RESUMO
Small cerebral blood vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of small cerebral blood vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5 mm spatial resolution (interpolated from 0.51×0.51×0.64 mm3) at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Small cerebral blood vessels including small artery, arterioles, small veins, and venules on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of small cerebral blood vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.
Assuntos
Imageamento Tridimensional , Imageamento por Ressonância Magnética , Humanos , Idoso , Adulto , Pessoa de Meia-Idade , Imageamento Tridimensional/métodos , Imageamento por Ressonância Magnética/métodos , Angiografia por Ressonância Magnética/métodos , Artéria Cerebral Média , EncéfaloRESUMO
PURPOSE: Directly imaging the function of cerebral perforating arteries could provide valuable insight into the pathology of cerebral small vessel diseases (cSVD). Arterial pulsatility has been identified as a useful biomarker for assessing vascular dysfunction. In this study, we investigate the feasibility and reliability of using dual velocity encoding (VENC) phase-contrast MRI (PC-MRI) to measure the pulsatility of cerebral perforating arteries at 7 T. METHODS: Twenty participants, including 12 young volunteers and 8 elder adults, underwent high-resolution 2D PC-MRI scans with VENCs of 20 cm/s and 40 cm/s at 7T. The sensitivity of perforator detection and the reliability of pulsatility measurement of cerebral perforating arteries using dual-VENC PC-MRI were evaluated by comparison with the single-VENC data. The effects of temporal resolution in the PC-MRI acquisition and aging on the pulsatility measurements were investigated. RESULTS: Compared to the single VENCs, dual-VENC PC-MRI provided improved sensitivity of perforator detection and more reliable pulsatility measurements. Temporal resolution impacted the pulsatility measurements, as decreasing temporal resolution led to an underestimation of pulsatility. Elderly adults had elevated pulsatility in cerebral perforating arteries compared to young adults, but there was no difference in the number of detected perforators between the two age groups. CONCLUSION: Dual-VENC PC-MRI is a reliable imaging method for the assessment of pulsatility of cerebral perforating arteries, which could be useful as a potential imaging biomarker of aging and cSVD.