Association of Gene Expression and Tremor Network Structure.

BACKGROUND: Transcriptomic changes in the essential tremor (ET)-associated cerebello-thalamo-cortical "tremor network" and their association to brain structure have not been investigated. OBJECTIVE: The aim was to characterize molecular changes associated with network-level imaging-derived phenotypes (IDP) found in ET. METHODS: We performed an imaging-transcriptomic study in British adults using imaging-genome-wide association study summary statistics (UK Biobank "BIG40" cohort; n = 33,224, aged 40-69 years). We imputed imaging-transcriptomic associations for 184 IDPs and analyzed functional enrichment of gene modules and aggregate network-level phenotypes. Validation was performed in cerebellar-tissue RNA-sequencing data from ET patients and controls (n = 55). RESULTS: Among 237,896 individual predicted gene expression levels for 6063 unique genes/transcripts, we detected 2269 genome-wide significant associations (Bonferroni P < 2.102e-7, 0.95%). These were concentrated in intracellular volume fraction measures of white matter pathways and in genes with putative links to tremor (MAPT, ARL17A, KANSL1, SPPL2C, LRRC37A4P, PLEKHM1, and FMNL1). Whole-tremor-network cortical thickness was associated with a gene module linked to mitochondrial organization and protein quality control (r = 0.91, P = 2e-70), whereas white-gray T1-weighted magnetic resonance imaging (MRI) contrast in the tremor network was associated with a gene module linked to sphingolipid synthesis and ethanolamine metabolism (r = -0.90, P = 2e-68). Imputed association effect sizes and RNA-sequencing log-fold change in the validation dataset were significantly correlated for cerebellar peduncular diffusion MRI phenotypes, and there was a close overlap of significant associations between both datasets for gray matter phenotypes (χ2 = 6.40, P = 0.006). CONCLUSIONS: The identified genes and processes are potential treatment targets for ET, and our results help characterize molecular changes that could in future be used for patient treatment selection or prognosis prediction. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinson's Disease Risk Variant rs9638616 is Non-Specifically Associated with Altered Brain Structure and Function.

Background: A genome-wide association study (GWAS) variant associated with Parkinson's disease (PD) risk in Asians, rs9638616, was recently reported, and maps to WBSCR17/GALNT17, which is involved in synaptic transmission and neurite development. Objective: To test the association of the rs9638616 T allele with imaging-derived measures of brain microstructure and function. Methods: We analyzed 3-Tesla MRI and genotyping data from 116 early PD patients (aged 66.8±9.0 years; 39% female; disease duration 1.25±0.71 years) and 57 controls (aged 68.7±7.4 years; 54% female), of Chinese ethnicity. We performed voxelwise analyses for imaging-genetic association of rs9638616 T allele with white matter tract fractional anisotropy (FA), grey matter volume and resting-state network functional connectivity. Results: The rs9638616 T allele was associated with widespread lower white matter FA (t = -1.75, p = 0.042) and lower functional connectivity of the supplementary motor area (SMA) (t = -5.05, p = 0.001), in both PD and control groups. Interaction analysis comparing the association of rs9638616 and FA between PD and controls was non-significant. These imaging-derived phenotypes mediated the association of rs9638616 to digit span (indirect effect: ß= -0.21 [-0.42,-0.05], p = 0.031) and motor severity (indirect effect: ß= 0.15 [0.04,0.26], p = 0.045). Conclusions: We have shown that a novel GWAS variant which is biologically linked to synaptic transmission is associated with white matter tract and functional connectivity dysfunction in the SMA, supported by changes in clinical motor scores. This provides pathophysiologic clues linking rs9638616 to PD risk and might contribute to future risk stratification models.

Quantitative iron-neuromelanin MRI associates with motor severity in Parkinson's disease and matches radiological disease classification.

