Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke

Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data

Purpose

The study aimed to (1) assess the feasibility constrained spherical deconvolution (CSD) tractography to reconstruct crossing fiber bundles with unsedated neonatal diffusion MRI (dMRI), and (2) demonstrate the impact of spatial and angular resolution and processing settings on tractography and derived quantitative measures.

Methods

For the purpose of this study, the term-equivalent dMRIs (single-shell b800, and b2000, both 5 b0, and 45 gradient directions) of two moderate-late preterm infants (with and without motion artifacts) from a local cohort [Brain Imaging in Moderate-late Preterm infants (BIMP) study; Calgary, Canada] and one infant from the developing human connectome project with high-quality dMRI (using the b2600 shell, comprising 20 b0 and 128 gradient directions, from the multi-shell dataset) were selected. Diffusion tensor imaging (DTI) and CSD tractography were compared on b800 and b2000 dMRI. Varying image resolution modifications, (pre-)processing and tractography settings were tested to assess their impact on tractography. Each experiment involved visualizing local modeling and tractography for the corpus callosum and corticospinal tracts, and assessment of morphological and diffusion measures.

Results

Contrary to DTI, CSD enabled reconstruction of crossing fibers. Tractography was susceptible to image resolution, (pre-) processing and tractography settings. In addition to visual variations, settings were found to affect streamline count, length, and diffusion measures (fractional anisotropy and mean diffusivity). Diffusion measures exhibited variations of up to 23%.

Conclusion

Reconstruction of crossing fiber bundles using CSD tractography with unsedated neonatal dMRI data is feasible. Tractography settings affected streamline reconstruction, warranting careful documentation of methods for reproducibility and comparison of cohorts.

FlexDTI: flexible diffusion gradient encoding scheme-based highly efficient diffusion tensor imaging using deep learning

Objective. Most deep neural network-based diffusion tensor imaging methods require the diffusion gradients' number and directions in the data to be reconstructed to match those in the training data. This work aims to develop and evaluate a novel dynamic-convolution-based method called FlexDTI for highly efficient diffusion tensor reconstruction with flexible diffusion encoding gradient scheme.Approach. FlexDTI was developed to achieve high-quality DTI parametric mapping with flexible number and directions of diffusion encoding gradients. The method used dynamic convolution kernels to embed diffusion gradient direction information into feature maps of the corresponding diffusion signal. Furthermore, it realized the generalization of a flexible number of diffusion gradient directions by setting the maximum number of input channels of the network. The network was trained and tested using datasets from the Human Connectome Project and local hospitals. Results from FlexDTI and other advanced tensor parameter estimation methods were compared.Main results. Compared to other methods, FlexDTI successfully achieves high-quality diffusion tensor-derived parameters even if the number and directions of diffusion encoding gradients change. It reduces normalized root mean squared error by about 50% on fractional anisotropy and 15% on mean diffusivity, compared with the state-of-the-art deep learning method with flexible diffusion encoding gradient scheme.Significance. FlexDTI can well learn diffusion gradient direction information to achieve generalized DTI reconstruction with flexible diffusion gradient scheme. Both flexibility and reconstruction quality can be taken into account in this network.

White adipose tissue distribution and amount are associated with increased white matter connectivity

Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a deeper characterization of body composition is required, especially considering the links between abdominal obesity and metabolic dysfunction. This study aims to enhance our understanding of the relationship between obesity and WM connectivity by directly assessing the amount and distribution of fat tissue. Whole-body magnetic resonance imaging (MRI) was employed to evaluate total adipose tissue (TAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT), while MR liver spectroscopy measured liver fat content in 63 normal-weight, overweight, and obese males. WM connectivity was quantified using microstructure-informed tractography. Connectome-based predictive modeling was used to predict body composition metrics based on WM connectomes. Our analysis revealed a positive dependency between BMI, TAT, SAT, and WM connectivity in brain regions involved in reward processing and appetite regulation, such as the insula, nucleus accumbens, and orbitofrontal cortex. Increased connectivity was also observed in cognitive control and inhibition networks, including the middle frontal gyrus and anterior cingulate cortex. No significant associations were found between WM connectivity and VAT or liver fat. Our findings suggest that altered neural communication between these brain regions may affect cognitive processes, emotional regulation, and reward perception in individuals with obesity, potentially contributing to weight gain. While our study did not identify a link between WM connectivity and VAT or liver fat, further investigation of the role of various fat depots and metabolic factors in brain networks is required to advance obesity prevention and treatment approaches.

High-angular resolution diffusion imaging generation using 3d u-net

PURPOSE

To investigate the effects on tractography of artificial intelligence-based prediction of motion-probing gradients (MPGs) in diffusion-weighted imaging (DWI).

METHODS

The 251 participants in this study were patients with brain tumors or epileptic seizures who underwent MRI to depict tractography. DWI was performed with 64 MPG directions and b = 0 s/mm2 images. The dataset was divided into a training set of 191 (mean age 45.7 [± 19.1] years), a validation set of 30 (mean age 41.6 [± 19.1] years), and a test set of 30 (mean age 49.6 [± 18.3] years) patients. Supervised training of a convolutional neural network was performed using b = 0 images and the first 32 axes of MPG images as the input data and the second 32 axes as the reference data. The trained model was applied to the test data, and tractography was performed using (a) input data only; (b) input plus prediction data; and (c) b = 0 images and the 64 MPG data (as a reference).

RESULTS

In Q-ball imaging tractography, the average dice similarity coefficient (DSC) of the input plus prediction data was 0.715 (± 0.064), which was significantly higher than that of the input data alone (0.697 [± 0.070]) (p < 0.05). In generalized q-sampling imaging tractography, the average DSC of the input plus prediction data was 0.769 (± 0.091), which was also significantly higher than that of the input data alone (0.738 [± 0.118]) (p < 0.01).

CONCLUSION

Diffusion tractography is improved by adding predicted MPG images generated by an artificial intelligence model.

Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning

PURPOSE

The rising promise in the utility of advanced multi-parametric magnetic resonance (MR) imaging in radiotherapy (RT) treatment planning creates a necessity for testing and enhancing the accuracy of quantitative imaging analysis. Standardizing the analysis of diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) to generate meaningful and reproducible apparent diffusion coefficient (ADC) and fractional anisotropy (FA) lays the requisite needed for clinical integration. The aim of the demonstrated work is to benchmark the generation of the ADC and FA parametric map analyses using integrated tools in a commercial treatment planning system against the currently used ones.

METHODS

Three software packages were used for generating ADC and FA maps in this study; one tool was developed within a commercial treatment planning system, another by the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library FSL (Analysis Group, FMRIB, Oxford, United Kingdom), and an in-house tool developed at the M.D. Anderson Cancer Center. The ADC and FA maps generated by all three packages for 35 subjects were subtracted from one another, and the standard deviation of the images' differences was used to compare the reproducibility. The reproducibility of the ADC maps was compared with the Quantitative Imaging Biomarkers Alliance (QIBA) protocol, while that of the FA maps was compared to data in published literature.

RESULTS

Results show that the discrepancies between the ADC maps calculated for each patient using the three different software algorithms are less than 2% which meets the 3.6% recommended QIBA requirement. Except for a small number of isolated points, the majority of differences in FA maps for each patient produced by the three methods did not exceed 0.02 which is 10 times lower than the differences seen in healthy gray and white matter. The results were also compared to the maps generated by existing MR Imaging consoles and showed that the robustness of console generated ADC and FA maps is largely dependent on the correct application of scaling factors, that only if correctly placed; the differences between the three tested methods and the console generated values were within the recommended QIBA guidelines.

CONCLUSIONS

Cross-comparison difference maps demonstrated that quantitative reproducibility of ADC and FA metrics generated using our tested commercial treatment planning system were comparable to in-house and established tools as benchmarks. This integrated approach facilitates the clinical utility of diffusion imaging in radiation treatment planning workflow.

