Sarabi, M. S. | bioRxiv Science

bioRxiv2023

Vessel Density Mapping of Cerebral Small Vessels on 3D High Resolution Black Blood MRI

Cerebral small 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 cerebral small 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-0.5mm spatial resolution 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. Cerebral small vessels 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 cerebral small 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.

neuroscience↗

bioRxiv2019

An Automated 3D Analysis Framework for Optical Coherence Tomography Angiography

Optical Coherence Tomography Angiography (OCTA) is a novel, non-invasive imaging modality of retinal capillaries at micron resolution. While OCTA generates 3D image volumes, current analytic methods rely on 2D en face projection images for quantitative analysis. This obscures the 3D vascular geometry and prevents accurate characterization of retinal vessel networks. In this paper, we have developed an automated analysis framework that preserves the 3D geometry of OCTA data. This framework uses curvelet-based denoising, optimally oriented flux (OOF) vessel enhancement and projection artifact removal, as well as the generation of 3D vessel length from the Hamilton-Jacobi skeleton. We implement this method on a dataset of 338 OCTA scans from human subjects with diabetic retinopathy (DR) which is known to cause decrease in capillary density and compare them to healthy controls. Our results indicate that 3D vessel-skeleton-length (3D-VSL) captures differences in both superficial and deep capillary density that are not apparent in 2D vessel skeleton analyses. In statistical analysis, we show that the 3D small-vessel-skeleton-length (3D-SVSL), which is computed after the removal of the large vessels and associated projection artifacts, provides a novel metric to detect group differences between healthy controls and progressive stages of DR.\n\nThis work was supported in part by NIH grants UH3NS100614, R21EY027879, U01EY025864, K08EY027006, P41EB015922, P30EY029220, Research to Prevent Blindness, and UL1TR001855 and UL1TR000130 from the National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health.

bioengineering↗