Background: Neuromelanin- and iron-sensitive MRI studies in Parkinson's disease (PD) are limited by small sample sizes and lack detailed clinical correlation. In a large case-control PD cohort, we evaluated the diagnostic accuracy of quantitative iron-neuromelanin MRI parameters from the substantia nigra (SN), their radiological utility, and clinical association. Methods: PD patients and age-matched controls were prospectively recruited for motor assessment and midbrain neuromelanin- and iron-sensitive [quantitative susceptibility mapping (QSM) and susceptibility map-weighted imaging (SMWI)] MRI. Quantitative neuromelanin-iron parameters from the SN were assessed for their discriminatory performance in PD classification using ROC analysis compared to those of qualitative visual classification by radiological readers of differential experience and used to predict motor severity. Results: In total, 191 subjects (80 PD, mean age 65.0 years; 111 controls, 65.6) were included. SN masks showed (a) higher mean susceptibility (p < 0.0001) and smaller sizes after thresholding for low susceptibility (p < 0.0001) on QSM and (b) lower contrast range (p < 0.0001) and smaller sizes after thresholding for high-signal voxels (p < 0.0001) on neuromelanin-sensitive MRI in patients than in controls. Quantitative iron and neuromelanin parameters showed a moderate correlation with motor dysfunction (87.5%: 0.4< | r | <0.6, p < 0.0001), respectively. A composite quantitative neuromelanin-iron marker differentiated the groups with excellent performance (AUC 0.94), matching the diagnostic accuracy of the best-performing reader (accuracy 97%) using SMWI. Conclusion: Quantitative neuromelanin-iron MRI is associated with PD motor severity and matched best-performing radiological PD classification using SMWI, with the potential to improve diagnostic confidence in the clinics and track disease progression and response to neuroprotective therapies.

Ultra-high-field 7T MRI in Parkinson's disease: ready for clinical use?-a narrative review.

Background and Objective: The maturation of ultra-high-field magnetic resonance imaging (MRI) [≥7 Tesla (7T)] has improved our capability to depict and characterise brain structures efficiently, with better signal-to-noise ratio (SNR) and spatial resolution. We evaluated whether these improvements benefit the clinical detection and management of Parkinson's disease (PD). Methods: We performed a literature search in March 2023 in PubMed (MEDLINE), EMBASE and Google Scholar for articles on "7T MRI" AND "Parkinson*", written in English, published between inception and 1st March, 2023, which we synthesised in narrative form. Key Content and Findings: In deep-brain stimulation (DBS) surgical planning, early studies show that 7T MRI can distinguish anatomical substructures, and that this results in reduced adverse effects. In other areas, while there is strong evidence for improved accuracy and precision of 7T MRI-based measurements for PD, there is limited evidence for meaningful clinical translation. In particular, neuromelanin-iron complex quantification and visualisation in midbrain nuclei is enhanced, enabling depiction of nigrosomes 1-5, improved morphometry and vastly improved radiological assessments; however, studies on the related clinical outcomes, diagnosis, subtyping, differentiation of atypical parkinsonisms, and monitoring of treatment response using 7T MRI are lacking. Moreover, improvements in clinical utility must be great enough to justify the additional costs. Conclusions: Together, current evidence supports feasible future clinical implementation of 7T MRI for PD. Future impacts to clinical decision making for diagnosis, differentiation, and monitoring of progression or treatment response are likely; however, to achieve this, further longitudinal studies using 7T MRI are needed in prodromal, early-stage PD and parkinsonism cohorts focusing on clinical translational potential.

Serial deep gray nuclear DTI changes in Parkinson's disease over twelve years.

Background: Deep gray nuclear pathology relates to motor deterioration in idiopathic Parkinson's disease (PD). Inconsistent deep nuclear diffusion tensor imaging (DTI) findings in cross-sectional or short-term longitudinal studies have been reported. Long-term studies in PD are clinically challenging; decade-long deep nuclear DTI data are nonexistent. We investigated serial DTI changes and clinical utility in a case-control PD cohort of 149 subjects (72 patients/77 controls) over 12 years. Methods: Participating subjects underwent brain MRI at 1.5T; DTI metrics from segmented masks of caudate, putamen, globus pallidus and thalamus were extracted from three timepoints with 6-year gaps. Patients underwent clinical assessment, including Unified Parkinson Disease Rating Scale Part 3 (UPDRS-III) and Hoehn and Yahr (H&Y) staging. A multivariate linear mixed-effects regression model with adjustments for age and gender was used to assess between-group differences in DTI metrics at each timepoint. Partial Pearson correlation analysis was used to correlate clinical motor scores with DTI metrics over time. Results: MD progressively increased over time and was higher in the putamen (p < 0.001) and globus pallidus (p = 0.002). FA increased (p < 0.05) in the thalamus at year six, and decreased in the putamen and globus pallidus at year 12. Putaminal (p = 0.0210), pallidal (p = 0.0066) and caudate MD (p < 0.0001) correlated with disease duration. Caudate MD (p < 0.05) also correlated with UPDRS-III and H&Y scores. Conclusion: Pallido-putaminal MD showed differential neurodegeneration in PD over 12 years on longitudinal DTI; putaminal and thalamic FA changes were complex. Caudate MD could serve as a surrogate marker to track late PD progression.