Abnormal wiring of the structural connectome in adults with ADHD

Current knowledge of white matter changes in large-scale brain networks in adult attention-deficit/hyperactivity disorder (ADHD) is scarce. We collected diffusion-weighted magnetic resonance imaging data in 40 adults with ADHD and 36 neurotypical controls and used constrained spherical deconvolution-based tractography to reconstruct whole-brain structural connectivity networks. We used network-based statistic (NBS) and graph theoretical analysis to investigate differences in these networks between the ADHD and control groups, as well as associations between structural connectivity and ADHD symptoms assessed with the Adult ADHD Self-Report Scale or performance in the Conners Continuous Performance Test 2 (CPT-2). NBS revealed decreased connectivity in the ADHD group compared to the neurotypical controls in widespread unilateral networks, which included subcortical and corticocortical structures and encompassed dorsal and ventral attention networks and visual and somatomotor systems. Furthermore, hypoconnectivity in a predominantly left-frontal network was associated with higher amount of commission errors in CPT-2. Graph theoretical analysis did not reveal topological differences between the groups or associations between topological properties and ADHD symptoms or task performance. Our results suggest that abnormal structural wiring of the brain in adult ADHD is manifested as widespread intrahemispheric hypoconnectivity in networks previously associated with ADHD in functional neuroimaging studies.

Characterization and Classification of Spatial White Matter Tract Alteration Patterns in Glioma Patients Using Magnetic Resonance Tractography: A Systematic Review and Meta-Analysis

INTRODUCTION

Magnetic resonance (MR) tractography can be used to study the spatial relations between gliomas and white matter (WM) tracts. Various spatial patterns of WM tract alterations have been described in the literature. We reviewed classification systems of these patterns, and investigated whether low-grade gliomas (LGGs) and high-grade gliomas (HGGs) demonstrate distinct spatial WM tract alteration patterns.

METHODS

We conducted a systematic review and meta-analysis to summarize the evidence regarding MR tractography studies that investigated spatial WM tract alteration patterns in glioma patients.

RESULTS

Eleven studies were included. Overall, four spatial WM tract alteration patterns were reported in the current literature: displacement, infiltration, disruption/destruction and edematous. There was a considerable heterogeneity in the operational definitions of these terms. In a subset of studies, sufficient homogeneity in the classification systems was found to analyze pooled results for the displacement and infiltration patterns. Our meta-analyses suggested that LGGs displaced WM tracts significantly more often than HGGs (n = 259 patients, RR: 1.79, 95% CI [1.14, 2.79], I² = 51%). No significant differences between LGGs and HGGs were found for WM tract infiltration (n = 196 patients, RR: 1.19, 95% CI [0.95, 1.50], I² = 4%).

CONCLUSIONS

The low number of included studies and their considerable methodological heterogeneity emphasize the need for a more uniform classification system to study spatial WM tract alteration patterns using MR tractography. This review provides a first step towards such a classification system, by showing that the current literature is inconclusive and that the ability of fractional anisotropy (FA) to define spatial WM tract alteration patterns should be critically evaluated. We found variations in spatial WM tract alteration patterns between LGGs and HGGs, when specifically examining displacement and infiltration in a subset of the included studies.

Symptom-circuit mappings of the schizophrenia connectome

OBJECTIVE

This paper aims to model the anatomical circuits underlying schizophrenia symptoms, and to explore patterns of abnormal connectivity among brain networks affected by psychopathology.

METHODS

T1 magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), and resting-state functional MRI (rsfMRI) were obtained from a total of 126 patients with schizophrenia who were recruited for the study. The images were processed using the Omniscient software (https://www.o8t. com). We further apply the use of the Hollow-tree Super (HoTS) method to gain insights into what brain regions had abnormal connectivity that might be linked to the symptoms of schizophrenia.

RESULTS

The Positive and Negative Symptom Scale is characterised into 6 factors. Each symptom is mapped with specific anatomical abnormalities and circuits. Comparison between factors reveals co-occurrence in parcels in Factor 1 and Factor 2. Multiple large-scale networks are involved in SCZ symptomatology, with functional connectivity within Default Mode Network (DMN) and Central Executive Network (CEN) regions most frequently associated with measures of psychopathology.

CONCLUSION

We present a summary of the relevant anatomy for regions of the cortical areas as part of a larger effort to understand its contribution in schizophrenia. This unique machine learning-type approach maps symptoms to specific brain regions and circuits by bridging the diagnostic subtypes and analysing the features of the connectome.

A comparison of diffusion tensor imaging tractography and constrained spherical deconvolution with automatic segmentation in traumatic brain injury

Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.

Deep brain stimulation of the dentato-rubro-thalamic tract in a case of Holmes tremor: a constrained spherical deconvolution (CSD)-guided procedure

Deep brain stimulation (DBS) is an established treatment for movement disorders, including Holmes tremor (HT). HT is a rest and action tremor that occurs as a late symptom of brainstem lesions such as stroke. Unfortunately, it is frequently refractory to medical treatment, hence DBS surgery may be a good option. Due to variable results, the ideal target for DBS in HT still remains to be established, ranging from the thalamus to the globus pallidus internus, to the subthalamic nucleus. Pre-operative imaging also is very challenging, as the complexity of brain fiber architecture may prevent the correct positioning of the directional lead. Herein, we describe the case of a patient affected by a rubral tremor secondary to a brain hemorrhage, who had advanced pre-operative neuroimaging with constrained spherical deconvolution (CSD)-based tractography obtained from diffusion-weighted imaging (DWI) to identify the dentato-rubro-thalamic tract, involved in the pathophysiology of HT. The patient was then addressed to an awake DBS surgery, and with the help of intraoperative microelectrode recordings, a tailored DRTT-targeted procedure was performed. The stimulation determined an almost complete tremor suppression, with no significant side effects at a follow-up of 6 months, paving the way towards new effective techniques for the planning, i.e., CSD-based tractography and the treatment of refractory tremors.

Constrained spherical deconvolution -based tractography of major language tracts reveals post-stroke bilateral white matter changes correlated to aphasia

PURPOSE

Using constrained spherical deconvolution (CSD)-based tractography, we aimed to obtain conjoint analysis of diffusion measures of major language white matter (WM) tracts in post-stroke aphasic patients bilaterally, and to correlate the measures of each tract to the different language deficits.

MATERIAL AND METHODS

17 aphasic patients with left hemispheric stroke, at the subacute stage, and ten age- matched controls underwent diffusion MRI examination. CSD-based tractography was performed. Diffusion measures [fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD)] were extracted after dissection of major language tracts bilaterally. Aphasia was assessed using language subset of hemispheric stroke scale. Comparisons of diffusion measures, for all tracts, between the two groups were performed. Partial correlations between the diffusion measures and different language components were obtained.

RESULTS

In the left hemisphere, significant lower FA and or higher MD with higher RD of patients' WM tracts compared to the control group. Significant differences of diffusion measures were also evident in the right hemisphere yet, less prominent. All changes reflected damage of the tracts' integrity. Significant correlations were found between comprehension and FA of the left arcuate fasciculus (AF) and left inferior longitudinal fasciculus. Additionally, a significant correlation was found between MD of the right AF and repetition.

CONCLUSION

Conjoint analysis of diffusion measures, based on CSD tractography, can provide important markers for the underlying WM changes bilaterally. Moreover, our findings emphasize that language processing can be mediated by both ventral and dorsal streams and further highlight the contribution of the right AF in repetition.

Integration of structural brain networks is related to openness to experience: A diffusion MRI study with CSD-based tractography

Openness to experience is one of the big five traits of personality which recently has been the subject of several studies in neuroscience due to its importance in understanding various cognitive functions. However, the neural basis of openness to experience is still unclear. Previous studies have found largely heterogeneous results, suggesting that various brain regions may be involved in openness to experience. Here we suggested that performing structural connectome analysis may shed light on the neural underpinnings of openness to experience as it provides a more comprehensive look at the brain regions that are involved in this trait. Hence, we investigated the involvement of brain network structural features in openness to experience which has not yet been explored to date. The magnetic resonance imaging (MRI) data along with the openness to experience trait score from the self-reported NEO Five-Factor Inventory of 100 healthy subjects were evaluated from Human Connectome Project (HCP). CSD-based whole-brain probabilistic tractography was performed using diffusion-weighted images as well as segmented T1-weighted images to create an adjacency matrix for each subject. Using graph theoretical analysis, we computed global efficiency (GE) and clustering coefficient (CC) which are measures of two important aspects of network organization in the brain: functional integration and functional segregation respectively. Results revealed a significant negative correlation between GE and openness to experience which means that the higher capacity of the brain in combining information from different regions may be related to lower openness to experience.

Improving delineation of the corticospinal tract in the monkey brain scanned with conventional DTI by using a compressed sensing based algorithm

Background

The corticospinal tract (CST) is a major tract for motor function. It can be impaired by stroke. Its degeneration is associated with stroke outcome. Diffusion tensor imaging (DTI) tractography plays an important role in assessing fiber bundle integrity. However, it is limited in detecting crossing fibers in the brain. The crossing fiber angular resolution of intra-voxel structure (CFARI) algorithm shows potential to resolve complex fibers in the brain. The objective of the present study was to improve delineation of CST pathways in monkey brains scanned by conventional DTI.

