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

Abstract

Introduction: Functional 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. Methods: 5 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 conclusion: NORDIC 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.

Evaluating the capabilities and challenges of layer-fMRI VASO at 3T

“…One example is the hippocampus, which is located right above the air-filled ear canals. While there are specific neuroscientific hypotheses with predictions of memory encoding and memory retrieval across the layers in hippocampus, previous layer-fMRI studies of the hippocampus at 7T have been extremely difficult (Chang et al 2022;Deshpande et al 2022;Koster et al 2018;Maass et al 2014;Zhang et al 2022). Due to the reduced susceptibility artifacts at 3T, we believe that developments shown in this study will help facilitate more straightforward applications of layer-fMRI in susceptibility-challenged brain areas.…”

“…Previous layer-fMRI studies have been conducted at 3T (Akin and Özen 2019; Kim and Ress 2017; Knudsen et al 2022; Koopmans et al 2010; Lifshits et al 2018; Markuerki-aga et al 2020; Olman et al 2007; Puckett et al 2016; Ress et al 2007; Scheeringa et al 2016; Taso et al 2021; Wu et al 2018). Those studies were somewhat limited by unwanted sensitivities of large draining veins.…”

“…One very promising denoising candidate is NOise Reduction with DIstribution Corrected (NORDIC) PCA (Vizioli et al 2021). This approach of NORDIC-PCA denoising for layer-fMRI at 3T has been advocated for BOLD fMRI protocols by Knudsen et al, 2022. First investigations of ongoing research indicated that this approach is similarly helpful for layer-fMRI VASO.…”

“…Specifically: The need for UHF scanners limits layer-fMRI applications to ≈100 MRI labs globally and prohibits the widespread adoption of layer-fMRI as a neuroscientific imaging tool. Layer-fMRI at 3T (Akin and Özen 2019; Kim and Ress 2017; Knudsen et al 2022; Koop-mans et al 2010; Lifshits et al 2018; Markuerkiaga et al 2020; Olman et al 2007; Puckett et al 2016; Ress et al 2007; Scheeringa et al 2016; Taso et al 2021; Wu et al 2018) can increase the availability of layer-fMRI worldwide by two orders of magnitude. However, only about 8% of all the human layer-fMRI papers used 3T (source: https://layerfmri.com/papers/).…”

Evaluating the capabilities and challenges of layer-fMRI VASO at 3T

“…One very promising denoising candidate is NOise Reduction with DIstribution Corrected (NORDIC) PCA (49). This approach of NORDIC-PCA denoising for layer-fMRI at 3T has been advocated for BOLD fMRI protocols by Knudsen et al (6). First investigations of ongoing research indicated that this approach is similarly helpful for layer-fMRI VASO.…”