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Biomedical Imaging and Instrumentation

Biomedical Imaging and Instrumentation - Poster Session A

Poster G3 - Characterizing MRI Associations Between Blood-Brain Barrier Water Exchange Rate and Cerebral Blood Flow in Gray and White Matter

Thursday, October 24, 2024

10:00 AM - 11:00 AM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Barah A. Albuhwailah

Undergraduate Researcher
Department of Biomedical Engineering, University of California Davis
Carmichael, California, United States

Co-Author(s)

Yufei D. Zhu, BS

Graduate Researcher
Department of Biomedical Engineering, University of California Davis
Davis, California, United States

Last Author(s)

AF

Audrey P. Fan

Assistant Professor
Department of Biomedical Engineering, University of California Davis; Department of Neurology, University of California Davis, United States

Introduction: The blood-brain barrier (BBB) plays a crucial role in maintaining cerebral homeostasis by regulating the delivery of oxygen and nutrients, clearing toxic metabolites, and protecting the central nervous system. Water exchange across the BBB occurs through transmembrane aquaporin channels, and can be measured using non-invasive magnetic resonance imaging (MRI) technology, i.e. arterial spin labeling. These channels create the physiological bases for the measurement of Water Exchange Rate (Kw) as a marker of BBB permeability and integrity. Kw holds promise as a novel biomarker for various neurological and neuropsychiatric disorders. However, further detailed characterization of Kw in specific brain regions and tissue types is required. Additionally, cerebral blood flow (CBF) is known to differ between gray matter (GM) and white matter (WM), with GM typically exhibiting higher CBF[1]. This study aims to characterize Kw as a novel imaging biomarker in GM and WM and associate the values with the measured CBF as a comparison.

Materials and

Methods: Six healthy participants (3 females, ages 22-29) underwent scanning with a 3T Siemens Skyra MRI. Structural T1 images were acquired, followed by three diffusion-weighted arterial spin labeling (DW ASL) sequences (M1) to measure Kw at a post-labeling delay (PLD) of 1800ms based on an optimization protocol from Shao et al[2]. These sequences were repeated (M2) to assess intra-session repeatability. The flow-encoding arterial spin tagging (FEAST) PLD, used for calculating arterial transit time (ATT), was maintained at 900ms. Data processing involved the Water Exchange Quantification (WEQ) Toolbox to generate whole-brain ATT, CBF, and Kw maps, as well as global averages. This toolbox employs a two-compartment kinetic model to separate intravascular and extravascular ASL signals based on different diffusion properties. Parametric maps were linearly registered to T1 structural images using FSL FLIRT, and Freesurfer was used to segment the structural T1 images, isolating GM and WM signals. GM and WM masks with corresponding Kw means were calculated using Matlab.

Results, Conclusions, and Discussions: In the six participants, average Kw values were 130.0 ± 12.4 min^-1 for GM and 122.7 ± 15.6 min^-1 for WM, with corresponding CBF averages of 62.2 ± 17.1 mL/100 g/min and 55.3 ± 15.5 mL/100 g/min. Despite overall similarities, GM exhibited higher Kw and CBF values. Histograms of Kw and CBF distributions revealed the highest voxel concentration in GM and WM Kw ranges [128-146] and [116-135], and CBF ranges [60-71] and [49-58], respectively. The mean values observed for CBF are comparable to known GM averages, however, WM CBF means are higher than expected. Kw values are consistent with previous research for both GM and WM mean values[1]. Correlation analysis showed a trend of positive association between Kw and CBF, suggesting a possible relationship between these parameters. A limitation of this study is the partial volume effect, causing inconsistency in the observed CBF values in GM and WM. Future work will focus on assessing the robustness of Kw fitting functions under various noise conditions and expanding the study to a larger participant population.

Acknowledgements (Optional): This study is funded by the NIH grant R01-NS128179.