Methods

Healthy rhesus monkeys were scanned by diffusion MRI with 128 diffusion encoding directions to evaluate the CFARI algorithm. Four monkeys with ischemic occlusion were also scanned with DTI (b = 1000 s/mm², 30 diffusion directions) at 6, 48, and 96 hours post stroke. CST fibers were reconstructed with DTI and CFARI-based tractography and evaluated. A two-way repeated MANOVA was used to determine significances of changes in DTI indices, tract number, and volumes of the CST between hemispheres or post-stroke time points.

Results

CFARI algorithm revealed substantially more fibers originated from the ventral premotor cortex in healthy and stroke monkey brains than DTI tractography. In addition, CFARI showed better sensitivity in detecting CST abnormality than DTI tractography following stroke.

Conclusion

CFARI significantly improved delineation of the CST in the brain scanned by DTI with 30 gradient directions. It showed better sensitivity in detecting abnormity of the CST following stroke. Preliminary results suggest that CFARI could facilitate prediction of function outcomes after stroke.

Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity

Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function.

Structural disconnections associated with language impairments in chronic post-stroke aphasia using disconnectome maps

Inconsistent findings have been reported about the impact of structural disconnections on language function in post-stroke aphasia. This study investigated patterns of structural disconnections associated with chronic language impairments using disconnectome maps. Seventy-six individuals with post-stroke aphasia underwent a battery of language assessments and a structural MRI scan. Support-vector regression disconnectome-symptom mapping analyses were performed to examine the correlations between disconnectome maps, representing the probability of disconnection at each white matter voxel and different language scores. To further understand whether significant disconnections were primarily representing focal damage or a more extended network of seemingly preserved but disconnected areas beyond the lesion site, results were qualitatively compared to support-vector regression lesion-symptom mapping analyses. Part of the left white matter perisylvian network was similarly disconnected in 90% of the individuals with aphasia. Surrounding this common left perisylvian disconnectome, specific structural disconnections in the left fronto-temporo-parietal network were significantly associated with aphasia severity and with lower performance in auditory comprehension, syntactic comprehension, syntactic production, repetition and naming tasks. Auditory comprehension, repetition and syntactic processing deficits were related to disconnections in areas that overlapped with and extended beyond lesion sites significant in SVR-LSM analyses. In contrast, overall language abilities as measured by aphasia severity and naming seemed to be mostly explained by focal damage at the level of the insular and central opercular cortices, given the high overlap between SVR-DSM and SVR-LSM results for these scores. While focal damage seems to be sufficient to explain broad measures of language performance, the structural disconnections between language areas provide additional information on the neural basis of specific and persistent language impairments at the chronic stage beyond lesion volume. Leveraging routinely available clinical data, disconnectome mapping furthers our understanding of anatomical connectivity constraints that may limit the recovery of some language abilities in chronic post-stroke aphasia.

Spatially bivariate EEG-neurofeedback can manipulate interhemispheric inhibition

Human behavior requires inter-regional crosstalk to employ the sensorimotor processes in the brain. Although external neuromodulation techniques have been used to manipulate interhemispheric sensorimotor activity, a central controversy concerns whether this activity can be volitionally controlled. Experimental tools lack the power to up- or down-regulate the state of the targeted hemisphere over a large dynamic range and, therefore, cannot evaluate the possible volitional control of the activity. We addressed this difficulty by using the recently developed method of spatially bivariate electroencephalography (EEG)-neurofeedback to systematically enable the participants to modulate their bilateral sensorimotor activities. Here, we report that participants learn to up- and down-regulate the ipsilateral excitability to the imagined hand while maintaining constant contralateral excitability; this modulates the magnitude of interhemispheric inhibition (IHI) assessed by the paired-pulse transcranial magnetic stimulation (TMS) paradigm. Further physiological analyses revealed that the manipulation capability of IHI magnitude reflected interhemispheric connectivity in EEG and TMS, which was accompanied by intrinsic bilateral cortical oscillatory activities. Our results show an interesting approach for neuromodulation, which might identify new treatment opportunities, e.g., in patients suffering from a stroke.

Quantitative comparison of corticospinal tracts arising from different cortical areas in humans

The corticospinal tract (CST), which plays a major role in the control of voluntary limb movements, arises from multiple motor- and somatosensory-related areas in monkeys. Although the cortical origin and quantitative differences in CSTs among the cortical areas are well-documented in monkeys, they are unclear in humans. We quantitatively investigated the CSTs from the cerebral cortex to the cervical cord in healthy volunteers using fiber tractography of diffusion-weighted magnetic resonance imaging. The corticospinal (CS) streamlines arose from nine cortical areas: primary motor area (mean ± SD = 49.71 ± 1.61%), dorsal (16.33 ± 1.37%) and ventral (11.02 ± 0.90%) premotor cortex, supplementary motor area (5.14 ± 0.36%), pre-supplementary motor area (2.46 ± 0.26%), primary somatosensory cortex (11.06 ± 0.91%), Brodmann area 5 (0.88 ± 0.09%), caudal cingulate zone (1.70 ± 0.30%), and posterior part of the rostral cingulate zone (1.70 ± 0.34%). In all cortical areas, the number of CS streamlines gradually decreased from the rostral to caudal spinal segments, but the proportion was maintained throughout the cervical cord. Over 75% of CS streamlines arose from the lateral surface of the frontal lobe, which may explain the voluntary control of dexterous and flexible limb movements in humans. (197/200 words).

Brain microstructural antecedents of visual difficulties in infants born very preterm

Infants born very preterm (VPT) are at risk of later visual problems. Although neonatal screening can identify ophthalmologic abnormalities, subtle perinatal brain injury and/or delayed brain maturation may be significant contributors to complex visual-behavioral problems. Our aim was to assess the micro and macrostructural antecedents of early visual-behavioral difficulties in VPT infants by using diffusion MRI (dMRI) at term-equivalent age. We prospectively recruited a cohort of 262 VPT infants (≤32 weeks gestational age [GA]) from five neonatal intensive care units. We obtained structural and diffusion MRI at term-equivalent age and administered the Preverbal Visual Assessment (PreViAs) questionnaire to parents at 3-4 months corrected age. We used constrained spherical deconvolution to reconstruct nine white matter tracts of the visual pathways with high reliability and performed fixel-based analysis to derive fiber density (FD), fiber-bundle cross-section (FC), and combined fiber density and cross-section (FDC). In multiple logistic regression analyses, we related these tract metrics to visual-behavioral function. Of 262 infants, 191 had both high-quality dMRI and completed PreViAs, constituting the final cohort: mean (SD) GA was 29.3 (2.4) weeks, 90 (47.1%) were males, and postmenstrual age (PMA) at MRI was 42.8 (1.3) weeks. FD and FC of several tracts were altered in infants with (N = 59) versus those without retinopathy of prematurity (N = 132). FDC of the left posterior thalamic radiations (PTR), left inferior longitudinal fasciculus (ILF), right superior longitudinal fasciculus (SLF), and left inferior fronto-occipital fasciculus (IFOF) were significantly associated with visual attention scores, prior to adjusting for confounders. After adjustment for PMA at MRI, GA, severe retinopathy of prematurity, and total brain volume, FDC of the left PTR, left ILF, and left IFOF remained significantly associated with visual attention. Early visual-behavioral difficulties in VPT infants are preceded by micro and macrostructural abnormalities in several major visual pathways at term-equivalent age.

Associations Between White Matter Microstructures and Cognitive Functioning in 8-Year-Old Children: A Track-Weighted Imaging Study

PURPOSE

Quantitative tractography using diffusion-weighted magnetic resonance imaging data is widely used in characterizing white matter microstructure throughout childhood, but more studies are still needed to investigate comprehensive brain-behavior relationships between tract-specific white matter measures and multiple cognitive functions in children.

METHODS

In this study, we analyzed diffusion-weighted MRI data of 71 healthy 8-year-old children utilizing white matter tract-specific quantitative measures derived from diffusion-weighted MRI tractography based on a novel track-weighted imaging approach. Track density imaging, average path length map and 4 track-weighted diffusion tensor imaging measures including: mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for 63 white matter tracts. The track-weighted imaging measures were then correlated with a comprehensive set of neuropsychological test scores in different cognitive domains including intelligence, language, memory, academic skills, and executive functions to identify tract-specific brain-behavior relationships.