Microstructure of Brain Nuclei in Early Parkinson's Disease: Longitudinal Diffusion Kurtosis Imaging.

BACKGROUND: Diffusion kurtosis imaging provides in vivo measurement of microstructural tissue characteristics and could help guide management of Parkinson's disease. OBJECTIVE: To investigate longitudinal diffusion kurtosis imaging changes on magnetic resonance imaging in the deep grey nuclei in people with early Parkinson's disease over two years, and whether they correlate with disease progression. METHODS: We conducted a longitudinal case-control study of early Parkinson's disease. 262 people (Parkinson's disease: n = 185, aged 67.5±9.1 years; 43% female; healthy controls: n = 77, aged 66.6±8.1 years; 53% female) underwent diffusion kurtosis imaging and clinical assessment at baseline and two-year timepoints. We automatically segmented five nuclei, comparing the mean kurtosis and other diffusion kurtosis imaging indices between groups and over time using repeated-measures analysis of variance, and Pearson correlation with the two-year change in Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III. RESULTS: At baseline, mean kurtosis was higher in Parkinson's disease than controls in the substantia nigra, putamen, thalamus and globus pallidus when adjusting for age, sex, and levodopa equivalent daily dose (p < 0.027). These differences grew over two years, with mean kurtosis increasing for the Parkinson's disease group while remaining stable for the control group; evident in significant "group ×time" interaction effects for the putamen, thalamus and globus pallidus (ηp2= 0.08-0.11, p < 0.015). However, we did not detect significant correlations between increasing mean kurtosis and declining motor function in the Parkinson's disease group. CONCLUSION: Diffusion kurtosis imaging of specific grey matter structures shows abnormal microstructure in PD at baseline and abnormal progression in PD over two years.

Plasma Neurofilament Light Concentration Is Associated with Diffusion-Tensor MRI-Based Measures of Neurodegeneration in Early Parkinson's Disease.

BACKGROUND: Neurofilament light is a marker of axonal degeneration, whose measurement from peripheral blood was recently made possible by new assays. OBJECTIVE: We aimed to determine whether plasma neurofilament light chain (NfL) concentration reflects brain white matter integrity in patients with early Parkinson's disease (PD). METHODS: 137 early PD patients and 51 healthy controls were included. Plasma NfL levels were measured using ultrasensitive single molecule array. 3T MRI including diffusion tensor imaging was acquired for voxelwise analysis of association between NfL and both fractional anisotropy (FA) and mean diffusivity (MD) in white matter tracts and subcortical nuclei. RESULTS: A pattern of brain microstructural changes consistent with neurodegeneration was associated with increased plasma NfL in most of the frontal lobe and right internal capsule, with decreased FA and increased MD. The same clusters were also associated with poorer global cognition. A significant cluster in the left putamen was associated with increased NfL, with a significantly greater effect in PD than controls. CONCLUSION: Plasma NfL may be associated with brain microstructure, as measured using diffusion tensor imaging, in patients with early PD. Higher plasma NfL was associated with a frontal pattern of neurodegeneration that also correlates with cognitive performance in our cohort. This may support a future role for plasma NfL as an accessible biomarker for neurodegeneration and cognitive dysfunction in PD.

Essential tremor.

