Biology subjects

Yang, J. Y.-M.

Publications and source records attributed to Yang, J. Y.-M..

4 recordsLinked to original sources

bioRxiv2025

TRAMFIX: TRavelling Across Melbourne for FIXel-based analysis (a reproducibility study)

Fixel-based analysis (FBA) has gained substantial interest for its ability to probe fibre-specific changes in the brains white matter from diffusion-weighted imaging data. However, the reproducibility and reliability of fixel-based measures across different scanners remains largely unknown. In this work, we present TRAMFIX: a multisite dataset of travelling participants (n=10 healthy adults) scanned across four 3T MRI scanners using a harmonised multi-shell DWI protocol. DWI data were processed using two pipelines that can adopted when performing multi-site FBA studies (site-specific versus pooled processing). We extracted fixel-based measures of fibre density (FD), fibre cross-section (FC), and fibre density and cross-section (FDC), as well as diffusion tensor imaging (DTI)-based fractional anisotropy (FA) and mean diffusivity (MD) from the harmonised protocol. Within-subject coefficients of variation (CVws) and intraclass correlation coefficients (ICC) of FBA and DTI measures were computed at multiple resolutions of computation and analysis: (i) the whole-brain averaged level, (ii) tract-level, and (iii) fixel- or voxel-level. Fixel-based metrics demonstrated high reproducibility and reliability at the whole-brain level (CVws ranging between 0.51% to 1.57% and ICC between 0.93 and 0.996). While reproducibility and reliability remained high for tract-averaged FBA measures (particularly the FC and FDC metrics), some tracts exhibited lower ICC values < 0.8 for the FD measure. When examining fixel-level reliability and reproducibility clear spatial patterns emerged, with lower ICC across subcortical and cerebellar regions, and higher CVws at the cortical boundaries. Across all levels, tensor-based metrics demonstrated slightly lower reproducibility and reliability metrics than FBA measures, suggesting that FBA metrics are just as, if not more, reproducible than DTI metrics across scanners when using identical protocols. Our findings provide support for the reproducibility and reliability of fixel-based measures, highlighting their potential for use in multi-site FBA studies. Future work examining protocol-related differences, as well as appropriate harmonisation strategies when pooling data across sites and scanners, will be valuable.

neuroscience↗

bioRxiv2024

Mild traumatic brain injury is associated with increased thalamic subregion volume in the subacute period following injury

Structural vulnerability of the thalamus remains under investigated in mild traumatic brain injury (mTBI), and few studies have addressed its constituent nuclei using robust segmentation methods. This study aimed to investigate thalamic subnuclei volume in the subacute period following mTBI. Trauma control (TC) and mTBI patients aged 18 - 60 years old completed an MRI neuroimaging protocol including both high resolution structural (T1w) and diffusion weighted sequences at 6 - 11 weeks following injury (mean: 57 days; sd 11). Each thalamus was segmented into its constituent subnuclei, which were grouped into eight lateralised subregions. Volumes of the subregions were calculated. Neurite Orientation Dispersion and Density (NODDI) maps with parameters optimised for grey matter were computed for the same subregions. Group differences in subregion volumes and NODDI parameters were investigated using Bayesian linear modelling, with age, sex, and intracranial volume included as covariates. Comparisons of mTBI (n = 39) and TC (n = 28) groups revealed evidence of relatively increased grey matter volume in the mTBI group for the bilateral medial and right intralaminar subregions (BF10 > 3). Of the subregions which showed volume differences, there was no evidence for differences in NODDI metrics between groups. This study demonstrates that in the subacute period following mTBI, there is evidence of increased volume in specific thalamic subregions. Putative mechanisms underpinning the increased volume observed here are disordered remyelination, or myelin debris yet to be cleared. Significance statementDespite the prevalence of continued cognitive, somatic, and vestibular symptoms in the subacute period (6 - 12 weeks) following an mTBI, a clear neuropathophysiological profile is yet to be determined. One key vulnerable structure in mTBI could be the thalamus, a subcortical grey matter structure which comprises numerous subregions. The present study investigated whether changes in thalamic subregion volume are evident in the subacute period. For the first time, we show that at approximately 8 weeks following injury, mTBI is associated with increased volume in specific thalamus subregions. This provides an important avenue for continued investigation into the clinical significance of these findings.

