Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes.

Repetitive subconcussive head impacts (RSHI) are believed to induce sub-clinical brain injuries, potentially resulting in cumulative, long-term brain alterations. This study explores patterns of longitudinal brain white matter changes across sports with RSHI-exposure. A systematic literature search identified 22 datasets with longitudinal diffusion magnetic resonance imaging data. Four datasets were centrally pooled to perform uniform quality control and data preprocessing. A total of 131 non-concussed active athletes (American football, rugby, ice hockey; mean age: 20.06 ± 2.06 years) with baseline and post-season data were included. Nonparametric permutation inference (one-sample t tests, one-sided) was applied to analyze the difference maps of multiple diffusion parameters. The analyses revealed widespread lateralized patterns of sports-season-related increases and decreases in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) across spatially distinct white matter regions. Increases were shown across one MD-cluster (3195 voxels; mean change: 2.34%), one AD-cluster (5740 voxels; mean change: 1.75%), and three RD-clusters (817 total voxels; mean change: 3.11 to 4.70%). Decreases were shown across two MD-clusters (1637 total voxels; mean change: -1.43 to -1.48%), two RD-clusters (1240 total voxels; mean change: -1.92 to -1.93%), and one AD-cluster (724 voxels; mean change: -1.28%). The resulting pattern implies the presence of strain-induced injuries in central and brainstem regions, with comparatively milder physical exercise-induced effects across frontal and superior regions of the left hemisphere, which need further investigation. This article highlights key considerations that need to be addressed in future work to enhance our understanding of the nature of observed white matter changes, improve the comparability of findings across studies, and promote data pooling initiatives to allow more detailed investigations (e.g., exploring sex- and sport-specific effects).

Voxel-based diktiometry: Combining convolutional neural networks with voxel-based analysis and its application in diffusion tensor imaging for Parkinson's disease.

Extracting population-wise information from medical images, specifically in the neurological domain, is crucial to better understanding disease processes and progression. This is frequently done in a whole-brain voxel-wise manner, in which a population of patients and healthy controls are registered to a common co-ordinate space and a statistical test is performed on the distribution of image intensities for each location. Although this method has yielded a number of scientific insights, it is further from clinical applicability as the differences are often small and altogether do not permit for a high-performing classifier. In this article, we take the opposite approach of using a high-performing classifier, specifically a traditional convolutional neural network, and then extracting insights from it which can be applied in a population-wise manner, a method we call voxel-based diktiometry. We have applied this method to diffusion tensor imaging (DTI) analysis for Parkinson's disease (PD), using the Parkinson's Progression Markers Initiative database. By using the network sensitivity information, we can decompose what elements of the DTI contribute the most to the network's performance, drawing conclusions about diffusion biomarkers for PD that are based on metrics which are not readily expressed in the voxel-wise approach.

FDG PET in the differential diagnosis of degenerative parkinsonian disorders: usefulness of voxel-based analysis in clinical practice.

BACKGROUND: The early differential diagnosis among neurodegenerative parkinsonian disorders becomes essential to set up the correct clinical-therapeutic approach. The increased utilization of [18F] fluoro-deoxy-glucose positron emission tomography (FDG PET) and the pressure for cost-effectiveness request a systematic evaluation and a validation of its utility in clinical practice. This retrospective study aims to consider the contribution, in terms of increasing accuracy and increasing diagnostic confidence, of voxel-based FDG PET analyses in the differential diagnosis of these disorders, including Parkinson's disease, multiple system atrophy, progressive supranuclear palsy, and cortico-basal syndrome. METHOD: Eighty-three subjects with a clinically confirmed diagnosis of degenerative parkinsonian disorders who underwent FDG brain PET/CT were selected. A voxel-based analysis was set up using statistical parametric mapping (SPM) on MATLAB to produce maps of brain hypometabolism and relative hypermetabolism. Four nuclear physicians (two expert and two not expert), blinded to the patients' symptoms, other physicians' evaluations, and final clinical diagnosis, independently evaluated all data by visual assessment and by adopting metabolic maps. RESULTS: In not-expert evaluators, the support of both hypometabolism and hypermetabolism maps results in a significant increase in diagnostic accuracy as well as clinical confidence. In expert evaluators, the increase in accuracy and in diagnostic confidence is mainly supported by hypometabolism maps alone. CONCLUSIONS: In this study, we demonstrated the additional value of combining voxel-based analyses with qualitative assessment of brain PET images. Moreover, maps of relative hypermetabolism can also make their contribution in clinical practice, particularly for less experienced evaluators.

