Evaluation of FatNav‐Based Prospective Motion Correction for Perivascular Space Imaging With T2‐Weighted MRI at 7 T

ABSTRACT Subject motion during MRI acquisition is one of the major factors limiting image quality and diagnostic value. Previous studies have demonstrated the effectiveness of prospective motion correction (PMC) in mitigating motion‐related artifacts. However, the effectiveness of PMC for the visualization of perivascular spaces (PVS) has not yet been systematically evaluated in clinical populations. PVS imaging was performed using a T2‐weighted 3D turbo spin echo (TSE) sequence with fat navigator (FatNav)‐based PMC. Ten healthy participants were scanned with and without PMC while performing gradual instructed motion. To further evaluate the effectiveness of PMC in a clinical setting, 62 patients were scanned after being instructed to keep their heads still. Among them, 28 patients underwent paired PMC‐on and PMC‐off scans, whereas 34 patients underwent PMC‐on scans only. The degree of motion and its impact on overall image quality was assessed by two experienced radiologists using a 4‐point Likert scale. Quantitative metrics were further evaluated including structural similarity index measure (SSIM), peak signal‐to‐noise ratio (PSNR), PVS count, PVS volume, and contrast‐to‐noise ratio (CNR) between PVS and neighboring tissue. The motion scores were significantly larger in subjects with instructed motion than in patients with involuntary motion (10.3 ± 5.3 mm vs. 1.47 ± 0.97 mm). For instructed motion, PMC significantly improved visual scores and quantitative metrics and weakened negative correlations between motion and the metrics. For involuntary motion, PMC significantly increased CNR ( p < 0.001) and attenuated negative correlations between visual score and motion severity. The improvement in PVS CNR after PMC correlated strongly with motion score ( = 0.40, p = 0.04). However, no significant difference was observed in PVS count and volume between images with and without PMC. In conclusion, FatNav‐based PMC improved the motion robustness of 3D TSE images and PVS quantification in the presence of substantial motion, whereas its benefits for small involuntary motion appeared to be limited.