Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas

Abdalla Z Mohamed; Richard Kwiatek; Peter Del Fante; Vince D Calhoun; Jim Lagopoulos; Zack Y Shan

doi:10.1002/jmri.29286

Back

Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas

Journal article

Open access

Peer reviewed

Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas

Abdalla Z Mohamed, Richard Kwiatek, Peter Del Fante, Vince D Calhoun, Jim Lagopoulos and Zack Y Shan

Journal of Magnetic Resonance Imaging, Vol.60(5), pp.1880-1891

2024

DOI: https://doi.org/10.1002/jmri.29286

PMID: 38339792

Appears in Thompson Institute Research Collection

Files and links (1)

pdf

Magnetic Resonance Imaging - 2024 - Mohamed - Functional MRI of the Brainstem for Assessing Its Autonomic Functions From2.82 MBDownload View

Published VersionCC BY V4.0, Open Access

Abstract

brain atlas

brainstem

functional MRI (fMRI)

central autonomic nervous system

Thompson Institute Special Collection

Neuroimaging

Chronic fatigue syndrome

Background The brainstem is a crucial component of the central autonomic nervous (CAN) system. Functional MRI (fMRI) of the brainstem remains challenging due to a range of factors, including diverse imaging protocols, analysis, and interpretation. Purpose To develop an fMRI protocol for establishing a functional atlas in the brainstem. Study Type Prospective cross-sectional study. Subjects Ten healthy subjects (four males, six females). Field Strength/Sequence Using a 3.0 Tesla MR scanner, we acquired T1-weighted images and three different fMRI scans using fMRI protocols of the optimized functional Imaging of Brainstem (FIBS), the Human Connectome Project (HCP), and the Adolescent Brain Cognitive Development (ABCD) project. Assessment The temporal signal-to-noise-ratio (TSNR) of fMRI data was compared between the FIBS, HCP, and ABCD protocols. Additionally, the main normalization algorithms (i.e., FSL-FNIRT, SPM-DARTEL, and ANTS-SyN) were compared to identify the best approach to normalize brainstem data using root-mean-square (RMS) error computed based on manually defined reference points. Finally, a functional autonomic brainstem atlas that maps brainstem regions involved in the CAN system was defined using meta-analysis and data-driven approaches. Statistical Tests ANOVA was used to compare the performance of different imaging and preprocessing pipelines with multiple comparison corrections (P ≤ 0.05). Dice coefficient estimated ROI overlap, with 50% overlap between ROIs identified in each approach considered significant. Results The optimized FIBS protocol showed significantly higher brainstem TSNR than the HCP and ABCD protocols (P ≤ 0.05). Furthermore, FSL-FNIRT RMS error (2.1 ± 1.22 mm; P ≤ 0.001) exceeded SPM (1.5 ± 0.75 mm; P ≤ 0.01) and ANTs (1.1 ± 0.54 mm). Finally, a set of 12 final brainstem ROIs with dice coefficient ≥0.50, as a step toward the development of a functional brainstem atlas. Data Conclusion The FIBS protocol yielded more robust brainstem CAN results and outperformed both the HCP and ABCD protocols. Evidence Level 2 Technical Efficacy Stage 1

Details

Title: Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas
Authors: Abdalla Z Mohamed - University of the Sunshine Coast, Queensland, Thompson Institute
Richard Kwiatek - University of the Sunshine Coast, Queensland, Thompson Institute
Peter Del Fante - University of the Sunshine Coast, Queensland, Thompson Institute
Vince D Calhoun - Georgia State University
Jim Lagopoulos (Author) - University of the Sunshine Coast, Queensland, Thompson Institute
Zack Y Shan - University of the Sunshine Coast, Queensland, Thompson Institute
Publication details: Journal of Magnetic Resonance Imaging, Vol.60(5), pp.1880-1891
Publisher: John Wiley & Sons, Inc.
Date published: 2024
DOI: 10.1002/jmri.29286
ISSN: 1522-2586; 1053-1807
PMID: 38339792
Copyright note: © 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Data Availability: The original data and analysis scripts used in this project are available through a reasonable request to the corresponding author. The different software packages used in the preparation of this manuscript are publicly available.
Grants: Multimodal MRI of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Understanding its Neuropathophysiology and Developing an Objective Neuromarker, 1184219, National Health and Medical Research Council (Australia, Canberra) - NHMRC
Organisation Unit: Thompson Institute
Language: English
Record Identifier: 991006998402621
Output Type: Journal article

Metrics

4 File views/ downloads

61 Record Views

5 Times Cited - Web of Science

See more details

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Radiology, Nuclear Medicine & Medical Imaging

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites