Abstract
The detection and association of in vivo biomarkers in white matter (WM) pathology after acute and chronic mild traumatic brain injury (mTBI) are needed to improve care and develop therapies. In this study, we used the diffusion MRI method of hybrid diffusion imaging (HYDI)to detect white matter alterations in patients with chronic TBI (cTBI). 40 patients with cTBI presenting symptoms at least three months post injury, and 17 healthy controls underwent magnetic resonance HYDI. cTBI patients were assessed with a battery of neuropsychological tests. A voxel-wise statistical analysis within the white matter skeleton was performed to study between group differences in the diffusion models. In addition, a partial correlation analysis controlling for age, sex, and time after injury was performed within the cTBI cohort, to test for associations between diffusion metrics and clinical outcomes. The advanced diffusion modeling technique of neurite orientation dispersion and density imaging (NODDI) showed large clusters of between-group differences resulting in lower values in the cTBI across the brain, where the single compartment diffusion tensor model failed to show any significant results. However, the diffusion tensor model appeared to be just as sensitive in detecting self-reported symptoms in the cTBI population using a within-group correlation. To the best of our knowledge this study provides the first application of HYDI in evaluation of cTBI using combined DTI and NODDI, significantly enhancing our understanding of the effects of concussion on white matter microstructure and emphasizing the utility of full characterization of complex diffusion to diagnose, monitor, and treat brain injury.
Highlights
In Hybrid diffusion imaging (HYDI), multiple sampling spheres in q-space offer data needed for a range of diffusion reconstruction methods- such as Diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), q-ball imaging (QBI), and diffusion spectrum imaging (DSI). (Wu et al, 2018) HYDI utilizes lower b-value shells with high angular contrast-to-noise ratios, offering a better characterization of complex tissue organization. (Daianu et al, 2015) unlike other studies of both DTI and NODDI, the HYDI sequence is advantageous as multiple models can be fit using a single acquisition, decreasing total imaging time especially when combined with simultaneous multi slice acquisi tion, making it feasible in a clinical setting
We demonstrate the advantages of modeling higher-order diffusion sequences using an advanced multi-shell HYDI sequence for detecting white matter injury in chronic Traumatic brain injury (TBI) (cTBI)
The main findings of this study are (i) HYDI can be used to delineate WM alterations in cTBI using both NODDI and DTI using a single image acquisition (ii) NODDI is sensitive to white matter pathology in the posterior periventricular regions following cTBI, and can detect differences in voxels not detected by conventional DTI and (iii) both DTI and NODDI metrics are significant in partial correlations with neuropsychological outcomes, after controlling for age, sex, and time after injury
Summary
Traumatic brain injury (TBI) is a significant public health problem which occurs as a result of multiple incidents, including vehicle acci dents, falls, athletic collisions, blast-related trauma, and abuse or as sault. (Asken et al, 2018) Symptoms of TBI include a range of short- and long-term adverse clinical outcomes, including cognitive impairments or emotional dysregulation, resulting from traumatic axonal injury. (Kraus et al, 2007) Despite the increasing evidence that mTBI causes axonal shearing of white matter (WM) microstructure, the lack of reliable and objective tools to measure this pathology is a barrier to clinical translation. (Levin and Diaz-Arrastia, 2015; Radhakrishnan et al, 2016) As a result, it is commonly assumed that subjects with mTBI will return to premorbid levels of functioning shortly after the traumatic event, which often results in insufficient follow-up care. (Yamagata et al, 2020).Diffusion tensor imaging (DTI) is a non-invasive magnetic resonance imaging (MRI) technique for assessing WM microstructure in vivo, and has revealed diffuse axonal injury in TBI subjects in the absence of injury signs on conventional MRI. (Maruta et al, 2016) DTI studies of mTBI have shown microstructural disruption to be associated with neuro cognitive and behavioral deficits after mild and chronic TBI. (Yamagata et al, 2020; Wu et al, 2018; Wallace et al, 2018) traditional DTI metrics represent basic statistical descriptions of diffusion that may not directly correspond to biophysically meaningful parameters of the underlying tissue. (Palacios et al, 2018) DTI assumes Gaussian diffusion within a single microstructural compartment, and may be insensitive to the complexity of WM structure which requires a non-Gaussian model with multiple compartments. (Jones and Cer cignani, 2010) WM differences in mTBI have been delineated using DTI, the magnitude, direction, locations, and time span of these changes have been inconsistent among studies. (Wu et al, 2018; Inglese et al, 2005) For example, several papers report reduced WM fractional anisotropy (FA) in mTBI, while others reporting elevations or no changes in FA. (Eierud et al, 2014) This can be attributed to a number of reasons, including the inherent dynamic nature of microstructural WM alterations after mTBI, heterogenous population phenotypes, and small sample sizes.Due to the complexity of chronic and acute TBI, the combination of higher-order biophysical measurements based on diffusion MRI has the potential for better characterizing the underlying microarchitectural changes in brain tissue. (Palacios et al, 2020a, 2020b) A more advanced multicompartment diffusion model known as neurite orientation dispersion and density imaging (NODDI) utilizes high-performance magnetic field gradients to probe more complex non-Gaussian WM diffusion, and measures the properties of three microstructural envi ronments: intracellular, extracellular, and free water. (Zhang et al, 2012) An increasing number of recent studies have applied NODDI to examine white matter changes following mTBI. (Wu et al, 2018; Pala cios et al, 2018; Mayer et al, 2010; Churchill et al, 2017) Findings in these papers reveal that NODDI metrics may be more sensitive and likely influenced by different factors than DTI metrics, providing more sensi tive and useful diagnostic information. (Gazdzinski et al, 2020) To translate research findings into clinical practice, replication and gener alization of these diffusion sequences are essential, (Lerma-Usabiaga et al, December 2018) with neuroimaging findings reproducible in an independent dataset acquired under real-world conditions.Hybrid diffusion imaging (HYDI) is a comprehensive diffusion sequence (Alexander et al, 2006) comprising multiple diffusionweighting shells which offers diffusion compartments sensitive to different diffusivities and multiple diffusion-weighting directions in each shell to capture the directionalities of each compartment. Due to the complexity of chronic and acute TBI, the combination of higher-order biophysical measurements based on diffusion MRI has the potential for better characterizing the underlying microarchitectural changes in brain tissue. (Daianu et al, 2015) unlike other studies of both DTI and NODDI, the HYDI sequence is advantageous as multiple models can be fit using a single acquisition, decreasing total imaging time especially when combined with simultaneous multi slice acquisi tion, making it feasible in a clinical setting. We aim to compare and evaluate the extent at which in both NODDI and DTI measurements correlate to self-reported symptoms in mTBI within a chronic popula tion, to further validate diffusion biomarkers and explore the prognostic significance of advanced imaging techniques
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