Synopsis

Keywords: Vessel Wall, Vessels

Symptomatic cerebral vascular stenosis diseases include acute ischemic infarction and transient ischemic syndrome. Patients with these diseases often have a high risk of recurrence in the short term, which may have serious adverse consequences. High-resolution MR vessel wall imaging (HR-VWI) technique has provided new possibilities to assess the threat of stroke recurrence due to stenosis caused by intracranial plaque. The present study confirms that plaque morphological parameters obtained by HR-VWI can provide an effective prediction of stroke recurrence risk in patients with intracranial arterial stenosis.

Introduction

Intracranial arterial stenosis due to intracranial plaque is a high-risk factor for cerebrovascular diseases including ischemic stroke and transient ischemic attack. Previous studies have shown that these diseases have a high mortality and disability rate and a high risk of recurrence, thus early evaluation and detection are key to prevent adverse outcomes¹. High-resolution MR vessel wall imaging is increasingly used in the diagnosis and study of intracranial arterial stenosis due to its ability to qualitatively and quantitatively study intracranial vessel wall lesions². In this study, we extracted morphological indices of intracranial plaque using high-resolution vessel wall imaging (HR-VWI) and evaluated the effectiveness of this approach in identifying people at risk for ischemic stroke recurrence.

Methods

Patients and Questionnaire:
The current study was approved by the institutional review board. Written informed consent was obtained from each patient. A total of 126 patients with intracranial stenosis on MRA were recruited, exclusion criteria were: (1) patients who were diagnosed as vasculitis, dissection, vasospasm, Moyamoya disease, or reversible cerebral vasoconstriction syndrome (n = 21); (2) patients with a history of brain surgery (n = 9); (3) patients with incomplete clinicopathological information (n = 7). The detailed information of patients was shown in Table 1. The risk of stroke recurrence for each patient was assessed using the Essen Stroke Risk Score (ESRS), and patients were divided into high-risk group and low-risk group according to their score of ESRS scale (< 3 for low-risk).
Imaging protocol:
MRI Examinations were performed on a 3.0 T MR scanner (uMR 770, United Imaging Healthcare, Shanghai, China). Protocols were: (1) Time-of-flight MRA: repetition time/echo time (TR/TE) = 19.1/3.6 msec, field of view (FOV) = 220×180 $$$mm^{2}$$$, matrix size = 672×438, slice thickness = 0.6 $$$mm$$$, compress sensing-based acceleration factor (uCS) = 3.5, acquisition time = 2 minute 21 seconds; (2) T1-weighted 3D MATRIX (Modulated flip Angle Technique in Refocused Imaging with extended echo train) sequence: TR/TE = 902/13.92 msec, FOV = 192×172 $$$mm^{2}$$$, matrix size = 481×432, slice thickness = 0.4 $$$mm$$$, uCS = 4.9, acquisition time = 6 minute 8 seconds. Post-contrast images were obtained using same T1w MATRIX sequence with identical parameters after intravenous injection of gadolinium contrast (dosage: 0.1 mmol/kg) agent and a 5 minutes interval.
Image analysis:
Preprocessing of HR-VWI image was complicated with a dedicated plaque analysis software (uWS PlaqueTool, United Imaging Healthcare, Shanghai, China). First, a central line extraction algorithm and a vessel wall segmentation algorithm were used to automatically perform curved-planar reconstruction of all intracranial arteries and segmentation of the vessel wall and lumen. Second, the narrow point was manually selected at the most narrowed position of the entire vessel, while the reference points was selected at the site of normal vessel proximal or distal to the lesion site. Then the quantitative parameters including lumen diameter (LD), lumen area (LA), wall thickness (WT), normalized wall index (NWI), stenosis rate and remodeling index (RI) were automatically calculated. Further plaque component analysis was completed at pre-defined narrow point, after manually outlining the plaque and plaque components, the software automatically outputs the percentage of intraplaque hemorrhage (IPH).
Statistical analysis:
Mann-Whitney U test was used for parameters comparison, combined parameter was generated by logistic regression and the discriminatory performance of single and combined parameters was further assessed by receiver operating characteristic (ROC) analysis and DeLong’s test.

Results

Eighty-nine subjects with evidence of intracranial atherosclerosis on clinical imaging were recruited (Table 1). The results demonstrated that RI of high recurrence risk patients was significantly lower than low-risk patients (P = 0.02). Figure 2 showed that RI was the only single parameter which was able to significantly identify high-risk patients (AUC=0.649, P = 0.02). The combined parameter generated by RI and percentage of IPH, could slightly improve the discriminatory performance (AUC=0.693, P < 0.01).

Discussion and Conclusion

Our results suggest that imaging indices obtained by HR-VWI can effectively identify people with high risk for stroke recurrence, thus contributing to the early identification and screening accuracy of such high-risk patients.

Acknowledgements

No acknowledgement found.