Voxel-Based quantitative MRI reveals spatial patterns of grey matter alteration in multiple sclerosis.

Despite robust postmortem evidence and potential clinical importance of gray matter (GM) pathology in multiple sclerosis (MS), assessing GM damage by conventional magnetic resonance imaging (MRI) remains challenging. This prospective cross-sectional study aimed at characterizing the topography of GM microstructural and volumetric alteration in MS using, in addition to brain atrophy measures, three quantitative MRI (qMRI) parameters-magnetization transfer (MT) saturation, longitudinal (R1), and effective transverse (R2*) relaxation rates, derived from data acquired during a single scanning session. Our study involved 35 MS patients (14 relapsing-remitting MS; 21 primary or secondary progressive MS) and 36 age-matched healthy controls (HC). The qMRI maps were computed and segmented in different tissue classes. Voxel-based quantification (VBQ) and voxel-based morphometry (VBM) statistical analyses were carried out using multiple linear regression models. In MS patients compared with HC, three configurations of GM microstructural/volumetric alterations were identified. (a) Co-localization of GM atrophy with significant reduction of MT, R1, and/or R2*, usually observed in primary cortices. (b) Microstructural modifications without significant GM loss: hippocampus and paralimbic cortices, showing reduced MT and/or R1 values without significant atrophy. (c) Atrophy without significant change in microstructure, identified in deep GM nuclei. In conclusion, this quantitative multiparametric voxel-based approach reveals three different spatially-segregated combinations of GM microstructural/volumetric alterations in MS that might be associated with different neuropathology.

Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease-related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel-based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel-based analysis (FBA) is a recent framework that offers tract-specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug-naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re-organization in the early stage.

Voxel-based analysis and multivariate pattern analysis of diffusion tensor imaging study in anti-NMDA receptor encephalitis.

PURPOSE: This study aimed to investigate brain white matter (WM) changes and their relationship to cognition in patients with anti-N-methyl-D-aspartate (anti-NMDA) receptor encephalitis. Multivariate pattern analysis (MVPA) was used to explore brain regions that play an important role in classification. METHODS: Fifteen patients and fifteen controls underwent Montreal Cognitive Assessment (MoCA) and diffusion tensor imaging. Based on fractional anisotropy (FA) and mean diffusivity (MD) for MVPA classification, the weights of each brain region were calculated. RESULTS: Compared with the controls, the patients showed an FA reduction in right middle temporal gyrus, left middle cerebellar peduncle, right praecuneus, and an MD increase in left medial temporal gyrus and left frontal lobe. The MoCA score for patients was lower than controls, especially in executive function, fluency, delayed recall and visual perception items. The FA value of right praecuneus was positively correlated with total MoCA score and fluency score. The MD of left frontal lobe was negatively correlated with total MoCA score, and MD of the left medial temporal gyrus was positively correlated with delayed recall. The accuracy, sensitivity and specificity of classification based on FA were 70%, 60% and 80%, respectively. Based on MD, they were each 80%. The brain regions with large weights from FA and MD overlap in temporal lobe, cerebellum and hippocampus. CONCLUSIONS: These results suggest that WM changes are associated with cognitive deficits. MVPA based on FA and MD has good classification ability. Our study may provide new insights into the pathophysiological mechanisms of residual cognitive deficits.

Application of super-resolution track-density technique: Earlier detection of aging-related subtle alterations than morphological changes in corpus callosum from normal population?