RESULTS

Significant correlations (P < .05, false discovery rate corrected; r = 0.27-0.57) were found in multiple white matter tracts, with a total of 40 correlations identified between various track-weighted imaging measures including average path length map, track-weighted imaging-fractional anisotropy, and neuropsychological test scores and subscales. Specifically, track-weighted imaging measures indicative of better white matter connectivity and/or microstructural development significantly correlated with higher IQ and better language abilities.

CONCLUSION

Our findings demonstrate the ability of track-weighted imaging measures in establishing associations between white matter and cognitive functioning in healthy children and can serve as a reference for normal brain/cognition relationships in young school-age children and further aid in identifying imaging biomarkers predictive of adverse neurodevelopmental outcomes.

Assessment of peripheral neuropathy in type 2 diabetes by diffusion tensor imaging

BACKGROUND

To evaluate the diagnostic accuracy of diffusion tensor imaging (DTI) in diabetic peripheral neuropathy (DPN) for patients with type 2 diabetes and detect the correlations with electrophysiology.

METHODS

A total of 27 patients with type 2 diabetes with DPN, 24 patients with type 2 diabetes without peripheral neuropathy (NDPN), as well as 32 healthy controls (HC) were enrolled in this study. Clinical examinations and neurophysiologic tests were used to determine the presence of DPN. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of peripheral nerves, including the tibial nerve (TN) and common peroneal nerve (CPN), were calculated. Receiver operating characteristic (ROC) analysis was performed for FA and ADC values. Pearson's correlation coefficient was used to assess the correlation between DTI and electrophysiology parameters in the patient group.

RESULTS

The tibial and common peroneal nerve FAs were lowest (P=0.003, 0.001, respectively) and ADC was highest (P=0.004, 0.005, respectively) in the DPN group. The FA value of the axonal injury group was lower than that in the demyelination group (P=0.035, 0.01, respectively), while the ADC value was higher (P=0.02, 0.01, respectively). In the DPN group, FA value was positively correlated with motor conduction velocity (MCV) (tibial nerve: r=0.420, P=0.007; common peroneal nerve: r=0.581, P<0.001) and motor amplitude (MA) (tibial nerve: r=0.623, P<0.001; common peroneal nerve: r=0.513; P=0.001), while ADC values was negatively correlated with MCV (tibial nerve: r=-0.320, P=0.044; common peroneal nerve: r=-0.569; P<0.001), and MA (tibial nerve: r=-0.491, P=0.001; common peroneal nerve: r=-0.524; P=0.001).

CONCLUSIONS

With a lower FA value and higher ADC value, DTI accurately discriminated DPN. The DTI multi-parameter quantitative analysis of peripheral nerves differentiated DPN axonal injury from the demyelinating lesion, and hence, could be applied in the diagnosis of DPN.

A Comparative Study of Diffusion Fiber Reconstruction Models for Pyramidal Tract Branches

Currently, comparative studies evaluating the quantification accuracy of pyramidal tracts (PT) and PT branches that were tracked based on four mainstream diffusion models are deficient. The present study aims to evaluate four mainstream models using the high-quality Human Connectome Project (HCP) dataset. Diffusion tensor imaging (DTI), diffusion spectral imaging (DSI), generalized Q-space sampling imaging (GQI), and Q-ball imaging (QBI) were used to construct the PT and PT branches in 50 healthy volunteers from the HCP. False and true PT fibers were identified based on anatomic information. One-way repeated measure analysis of variance and post hoc paired-sample t-test were performed to identify the best PT and PT branch quantification model. The number, percentage, and density of true fibers of PT obtained based on GQI and QBI were significantly larger than those based on DTI and DSI (all p < 0.0005, Bonferroni corrected), whereas false fibers yielded the opposite results (all p < 0.0005, Bonferroni corrected). More trunk branches (PT_trunk) were present in the four diffusion models compared with the upper limb (PT_Ulimb), lower limb (PT_Llimb), and cranial (PT_cranial) branches. In addition, significantly more true fibers were obtained in PT_trunk, PT_Ulimb, and PT_Llimb based on the GQI and QBI compared with DTI and DSI (all p < 0.0005, Bonferroni corrected). Finally, GQI-based group probabilistic maps showed that the four PT branches exhibited relatively unique spatial distributions. Therefore, the GQI and QBI represent better diffusion models for the PT and PT branches. The group probabilistic maps of PT branches have been shared with the public to facilitate more precise studies on the plasticity of and the damage to the motor pathway.

Nucleus accumbens projections: Validity and reliability of fiber reconstructions based on high-resolution diffusion-weighted MRI

Clinical effects of deep brain stimulation are largely mediated by the activation of myelinated axons. Hence, increasing attention has been paid in the past on targeting white matter tracts in addition to gray matter. Aims of the present study were: (i) visualization of discrete afferences and efferences of the nucleus accumbens (NAc), supposed to be a major hub of neural networks relating to mental disorders, using probabilistic fiber tractography and a data driven approach, and (ii) validation of the applied methodology for standardized routine clinical applications. MR‐data from 11 healthy subjects and 7 measurement sessions each were acquired on a 3T MRI‐scanner. For probabilistic fiber tracking the NAc as a seed region and the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), amygdala (AMY), hippocampus (HPC), dorsomedial thalamus (dmT) and ventral tegmental area (VTA) as target regions were segmented for each subject and both hemispheres. To quantitatively assess the reliability and stability of the reconstructions, we filtered and clustered the individual fiber‐tracts (NAc to target) for each session and subject and performed a point‐by‐point calculation of the maximum cluster distances for intra‐subject comparison. The connectivity patterns formed by the obtained fibers were in good concordance with published data from tracer and/or fiber‐dissection studies. Furthermore, the reliability assessment of the (NAc to target)‐fiber‐tracts yielded to high correlations between the obtained clustered‐tracts. Using DBS with directional lead technology, the workflow elaborated in this study may guide selective electrical stimulation of NAc projections.

Connectivity-based parcellation of normal and anatomically distorted human cerebral cortex

For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients (n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset (n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.

White Matter Microstructural Differences in Youth With Classical Congenital Adrenal Hyperplasia

CONTEXT

Gray matter morphology in the prefrontal cortex and subcortical regions, including the hippocampus and amygdala, are affected in youth with classical congenital adrenal hyperplasia (CAH). It remains unclear if white matter connecting these aforementioned brain regions is compromised in youth with CAH.

OBJECTIVE

To examine brain white matter microstructure in youth with CAH compared to controls.

DESIGN

A cross-sectional sample of 23 youths with CAH due to 21-hydroxylase deficiency (12.9 ± 3.5 year; 61% female) and 33 healthy controls (13.1 ± 2.8 year; 61% female) with 3T multishell diffusion-weighted magnetic resonance brain scans.

MAIN OUTCOME MEASURES

Complementary modeling approaches, including diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), to examine in vivo white matter microstructure in six white matter tracts that innervate the prefrontal and subcortical regions.

RESULTS

DTI showed CAH youth had lower fractional anisotropy in both the fornix and stria terminalis and higher mean diffusivity in the fornix compared to controls. NODDI modeling revealed that CAH youth have a significantly higher orientation dispersion index in the stria terminalis compared to controls. White matter microstructural integrity was associated with smaller hippocampal and amygdala volumes in CAH youth.

CONCLUSIONS

These patterns of microstructure reflect less restricted water diffusion likely due to less coherency in oriented microstructure. These results suggest that white matter microstructural integrity in the fornix and stria terminalis is compromised and may be an additional related brain phenotype alongside affected hippocampus and amygdala neurocircuitry in individuals with CAH.

Exploring Peritumoral Neural Tracts by Using Neurite Orientation Dispersion and Density Imaging

Diffusion Tensor Imaging (DTI) tractography has been widely used in brain tumor surgery to ensure thorough resection and minimize functional damage. However, due to enhanced anisotropic uncertainty in the area with peritumoral edema, diffusion tractography is generally not practicable leading to high false-negative results in neural tracking. In this study, we evaluated the usefulness of the neurite orientation dispersion and density imaging (NODDI) derived tractography for investigating structural heterogeneity of the brain in patients with brain tumor. A total of 24 patients with brain tumors, characterized by peritumoral edema, and 10 healthy counterparts were recruited from 2014 to 2021. All participants underwent magnetic resonance imaging. Moreover, we used the images obtained from the healthy participants for calibrating the orientation dispersion threshold for NODDI-derived corticospinal tract (CST) reconstruction. Compared to DTI, NODDI-derived tractography has a great potential to improve the reconstruction of fiber tracking through regions of vasogenic edema. The regions with edematous CST in NODDI-derived tractography demonstrated a significant decrease in the intracellular volume fraction (VF_ic, p < 0.000) and an increase in the isotropic volume fraction (VF_iso, p < 0.014). Notably, the percentage of the involved volume of the concealed CST and lesion-to-tract distance could reflect the motor function of the patients. After the tumor resection, four patients with 1–5 years follow-up were showed subsidence of the vasogenic edema and normal CST on DTI tractography. NODDI-derived tractography revealed tracts within the edematous area and could assist neurosurgeons to locate the neural tracts that are otherwise not visualized by conventional DTI tractography.