Essential tremor (ET) is one of the most common movement disorders, with a reported >60 million affected individuals worldwide. The definition and underlying pathophysiology of ET are contentious. Patients present primarily with motor features such as postural and action tremors, but may also have other non-motor features, including cognitive impairment and neuropsychiatric symptoms. Genetics account for most of the ET risk but environmental factors may also be involved. However, the variable penetrance and challenges in validating data make gene-environment analysis difficult. Structural changes in cerebellar Purkinje cells and neighbouring neuronal populations have been observed in post-mortem studies, and other studies have found GABAergic dysfunction and dysregulation of the cerebellar-thalamic-cortical circuitry. Commonly prescribed medications include propranolol and primidone. Deep brain stimulation and ultrasound thalamotomy are surgical options in patients with medically intractable ET. Further research in post-mortem studies, and animal and cell-based models may help identify new pathophysiological clues and therapeutic targets and, together with advances in omics and machine learning, may facilitate the development of precision medicine for patients with ET.

Utility of quantitative susceptibility mapping and diffusion kurtosis imaging in the diagnosis of early Parkinson's disease.

OBJECTIVE: To investigate the utility of quantitative susceptibility mapping (QSM) and diffusion kurtosis imaging (DKI) as complementary tools in characterizing pathological changes in the deep grey nuclei in early Parkinson's disease (PD) and their clinical correlates to aid in diagnosis of PD. METHOD: Patients with a diagnosis of PD made within a year and age-matched healthy controls were recruited. All participants underwent clinical evaluation using the Unified Parkinson's Disease Rating Scale (MDS-UPDRS III) and Hoehn & Yahr stage (H&Y), and brain 3 T MRI including QSM and DKI. Regions-of-interest (ROIs) in the caudate nucleus, putamen, globus pallidus, and medial and lateral substantia nigra (SN) were manually drawn to compare the mean susceptibility (representing iron deposition) and DKI indices (representing restricted water diffusion) between PD patients and healthy controls and in correlation with MDS-UPDRS III and H&Y, focusing on susceptibility value, mean diffusivity (MD) and mean kurtosis (MK). RESULTS: There were forty-seven PD patients (aged 68.7 years, 51% male, disease duration 0.78 years) and 16 healthy controls (aged 67.4 years, 63% male). Susceptibility value was increased in PD in all ROIs except the caudate, and was significantly different after multiple comparison correction in the putamen (PD: 64.75 ppb, HC: 44.61 ppb, p = 0.004). MD was significantly higher in PD in the lateral SN, putamen and caudate, the regions with the lowest susceptibility value. In PD patients, we found significant association between the MDS-UPDRS III score and susceptibility value in the putamen after correcting for age and sex (ß = 0.21, p = 0.003). A composite DKI-QSM diagnostic marker based on these findings successfully differentiated the groups (p < 0.0001) and had "good" classification performance (AUC = 0.88). CONCLUSIONS: QSM and DKI are complementary tools allowing a better understanding of the complex contribution of iron deposition and microstructural changes in the pathophysiology of PD.

Diffusion kurtosis imaging detects subclinical white matter abnormalities in Phenylketonuria.

OBJECTIVE: Phenylketonuria (PKU) is an autosomal recessive disorder whereby deficiencies in phenylalanine metabolism cause progressive neurological dysfunction. Managing PKU is challenging, with disease monitoring focussed on short-term phenylalanine control rather than measures of neuronal damage. Conventional imaging lacks sensitivity, however diffusion kurtosis imaging (DKI), a new MRI method may reveal subclinical white matter structural changes in PKU. METHODS: This cohort study involved adults with PKU recruited during routine clinical care. MRI, neurocognitive assessment and historical phenylalanine (Phe) levels were collected. A hypothesis-generating case study comparing diet-compliant and non-compliant siblings confirmed that DKI metrics are sensitive to dietary adherence and prompted a candidate metric (Krad/KFA ratio). We then tested this metric in a Replication cohort (PKU = 20; controls = 43). RESULTS: Both siblings scored outside the range of controls for all DKI-based metrics, with severe changes in the periventricular white matter and a gradient of severity toward the cortex. Krad/KFA provided clear separation by diagnosis in the Replication cohort (p < 0.001 in periventricular, deep and pericortical compartments). The ratio also correlated negatively with attention (r = -0.51 & -0.50, p < 0.05) and positively with 3-year mean Phe (r = 0.45 & 0.58, p < 0.01). CONCLUSION: DKI reveals regionally-specific, progressive abnormalities of brain diffusion characteristics in PKU, even in the absence of conspicuous clinical signs or abnormalities on conventional MRI. A DKI-based marker derived from these scores (Krad/KFA ratio) was sensitive to cognitive impairment and PKU control over the medium term and may provide a meaningful subclinical biomarker of end-organ damage.