neuroscience↗

bioRxiv2021

Participant followup rate can bias structural imaging measures in longitudinal studies

Longitudinal MRI analysis is essential to accurately describe neuroanatomical changes over time. Loss of participants to followup (dropout) in longitudinal studies is inevitable and can lead to great difficulty in interpretation of statistical results if dropout is correlated with a study outcome or exposure. Beyond this, technical aspects of longitudinal MRI analysis require specialised processing pipelines to improve reliability while avoiding bias towards individual timepoints. In this article we test whether there is an additional problem that must be considered in longitudinal imaging studies, namely whether dropout has an impact on the function of FreeSurfer, a popular software pipeline used to estimate important structural brain metrics. We find that the number of acquisitions available per individual can impact the estimation of cortical thickness and brain volume using the FreeSurfer longitudinal pipeline, and can induce group differences in brain metrics. The effect on trajectories of brain metrics is smaller than the effect on brain metrics. HighlightsO_LILongitudinal MRI analysis is essential to accurately track neuroanatomical changes over time C_LIO_LILongitudinal MRI analysis requires specialised processing pipelines to reduce bias towards single timepoints C_LIO_LIParticipant drop out or loss can bias neuroanatomical measures derived from longitudinal pipelines C_LIO_LIWe find that group differences in the number of acquisitions available to analyse can cause group differences in estimated cortical thickness and brain volume C_LIO_LIThis bias appears to be due to the number of scans used to create individualised templates in the Freesurfer longitudinal pipeline C_LIO_LIThe effect on estimates of brain metric trajectories appears smaller than the effect on the estimates of brain metrics C_LI

neuroscience↗

bioRxiv2019

White Matter Extension of the Melbourne Children’s Regional Infant Brain Atlas: M-CRIB-WM

BackgroundUnderstanding typically developing infant brain structure is crucial in investigating neurological disorders of early childhood. Brain atlases providing standardised identification of neonatal brain regions are key in such investigations. Our previously developed Melbourne Childrens Regional Infant Brain (M-CRIB) and M-CRIB 2.0 neonatal brain atlases provide standardised parcellation of 100 and 94 brain regions respectively, including cortical, subcortical, and cerebellar regions. The aim of this study was to extend the M-CRIB atlas coverage to include 54 white matter regions.\n\nMethodsParticipants were ten healthy term-born neonates who comprised the sample for the M-CRIB and M-CRIB 2.0 atlases. WM regions were manually segmented on T2 images and co-registered diffusion tensor imaging-based, direction-encoded colour maps. Our labelled regions are based on those in the JHU-neonate-SS atlas, but differ in the following ways: 1) we included five corpus callosum subdivisions instead of a left / right division; 2) we included a left / right division for the middle cerebellar peduncle; and 3) we excluded the three brainstem divisions. All segmentations were reviewed and approved by a paediatric radiologist and a neurosurgery research fellow for anatomical accuracy.\n\nResultsThe resulting neonatal WM atlas comprises 54 WM regions: 24 paired regions, and six unpaired regions comprising five corpus callosum subdivisions and one pontine crossing tract. Detailed protocols for manual WM parcellations are provided, and the M-CRIB-WM atlas is presented together with the existing M-CRIB and M-CRIB 2.0 cortical, subcortical and cerebellar parcellations in ten individual neonatal MRI datasets.\n\nConclusionThe updated M-CRIB atlas including the WM parcellations will be made publicly available. The atlas will be a valuable tool that will help facilitate neuroimaging research into neonatal WM development in both healthy and diseased states.

neuroscience↗