Early micro- and macrostructure of sensorimotor tracts and development of cerebral palsy in high risk infants

Infants born very preterm (VPT) are at high risk of motor impairments such as cerebral palsy (CP), and diagnosis can take 2 years. Identifying in vivo determinants of CP could facilitate presymptomatic detection and targeted intervention. Our objectives were to derive micro‐ and macrostructural measures of sensorimotor white matter tract integrity from diffusion MRI at term‐equivalent age, and determine their association with early diagnosis of CP. We enrolled 263 VPT infants (≤32 weeks gestational age) as part of a large prospective cohort study. Diffusion and structural MRI were acquired at term. Following consensus guidelines, we defined early diagnosis of CP based on abnormal structural MRI at term and abnormal neuromotor exam at 3–4 months corrected age. Using Constrained Spherical Deconvolution, we derived a white matter fiber orientation distribution (fOD) for subjects, performed probabilistic whole‐brain tractography, and segmented nine sensorimotor tracts of interest. We used the recently developed fixel‐based (FB) analysis to compute fiber density (FD), fiber‐bundle cross‐section (FC), and combined fiber density and cross‐section (FDC) for each tract. Of 223 VPT infants with high‐quality diffusion MRI data, 14 (6.3%) received an early diagnosis of CP. The cohort's mean (SD) gestational age was 29.4 (2.4) weeks and postmenstrual age at MRI scan was 42.8 (1.3) weeks. FD, FC, and FDC for each sensorimotor tract were significantly associated with early CP diagnosis, with and without adjustment for confounders. Measures of sensorimotor tract integrity enhance our understanding of white matter changes that antecede and potentially contribute to the development of CP in VPT infants.

Functional Contributions of the Arcuate Fasciculus to Language Processing

Current evidence strongly suggests that the arcuate fasciculus (AF) is critical for language, from spontaneous speech and word retrieval to repetition and comprehension abilities. However, to further pinpoint its unique and differential role in language, its anatomy needs to be explored in greater detail and its contribution to language processing beyond that of known cortical language areas must be established. We address this in a comprehensive evaluation of the specific functional role of the AF in a well-characterized cohort of individuals with chronic aphasia (n = 33) following left hemisphere stroke. To evaluate macro- and microstructural integrity of the AF, tractography based on the constrained spherical deconvolution model was performed. The AF in the left and right hemispheres were then manually reconstructed using a modified 3-segment model (Catani et al., 2005), and a modified 2-segment model (Glasser and Rilling, 2008). The normalized volume and a measure of microstructural integrity of the long and the posterior segments of the AF were significantly correlated with language indices while controlling for gender and lesion volume. Specific contributions of AF segments to language while accounting for the role of specific cortical language areas – inferior frontal, inferior parietal, and posterior temporal – were tested using multiple regression analyses. Involvement of the following tract segments in the left hemisphere in language processing beyond the contribution of cortical areas was demonstrated: the long segment of the AF contributed to naming abilities; anterior segment – to fluency and naming; the posterior segment – to comprehension. The results highlight the important contributions of the AF fiber pathways to language impairments beyond that of known cortical language areas. At the same time, no clear role of the right hemisphere AF tracts in language processing could be ascertained. In sum, our findings lend support to the broader role of the left AF in language processing, with particular emphasis on comprehension and naming, and point to the posterior segment of this tract as being most crucial for supporting residual language abilities.

An overview of fractional anisotropy as a reliable quantitative measurement for the corticospinal tract (CST) integrity in correlation with a Fugl-Meyer assessment in stroke rehabilitation

[Purpose] Understanding the essential mechanisms in post-stroke recovery not only provides important basic insights into brain function and plasticity but can also guide the development of new therapeutic approaches for stroke patients. This review aims to give an overview of how various variables of Magnetic Resonance-Diffusion Tensor Imaging (MR-DTI) metrics of fractional anisotropy (FA) can be used as a reliable quantitative measurement and indicator of corticospinal tract (CST) changes, particularly in relation to functional motor outcome correlation with a Fugl-Meyer assessment in stroke rehabilitation. [Methods] PubMed electronic database was searched for the relevant literature, using key words of diffusion tensor imaging (dti), corticospinal tract, and stroke. [Results] We reviewed the role of FA in monitoring CST remodeling and its role of predicting motor recovery after stroke. We also discussed the mechanism of CST remodeling and its modulation from the value of FA and FMA-UE. [Conclusion] Heterogeneity of post-stroke brain disorganization and motor impairment is a recognized challenge in the development of accurate indicators of CST integrity. DTI-based FA measurements offer a reliable and evidence-based indicator for CST integrity that would aid in predicting motor recovery within the context of stroke rehabilitation.

Advanced non-invasive MRI of neuroplasticity in ischemic stroke: Techniques and applications

Ischemic stroke represents a serious medical condition which could cause survivors suffer from long-term and even lifetime disabilities. After a stroke attack, the brain would undergo varying degrees of recovery, in which the central nervous system could be reorganized spontaneously or with the help of appropriate rehabilitation. Magnetic resonance imaging (MRI) is a non-invasive technique which can provide comprehensive information on structural, functional and metabolic features of brain tissue. In the last decade, there has been an increased technical advancement in MR techniques such as voxel-based morphological analysis (VBM), diffusion magnetic resonance imaging (dMRI), functional magnetic resonance imaging (fMRI), arterial spin-labeled perfusion imaging (ASL), magnetic sensitivity weighted imaging (SWI), quantitative sensitivity magnetization (QSM) and magnetic resonance spectroscopy (MRS) which have been proven to be a valuable tool to study the brain tissue reorganization. Due to MRI indices of neuroplasticity related to neurological outcome could be translated to the clinic. The ultimate goal of this review is to equip readers with a fundamental understanding of advanced MR techniques and their corresponding clinical application for improving the ability to predict neuroplasticity that are most suitable for stroke management.

Test-retest reliability and minimal detectable change of corticospinal tract integrity in chronic stroke

Diffusion tensor imaging (DTI) can be used to index white matter integrity of the corticospinal tract (CST) after stroke; however, the psychometric properties of DTI-based measures of white matter integrity are unknown. The purpose of this study was to examine test-retest reliability as determined by intraclass correlation coefficients (ICC) and calculate minimal detectable change (MDC) of DTI-based measures of CST integrity using three different approaches: a Cerebral Peduncle approach, a Probabilistic Tract approach, and a Tract Template approach. Eighteen participants with chronic stroke underwent DTI on the same magnetic resonance imaging scanner 4 days apart. For the Cerebral Peduncle approach, a researcher hand drew masks at the cerebral peduncle. For the Probabilistic Tract approach, tractography was seeded in motor areas of the cortex to the cerebral peduncle. For the Tract Template approach, a standard CST template was transformed into native space. For all approaches, the researcher performing analyses was blind to participant number and day of data collection. All three approaches had good to excellent test-retest reliability for fractional anisotropy (FA; ICCs >0.786). Mean diffusivity, axial diffusivity, and radial diffusivity were less reliable than FA. The ICC values were highest and MDC values were the smallest for the most automated approach (Tract Template), followed by the combined manual/automated approach (Probabilistic Tract) then the manual approach (Cerebral Peduncle). The results of this study may have implications for how DTI-based measures of CST integrity are used to define impairment, predict outcomes, and interpret change after stroke.

