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

Autor: Mohamed AZ; Thompson Institute, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia., Kwiatek R; Thompson Institute, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia., Del Fante P; Thompson Institute, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia., Calhoun VD; Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA., Lagopoulos J; Thompson Brain and Mind Healthcare, Birtinya, Queensland, Australia., Shan ZY; Thompson Institute, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia.
Jazyk: angličtina
Zdroj: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2024 Nov; Vol. 60 (5), pp. 1880-1891. Date of Electronic Publication: 2024 Feb 09.
DOI: 10.1002/jmri.29286
Abstrakt: 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.
(© 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)
Databáze: MEDLINE
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