Plaque Evolution and Vessel Wall Remodeling of Intracranial Arteries: A Prospective, Longitudinal Vessel Wall MRI Study.

BACKGROUND: Progression of intracranial atherosclerotic disease (ICAD) is associated with ischemic stroke events and can be quantified with three-dimensional (3D) intracranial vessel wall (IVW) MRI. However, longitudinal 3D IVW studies are limited and ICAD evolution remains relatively unknown. PURPOSE: To evaluate ICAD changes longitudinally and to characterize the imaging patterns of atherosclerotic plaque evolution. STUDY TYPE: Prospective. POPULATION: 37 patients (69 ± 12 years old, 12 females) with angiography confirmed ICAD. FIELD STRENGTH/SEQUENCE: 3.0T/3D time-of-flight gradient echo sequence and T1- and proton density-weighted fast spin echo sequences. ASSESSMENT: Each patient underwent baseline and 1-year follow-up IVW. Then, IVW data from both time points were jointly preprocessed using a multitime point, multicontrast, and multiplanar viewing workflow (known as MOCHA). Lumen and outer wall of plaques were traced and measured, and plaques were then categorized into progression, stable, and regression groups based on changes in plaque wall thickness. Patient demographic and clinical data were collected. Culprit plaques were identified based on cerebral ischemic infarcts. STATISTICAL TESTS: Generalized estimating equations-based linear and logistic regressions were used to assess associations between vascular risk factors, medications, luminal stenosis, IVW plaque imaging features, and longitudinal changes. A two-sided P-value<0.05 was considered statistically significant. RESULTS: Diabetes was significantly associated with ICAD progression, resulting in 6.6% decrease in lumen area and 6.7% increase in wall thickness at 1-year follow-up. After accounting for arterial segments, baseline contrast enhancement predicted plaque progression (odds ratio = 3.61). Culprit plaques experienced an average luminal expansion of 10.9% after 1 year. 74% of the plaques remained stable during follow-up. The regression group (18 plaques) showed significant increase in minimum lumen area (from 7.4 to 8.3 mm2), while the progression group (13 plaques) showed significant decrease in minimum lumen area (from 5.4 to 4.3 mm2). DATA CONCLUSION: Longitudinal 3D IVW showed ICAD remodeling on the lumen side. Culprit plaques demonstrated longitudinal luminal expansion compared with their non-culprit counterparts. Baseline plaque contrast enhancement and diabetes mellitus were found to be significantly associated with ICAD changes. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

DANTE-CAIPI Accelerated Contrast-Enhanced 3D T1: Deep learning-based image quality improvement for Vessel Wall MR.

BACKGROUND AND PURPOSE: Accelerated and blood-suppressed post-contrast 3D intracranial vessel wall MRI (IVW) enables high-resolution rapid scanning but is associated with low SNR. We hypothesized that a deep-learning (DL) denoising algorithm applied to accelerated, blood-suppressed post-contrast IVW can yield high-quality images with reduced artifacts and higher SNR in shorter scan times. MATERIALS AND METHODS: Sixty-four consecutive patients underwent IVW, including conventional post-contrast 3D T1-sampling perfection with application-optimized contrasts by using different flip angle evolution (SPACE) and delay-alternating with nutation for tailored excitation (DANTE) blood-suppressed and CAIPIRINHIA-accelerated (CAIPI) 3D T1-weighted TSE post-contrast sequences (DANTE-CAIPI-SPACE). DANTE-CAIPI-SPACE acquisitions were then denoised using an unrolled deep convolutional network (DANTECAIPI-SPACE+DL). SPACE, DANTE-CAIPI-SPACE, and DANTE-CAIPI-SPACE+DL images were compared for overall image quality, SNR, severity of artifacts, arterial and venous suppression, and lesion assessment using 4-point or 5-point Likert scales. Quantitative evaluation of SNR and contrast-to-noise ratio (CNR) was performed. RESULTS: DANTE-CAIPI-SPACE+DL showed significantly reduced arterial (1 [1-1.75] vs. 3 [3-4], p<0.001) and venous flow artifacts (1 [1-2] vs. 3 [3-4], p<0.001) compared to SPACE. There was no significant difference between DANTE-CAIPI-SPACE+DL and SPACE in terms of image quality, SNR, artifact ratings and lesion assessment. For SNR ratings, DANTE-CAIPI-SPACE+DL was significantly better compared to DANTE-CAIPI-SPACE (2 [1-2], vs. 3 [2-3], p<0.001). No statistically significant differences were found between DANTECAIPI-SPACE and DANTE-CAIPI-SPACE+DL for image quality, artifact, arterial blood and venous blood flow artifacts, and lesion assessment. Quantitative vessel wall SNR and CNR median values were significantly higher for DANTE-CAIPI-SPACE+DL (SNR: 9.71, CNR: 4.24) compared to DANTE-CAIPI-SPACE (SNR: 5.50, CNR: 2.64), (p<0.001 for each), but there was no significant difference between SPACE (SNR: 10.82, CNR: 5.21) and DANTE-CAIPI-SPACE+DL. CONCLUSIONS: Deep-learning denoised post-contrast T1-weighted DANTE-CAIPI-SPACE accelerated and blood-suppressed IVW showed improved flow suppression with a shorter scan time and equivalent qualitative and quantitative SNR measures relative to conventional post-contrast IVW. It also improved SNR metrics relative to post-contrast DANTE-CAIPI-SPACE IVW. Implementing deep-learning denoised DANTE-CAIPI-SPACE IVW has the potential to shorten protocol time while maintaining or improving the image quality of IVW. ABBREVIATIONS: DL=deep learning; IVW=Intracranial vessel wall MRI; SPACE=sampling perfection with application-optimized contrasts by using different flip angle evolution; DANTE=delay-alternating with nutation for tailored excitation; CAIPI=controlled aliasing in parallel imaging; CNR=contrast-to-noise ratio.