Poster No:
2389
Submission Type:
Abstract Submission
Authors:
Zeinab Eftekhari1,2, Thomas Shaw1,3,4, Robert Henderson5,6, Wolfgang Bogner7, Markus Barth1,4,8
Institutions:
1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia, 2ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT), The University of Queensland, Brisbane, Australia, 3Neurology Department, Royal Brisbane and Women’s Hospital,, Brisbane,, Australia, 4School of Electrical Engineering and computer Science, The University of Queensland, Brisbane,, Australia, 5Neurology Department, Royal Brisbane and Women’s Hospital, Brisbane, Australia, 6Centre for Clinical Research, The University of Queensland, Brisbane,, Australia, 7High-field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University, Vienna, Austria, 8ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT), The University of Queensland, Brisbane,, Australia
First Author:
Zeinab Eftekhari
Centre for Advanced Imaging, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT), The University of Queensland
Brisbane, Australia|Brisbane, Australia
Co-Author(s):
Thomas Shaw, PhD
Centre for Advanced Imaging, The University of Queensland|Neurology Department, Royal Brisbane and Women’s Hospital,|School of Electrical Engineering and computer Science, The University of Queensland
Brisbane, Australia|Brisbane,, Australia|Brisbane,, Australia
Robert Henderson
Neurology Department, Royal Brisbane and Women’s Hospital|Centre for Clinical Research, The University of Queensland
Brisbane, Australia|Brisbane,, Australia
Wolfgang Bogner
High-field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University
Vienna, Austria
Markus Barth
Centre for Advanced Imaging, The University of Queensland|School of Electrical Engineering and computer Science, The University of Queensland|ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT), The University of Queensland
Brisbane, Australia|Brisbane,, Australia|Brisbane,, Australia
Introduction:
Motor neuron disease (MND) is a progressive condition marked by the degeneration of motor neurons, leading to physical deterioration and death. Magnetic Resonance Spectroscopy (MRS) provides a distinctive, non-invasive method for quantifying neurochemical alterations at the molecular level in MND patients. Initial findings suggest that the concentrations of specific metabolites may be impacted in MND [1]. However, limited studies have explored 7T for measuring metabolite changes in MND with different onset locations/phenotypes or used sLASER MRS which is beneficial due to its enhanced signal-to-noise ratio, reduced chemical shift displacement, and more precise quantification of neurochemical changes [2]. This study aimed to investigate changes in metabolite ratios across the motor cortex using 7T MRS. Our investigation focused on N- Acetyl aspartate (NAA), Glutamate (Glu), and Glutamine (Gln) concentrations in cortical areas corresponding to MND symptoms, as well as regions unaffected by the disease. The goal was to improve diagnostic accuracy and enable effective early-stage disease monitoring.
Methods:
Five non-neurodegenerative controls (NC) and five MND patients, (2 bulbar onset, 2 lower limb onset, and 1 upper limb onset), were scanned using a 7T whole-body research scanner (Siemens MAGNETOM) equipped with a 32-channel head coil (Nova Medical). The protocol included short-TE semi-LASER [3] (TE=28 ms, TR= 8s, 32 averages) and 3D T1-weighted MP2RAGE. MR spectra were collected from two distinct regions within the motor cortex for MND patients, one affected and one unaffected region (Figure 1). For the control group, the precentral gyrus (representing upper limb regions in the motor homunculus) and the paracentral lobule (representing lower limb regions) were selected. Data processing and analysis were conducted using the Osprey MRS analysis toolbox [4] in MATLAB (v.R2022a). Metabolite signals were quantified using LCModel (v6.3) [5] and the resulting mean absolute concentrations ± SD of NAA, Glu and Gln were reported for all comparative analyses.
Results:
We observed notable differences in neurochemical profiles between MND patients and NCs. NAA levels are 22.4% lower in affected regions (11.8 ± 1.5 mM) and 17% lower in non-affected regions (12.6 ± 1.3 mM) in MND patients, while NCs had mean absolute concentrations of 13.7 ± 0.7 mM in the lower limb and 15.2 ± 0.4 mM in the upper limb ROI. Gln levels were elevated by 23.3% in affected regions (3.8 ± 1 mM) and 5.9% in non-affected regions (2.8 ± 1 mM) in patients compared to NCs, who displayed mean absolute concentrations of 3.1 ± 0.6 mM in the lower limb and 2.6 ± 0.3 mM in the upper limb. Additionally, Glu levels were 14.6% lower in asymptomatic regions of MND patients (8.6 ± 0.6 mM) compared to NCs (9.4 ± 0.4 mM).
Conclusions:
This study demonstrates the feasibility of robustly acquiring single voxel MRS data from different regions of the motor cortex at 7T within a reasonable acquisition time for the relevant patient groups and the capability of MRS to detect neurochemical alterations in regions without observable phenotypic symptoms. Our preliminary results suggest a potential trend of lower NAA, Glu and higher Gln levels in MND when compared to non-neurodegenerative controls (NCs). Metabolite ratios derived from MRS may serve as valuable in vivo diagnostic markers and enable the measurement and monitoring of hyperexcitability, which holds potential as a biomarker for subtype/phenotype categorization and disease monitoring. Our continued investigation aims to identify potential patterns in Glu and Gln levels throughout the disease progression, with the aim of measuring excitotoxicity in vivo.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Novel Imaging Acquisition Methods:
MR Spectroscopy 1
Physiology, Metabolism and Neurotransmission :
Cerebral Metabolism and Hemodynamics
Keywords:
Degenerative Disease
Glutamate
Magnetic Resonance Spectroscopy (MRS)
Motor
Movement Disorder
MR SPECTROSCOPY
MRI
Neuron
Neuroses
Neurotransmitter
1|2Indicates the priority used for review
Provide references using author date format
[1] G. Öz, Magnetic resonance spectroscopy of degenerative brain diseases. Springer, 2016.
[2] S. Caldwell and D. L. Rothman, "1H magnetic resonance spectroscopy to understand the biological basis of als, diagnose patients earlier, and monitor disease progression," Frontiers in Neurology, vol. 12, p. 701170, 2021.
[3] D. K. Deelchand et al., "Across-vendor standardization of semi-LASER for single-voxel MRS at 3T," NMR Biomed, vol. 34, no. 5, p. e4218, May 2021, doi: 10.1002/nbm.4218.
[4] G. Oeltzschner et al., "Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data," Journal of neuroscience methods, vol. 343, p. 108827, 2020.
[5] S. W. Provencher, "Estimation of metabolite concentrations from localized in vivo proton NMR spectra," Magnetic resonance in medicine, vol. 30, no. 6, pp. 672-679, 1993.