BACKGROUND: There are rare quantitative fiber density measurement techniques based on voxel measure changes of each corpus callosum (CC) subsegment with age. PURPOSE: To observe the regularity of corpus callosum development in normal aging from subvoxel to macroscopic volume. STUDY TYPE: Retrospective. SUBJECTS: In all, 131 healthy volunteers divided into six age groups. FIELD STRENGTH/SEQUENCE: 3T MR with 32-channel head coil T1 -3D and diffusion-weighted imaging with six b-values in a 30 directions sequence. ASSESSMENT: Track-density imaging (TDI) was used to visualize the complexity and the differences occurring in corpus callosum (CC) with age. TDI were reconstructed with a higher spatial voxel resolution of 0.1 mm subvoxel; TDI values are recognized as a subvoxel metric of real tract density. We reconstructed track density maps by using probabilistic streamline tractography combined with constrained spherical deconvolution. The CC was segmented into five subregions, and TDI, volume, and fractional anisotropy (FA) of each subregion in all the groups were measured using T1 W-3D images and compared. STATISTICAL TEST: Polynomial regression was done to between age and (CC1, CC2, CC3, CC4, CC5) of TDI/volume/FA. Multiple comparisons test two-way analysis of variance (ANOVA) were used to compare the differences between different age groups and sex groups in each subregion. Fisher's least significant difference test was used for the correction of the multiple comparisons. RESULTS: From the 20-70 age groups, TDI values of CC2, CC3, and CC4 increased until 40 years, when they were highest, and then decreased. CC2 (7.35556, 7.56587, 8.06036, 7.53841, 6.6956, 6.56494), CC3 (7.75372, 8.41447, 9.13178, 8.72605, 7.50106, 5.69513), CC4 (8.63414, 9.1518, 9.22451, 9.03154, 8.11556, 7.1967). There was a significant difference in the CC3 TDI between the 50/60 years groups and the 60/70 years groups (P = 0.03853 and 0.00285, respectively). The volumes of CC2, CC3, and CC4 increased between 30 and 50 years and decreased between 50 and 60 years, CC2 (0.06557, 0.07244, 0.08062, 0.07353, 0.08576, 0.06294), CC3 (0.03421, 0.03867, 0.03891, 0.03916, 0.03058, 0.03658), CC4 (0.0242, 0.01948, 0.02445, 0.02887, 0.01938, 0.01956). FA of CC2, CC3, and CC4 decreased between years 40 and 60.CC2 (0.45981, 0.47392, 0.45654, 0.45702, 0.39982, 0.35767), CC3 (0.4628, 0.49056, 0.49701, 0.46667, 0.44795, 0.36799), CC4 (0.46599, 0.52887, 0.4971, 0.53257, 0.42861, 0.43158). DATA CONCLUSION: TDI had high sensitivity for the detection of age-related CC differences. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:164-175.

Microstructural brain abnormalities correlate with neurocognitive dysfunction in minimal hepatic encephalopathy: a diffusion kurtosis imaging study.

PURPOSE: To investigate the diffusion kurtosis imaging (DKI) in early minimal hepatic encephalopathy (MHE) diagnosis and evaluate the correlations between changes in DKI metrics and cognitive performance. METHODS: We enrolled 116 cirrhosis patients, divided into non-HE (n = 61) and MHE (n = 55), and 46 normal controls (NCs). All patients underwent cognitive testing before magnetic resonance imaging. DKI metrics were calculated through whole-brain voxel-based analysis (VBA) and differences between the groups were assessed. Pearson correlation between the DKI metrics and cognitive performance was analysed. The receiver operating characteristic (ROC) curve was used to analyse the diagnostic efficiency of DKI metrics for MHE. RESULTS: MHE patients had significantly altered DKI metrics in a wide range of regions; lower fractional anisotropy (FA) and higher mean diffusivity (MD) are mainly located in the corpus callosum, left temporal white matter (WM), and right medial frontal WM. Furthermore, significantly altered kurtosis metrics included lower mean kurtosis (MK) in the corpus callosum and left thalamus, lower radial kurtosis (RK) in the corpus callosum, and lower axial kurtosis (AK) in the right anterior thalamic radiation. Alterations in axial diffusivity (AD), radial diffusivity (RD), and MD were closely correlated with cognitive scores. The ROC curves indicated AD in the forceps minor had the highest predictive performance for MHE in the cirrhosis patients (area under curve = 0.801, sensitivity = 77.05%, specificity = 74.55%). CONCLUSIONS: Altered DKI metrics indicate brain microstructure abnormalities in MHE patients, some of which may be used as neuroimaging markers for early MHE diagnosis.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging.

