Fibre-specific white matter differences: preliminary findings from the Australian Epilepsy project
Poster No:
2178
Submission Type:
Abstract Submission
Authors:
Remika Mito1,2, Robert Smith1,3, Aaron Capon1, Loren Lindemayer1, David Abbott1,3, Heath Pardoe1,3, Mangor Pedersen4, Chris Tailby1,3, David Vaughan1,3, Graeme Jackson1,3, for the Australian Epilepsy Project Investigators1
Institutions:
1Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia, 2Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia, 3Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia, 4Auckland University of Technology, Auckland, Auckland, New Zealand
First Author:
Remika Mito
Florey Institute of Neuroscience and Mental Health|Department of Psychiatry, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Department of Psychiatry, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Co-Author(s):
Robert Smith
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
David Abbott, PhD
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Heath Pardoe
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Mangor Pedersen, Associate Professor
Auckland University of Technology
Auckland, Auckland, New Zealand
Auckland University of Technology
Auckland, Auckland, New Zealand
Chris Tailby, PhD
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
David Vaughan, PhD
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Graeme Jackson
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health|Florey Department of Neuroscience and Mental Health, The University of Melbourne
Melbourne, Victoria, Australia|Melbourne, Victoria, Australia
for the Australian Epilepsy Project Investigators
Florey Institute of Neuroscience and Mental Health
Melbourne, Victoria, Australia
Florey Institute of Neuroscience and Mental Health
Melbourne, Victoria, Australia
Introduction:
Epilepsy is one of the most common chronic neurological conditions and is understood to be characterised by disruption to large-scale brain networks1,2. Diffusion-weighted imaging (DWI) has enabled investigation of structural brain network changes in the epilepsies. Here, we applied advanced DWI analyses to investigate fibre-specific abnormalities in participants from the Australian Epilepsy Project (AEP). We hypothesised that epilepsy patients, particularly those with drug-resistant epilepsy, would exhibit large-scale changes in brain white matter pathways when compared to neurologically healthy controls. We also explored individual variability in large-scale white matter differences across the clinical cohorts when compared to the normative cohort.
Methods:
Adult participants (aged 18 to 65) who have been recruited to date into the AEP in three clinical categories were included:
(i) First unprovoked seizure (FUS) but with no diagnosis of epilepsy (n=42)
(ii) New diagnosis of epilepsy (NDE) made in the past 6 months (n=68)
(iii) Drug-resistant epilepsy (DRE) despite trial of 2 or more medications (n=56)
Neurologically healthy adult control participants recruited to date into the AEP (HC; n=74) were also included.
Multi-shell DWI data were acquired at 3T on a Siemens Prisma with the following parameters: TE/TR = 83/3065 ms; voxel size = 1.8 mm3; b-values = 0, 300, 1000, 3000 s/mm3. DWI data were preprocessed using MRtrix3_connectome3, and fibre orientation distribution (FOD) functions were extracted using multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD)4. Spatial correspondence was achieved using an unbiased study specific template. A measure of fibre density and cross-section (FDC) was computed, and whole-brain fixel-based analysis (FBA)5 performed to compare across groups, and between each clinical group and controls. Age and log-transformed estimated intracranial volume (eICV6; based on FreeSurfer estimate from structural T1-weighted images) were used as nuisance covariates.
Post-hoc analyses were performed to explore individual variability in widespread white matter abnormalities. Mean FDC values across the 'fixels' (fibre populations within a voxel) that exhibited significant differences on the F-test (affected fixel mask) were extracted for each participant, and a linear model computed for mean FDC as a function of eICV in the HC group only. Individuals were identified as outliers if standardised residuals were > 3.
(i) First unprovoked seizure (FUS) but with no diagnosis of epilepsy (n=42)
(ii) New diagnosis of epilepsy (NDE) made in the past 6 months (n=68)
(iii) Drug-resistant epilepsy (DRE) despite trial of 2 or more medications (n=56)
Neurologically healthy adult control participants recruited to date into the AEP (HC; n=74) were also included.
Multi-shell DWI data were acquired at 3T on a Siemens Prisma with the following parameters: TE/TR = 83/3065 ms; voxel size = 1.8 mm3; b-values = 0, 300, 1000, 3000 s/mm3. DWI data were preprocessed using MRtrix3_connectome3, and fibre orientation distribution (FOD) functions were extracted using multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD)4. Spatial correspondence was achieved using an unbiased study specific template. A measure of fibre density and cross-section (FDC) was computed, and whole-brain fixel-based analysis (FBA)5 performed to compare across groups, and between each clinical group and controls. Age and log-transformed estimated intracranial volume (eICV6; based on FreeSurfer estimate from structural T1-weighted images) were used as nuisance covariates.
Post-hoc analyses were performed to explore individual variability in widespread white matter abnormalities. Mean FDC values across the 'fixels' (fibre populations within a voxel) that exhibited significant differences on the F-test (affected fixel mask) were extracted for each participant, and a linear model computed for mean FDC as a function of eICV in the HC group only. Individuals were identified as outliers if standardised residuals were > 3.
Results:
Whole-brain FBA revealed significant (family-wise error (FWE) corrected p < 0.05) group differences on an F-test across extensive white matter fixels (Figure 1A). These significant group differences appeared to be driven predominantly by significantly decreased FDC in the DRE cohort when compared to controls, while no significant differences were observed in the FUS or NDE cohorts compared to controls (Figure 1B-D).
Figure 2A shows the density distribution of mean FDC values within the affected fixel mask across individuals by cohort. The DRE cohort exhibited a distribution shift in these mean FDC values when compared to controls (as expected given the whole-brain result), but there were also individuals in the NDE and FUS cohorts who appeared to exhibit widespread white matter abnormality (Figure 2B).
Figure 2A shows the density distribution of mean FDC values within the affected fixel mask across individuals by cohort. The DRE cohort exhibited a distribution shift in these mean FDC values when compared to controls (as expected given the whole-brain result), but there were also individuals in the NDE and FUS cohorts who appeared to exhibit widespread white matter abnormality (Figure 2B).
Conclusions:
In this study, we demonstrated fibre tract-specific white matter changes in fibre density and cross-section (FDC) in epilepsy patients from the Australian Epilepsy Project. Group comparisons demonstrated significant and widespread changes only in the drug-resistant epilepsy cohort when compared to controls; however, post-hoc exploration identified individual outliers with substantial white matter abnormality across all 3 clinical cohorts. Future work that examines individual differences from the normative cohort in fibre-specific measures, and their association with clinical parameters will be valuable.
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity 1
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
ADULTS
Epilepsy
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Provide references using author date format
2. Hatton, S. N. et al. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-Epilepsy study. Brain 143, 2454–2473 (2020).
3. Smith, R. & Connelly, A. MRtrix3_connectome: A BIDS Application for quantitative structural connectome construction. in Organisation for Human Brain Mapping 1063 (2019).
4. Jeurissen, B., Tournier, J. D., Dhollander, T., Connelly, A. & Sijbers, J. Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage 103, 411–426 (2014).
5. Raffelt, D. A. et al. Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage 144, 58–73 (2017).
6. Smith, R. E., Dhollander, T. & Connelly, A. On the regression of intracranial volume in Fixel-Based Analysis. in International Society of Magnetic Resonance in Medicine 3385 (2019).