Diffusion MRI as a complementary assessment to cognition, emotion, and motor dysfunction after sports-related concussion: a systematic review and critical appraisal of the literature.

Sports-related concussion (SRC) is a complex and heterogeneous injury with psychological, cognitive and functional consequences. Advances in diffusion magnetic resonance imaging (dMRI) allow sensitive measurement of white matter pathology post-SRC and may provide insight into injury and recovery. We systematically reviewed and meta-analyzed the literature examining dMRI alongside cognitive, emotional or motor assessments to determine relationships between these analyses. Sixteen studies examining young athletes (n = 6) or retired professionals (n = 10) met the inclusion criteria, with 12 emotional, 10 cognitive and four motor assessments. Studies had heterogeneous methodology, moderate quality and modest sample sizes. Fractional anisotropy (FA) was the most frequent dMRI metric, with SRC-induced changes described most commonly in the frontal lobe and least in the cerebellum and brainstem. There is an emerging complementary role for dMRI as part of a comprehensive assessment battery for SRC. However, larger-scale studies with broader subject populations (specifically, in females and in the 30-45 year age range) are needed to corroborate findings and determine the true diagnostic utility of dMRI post-SRC.

Neurocognitive Dysfunction and Smaller Brain Volumes in Adolescents and Adults With a Fontan Circulation.

BACKGROUND: Neurocognitive outcomes beyond childhood in people with a Fontan circulation are not well defined. This study aimed to investigate neurocognitive functioning in adolescents and adults with a Fontan circulation and associations with structural brain injury, brain volumetry, and postnatal clinical factors. METHODS: In a binational study, participants with a Fontan circulation without a preexisting major neurological disability were prospectively recruited from the Australia and New Zealand Fontan Registry. Neurocognitive function was assessed by using Cogstate software in 107 participants with a Fontan circulation and compared with control groups with transposition of the great arteries (n=50) and a normal circulation (n=41). Brain MRI with volumetric analysis was performed in the participants with a Fontan circulation and compared with healthy control data from the ABIDE I and II (Autism Brain Imaging Data Exchange) and PING (Pediatric Imaging, Neurocognition, and Genetics) data repositories. Clinical data were retrospectively collected. RESULTS: Of the participants with a Fontan circulation who had a neurocognitive assessment, 55% were male and the mean age was 22.6 years (SD 7.8). Participants with a Fontan circulation performed worse in several areas of neurocognitive function compared with those with transposition of the great arteries and healthy controls (P<0.05). Clinical factors associated with worse neurocognitive outcomes included more inpatient days during childhood, younger age at Fontan surgery, and longer time since Fontan procedure (P<0.05). Adults with a Fontan circulation had more marked neurocognitive dysfunction than adolescents with a Fontan circulation in 2 domains (psychomotor function, P=0.01 and working memory, P=0.02). Structural brain injury was present in the entire Fontan cohort; the presence of white matter injury was associated with worse paired associate learning (P<0.001), but neither the presence nor severity of infarct, subcortical gray matter injury, and microhemorrhage was associated with neurocognitive outcomes. Compared with healthy controls, people with a Fontan circulation had smaller global brain volumes (P<0.001 in all regions) and smaller regional brain volumes in most cerebral cortical regions (P<0.05). Smaller global brain volumes were associated with worse neurocognitive functioning in several domains (P<0.05). A significant positive association was also identified between global brain volumes and resting oxygen saturations (P≤0.04). CONCLUSIONS: Neurocognitive impairment is common in adolescents and adults with a Fontan circulation and is associated with smaller gray and white matter brain volume. Understanding modifiable factors that contribute to brain injury to optimize neurocognitive function is paramount.

Dorsolateral prefrontal circuit effective connectivity mediates the relationship between white matter structure and PASAT-3 performance in multiple sclerosis.

