Structural Connectivity Differences In White Matter Tracts Of Nerve Growth Factor Mutation Carriers
Poster No:
876
Submission Type:
Abstract Submission
Authors:
Arnas Tamasauskas1, Andrew Marshall1, Irene Perini2, India Morrison2
Institutions:
1University of Liverpool, Liverpool, Merseyside, 2Linköping University, Linköping, Linköping
First Author:
Co-Author(s):
Introduction:
The research of pain and nociceptive reactions of people with Nerve Growth Factor (NGF) mutations has revealed congenitally reduced density of C-nociceptor afferent fibres in the peripheral nerve system, but the impact of these gene mutations on whole brain connectivity has not yet been explored.
Methods:
This study utilised Diffusion Tensor Imaging (DTI) and T1-weighted scans of a group of 11 R221W heterozygous carriers, who have impaired pain and temperature perception, and 11 gender-, age-, and education-matched healthy controls. DTI scans were acquired using single phase encoding. For preprocessing, Synb0, was utilised to synthesize reverse phase encoding from T1 scans. Whole-brain Voxel-based Tract-Based Spatial Statistics (TBSS) and Fixel-based group comparison analyses were performed to examine different metrics of white-matter structure and integrity. More specifically, TBSS investigated: fractional anisotropy (FA), mean diffusivity (MD), and Radial Diffusivity (RD), while Fixel-based statistics were used to analyse: microstructural fibre density (FD), fibre cross-section (FC), and combined fibre density and cross-section metric (FDC). Significance thresholding (p<0.05) was applied to Fixel FD, FC and FDC metrics, which were then registered to a John Hopkins University (JHU) ICBM-DTI-81 white-matter labels atlas using FSL Linear Image Registration Tool. Additionally, these tracts were converted to Voxels and used for Region of Interest (ROI) specified Probabilistic Second-order Integration over Fibre Orientation Distributions (iFOD2).
Results:
TBSS analysis showed no significant differences between the R221W carrier group and healthy controls in FA, MD or RD. Fixel-based group comparison between R221W carriers and healthy controls showed significant FD and FDC reductions in specific white matter tracts in midbrain and pons (p < 0.05) (Figure 1), but no significant differences in FC. JHU atlas-based White-matter investigations provided specificity in identifying tracts with significantly reduced FD and FDC of R221W carrier group as compared to healthy controls. These affected tracts were: the middle cerebellar peduncle, corticospinal tract, medial lemniscus, and inferior and superior cerebellar peduncles. Some minimal but significant (p<0.005) FD and FDC differences were seen in: corona radiata, as well as slight FD differences in external capsule, and slight FDC differences in internal capsule and uncinate fasciculus. Voxel-based iFOD2 analysis supported significant difference findings in FD and FDC populations in the midbrain, pons, cerebellum, and parts of temporal and occipital cortices. (p < 0.05) (Figure 2).
Conclusions:
While Voxel-based statistics did not indicate any significant structural white matter differences, Fixel-based FD and FDC findings suggest reduced intra-axonal volume in the spinothalamic and corticothalamic tracts of R221W carriers. This would indicate that the reduction of C-nociceptor afferent nerve density of R221W carriers is not constrained to the periphery, but is also present in parts of the brain. Particularly, brainstem pathways to the cerebellum and deep brain structures appear to have the most fibre density and cross-section reduction. However, the differences are not constrained to the brainstem as some differences are present in tracts located in occipital and temporal lobes. Fixel-based analyses provided a more detailed investigation of fibre orientations than TBSS, but iFOD2 provided additional support for significant difference findings in fibre density and cross-section when converted to voxel-based metrics. Further ROI TBSS, Fixel-based and Voxel-based analyses are needed to investigate the differences in intra-axonal volume and crossing-fibres of specific brain regions.
Genetics:
Neurogenetic Syndromes 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Diffusion MRI
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral 2
Keywords:
MRI
Neurological
Pain
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Provide references using author date format
Schilling, K. G., Blaber, J., Hansen, C., Cai, L., Rogers, B., Anderson, A. W., ... & Landman, B. A. (2020). Distortion correction of diffusion weighted MRI without reverse phase-encoding scans or field-maps. PLoS One, 15(7), e0236418.
Schilling, K. G., Blaber, J., Huo, Y., Newton, A., Hansen, C., Nath, V., ... & Landman, B. A. (2019). Synthesized b0 for diffusion distortion correction (Synb0-DisCo). Magnetic resonance imaging, 64, 62-70.
Smith, S. M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., ... & Behrens, T. E. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage, 31(4), 1487-1505.
Raffelt, D. A., Tournier, J. D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A. (2017). Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage, 144, 58-73.
Mori, S., Wakana, S., Van Zijl, P. C., & Nagae-Poetscher, L. M. (2005). MRI atlas of human white matter. Elsevier.
Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical image analysis, 5(2), 143-156.
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825-841.
Tournier, J. Donald, Fernando Calamante, and Alan Connelly. "Improved probabilistic streamlines tractography by 2nd order integration over fibre orientation distributions." Proceedings of the international society for magnetic resonance in medicine. Vol. 1670. John Wiley & Sons, Inc, New Jersey, 2010.