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78µm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40µm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling neuroplastic events that characterize the critical period for vocal learning in zebra finch ontogeny.

A Comparative evaluation of voxel-based spatial mapping in diffusion tensor imaging.

This paper presents a comparative evaluation of methods for automated voxel-based spatial mapping in diffusion tensor imaging studies. Such methods are an essential step in computational pipelines and provide anatomically comparable measurements across a population in atlas-based studies. To better understand their strengths and weaknesses, we tested a total of eight methods for voxel-based spatial mapping in two types of diffusion tensor templates. The methods were evaluated with respect to scan-rescan reliability and an application to normal aging. The methods included voxel-based analysis with and without smoothing, two types of region-based analysis, and combinations thereof with skeletonization. The templates included a study-specific template created with DTI-TK and the IIT template serving as a standard template. To control for other factors in the pipeline, the experiments used a common dataset, acquired at 1.5T with a single shell high angular resolution diffusion MR imaging protocol, and tensor-based spatial normalization with DTI-TK. Scan-rescan reliability was assessed using the coefficient of variation (CV) and intraclass correlation (ICC) in eight subjects with three scans each. Sensitivity to normal aging was assessed in a population of 80 subjects aged 25-65 years old, and methods were compared with respect to the anatomical agreement of significant findings and the R2 of the associated models of fractional anisotropy. The results show that reliability depended greatly on the method used for spatial mapping. The largest differences in reliability were found when adding smoothing and comparing voxel-based and region-based analyses. Skeletonization and template type were found to have either a small or negligible effect on reliability. The aging results showed agreement among the methods in nine brain areas, with some methods showing more sensitivity than others. Skeletonization and smoothing were not major factors affecting sensitivity to aging, but the standard template showed higher R2 in several conditions. A structural comparison of the templates showed that large deformations between them may be related to observed differences in patterns of significant voxels. Most areas showed significantly higher R2 with voxel-based analysis, particularly when clusters were smaller than the available regions-of-interest. Looking forward, these results can potentially help to interpret results from existing white matter imaging studies, as well as provide a resource to help in planning future studies to maximize reliability and sensitivity with regard to the scientific goals at hand.

Comparison of two different analysis approaches for DTI free-water corrected and uncorrected maps in the study of white matter microstructural integrity in individuals with depression.

Diffusion tensor imaging (DTI) has often been used to examine white matter (WM) tract abnormalities in depressed subjects, but these studies have yielded inconsistent results, probably, due to gender composition or small sample size. In this study, we applied different analysis pipelines to a relatively large sample of individuals with depression to determine whether previous findings in depression can be replicated with these pipelines. We used a "standard" DTI algorithm and maps computed through a free-water (FW) corrected DTI. This latter algorithm is able to identify and separate the effects of extracellular FW on DTI metrics. Additionally, skeletonized and WM voxel-based analysis (VBA) methods were used. Using the skeletonized method, DTI maps showed lower fractional anisotropy (FA) in depressed subjects in the left brain hemisphere, including the anterior thalamic radiation (ATR L), cortical spinal tract (CST L), inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF L). Differences in radial diffusivity (RD) were also found. For the VBA using RD, we found different results when we used FW uncorrected and corrected DTI metrics. Relative to the VBA approach, the skeletonized analysis was able to identify more clusters where WM integrity was altered in depressed individuals. Different significant correlations were found between RD and the Patient Health Questionnaire in the CST L, and SLF L. In conclusion, the skeletonized method revealed more clusters than the VBA and individuals with depression showed multiple WM abnormalities, some of which were correlated with disease severity Hum Brain Mapp 38:4690-4702, 2017. © 2017 Wiley Periodicals, Inc.