Three decades ago a series of parallel circuits were described involving the frontal cortex and deep grey matter structures, with putative roles in control of motor and oculomotor function, cognition, behaviour and emotion. The circuit comprising the dorsolateral prefrontal cortex, caudate, globus pallidus and thalamus has a putative role in regulating executive functions. The aim of this study is to investigate effective connectivity (EC) of the dorsolateral-prefrontal circuit and its association with PASAT-3 performance in people with multiple sclerosis(MS). We use Granger causality analysis of resting-state functional MRI from 52 people with MS and 36 healthy people to infer that reduced EC in the afferent limb of the dorsolateral prefrontal circuit occurs in the people with MS with cognitive dysfunction (left: p = .006; right: p = .029), with bilateral EC reductions in this circuit resulting in more severe cognitive dysfunction than unilateral reductions alone (p = .002). We show that reduced EC in the afferent limb of the dorsolateral prefrontal circuit mediates the relationship between cognitive performance and macrostrucutral and microstructural alterations of white matter tracts in components of the circuit. Specificity is shown by the absence of any relationship between cognition and EC in the analogous and anatomically proximal motor circuit. We demonstrate good stability of the EC measures in people with MS over an interval averaging 8-months. Key positive and negative results are replicated in an independent cohort of people with MS. Our findings identify the dorsolateral prefrontal circuit as a potential target for therapeutic strategies aimed at improving cognition in people with MS.

Characterizing the Risk of Depression Following Mild Traumatic Brain Injury: A Meta-Analysis of the Literature Comparing Chronic mTBI to Non-mTBI Populations.

Objective: Mild traumatic brain injury (mTBI) is associated with depressed mood acutely post-injury, but there is little evidence regarding long-term depression. The aim of this study was to determine the odds ratio (OR) of depression chronically following mTBI. Methods: We searched Medline (PubMed), ProQuest, and Web of Science from date of database creation to January 23, 2019, for eligible studies examining depression at least 6 months post-injury in adult subjects with mTBI of any etiology, including civilians and military. Three authors independently reviewed titles and abstracts for study eligibility. Data were extracted and collated by two investigators. Risk of bias was assessed with the SIGN methodology. Study data were pooled using random-effects meta-analysis. The primary exposure was mTBI, and the primary outcome was depression. Secondary exploratory variables were time of assessment, age at injury, age at assessment, sex, and etiology. Results: We included 47 cross-sectional studies (n = 25,103 mTBI and 29,982 control), 26 cohort studies (n = 70,119 mTBI, 262,034 control), four prospective observational studies (n = 1,058 mTBI and 733 control), two prospective longitudinal studies (n = 119 mTBI, 81 control), two case-control studies (n = 56 mTBI, 56 control), and one randomized controlled trial (n = 252 mTBI, 3,214 control). mTBI was associated with a 3.29-fold increased risk of depression (OR 3.29, 95% CI 2.68-4.03, I 2 = 96%). The OR for depression did not change when subjects were assessed at 6-12 months (OR 2.43, 1.45-4.07), years 1-2 (OR 4.12, 2.10-8.07); 2-10 (OR 3.28, 2.42-4.46), or 10+ (OR 3.42, 1.51-7.77). Similar risk of depression was sustained across different age at injury (<25: OR 2.26, 1.82-2.81; 25-35: OR 4.67, 3.06-7.14; >35: OR 2.69, 1.42-5.10) and different age at assessment (<40 years: OR 3.14, 2.48-3.99; >40 years: OR 4.57, 2.54-8.24). Female sex had a non-significant increase in OR (OR 19.97, 2.39-166.93) compared to male (OR 3.0, 2.33-3.86). mTBI etiology had no impact on depression. Conclusions: Those experiencing mTBI are more than three times more likely to experience depression compared to those without a history of mTBI, and this risk remains decades beyond the mTBI event. Future longitudinal studies are needed to identify and mitigate this risk.

Performance gains with Compute Unified Device Architecture-enabled eddy current correction for diffusion MRI.