The impact of position-orientation adaptive smoothing in diffusion weighted imaging-From diffusion metrics to fiber tractography

In contrast to commonly used approaches to improve data quality in diffusion weighted imaging, position-orientation adaptive smoothing (POAS) provides an edge-preserving post-processing approach. This study aims to investigate its potential and effects on image quality, diffusion metrics, and fiber tractography of the corticospinal tract in relation to non-post-processed and averaged data. 22 healthy volunteers were included in this study. For each volunteer five clinically applicable diffusion weighted imaging data sets were acquired and post-processed by standard averaging and POAS. POAS post-processing led to significantly higher signal-to-noise-ratios (p < 0.001), lower fractional anisotropy across the whole brain (p < 0.05) and reduced intra-subject variability of diffusion weighted imaging signal intensity and fractional anisotropy (p < 0.001, p = 0.006). Fiber tractography of the corticospinal tract resulted in significantly (p = 0.027, p = 0.014) larger tract volumes while fiber density was the lowest. Similarity across tractography results was highest for POAS post-processed data (p < 0.001). POAS post-processing enhances image quality, decreases the intra-subject variability of signal intensity and fractional anisotropy, increases fiber tract volume of the corticospinal tract, and leads to higher reproducibility of tractography results. Thus, POAS post-processing supports a reliable and more accurate fiber tractography of the corticospinal tract, being mandatory for the clinical use.

Sex differences in the effects of gonadal hormones on white matter microstructure development in adolescence

Adolescence is characterized by rapid brain development in white matter (WM) that is attributed in part to surges in gonadal hormones. To date, however, there have been few longitudinal investigations relating changes in gonadal hormones and WM development in adolescents. We acquired diffusion-weighted MRI to estimate mean fractional anisotropy (FA) from 10 WM tracts and salivary testosterone from 51 females and 29 males (ages 9-14 years) who were matched on pubertal stage and followed, on average, for 2 years. We tested whether interactions between sex and changes in testosterone levels significantly explained changes in FA. We found positive associations between changes in testosterone and changes in FA within the corpus callosum, cingulum cingulate, and corticospinal tract in females (all ps<0.05, corrected) and non-significant associations in males. We also collected salivary estradiol from females and found that increases in estradiol were associated with increases in FA in the left uncinate fasciculus (p = 0.04, uncorrected); however, this effect was no longer significant after accounting for changes in testosterone. Our findings indicate there are sex differences in how changes in testosterone relate to changes in WM microstructure of tracts that support impulse control and emotion regulation across the pubertal transition.

White matter microstructure of the extended limbic system in male and female youth with conduct disorder

BACKGROUND

Previous studies of conduct disorder (CD) have reported structural and functional alterations in the limbic system. However, the white matter tracts that connect limbic regions have not been comprehensively studied. The uncinate fasciculus (UF), a tract connecting limbic to prefrontal regions, has been implicated in CD. However, CD-related alterations in other limbic tracts, such as the cingulum and the fornix, have not been investigated. Furthermore, few studies have examined the influence of sex and none have been adequately powered to test whether the relationship between CD and structural connectivity differs by sex. We examined whether adolescent males and females with CD exhibit differences in structural connectivity compared with typically developing controls.

METHODS

We acquired diffusion-weighted magnetic resonance imaging data from 101 adolescents with CD (52 females) and 99 controls (50 females). Data were processed for deterministic spherical deconvolution tractography. Virtual dissections of the UF, the three subdivisions of the cingulum [retrosplenial cingulum (RSC), parahippocampal and subgenual cingulum], and the fornix were performed and measures of fractional anisotropy (FA) and hindrance-modulated orientational anisotropy (HMOA) were analysed.

RESULTS

The CD group had lower FA and HMOA in the right RSC tract relative to controls. Importantly, these effects were moderated by sex - males with CD significantly lower FA compared to male controls, whereas CD and control females did not differ.

CONCLUSIONS

Our results highlight the importance of considering sex when studying the neurobiological basis of CD. Sex differences in RSC connectivity may contribute to sex differences in the clinical presentation of CD.

Topographic diversity of structural connectivity in schizophrenia

The neurobiological heterogeneity of schizophrenia is widely accepted, but it is unclear how mechanistic differences converge to produce the observed phenotype. Establishing a pathophysiological model that accounts for both neurobiological heterogeneity and phenotypic similarity is essential to inform stratified treatment approaches. In this cross-sectional diffusion tensor imaging study, we recruited 77 healthy controls, and 70 patients with DSM-IV diagnosis of schizophrenia. We first confirmed the heterogeneity in structural connectivity by showing a reduced between-individual similarity of the structural connectivity in patients compared to healthy controls. Second, at a system level, we found the diversity of the topographic distribution of the strength of structural connectivity was significantly reduced in patients (P = 7.21 × 10^-7, T₁₄₂ = 5.19 [95% CI: 3.37-7.52], Cohen's d = 0.91), and this affected 65 of the 90 brain regions examined (False Discovery Rate <5%). Third, when topographic diversity was used as a discriminant feature to train a model for classifying patients from controls, it significantly improved the accuracy on an independent sample (T₉₉ = 5.54; P < 0.001). These findings suggest a highly individualized pattern of structural dysconnectivity underlies the heterogeneity of schizophrenia, but these disruptions likely converge on an emergent common pathway to generate the clinical phenotype of the disorder.

Microstructural characterization of corticospinal tract in subacute and chronic stroke patients with distal lesions by means of advanced diffusion MRI

PURPOSE

The aim of the paper is to evaluate if advanced dMRI techniques, including diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI), could provide novel insights into the subtle microarchitectural modifications occurring in the corticospinal tract (CST) of stroke patients in subacute and chronic phases.

METHODS

Seventeen subjects (age 68 ± 11 years) in the subacute phase (14 ± 3 days post-stroke), 10 of whom rescanned in the chronic phase (231 ± 36 days post-stroke), were enrolled. Images were acquired using a 3-T MRI scanner with a two-shell EPI protocol (20 gradient directions, b = 700 s/mm², 3 b = 0; 64 gradient directions, b = 2000 s/mm², 9 b = 0). DTI-, DKI-, and NODDI-derived parameters were calculated in the posterior limb of the internal capsule (PLIC) and in the cerebral peduncle (CP).

RESULTS

In the subacute phase, a reduction of FA, AD, and KA values was correlated with an increase of ODI, RD, and AK parameters, in both the ipsilesional PLIC and CP, suggesting that increased fiber dispersion can be the main structural factor. In the chronic phase, a reduction of FA and an increase of ODI persisted in the ipsilesional areas. This was associated with reduced F_ic and increased MD, with a concomitant reduction of MK and increase of RD, suggesting that fiber reduction, possibly due to nerve degeneration, could play an important role.

CONCLUSIONS

This study shows that advanced dMRI approaches can help elucidate the underpinning architectural modifications occurring in the CST after stroke. Further follow-up studies on bigger cohorts are needed to evaluate if DKI- and NODDI-derived parameters might be proposed as complementary biomarkers of brain microstructural alterations.

Diffusion Tensor Imaging Biomarkers to Predict Motor Outcomes in Stroke: A Narrative Review

Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2-7 days (acute), and >7-90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.

Predicting Motor Outcomes in Stroke Patients Using Diffusion Spectrum MRI Microstructural Measures

Improved understanding of neuroimaging signal changes and their relation to patient outcomes after ischemic stroke is needed to improve ability to predict motor improvement and make therapy recommendations. The posterior limb of the internal capsule (PLIC) is a hub of afferent and efferent motor signaling and this work proposes new, image-based methods for prognosis based on interhemispheric differences in the PLIC. In this work, nine acute supratentorial ischemic stroke patients with motor impairment received a baseline, 203-direction diffusion brain MRI and a clinical assessment 3–12 days post-stroke and were compared to nine age-matched healthy controls. Asymmetries based on the mean and Kullback-Leibler divergence in the ipsilesional and contralesional PLIC were calculated for diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) measures from the baseline MRI. Predictions of upper extremity Fugl-Meyer (FM) scores at 5-weeks follow-up from baseline measures of PLIC asymmetry in diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) models were evaluated. For the stroke participants, the baseline asymmetry measures in the PLIC for the orientation dispersion index of the neurite orientation dispersion and density imaging (NODDI) model were highly correlated with upper extremity FM outcomes (r² = 0.83). Use of DSI and the NODDI orientation dispersion index parameter shows promise of being more predictive of stroke recovery and to help better understand white matter changes in stroke, beyond DTI measures. The new finding that baseline interhemispheric differences in the PLIC calculated from the orientation dispersion index of the NODDI model are highly correlated with upper extremity functional outcomes may lead to improved image-based motor-outcome prediction after middle cerebral artery ischemic stroke.