User-independent diffusion tensor imaging analysis pipelines in a rat model presenting ventriculomegalia: A comparison study.

Automated analysis of diffusion tensor imaging (DTI) data is an appealing way to process large datasets in an unbiased manner. However, automation can sometimes be linked to a lack of interpretability. Two whole-brain, automated and voxelwise methods exist: voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). In VBA, the amount of smoothing has been shown to influence the results. TBSS is free of this step, but a projection procedure is introduced to correct for residual misalignments. This projection assigns the local highest fractional anisotropy (FA) value to the mean FA skeleton, which represents white matter tract centers. For both methods, the normalization procedure has a major impact. These issues are well documented in humans but, to our knowledge, not in rodents. In this study, we assessed the quality of three different registration algorithms (ANTs SyN, DTI-TK and FNIRT) using study-specific templates and their impact on automated analysis methods (VBA and TBSS) in a rat pup model of diffuse white matter injury presenting large unilateral deformations. VBA and TBSS results were stable and anatomically coherent across the three pipelines. For VBA, in regions around the large deformations, interpretability was limited because of the increased partial volume effect. With TBSS, two of the three pipelines found a significant decrease in axial diffusivity (AD) at the known injury site. These results demonstrate that automated voxelwise analyses can be used in an animal model with large deformations.

Methods for the computation of templates from quantitative magnetic susceptibility maps (QSM): Toward improved atlas- and voxel-based analyses (VBA).

PURPOSE: To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM). MATERIALS AND METHODS: We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1 -weighted (T1 w) images. One method that used only T1 w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1 w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model. RESULTS: The overall quality of the templates was better for strategies including both susceptibility and T1 w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1 w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05). CONCLUSION: Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1 w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1 w images (CONV) results in reduced image quality compared to all other approaches studied. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.

Brain Microstructural Abnormalities in Patients With Cirrhosis Without Overt Hepatic Encephalopathy: A Voxel-Based Diffusion Kurtosis Imaging Study.

OBJECTIVE: This study aimed to investigate whole-brain microstructural abnormalities and their correlation with cognitive impairment in patients with cirrhosis using diffusion kurtosis imaging (DKI). SUBJECTS AND METHODS: Eighteen patients with cirrhosis and 17 healthy control subjects underwent DKI. Cognition was measured using psychometric hepatic encephalopathy (HE) scores. Whole-brain voxel-based analyses were performed to investigate between-group differences in DKI-derived parameters, including mean kurtosis, axial kurtosis, and radial kurtosis. RESULTS: Compared with control subjects, the patients with cirrhosis had lower psychometric HE scores, indicating cognitive impairments. The patients with cirrhosis had significantly lower global mean kurtosis, axial kurtosis, and radial kurtosis in gray matter (GM) and white matter (WM). Voxel-based analyses showed that patients with cirrhosis had decreased mean kurtosis, axial kurtosis, and radial kurtosis in diffuse GM regions (particularly in the cingulate cortex, precuneus, insular cortex, frontal areas, basal ganglia, hippocampus and parahippocampal gyrus, supramarginal gyrus and angular gyrus, postcentral and precentral gyrus, and cerebellum) and WM regions (particularly in the corpus callosum, internal capsule, frontal regions, parietal regions, occipital regions, and cerebellum). The DKI metrics were positively correlated with psychometric HE score among patients. CONCLUSION: Lower DKI parameters suggest decreased brain microstructural complexity in patients with cirrhosis, which may contribute to the neurobiologic basis of cognitive impairment.

STEAM - Statistical Template Estimation for Abnormality Mapping: A personalized DTI analysis technique with applications to the screening of preterm infants.