Correcting for eddy currents, movement-induced distortion and gradient inhomogeneities is imperative when processing diffusion MRI (dMRI) data, but is highly computing resource-intensive. Recently, Compute Unified Device Architecture (CUDA) was implemented for the widely-used eddy-correction software, 'eddy', which reduces processing time and allows more comprehensive correction. We investigated processing speed, performance and compatibility of CUDA-enabled eddy-current correction processing compared to commonly-used non-CUDA implementations. Four representative dMRI datasets from the Human Connectome Project, Alzheimer's Disease Neuroimaging Initiative and Chronic Diseases Connectome Project were processed on high-specification and regular workstations through three different configurations of 'eddy'. Processing times and graphics processing unit (GPU) resources used were monitored and compared. Using CUDA reduced the 'eddy' processing time by a factor of up to five. The CUDA slice-to-volume correction method was also faster than non-CUDA eddy except when datasets were large. We make a series of recommendations for eddy configuration and hardware. We suggest that users of eddy-correction software for dMRI processing utilise CUDA and take advantage of the slice-to-volume correction option. We recommend that users run eddy on computers with at least 32GB motherboard random access memory (RAM), and a graphics card with at least 4.5GB RAM and 3750 cores to optimise processing time.

Characteristic patterns of white matter tract injury in sport-related concussion: An image based meta-analysis.

Sports-related concussion (SRC) is sustained by millions of people per year, yet the spatiotemporal patterns of white matter (WM) injury remain poorly understood. Several SRC studies have implemented the standardised approach Tract-Based Spatial Statistics (TBSS). The aim of this image-based meta-analysis was to identify consensus patterns of SRC-related WM injury across TBSS studies. We included studies comparing the diffusion MRI measurement fractional anisotropy (FA) in SRC or subconcussive injury vs. controls using TBSS, as FA is the most frequently examined diffusion tensor imaging metric. Authors of eligible studies were contacted to request unthresholded statistical map outputs from TBSS, and image-based meta-analyses were performed using Seed-Based d-Mapping. Eight studies contributed to our meta-analyses, comprising 174 SRC or subconcussive injury participants and 160 controls. Our primary meta-analysis (n = 8), encompassing subjects with acute SRC (n = 2), chronic SRC (n = 4) and subconcussive injuries (n = 2) revealed dominant bilateral increased FA in the superior longitudinal fasciculus (SLF) and internal capsule. Subconcussive injury was associated with small clusters of increased and decreased FA in the arcuate fasciculus compared to control. In acute SRC, we found diffuse foci of raised FA at WM/grey matter border-zone associated with the bilateral SLF and right inferior fronto-occipital fasciculus. In contrast, chronic SRC had a pattern of deep WM alteration, asymmetrically located in the right optic radiations and arcuate fasciculus. Our findings represent the most powerful analysis of TBSS data in SRC, supporting the use of this approach to analyse diffusion data. TBSS is sensitive to WM abnormalities resulting from SRC or subconcussive injury over a range of temporal and clinical scenarios. Our data show spatially concordant patterns of WM injury unique to subconcussive, acute and chronic phases, highlighting the future utility of diffusion MRI for concussion diagnosis.

Graph Theoretic Analysis of Brain Connectomics in Multiple Sclerosis: Reliability and Relationship with Cognition.

Research suggests that disruption of brain networks might explain cognitive deficits in multiple sclerosis (MS). The reliability and effectiveness of graph theoretic network metrics as measures of cognitive performance were tested in 37 people with MS and 23 controls. Specifically, relationships with cognitive performance (linear regression against the paced auditory serial addition test-3 seconds [PASAT-3], symbol digit modalities test [SDMT], and attention network test) and 1-month reliability (using the intraclass correlation coefficient [ICC]) of network metrics were measured using both resting-state functional and diffusion magnetic resonance imaging data. Cognitive impairment was directly related to measures of brain network segregation and inversely related to network integration (prediction of PASAT-3 by small worldness, modularity, characteristic path length, R2 = 0.55; prediction of SDMT by small worldness, global efficiency, and characteristic path length, R2 = 0.60). Reliability of the measures for 1 month in a subset of nine participants was mostly rated as good (ICC >0.6) for both controls and MS patients in both functional and diffusion data, but was highly dependent on the chosen parcellation and graph density, with the 0.2-0.5 density range being the most reliable. This suggests that disrupted network organization predicts cognitive impairment in MS and its measurement is reliable for a 1-month period. These new findings support the hypothesis of network disruption as a major determinant of cognitive deficits in MS and the future possibility of the application of derived metrics as surrogate outcomes in trials of therapies for cognitive impairment.