Real-Time Semi-Automated and Automated Voxel Placement using fMRI Targets for Repeated Acquisition Magnetic Resonance Spectroscopy.
Data acquisition
Longitudinal
Magnetic resonance spectroscopy (MRS)
Reliability
Reproducibility
Voxel placement
Journal
Journal of neuroscience methods
ISSN: 1872-678X
Titre abrégé: J Neurosci Methods
Pays: Netherlands
ID NLM: 7905558
Informations de publication
Date de publication:
15 05 2023
15 05 2023
Historique:
received:
15
05
2022
revised:
02
04
2023
accepted:
06
04
2023
pmc-release:
15
05
2024
medline:
25
5
2023
pubmed:
10
4
2023
entrez:
9
4
2023
Statut:
ppublish
Résumé
Currently, magnetic resonance spectroscopy (MRS) is dependent on the investigative team to manually prescribe, or demarcate, the desired tissue volume-of-interest. The need for a new method to automate precise voxel placements is warranted to improve the utility and interpretability of MRS data. We propose and validate robust and real-time methods to automate MRS voxel placement using functionally defined coordinates within the prefrontal cortex. Data were collected and analyzed using two independent prospective studies: 1) two independent imaging days with each consisting of a multi-session sandwich design (MRS data only collected on one of the days determined based on scan time) and 2) a longitudinal design. Participants with fibromyalgia syndrome (N = 50) and major depressive disorder (N = 35) underwent neuroimaging. MRS acquisitions were acquired at 3-tesla. Evaluation of the reproducibility of spatial location and tissue segmentation was assessed for: 1) manual, 2) semi-automated, and 3) automated voxel prescription approaches RESULTS: Variability of voxel grey and white matter tissue composition was reduced using automated placement protocols. Spatially, post- to pre-voxel center-of-gravity distance was reduced and voxel overlap increased significantly across datasets using automated compared to manual procedures COMPARISON WITH EXISTING METHODS: Manual prescription, the current standard in the field, can produce inconsistent data across repeated acquisitions. Using automated voxel placement, we found reduced variability and more consistent voxel placement across multiple acquisitions CONCLUSIONS: These results demonstrate the within subject reliability and reproducibility of a method for reducing variability introduced by spatial inconsistencies during MRS acquisitions. The proposed method is a meaningful advance toward improved consistency of MRS data in neuroscience and can be utilized for multi-session and longitudinal studies.
Sections du résumé
BACKGROUND
Currently, magnetic resonance spectroscopy (MRS) is dependent on the investigative team to manually prescribe, or demarcate, the desired tissue volume-of-interest. The need for a new method to automate precise voxel placements is warranted to improve the utility and interpretability of MRS data.
NEW METHOD
We propose and validate robust and real-time methods to automate MRS voxel placement using functionally defined coordinates within the prefrontal cortex. Data were collected and analyzed using two independent prospective studies: 1) two independent imaging days with each consisting of a multi-session sandwich design (MRS data only collected on one of the days determined based on scan time) and 2) a longitudinal design. Participants with fibromyalgia syndrome (N = 50) and major depressive disorder (N = 35) underwent neuroimaging. MRS acquisitions were acquired at 3-tesla. Evaluation of the reproducibility of spatial location and tissue segmentation was assessed for: 1) manual, 2) semi-automated, and 3) automated voxel prescription approaches RESULTS: Variability of voxel grey and white matter tissue composition was reduced using automated placement protocols. Spatially, post- to pre-voxel center-of-gravity distance was reduced and voxel overlap increased significantly across datasets using automated compared to manual procedures COMPARISON WITH EXISTING METHODS: Manual prescription, the current standard in the field, can produce inconsistent data across repeated acquisitions. Using automated voxel placement, we found reduced variability and more consistent voxel placement across multiple acquisitions CONCLUSIONS: These results demonstrate the within subject reliability and reproducibility of a method for reducing variability introduced by spatial inconsistencies during MRS acquisitions. The proposed method is a meaningful advance toward improved consistency of MRS data in neuroscience and can be utilized for multi-session and longitudinal studies.
Identifiants
pubmed: 37031764
pii: S0165-0270(23)00072-9
doi: 10.1016/j.jneumeth.2023.109853
pmc: PMC10249508
mid: NIHMS1899173
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
109853Subventions
Organisme : NCCIH NIH HHS
ID : F32 AT010420
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH125850
Pays : United States
Organisme : NCCIH NIH HHS
ID : R33 AT009305
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA118681
Pays : United States
Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None.
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