Dataset Information

High-resolution structural and functional assessments of cerebral microvasculature using 3D Gas ?R2*-mMRA.

ABSTRACT: The ability to evaluate the cerebral microvascular structure and function is crucial for investigating pathological processes in brain disorders. Previous angiographic methods based on blood oxygen level-dependent (BOLD) contrast offer appropriate visualization of the cerebral vasculature, but these methods remain to be optimized in order to extract more comprehensive information. This study aimed to integrate the advantages of BOLD MRI in both structural and functional vascular assessments. The BOLD contrast was manipulated by a carbogen challenge, and signal changes in gradient-echo images were computed to generate ?R2* maps. Simultaneously, a functional index representing the regional cerebral blood volume was derived by normalizing the ?R2* values of a given region to those of vein-filled voxels of the sinus. This method is named 3D gas ?R2*-mMRA (microscopic MRA). The advantages of using 3D gas ?R2*-mMRA to observe the microvasculature include the ability to distinguish air-tissue interfaces, a high vessel-to-tissue contrast, and not being affected by damage to the blood-brain barrier. A stroke model was used to demonstrate the ability of 3D gas ?R2*-mMRA to provide information about poststroke revascularization at 3 days after reperfusion. However, this technique has some limitations that cannot be overcome and hence should be considered when it is applied, such as magnifying vessel sizes and predominantly revealing venous vessels.

SUBMITTER: Huang CH

PROVIDER: S-EPMC3817180 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

High-resolution structural and functional assessments of cerebral microvasculature using 3D Gas ΔR2*-mMRA.

Huang Chien-Hsiang CH Chen Chiao-Chi V CC Siow Tiing-Yee TY Hsu Sheng-Hsiou S SH Hsu Yi-Hua YH Jaw Fu-Shan FS Chang Chen C

PloS one 20131104 11

The ability to evaluate the cerebral microvascular structure and function is crucial for investigating pathological processes in brain disorders. Previous angiographic methods based on blood oxygen level-dependent (BOLD) contrast offer appropriate visualization of the cerebral vasculature, but these methods remain to be optimized in order to extract more comprehensive information. This study aimed to integrate the advantages of BOLD MRI in both structural and functional vascular assessments. The ...[more]

PMID: 24223773

Similar Datasets

Project description: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.

Project description:MR Fingerprinting (MRF) is a relatively new imaging framework capable of providing accurate and simultaneous quantification of multiple tissue properties for improved tissue characterization and disease diagnosis. While 2D MRF has been widely available, extending the method to 3D MRF has been an actively pursued area of research as a 3D approach can provide a higher spatial resolution and better tissue characterization with an inherently higher signal-to-noise ratio. However, 3D MRF with a high spatial resolution requires lengthy acquisition times, especially for a large volume, making it impractical for most clinical applications. In this study, a high-resolution 3D MR Fingerprinting technique, combining parallel imaging and deep learning, was developed for rapid and simultaneous quantification of T1 and T2 relaxation times. Parallel imaging was first applied along the partition-encoding direction to reduce the amount of acquired data. An advanced convolutional neural network was then integrated with the MRF framework to extract features from the MRF signal evolution for improved tissue characterization and accelerated mapping. A modified 3D-MRF sequence was also developed in the study to acquire data to train the deep learning model that can be directly applied to prospectively accelerate 3D MRF scans. Our results of quantitative T1 and T2 maps demonstrate that improved tissue characterization can be achieved using the proposed method as compared to prior methods. With the integration of parallel imaging and deep learning techniques, whole-brain (26?×?26?×?18?cm3) quantitative T1 and T2 mapping with 1-mm isotropic resolution were achieved in ~7?min. In addition, a ~7-fold improvement in processing time to extract tissue properties was also accomplished with the deep learning approach as compared to the standard template matching method. All of these improvements make high-resolution whole-brain quantitative MR imaging feasible for clinical applications.

Dataset Information

High-resolution structural and functional assessments of cerebral microvasculature using 3D Gas ?R2*-mMRA.

Publications

High-resolution structural and functional assessments of cerebral microvasculature using 3D Gas ΔR2*-mMRA.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets