Identification of high risk clinical and imaging features for intracranial artery dissection using high-resolution cardiovascular magnetic resonance

Abstract

Background: Intracranial artery dissection (IAD) often causes headache and cerebral vascular ischemic events. The imaging characteristics of IAD remain unclear. This study aims to characterize the appearance of culprit and non-culprit IAD using high-resolution cardiovascular magnetic resonance imaging (hrCMR) and quantify the incremental value of hrCMR in identifying higher risk lesions.

Methods: Imaging data from patients who underwent intervention examination or treatment using digital subtraction angiography (DSA) and hrCMR using a 3 T CMR system within 30 days after the onset of neurological symptoms were collected. The CMR protocol included diffusion-weighted imaging (DWI), black blood T1-, T2- and contrast-enhanced T1-weighted sequences. Lesions were classified as culprit and non-culprit according to imaging findings and patient clinical presentations. Univariate and multivariate analyses were performed to assess the difference between culprit and non-culprit lesions and complementary value of hrCMR in identifying higher risk lesions.

Results: In total, 75 patients were included in this study. According to the morphology, lesions could be classified into five types: Type I, classical dissection (n = 50); Type II, fusiform aneurysm (n = 1); Type III, long dissected aneurysm (n = 3); Type IV, dolichoectatic dissecting aneurysm (n = 9) and Type V, saccular aneurysm (n = 12). Regression analyses showed that age and hypertension were both associated with culprit lesions (age: OR, 0.83; 95% CI 0.75-0.92; p < 0.001 and hypertension: OR, 66.62; 95% CI 5.91-751.11; p = 0.001). Hematoma identified by hrCMR was significantly associated with culprit lesions (OR, 16.80; 95% CI 1.01-280.81; p = 0.037). Moreover, 17 cases (16 lesions were judged to be culprit) were diagnosed as IAD but not visible in DSA and 15 were Type I lesion.

Conclusion: hrCMR is helpful in visualizing and characterizing IAD. It provides a significant complementary value over DSA for the diagnosis of IAD.

Keywords: Cardiovascular magnetic resonance; Intracranial artery dissection; Intramural hematoma; MRI; Stroke.

Fig. 1

Representative high-resolution cardiovascular magnetic resonance (hrCMR) images of intracranial artery dissection (IAD) with different morphological and compositional features

Fig. 2

Different types of IAD with matched schematic drawings (longitudinal and cross-sectional view). Type I: Classical dissection; Type II: Fusiform aneurysm; Type III: Long dissected aneurysm; Type IV: Dolichoectatic dissecting aneurysm; Type V: Saccular aneurysm

Fig. 3

The cases of IAD. a a 51-year-old woman with acute transient ischemic attack (TIA). Both magnetic resonance angiography (MRA) and digital subtraction angiography (DSA) show an aneurysm with irregular surface on the M1 segment of right middle cerebral artery (MCA). T1-weighted and contrast enhanced (CE-T1) images show the lumen (yellow arrow) and pseudolumen (white star) on the right. b a 49-year-old man with acute ischemic symptom. Neither MRA nor DSA demonstrate an aneurysm or a dissection of the basilar artery (BA). T1-weighted and CE-T1 images show the lumen (yellow arrow) and pseudolumen (white star) on the right. c a 56-year-old man with dizziness and headache. MRA demonstrates an irregular aneurysm on the bottom of the BA, and no acute infarction was found in DWI. T1-weighted and T1-weighted enhancement (CE-T1) hrCMR are shown on the right. d a 44-year-old man with acute ischemic stroke on the left brainstem. MRA demonstrates an elliptic aneurysm on the BA, and DWI shows a sheet acute infarct in distribution of BA. T1-weighted and CE-T1 images are shown on the right

Fig. 4

The power of different features and parameters in differentiating culprit and non-culprit lesions. a Four lower curves show the diagnostic performance of each independent parameters to identify the culprit IAD; b the four higher curves show diagnostic performance of combining the traditional features (age and hypertension) and DSA with or without hrCMR feature (hematoma) to differentiate the culprit dissection from non-culprit one, and the highest area under the curve (AUC) value of receiver operator characteristics (ROC) pooling traditional features and hrCMR feature was the AUC value of ROC pooling traditional features and hrCMR feature (0.940) is higher than that of ROC from DSA + hrCMR (0.918)