We introduce the STEAM DTI analysis engine: a whole brain voxel-based analysis technique for the examination of diffusion tensor images (DTIs). Our STEAM analysis technique consists of two parts. First, we introduce a collection of statistical templates that represent the distribution of DTIs for a normative population. These templates include various diffusion measures from the full tensor, to fractional anisotropy, to 12 other tensor features. Second, we propose a voxel-based analysis (VBA) pipeline that is reliable enough to identify areas in individual DTI scans that differ significantly from the normative group represented in the STEAM statistical templates. We identify and justify choices in the VBA pipeline relating to multiple comparison correction, image smoothing, and dealing with non-normally distributed data. Finally, we provide a proof of concept for the utility of STEAM on a cohort of 134 very preterm infants. We generated templates from scans of 55 very preterm infants whose T1 MRI scans show no abnormalities and who have normal neurodevelopmental outcome. The remaining 79 infants were then compared to the templates using our VBA technique. We show: (a) that our statistical templates display the white matter development expected over the modeled time period, and (b) that our VBA results detect abnormalities in the diffusion measurements that relate significantly with both the presence of white matter lesions and with neurodevelopmental outcomes at 18months. Most notably, we show that STEAM produces personalized results while also being able to highlight abnormalities across the whole brain and at the scale of individual voxels. While we show the value of STEAM on DTI scans from a preterm infant cohort, STEAM can be equally applied to other cohorts as well. To facilitate this whole-brain personalized DTI analysis, we made STEAM publicly available at http://www.sfu.ca/bgb2/steam.

Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping.

A biological parameter that would be valuable to be able to extract from diffusion MRI data is the local white matter axonal density. Track-density imaging (TDI) has been used as if it could provide such a measure; however, this has been the subject of controversy, primarily due to the fact that track-count quantitation is highly sensitive to tracking biases and errors. The spherical-deconvolution informed filtering of tractograms (SIFT) post-processing method was recently introduced to minimise tractography biases, and thus provides a more biologically meaningful measure that could be used in track-count mapping (i.e. TDI following SIFT). The TDI intensity following SIFT ideally corresponds to the orientational average of the fibre orientation distribution (FOD), which corresponds to the total Apparent Fibre Density (AFDtotal) within the AFD framework; in fact, AFDtotal provides a direct measure of local fibre density at native resolution that does not rely on fibre-tracking. In this study, we demonstrate problems associated with quantitative TDI investigations, which can be avoided by using SIFT processing or directly by using AFDtotal maps. We also characterise the intra- and inter-subject reproducibility of TDI maps (with and without SIFT pre-processing) and AFDtotal maps. It is shown that SIFT improves the quantitative characteristics of TDI, but is still vastly inferior to the properties of the AFDtotal parameter itself, because the latter does not require tracking. While standard TDI might be preferable in applications when high anatomical contrast is required, particularly when combined with super-resolution, for voxel-wise quantitation of total tract density (i.e. without tract orientation information) at native resolution, the total AFD maps are preferable to TDI or other related track-count maps. Regardless of the track-count measure, it should be noted that all of these voxel-averaged approaches discard important information that is retained in fibre-specific approaches such as AFD.

Cerebral maturation in the early preterm period-A magnetization transfer and diffusion tensor imaging study using voxel-based analysis.

The magnetization transfer ratio (MTR) and diffusion tensor imaging (DTI) correlates of early brain development were examined in cohort of 18 very preterm neonates (27-31 gestational weeks) presenting with normal radiological findings scanned within 2weeks after birth (28-32 gestational weeks). A combination of non-linear image registration, tissue segmentation, and voxel-wise regression was used to map the age dependent changes in MTR and DTI-derived parameters in 3D across the brain based on the cross-sectional in vivo preterm data. The regression coefficient maps obtained differed between brain regions and between the different quantitative MRI indices. Significant linear increases as well as decreases in MTR and DTI-derived parameters were observed throughout the preterm brain. In particular, the lamination pattern in the cerebral wall was evident on parametric and regression coefficient maps. The frontal white matter area (subplate and intermediate zone) demonstrated a linear decrease in MTR. While the intermediate zone showed an unexpected decrease in fractional anisotropy (FA) with age, with this decrease (and the increase in mean diffusivity (MD)) driven primarily by an increase in radial diffusivity (RD) values, the subplate showed no change in FA (and an increase in MD). The latter was the result of a concomitant similar increase in axial diffusivity (AD) and RD values. Interpreting the in vivo results in terms of available histological data, we present a biophysical model that describes the relation between various microstructural changes measured by complementary quantitative methods available on clinical scanners and a range of maturational processes in brain tissue.