The effects of five sessions of continuous theta burst stimulation over contralesional sensorimotor cortex paired with paretic skilled motor practice in people with chronic stroke

BACKGROUND

In individuals with chronic stroke, impairment of the paretic arm may be exacerbated by increased contralesional transcallosal inhibition (TCI). Continuous theta burst stimulation (cTBS) can decrease primary motor cortex (M1) excitability and TCI. However, contralesional cTBS shows inconsistent effects after stroke. Variable effects of cTBS could stem from failure to pair stimulation with skilled motor practice or a focus of applying cTBS over M1.

OBJECTIVE

Here, we investigated the effects of pairing cTBS with skilled practice on motor learning and arm function. We considered the differential effects of stimulation over two different brain regions: contralesional M1 (M1c) or contralesional primary somatosensory cortex (S1c).

METHODS

37 individuals with chronic stroke participated in five sessions of cTBS and paretic arm skilled practice of a serial targeting task (STT); participants received either cTBS over M1c or S1c or sham before STT practice. Changes in STT performance and Wolf Motor Function Test (WMFT) were assessed as primary outcomes. Assessment of bilateral corticospinal, intracortical excitability and TCI were secondary outcomes.

RESULTS

cTBS over sensorimotor cortex did not improve STT performance and paretic WMFT-rate beyond sham cTBS. TCI was reduced bi-directionally following the intervention, regardless of stimulation group. In addition, we observed an association between STT performance change and paretic WMFT-rate change in the M1c stimulation group only.

CONCLUSIONS

Multiple sessions of STT practice can improve paretic arm function and decrease TCI bilaterally, with no additional benefit of prior cTBS. Our results suggest that improvement in STT practice following M1c cTBS scaled with change in paretic arm function in some individuals. Our results highlight the need for a better understanding of the mechanisms of cTBS to effectively identify who may benefit from this form of brain stimulation.

White matter organization in developmental coordination disorder: A pilot study exploring the added value of constrained spherical deconvolution

Previous studies of white matter organization in sensorimotor tracts in developmental coordination disorder (DCD) have adopted diffusion tensor imaging (DTI), a method unable to reconcile pathways with ‘crossing fibres’. In response to limitations of the commonly adopted DTI approach, the present study employed a framework that can reconcile the ‘crossing fibre’ problem (i.e., constrained spherical deconvolution- CSD) to characterize white matter tissue organization of sensorimotor tracts in young adults with DCD. Participants were 19 healthy adults aged 18–46: 7 met diagnostic criteria for DCD (4 females) and 12 were controls (3 females). All underwent high angular diffusion MRI. After preprocessing, the left and right corticospinal tracts (CST) and superior longitudinal fasciculi (SLF) were delineated and all tracts were then generated using both CSD and DTI tractography respectively. Based on the CSD model, individuals with DCD demonstrated significantly decreased mean apparent fibre density (AFD) in the left SLF relative to controls (with large effect size, Cohen's d = 1.32) and a trend for decreased tract volume of the right SLF (with medium-large effect size, Cohen's d = 0.73). No differences in SLF microstructure were found between groups using DTI, nor were differences in CST microstructure observed across groups regardless of hemisphere or diffusion model. Our data are consistent with the view that motor impairment characteristic of DCD may be subserved by white matter abnormalities in sensorimotor tracts, specifically the left and right SLF. Our data further highlight the benefits of higher order diffusion MRI (e.g. CSD) relative to DTI for clarifying earlier inconsistencies in reports speaking to white matter organization in DCD, and its contribution to poor motor skill in DCD.

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All previous diffusion studies of white matter in DCD have employed a tensor model

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We employed a non-tensor model to characterize microstructure in adults with DCD

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The non-tensor model showed atypical white matter organization in the SLF in DCD

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The tensor model failed to detect microstructural group differences for any tract

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Motor impairment characteristic of DCD may be subserved by white matter abnormalities

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We need to move beyond the tensor model in characterizing white matter in DCD

The Impact of Covert Lacunar Infarcts and White Matter Hyperintensities on Cognitive and Motor Outcomes After Stroke

BACKGROUND AND AIMS

In addition to overt stroke lesions, co-occurring covert lesions, including white matter hyperintensities (WMH) and covert lacunar infarcts (CLI), contribute to poststroke outcome. The purpose of this study was to examine the relationship between covert lesions, and motor and cognitive outcomes in individuals with chronic stroke.

METHODS

Volumetric quantification of clinically overt strokes, covert lesions (periventricular and deep: pWMH, dWMH, pCLI, dCLI), ventricular and sulcal CSF (vCSF, sCSF), and normal appearing white (NAWM) and gray matter (NAGM) was performed using structural magnetic resonance imaging. We assessed motor impairment and function, and global cognition, memory, and other cognitive domains. When correlation analysis identified more than one MR parameter relating to stroke outcomes, we used regression modeling to identify which factor had the strongest impact.

RESULTS

Neuropsychological and brain imaging data were collected from 30 participants at least 6 months following a clinically diagnosed stroke. Memory performance related to vCSF (r = -0.52, P = .004). The strongest predictor of nonmemory domains was pCLI (r² = 0.28, P = .004). Motor impairment and function were most strongly predicted by the volume of stroke and NAWM (r² = 0.36; P = .001), and dWMH (r² = 0.39; P = .001) respectively.

CONCLUSIONS

Covert lesion type and location have important consequences for post-stroke cognitive and motor outcome. Limiting the progression of covert lesions in aging populations may enhance the degree of recovery post-stroke.

Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann–Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.

Comparison of probabilistic tractography and tract-based spatial statistics for assessing optic radiation damage in patients with autoimmune inflammatory disorders of the central nervous system

Background

Diffusion Tensor Imaging (DTI) can evaluate microstructural tissue damage in the optic radiation (OR) of patients with clinically isolated syndrome (CIS), early relapsing-remitting multiple sclerosis and neuromyelitis optica spectrum disorders (NMOSD). Different post-processing techniques, e.g. tract-based spatial statistics (TBSS) and probabilistic tractography, exist to quantify this damage.

Objective

To evaluate the capacity of TBSS-based atlas region-of-interest (ROI) combination with 1) posterior thalamic radiation ROIs from the Johns Hopkins University atlas (JHU-TBSS), 2) Juelich Probabilistic ROIs (JUEL-TBSS) and tractography methods using 3) ConTrack (CON-PROB) and 4) constrained spherical deconvolution tractography (CSD-PROB) to detect OR damage in patients with a) NMOSD with prior ON (NMOSD-ON), b) CIS and early RRMS patients with ON (CIS/RRMS-ON) and c) CIS and early RRMS patients without prior ON (CIS/RRMS-NON) against healthy controls (HCs).

Methods

Twenty-three NMOSD-ON, 18 CIS/RRMS-ON, 21 CIS/RRMS-NON, and 26 HCs underwent 3 T MRI. DTI data analysis was carried out using JUEL-TBSS, JHU-TBSS, CON-PROB and CSD-PROB. Optical coherence tomography (OCT) and visual acuity testing was performed in the majority of patients and HCs.

Results

Absolute OR fractional anisotropy (FA) values differed between all methods but showed good correlation and agreement in Bland-Altman analysis. OR FA values between NMOSD and HC differed throughout the methodologies (p-values ranging from p < 0.0001 to 0.0043). ROC-analysis and effect size estimation revealed higher AUCs and R² for CSD-PROB (AUC = 0.812; R² = 0.282) and JHU-TBSS (AUC = 0.756; R² = 0.262), compared to CON-PROB (AUC = 0.742; R² = 0.179) and JUEL-TBSS (AUC = 0.719; R² = 0.161). Differences between CIS/RRMS-NON and HC were only observable in CSD-PROB (AUC = 0.796; R² = 0.094). No significant differences between CIS/RRMS-ON and HC were detected by any of the methods.

Conclusions

All DTI post-processing techniques facilitated the detection of OR damage in patient groups with severe microstructural OR degradation. The comparison of distinct disease groups by use of different methods may lead to different - either false-positive or false-negative - results. Since different DTI post-processing approaches seem to provide complementary information on OR damage, application of distinct methods may depend on the relevant research question.

A probabilistic atlas of human brainstem pathways based on connectome imaging data

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways.

Interhemispheric Pathways Are Important for Motor Outcome in Individuals with Chronic and Severe Upper Limb Impairment Post Stroke

Background

Severity of arm impairment alone does not explain motor outcomes in people with severe impairment post stroke.

Objective

Define the contribution of brain biomarkers to upper limb motor outcomes in people with severe arm impairment post stroke.

Methods

Paretic arm impairment (Fugl-Meyer upper limb, FM-UL) and function (Wolf Motor Function Test rate, WMFT-rate) were measured in 15 individuals with severe (FM-UL ≤ 30/66) and 14 with mild–moderate (FM-UL > 40/66) impairment. Transcranial magnetic stimulation and diffusion weight imaging indexed structure and function of the corticospinal tract and corpus callosum. Separate models of the relationship between possible biomarkers and motor outcomes at a single chronic (≥6 months) time point post stroke were performed.

Results

Age (ΔR²0.365, p = 0.017) and ipsilesional-transcallosal inhibition (ΔR²0.182, p = 0.048) explained a 54.7% (p = 0.009) variance in paretic WMFT-rate. Prefrontal corpus callous fractional anisotropy (PF-CC FA) alone explained 49.3% (p = 0.007) variance in FM-UL outcome. The same models did not explain significant variance in mild–moderate stroke. In the severe group, k-means cluster analysis of PF-CC FA distinguished two subgroups, separated by a clinically meaningful and significant difference in motor impairment (p = 0.049) and function (p = 0.006) outcomes.

Conclusion

Corpus callosum function and structure were identified as possible biomarkers of motor outcome in people with chronic and severe arm impairment.

Repetitive reaching training combined with transcranial Random Noise Stimulation in stroke survivors with chronic and severe arm paresis is feasible: a pilot, triple-blind, randomised case series

Background

Therapy that combines repetitive training with non-invasive brain stimulation is a potential avenue to enhance upper limb recovery after stroke. This study aimed to investigate the feasibility of transcranial Random Noise Stimulation (tRNS), timed to coincide with the generation of voluntary motor commands, during reaching training.

Methods

A triple-blind pilot RCT was completed. Four stroke survivors with chronic (6-months to 5-years) and severe arm paresis, not taking any medications that had the potential to alter cortical excitability, and no contraindications to tRNS or MRI were recruited. Participants were randomly allocated to 12 sessions of reaching training over 4-weeks with active or sham tRNS delivered over the lesioned hemisphere motor representation. tRNS was triggered to coincide with a voluntary movement attempt, ceasing after 5-s. At this point, peripheral nerve stimulation enabled full range reaching. To determine feasibility, we considered adverse events, training outcomes, clinical outcomes, corticospinal tract (CST) structural integrity, and reflections on training through in-depth interviews from each individual case.

Results

Two participants received active and two sham tRNS. There were no adverse events. All training sessions were completed, repetitive practice performed and clinically relevant improvements across motor outcomes demonstrated. The amount of improvement varied across individuals and appeared to be independent of group allocation and CST integrity.

Conclusion

Reaching training that includes tRNS timed to coincide with generation of voluntary motor commands is feasible. Clinical improvements were possible even in the most severely affected individuals as evidenced by CST integrity.

Trial registration

This study was registered on the Australian and New Zealand Clinical Trials Registry (ANZCTR) http://www.ANZCTR.org.au/ACTRN12614000952640.aspx. Registration date 4 September 2014, first participant date 9 September 2014.

Functional MRI vs. navigated TMS to optimize M1 seed volume delineation for DTI tractography. A prospective study in patients with brain tumours adjacent to the corticospinal tract

BACKGROUND

DTI-based tractography is an increasingly important tool for planning brain surgery in patients suffering from brain tumours. However, there is an ongoing debate which tracking approaches yield the most valid results. Especially the use of functional localizer data such as navigated transcranial magnetic stimulation (nTMS) or functional magnetic resonance imaging (fMRI) seem to improve fibre tracking data in conditions where anatomical landmarks are less informative due to tumour-induced distortions of the gyral anatomy. We here compared which of the two localizer techniques yields more plausible results with respect to mapping different functional portions of the corticospinal tract (CST) in brain tumour patients.

METHODS

The CSTs of 18 patients with intracranial tumours in the vicinity of the primary motor area (M1) were investigated by means of deterministic DTI. The core zone of the tumour-adjacent hand, foot and/or tongue M1 representation served as cortical regions of interest (ROIs). M1 core zones were defined by both the nTMS hot-spots and the fMRI local activation maxima. In addition, for all patients, a subcortical ROI at the level of the inferior anterior pons was implemented into the tracking algorithm in order to improve the anatomical specificity of CST reconstructions. As intra-individual control, we additionally tracked the CST of the hand motor region of the unaffected, i.e., non-lesional hemisphere, again comparing fMRI and nTMS M1 seeds. The plausibility of the fMRI-ROI- vs. nTMS-ROI-based fibre trajectories was assessed by a-priori defined anatomical criteria. Moreover, the anatomical relationship of different fibre courses was compared regarding their distribution in the anterior-posterior direction as well as their location within the posterior limb of the internal capsule (PLIC).

RESULTS

Overall, higher plausibility rates were observed for the use of nTMS- as compared to fMRI-defined cortical ROIs (p < 0.05) in tumour vicinity. On the non-lesional hemisphere, however, equally good plausibility rates (100%) were observed for both localizer techniques. fMRI-originated fibres generally followed a more posterior course relative to the nTMS-based tracts (p < 0.01) in both the lesional and non-lesional hemisphere.

CONCLUSION

NTMS achieved better tracking results than fMRI in conditions when the cortical tract origin (M1) was located in close vicinity to a brain tumour, probably influencing neurovascular coupling. Hence, especially in situations with altered BOLD signal physiology, nTMS seems to be the method of choice in order to identify seed regions for CST mapping in patients.

Tensor and non-tensor tractography for the assessment of the corticospinal tract of children with motor disorders: a comparative study

INTRODUCTION

Non-invasive measures of corticospinal tract (CST) integrity may help to guide clinical interventions, particularly in children and young people (CAYP) with motor disorders. We compared diffusion tensor imaging (DTI) metrics extracted from the CST generated by tensor and non-tensor based tractography algorithms.

METHODS

For a group of 25 CAYP undergoing clinical evaluation, the CST was reconstructed using (1) deterministic tensor-based tractography algorithm, (2) probabilistic tensor-based, and (3) constrained spherical deconvolution (CSD)-derived tractography algorithms.

RESULTS

Choice of tractography algorithm significantly altered the results of tracking. Larger tracts were consistently defined with CSD, with differences in FA but not MD values for tracts to the pre- or post-central gyrus. Differences between deterministic and probabilistic tensor-based algorithms were minimal. Non-tensor reconstructed tracts appeared to be more anatomically representative. Examining metrics along the tract, difference in FA values appeared to be greatest in voxels with predominantly single-fibre orientations. Less pronounced differences were seen outwith of these regions.

CONCLUSION

With an increasing interest in the applications of tractography analysis at all stages of movement disorder surgery, it is important that clinicians remain alert to the consequences of choice of tractography algorithm on subsequently generated tracts, including differences in volumes, anatomical reconstruction, and DTI metrics, the latter of which will have global as well as more regional effects. Tract-wide analysis of DTI based metrics is of limited utility, and a more segmental approach to analysis may be appropriate, particularly if disruption to a focal region of a white matter pathway is anticipated.

A Case of Hearing Loss after Bilateral Putaminal Hemorrhage: A Diffusion-tensor Imaging Study

Background

Magnetic resonance diffusion-tensor imaging (DTI) is a tool for the assessment of neural fiber integrity. We applied DTI in a patient with hearing loss that developed after bilateral putaminal hemorrhage.

Case

A 59-year-old woman was referred to our outpatient clinic for sequelae diagnosis. Six years earlier, she had suffered a left putaminal hemorrhage, but almost fully recovered. Four years later, she suffered a right putaminal hemorrhage, resulting in severe left hemiparesis and hearing loss. After receiving conservative acute care treatment, she was transferred to a long-term rehabilitation facility and returned home 7 months later, when her Functional Independence Measure score was 103 points. Although the patient could not respond to auditory stimuli, her writing and reading abilities were intact. Auditory examinations indicated that the brainstem response was normal, but pure tone audiometry was at the low end of the scale (105 dB). We examined the patient's brain using DTI, and the lesions were assessed in reference to the standard brain map transformed into her individual brain space. Fractional anisotropy and color brain maps indicated that the lesions were located within bilateral acoustic radiations. In addition, we applied fiber tracking analysis in which voxels of the medial geniculate bodies in the standard brain map were transformed into the patient's individual brain space and then taken as seeds for the fiber tracking. The resulting image showed bilateral disruption of acoustic radiation fibers.

Conclusion

By applying DTI, we identified the neuroanatomical pathology of hearing loss that developed after bilateral putaminal hemorrhage.