). In a large-scale international study involving 3,847 patients with TIA or minor strokes, it was found that the incidence of cardiovascular events (including stroke) was 6.4% in the first year and 6.4% from the second to fifth years (7). Yang et al. (8) discovered that asymptomatic intracranial arterial plaques are more stable than symptomatic intracranial arterial plaques, as quantified by the degree of plaque enhancement. Therefore, asymptomatic intracranial arterial plaques are less likely to rupture and block distal blood vessels, often resulting in less severe clinical consequences. Symptomatic ICAD indicates that patients have already experienced neurological deficits. Studies have shown that the annual stroke recurrence rate for symptomatic ICAD is as high as 12.6% (9), with a high likelihood of progressing to irreversible AIS. Thus, active prevention and treatment are necessary for these patients.

The Framingham Stroke Risk Profile (FSRP) is a commonly used scale for predicting the risk of stroke in the next decade (10). FSRP takes into account various clinical risk factors that can exacerbate arteriosclerosis and accelerate the progression of atherosclerosis. Additionally, high-resolution vascular wall imaging (HR-VWI) technology has been widely employed in the clinical diagnosis of ICAD, enabling the analysis of plaque composition, measurement of stenosis, assessment of remodeling patterns, and evaluation of plaque stability (11). Dynamic susceptibility contrast-enhanced perfusion imaging (DSC-PWI) can be utilized for qualitative analysis and quantitative measurement of ischemic lesions. Studies have demonstrated that PWI can identify more than 50% of ischemic lesions in patients with suspected hemispheric TIA (12). It can provide objective evidence for the diagnosis and treatment of symptomatic ICAD patients.

Risk assessment of stroke can significantly impact the management of risk factors. The pathogenesis of AIS involves perforating artery occlusion, arterial–arterial embolism, hypoperfusion, and mixed mechanisms (13), which encompass plaques and hypoperfusion. Most existing models used for predicting AIS only focus on clinical risk factors and macroangiopathy, neglecting the influence of cerebral perfusion status (14). Studies on TIA risk stratification often overlook the causes of macroangiopathy and solely concentrate on perfusion changes (15). Currently, clinical risk factor models combined with multimodal MRI (mMRI) do not consider the comprehensive impact of multiple clinical risk factors on ICAD (16); the FSRP score can address this limitation. The goal of this study is to develop a clinical-imaging model for predicting AIS utilizing mMRI in conjunction with the FSRP in patients with ICAD to achieve accurate risk stratification and early secondary stroke prevention.

From January 2021 to May 2023, a total of 189 patients with symptomatic ICAD were enrolled in this study, while 77 patients who did not meet the research criteria were excluded. As a result, 112 patients were included in the final analysis. Among them, there were 65 patients (53.8% men and 46.2% women) in the TIA group, with an average age of 57.00 ± 11.50 years, and 47 patients (70.2% men and 29.8% women) in the AIS group, with an average age of 56.19 ± 11.31 years. Figure 1 shows the flowchart illustrating the patient recruitment and exclusion process.

The study applied mMRI and traditional clinical risk factors to analyze the clinical and imaging markers in patients with ICAD. The results showed that in the AIS group, the proportion of FSRP-high risk, hyperhomocysteinemia, LDL, SQI, and ER were higher compared to the TIA group. Additionally, the MTT and TTP values in the lesion area of AIS patients were significantly longer than those in the TIA group. FSRP-high risk and higher ER were identified as independent risk factors for AIS. ROC and nomogram models combining clinical and imaging features were established, demonstrating good diagnostic efficacy and clinical practicability in predicting the possibility of AIS in patients with ICAD.

This study revealed that FSRP-high risk is an independent risk factor for AIS, indicating a higher burden of cardiovascular risk factors. The evaluation criteria of FSRP encompass various cardiovascular risk factors, which may increase the incidence of dominant cerebrovascular diseases, including stroke, through their detrimental effects on neurovascular function (24). Notably, the SBP in AIS patients was significantly higher than that in TIA patients, and increased SBP has been linked to an elevated risk of cardiovascular events-related mortality (25, 26). High Hcy levels, hypertension, and hyperhomocysteinemia are recognized as traditional cardiovascular risk factors and the study found that in AIS patients, the combination of high Hcy levels and hypertension can double the risk of cardiovascular disease (27). Moreover, the study revealed higher LDL levels in the AIS group compared to the TIA group. LDL, as a key factor in plaque lipid core, plays a crucial role in atherosclerotic cardiovascular disease (ASCVD) induction and is a primary target for ASCVD prevention (28). Therefore, relying solely on FSRP for stroke risk prediction may not be sufficient. Evaluating Hcy and blood lipid levels as complementary factors to FSRP can provide clinicians with a more comprehensive assessment of stroke risk in patients, enabling targeted secondary prevention measures.