Microstructural brain abnormalities of children of idiopathic generalized epilepsy with generalized tonic-clonic seizure: a voxel-based diffusional kurtosis imaging study.

PURPOSE: To investigate the diffusion abnormalities in the brain of children with idiopathic generalized epilepsy (IGE) with generalized tonic-clonic seizure (GTCS) by using diffusion kurtosis imaging (DKI). MATERIALS AND METHODS: Twenty-one IGE children with GTCS and 16 controls were recruited. DKI was performed and maps of radial diffusivity (λ⊥ ), axial diffusivity (λ// ), mean diffusivity (MD), fractional anisotropy (FA), radial kurtosis (K⊥ ), axial kurtosis (K// ) and mean kurtosis (MK) were calculated. Voxel-based analyses were employed to compare diffusion metrics in epilepsy versus the controls. RESULTS: In the case group, MD was found significantly higher in the right temporal lobe, the right occipital lobe, hippocampus, and some subcortical regions, while FA increased in bilateral supplementary motor area and the left superior frontal lobe (false discovery rate corrected P < 0.05). Analysis of λ⊥ and λ// showed that the increased MD was mainly due to the elevated λ// . Significantly decreased MK was also detected in bilateral temporo-occipital regions, the right hippocampus, the left insula, the left post-central area, and some subcortical regions (false discovery rate corrected P < 0.05). In most regions the changed MK were due to the decreased K// . CONCLUSION: The kurtosis parameters (K⊥ , K// , and MK) reflect different microstructural information in the IGE children with GTCS, and this support the value of DKI in studying children GTCS.

Regional patterns of grey matter atrophy and magnetisation transfer ratio abnormalities in multiple sclerosis clinical subgroups: a voxel-based analysis study.

BACKGROUND: In multiple sclerosis (MS), demyelination and neuro-axonal loss occur in the brain grey matter (GM). We used magnetic resonance imaging (MRI) measures of GM magnetisation transfer ratio (MTR) and volume to assess the regional localisation of reduced MTR (reflecting demyelination) and atrophy (reflecting neuro-axonal loss) in relapsing-remitting MS (RRMS), secondary progressive MS (SPMS) and primary progressive MS (PPMS). METHODS: A total of 98 people with MS (51 RRMS, 28 SPMS, 19 PPMS) and 29 controls had T1-weighted volumetric and magnetisation transfer scans. SPM8 was used to undertake voxel-based analysis (VBA) of GM tissue volumes and MTR. MS subgroups were compared with controls, adjusting for age and gender. A voxel-by-voxel basis correlation analysis between MTR and volume within each subject group was performed, using biological parametric mapping. RESULTS: MTR reduction was more extensive than atrophy. RRMS and SPMS patients showed proportionately more atrophy in the deep GM. SPMS and PPMS patients showed proportionately greater cortical MTR reduction. RRMS patients demonstrated the most correlation of MTR reduction and atrophy in deep GM. In SPMS and PPMS patients, there was less extensive correlation. CONCLUSIONS: These results suggest that in the deep GM of RRMS patients, demyelination and neuro-axonal loss may be linked, while in SPMS and PPMS patients, neuro-axonal loss and demyelination may occur mostly independently.

Improved DTI registration allows voxel-based analysis that outperforms tract-based spatial statistics.

Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter "skeleton" is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology.