DiffusionKit: a light one-stop solution for diffusion MRI data analysis

Background Diffusion magnetic resonance imaging (dMRI) techniques are receiving increasing attention due to their ability to characterize the arrangement map of white matter in vivo. However, the existing toolkits for dMRI analysis that have accompanied this surge possess noticeable limitations, such as large installation size, an incomplete pipeline, and a lack of cross-platform support. New method In this work, we developed a light, one-stop, cross-platform solution for dMRI data analysis, called DiffusionKit. It delivers a complete pipeline, including data format conversion, dMRI preprocessing, local reconstruction, white matter fiber tracking, fiber statistical analyses and various visualization schemes. Furthermore, DiffusionKit is a self-contained executable toolkit, without the need to install any other software. Results The DiffusionKit package is implemented in C/C++ and Qt/VTK, is freely available at http://diffusion.brainnetome.org and https://www.nitrc.org/projects/diffusionkit. The website of DiffusionKit includes test data, a complete tutorial and a series of tutorial examples. A mailing list has also been established for update notification and questions and answers. Comparison with existing methods DiffusionKit provides a full-function pipeline for dMRI data analysis, including data processing, modeling and visualization. Additionally, it provides both a graphical user interface (GUI) and command-line functions, which are helpful for batch processing. The standalone installation package has a small size and cross-platform support. Conclusions DiffusionKit provides a complete pipeline with cutting-edge methods for dMRI data analysis, including both a GUI interface and command-line functions. The rich functions for both data analysis and visualization will facilitate and benefit dMRI research

White matter microstructure alterations in idiopathic restless legs syndrome: a study combining crossing fiber-based and tensor-based approaches

IntroductionRestless legs syndrome (RLS) is a common sensorimotor disorder characterized by an irrepressible urge to move the legs and frequently accompanied by unpleasant sensations in the legs. The pathophysiological mechanisms underlying RLS remain unclear, and RLS is hypothesized to be associated with alterations in white matter tracts.MethodsDiffusion MRI is a unique noninvasive method widely used to study white matter tracts in the human brain. Thus, diffusion-weighted images were acquired from 18 idiopathic RLS patients and 31 age- and sex-matched healthy controls (HCs). Whole brain tract-based spatial statistics (TBSS) and atlas-based analyzes combining crossing fiber-based metrics and tensor-based metrics were performed to investigate the white matter patterns in individuals with RLS.ResultsTBSS analysis revealed significantly higher fractional anisotropy (FA) and partial volume fraction of primary (F1) fiber populations in multiple tracts associated with the sensorimotor network in patients with RLS than in HCs. In the atlas based analysis, the bilateral anterior thalamus radiation, bilateral corticospinal tract, bilateral inferior fronto-occipital fasciculus, left hippocampal cingulum, left inferior longitudinal fasciculus, and left uncinate fasciculus showed significantl increased F1, but only the left hippocampal cingulum showed significantly higher FA.DiscussionThe results demonstrated that F1 identified extensive alterations in white matter tracts compared with FA and confirmed the hypothesis that crossing fiber-based metrics are more sensitive than tensor-based metrics in detecting white matter abnormalities in RLS. The present findings provide evidence that the increased F1 metric observed in sensorimotor tracts may be a critical neural substrate of RLS, enhancing our understanding of the underlying pathological changes

Genotypes, Enterotoxin Gene Profiles, and Antimicrobial Resistance of <i>Staphylococcus aureus</i> Associated with Foodborne Outbreaks in Hangzhou, China

Staphylococcal food poisoning is an illness caused by the consumption of food that contains sufficient amounts of one or more enterotoxins. In the present study, a total of 37 S. aureus isolates were recovered from leftover food, swabs from a kitchen environment, and patient feces associated with four foodborne outbreaks that occurred in Hangzhou, southeast China, and were characterized by multilocus sequence typing (MLST), spa typing, pulse-field gel electrophoresis (PFGE), and antimicrobial susceptibility. Classical enterotoxin and enterotoxin-like genes were profiled by PCR analysis. ST6-t304 was the most common clone (40.54%), followed by ST2315-t11687 (32.43%). Six clusters (A to F) were divided based on PFGE patterns, and Clusters A and C were the most common types, constituting 86.49% of all isolates. Moreover, sea was the most frequently identified enterotoxin gene (81.08%), followed by the combination of seg&#8722;sei&#8722;selm&#8722;seln&#8722;sleo&#8722;selu and sec&#8722;sell (each 48.65%). Five isolates also harbored the exotoxin cluster sed&#8722;selj&#8722;ser. In addition, resistance to penicillin (97.30%), erythromycin (37.85), tetracycline (32.43%), clindamycin, gentamicin, and sulfamethoxazole (each 10.81%) was observed. Our research demonstrated the link between leftover foods and patients by molecular typing and detecting the profiles of enterotoxin or enterotoxin-like genes in human and food isolates. S. aureus maintains an extensive repertoire of enterotoxins and drug resistance genes that could cause potential health threats to consumers

How does B-value affect HARDI reconstruction using clinical diffusion MRI data?

Background: A number of imaging factors can affect the orientation distribution function (ODF) reconstruction in high angular resolution diffusion imaging (HARDI). The aim of this study was to investigate the effect of the b-value on the HARDI reconstruction and to seek for the appropriate b-value for ODF reconstruction from clinical HARDI data. Methods: Diffusion MRI data with various b-values were collected on a GE 3T MRI scanner. To reconstruct the diffusion ODF and fiber ODF, decomposition-based spherical polar Fourier imaging and deconvolution-based constrained spherical deconvolution approaches were applied separately. The full width at half maximum (FWHM) of the ODF and the angular difference of the peaks extracted from ODF were measured to investigate the effect of b-value on the ODF reconstruction. Visual inspection of the ODF was used to evaluate the reconstructions. Results: The FWHM of the ODFs in the corpus callosum, which was chosen as the region of interest (ROI), decreased with increasing b-values. The differences in the FWHM for the diffusion ODF and the fiber ODF between the b-values of 2000 s/mm and 2500 s/mm were not significant. The angular differences of the ODF between 2000 s/mm and 2500 s/mm were lowest in both single-directional and two-directional situations. The ODFs became sharper and crossing-fiber situations were detected with an increase in b-value. B = 2000 s/mm and above revealed most of the two-way or three-way crossing-fiber structures. Conclusions: Considering both the signal-to-noise ratio and the acquisition time, b = 2000 s/mm is the basic requirement for ODF reconstruction using current HARDI methods on clinical data. This study can provide a useful reference for researchers and clinicians attempting to set appropriate scan protocols for specific HARDI experiments

Table_1_White matter microstructure alterations in idiopathic restless legs syndrome: a study combining crossing fiber-based and tensor-based approaches.DOCX

IntroductionRestless legs syndrome (RLS) is a common sensorimotor disorder characterized by an irrepressible urge to move the legs and frequently accompanied by unpleasant sensations in the legs. The pathophysiological mechanisms underlying RLS remain unclear, and RLS is hypothesized to be associated with alterations in white matter tracts.MethodsDiffusion MRI is a unique noninvasive method widely used to study white matter tracts in the human brain. Thus, diffusion-weighted images were acquired from 18 idiopathic RLS patients and 31 age- and sex-matched healthy controls (HCs). Whole brain tract-based spatial statistics (TBSS) and atlas-based analyzes combining crossing fiber-based metrics and tensor-based metrics were performed to investigate the white matter patterns in individuals with RLS.ResultsTBSS analysis revealed significantly higher fractional anisotropy (FA) and partial volume fraction of primary (F1) fiber populations in multiple tracts associated with the sensorimotor network in patients with RLS than in HCs. In the atlas based analysis, the bilateral anterior thalamus radiation, bilateral corticospinal tract, bilateral inferior fronto-occipital fasciculus, left hippocampal cingulum, left inferior longitudinal fasciculus, and left uncinate fasciculus showed significantl increased F1, but only the left hippocampal cingulum showed significantly higher FA.DiscussionThe results demonstrated that F1 identified extensive alterations in white matter tracts compared with FA and confirmed the hypothesis that crossing fiber-based metrics are more sensitive than tensor-based metrics in detecting white matter abnormalities in RLS. The present findings provide evidence that the increased F1 metric observed in sensorimotor tracts may be a critical neural substrate of RLS, enhancing our understanding of the underlying pathological changes.</p

Correspondent functional topography of the human left inferior parietal lobule at rest and under task revealed using resting-state fMRI and coactivation based parcellation

The human left inferior parietal lobule (LIPL) plays a pivotal role in many cognitive functions and is an important node in the default mode network (DMN). Although many previous studies have proposed different parcellation schemes for the LIPL, the detailed functional organization of the LIPL and the exact correspondence between the DMN and LIPL subregions remain unclear. Mounting evidence indicates that spontaneous fluctuations in the brain are strongly associated with cognitive performance at the behavioral level. However, whether a consistent functional topographic organization of the LIPL during rest and under task can be revealed remains unknown. Here, they used resting-state functional connectivity (RSFC) and task-related coactivation patterns separately to parcellate the LIPL and identified seven subregions. Four subregions were located in the supramarginal gyrus (SMG) and three subregions were located in the angular gyrus (AG). The subregion-specific networks and functional characterization revealed that the four anterior subregions were found to be primarily involved in sensorimotor processing, movement imagination and inhibitory control, audition perception and speech processing, and social cognition, whereas the three posterior subregions were mainly involved in episodic memory, semantic processing, and spatial cognition. The results revealed a detailed functional organization of the LIPL and suggested that the LIPL is a functionally heterogeneous area. In addition, the present study demonstrated that the functional architecture of the LIPL during rest corresponds with that found in task processing

The human brainnetome atlas: A new brain atlas based on connectional architecture

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states

The corpus callosum used to calculate the FWHM.

<p>The corpus callosum used to calculate the FWHM.</p

The angular difference in the diffusion ODF obtained with SPFI between each pair of b-values.

<p>(a) The angular difference for one-directional situations.(b) the angular difference for two-directional situations. The color in the grid indicates the angular difference in the ODF between the two b-values in the x-axis and the y-axis.</p