The secondary prevention of ischemic stroke relies on identifying the cause of the initial stroke (29). The clinical application of HR-VWI and PWI has improved the ability to diagnose the etiology of patients with ICAD, including macroangiopathy and microcirculation ischemia. The study showed that the SQI and ER of plaque were higher in the AIS group compared to the TIA group. SQI and ER are quantitative indices representing plaque enhancement, which aligns with the findings of this study. Numerous studies have confirmed that enhanced intracranial atherosclerosis plaques are associated with recent ischemic events and can serve as indicators of plaque stability (8, 30, 31). Therefore, anti-inflammatory interventions may be the optimal clinical approach for stabilizing plaques and preventing AIS in ICAD patients with significantly enhanced plaques. The study also found that the extension of MTT and TTP was more significant in the AIS group compared to the TIA group, while no differences were observed in rCBF and rCBV between the two groups. MTT and TTP are time parameters, and their increased values indicate a slowdown in blood flow and decreased perfusion levels in brain tissue. This change occurs before the decrease in rCBF and rCBV, reflecting adjustments in cerebral hemodynamic reserve (32). Therefore, MTT and TTP serve as more sensitive indicators for detecting abnormal cerebral perfusion, assisting clinicians in identifying subclinical cerebral ischemia and providing timely treatment to improve microcirculation, ultimately preventing persistent cerebral hypoperfusion and stroke.

Previous studies have focused on comparing risk factors between AIS and non-AIS individuals. Non-AIS individuals often include asymptomatic volunteers, making it challenging to identify them in clinical practice unless they undergo physical examinations. This study emphasizes patients with symptomatic cerebral ischemia, who are considered to be at high risk of stroke, making it crucial to evaluate their AIS risk and implement effective prevention strategies.

Based on the clinical and imaging risk factors identified for AIS, a ROC model was established to predict AIS with an AUC value of 0.791, sensitivity of 85.11%, and specificity of 66.15%. Currently, numerous studies have been conducted to predict future stroke risk in TIA patients using various scoring and imaging techniques. Hayashi T et al. found that the AUC of ABCD2 in predicting future stroke in TIA patients was 0.662 (33). They developed a prediction model based on age, hemiplegia, macrovascular risk characteristics, and previous cerebral infarction, which improved the prediction ability of TIA stroke risk with an AUC value of 0.804. In contrast to our study, Hay T et al. only studied arterial lesions >50% as variable values, while our study did not limit the stenosis degree of the responsible artery, as even mild stenosis may be accompanied by unstable plaques. Ren et al. (34) established a prediction model for the recurrence of symptomatic ICAD patients (including AIS and TIA) by combining clinical risk factors and plaque enhancement, achieving an AUC value of only 0.685. Although their predicted recurrence population differed from our study, their results indicated limited predictive capability for ICAD recurrence using clinical risk factors and plaque enhancement alone. Previous studies have demonstrated a relationship between perfusion defects and ipsilateral AIS in TIA patients (35), suggesting that the addition of perfusion parameters to the model could further improve prediction performance. Furthermore, to facilitate a more intuitive and convenient assessment of stroke risk in specific patients with ICAD, we developed a nomogram chart that demonstrates superior clinical net benefits by enhancing the efficiency of clinical decision-making, avoiding inadequate or excessive medical treatment, and facilitating early clinical intervention for patients with ICAD, and, therefore, reducing the risk of AIS.

There are several limitations to this study. First, the sample size was small, so there is a need for larger prospective studies to further validate the findings. Second, Tmax, one of the commonly used perfusion parameters with high sensitivity in evaluating changes in cerebral perfusion, was not obtained in this study. Calculating Tmax requires expensive commercial software, making it inaccessible for many smaller medical institutions. Therefore, we believe that rCBF, rCBV, MTT, and TTP are more practical parameters than Tmax. Lastly, long-term patient follow-up is essential to verify the model’s ability to distinguish stroke. As we did not conduct long-term follow-ups of symptomatic ICAD patients, future investigations will focus on the prognosis and recurrence in these patients.

FSRP-high risk and high ER are identified as independent risk factors for AIS. The combined prediction model, integrating clinical and imaging markers, can effectively predict stroke risk in symptomatic ICAD patients.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Ethics Committee of the First Affiliated Hospital of Harbin Medical University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

JS: Formal analysis, Investigation, Methodology, Software, Writing – original draft. YS: Methodology, Formal analysis, Writing – original draft. YC: Investigation, Software, Writing – original draft. JL was responsible for technical guidance and manuscript revision. WW: Data curation, Project administration, Writing – review & editing, Validation.