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Bailey, C. J.

Publications and source records attributed to Bailey, C. J..

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Feasibility of 3T layer-dependent fMRI with GE-BOLD using NORDIC and phase regression

IntroductionFunctional MRI with spatial resolution in the submillimeter domain enables measurements of activation across cortical layers in humans. This is valuable as different types of cortical computations, e.g., feedforward versus feedback related activity, take place in different cortical layers. Layer-dependent fMRI (L-fMRI) studies have almost exclusively employed 7T scanners to overcome the reduced signal stability associated with small voxels. However, such systems are relatively rare and only a subset of those are clinically approved. In the present study, we examined the feasibility of L-fMRI at 3T using NORDIC denoising. Methods5 healthy subjects were scanned on a Siemens MAGNETOM Prisma 3T scanner. To assess across-session reliability, each subject was scanned in 3-8 sessions on 3-4 consecutive days. A 3D gradient echo EPI (GE-EPI) sequence was used for BOLD acquisitions (voxel size 0.82 mm isotopic, TR = 2.2 s) using a block designed finger tapping paradigm. NORDIC denoising was applied to the magnitude and phase time series to overcome limitations in tSNR and the denoised phase time series were subsequently used to correct for large vein contamination through phase regression. Results and conclusionNORDIC denoising resulted in temporal signal-to-noise ratio (tSNR) values comparable to or higher than commonly observed at 7T. Layer-dependent activation profiles could thus be extracted robustly, within and across sessions, from regions of interest located in the hand knob of the primary motor cortex (M1). Phase regression led to substantially reduced superficial bias in obtained layer profiles, although residual macrovascular contribution remained. We believe the present results support the feasibility of L-fMRI at 3T, which might help make L-fMRI available to a much wider community.

neuroscience↗

Capillary stall quantification from optical coherence tomography angiogram maximum intensity projections

Optical coherence tomography (OCT) is applicable to the study of cerebral microvasculature in vivo. Optimised acquisition schemes enable the generation of three-dimensional OCT angiograms, i.e., volumetric images of red blood cell flux in capillary networks, currently at a repetition rate of up to 1/10 seconds. This makes testable a new class of hypotheses that strive to bridge the gap between microscopic phenomena occurring at the spatial scale of neurons, and less invasive but crude techniques to measure macroscopic blood flow dynamics. Here we present a method for quantifying the occurrence of transient capillary stalls in OCT angiograms, i.e., events during which blood flow through a capillary branch is temporarily occluded. By making the assumption that information on such events is present predominantly in the imaging plane, we implemented a pipeline that automatically segments a network of interconnected capillaries from the maximum intensity projections (MIP) of a series of 3D angiograms. We then developed tools enabling rapid manual assessment of the binary flow status (open/stalled) of hundreds of capillary segments based on the intensity profile of each segment across time. The entire pipeline is optimized to run on a standard laptop computer, requiring no high-performance, low-availability resources, despite very large data volumes. To further reduce the threshold of adoption, and ultimately to support the development of reproducible research methods in the young field, we provide the documented code for scrutiny and re-use under a permissive open-source license.

neuroscience↗