Dataset Information

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

ABSTRACT: Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.

SUBMITTER: Pallast N

PROVIDER: S-EPMC6559195 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Pallast Niklas N Diedenhofen Michael M Blaschke Stefan S Wieters Frederique F Wiedermann Dirk D Hoehn Mathias M Fink Gereon R GR Aswendt Markus M

Frontiers in neuroinformatics 20190604

Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in huma ...[more]

PMID: 31231202

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Project description:Background:HIV RNA is identified in cerebrospinal fluid (CSF) within eight days of estimated viral exposure. Neurological findings and impaired neuropsychological testing performance are documented in a subset of individuals with acute HIV infection (AHI). The purpose of this study was to determine whether microstructural white matter and resting-state functional connectivity (rsFC) are disrupted in AHI. Methods:We examined 49 AHI (100% male; mean age?=?30?±?SD 9.9) and 23 HIV-uninfected Thai participants (78% male; age?=?30?±?5.5) with diffusion tensor imaging (DTI) and rsFC acquired at 3 Tesla, and four neuropsychological tests (summarized as NPZ-4). MRI for the AHI group was performed prior to combination antiretroviral treatment (ART) in 26 participants and on average two days (range:1-5) after ART in 23 participants. Fractional anisotropy (FA), mean (MD), axial (AD), and radial diffusivity (RD) were quantified for DTI. Seed-based voxelwise rsFC analyses were completed for the default mode (DMN), fronto-parietal, and salience and 6 subcortical networks. rsFC and DTI analyses were corrected for family-wise error, with voxelwise comparisons completed using t-tests. Group-specific voxelwise regressions were conducted to examine relationships between imaging indices, HIV disease variables, and treatment status. Results:The AHI group had a mean (SD) CD4 count of 421(234)?cells/mm3 plasma HIV RNA of 6.07(1.1)?log10?copies/mL and estimated duration of infection of 20(5.5) days. Differences between AHI and CO groups did not meet statistical significance for DTI metrics. Within the AHI group, voxelwise analyses revealed associations between brief exposure to ART and higher FA and lower RD and MD bilaterally in the corpus callosum, corona radiata, and superior longitudinal fasciculus (p?<?0.05). Diffusion indices were unrelated to clinical variables or NPZ-4. The AHI group had reduced rsFC between left parahippocampal cortex (PHC) of the DMN and left middle frontal gyrus compared to CO (p?<?0.002). Within AHI, ART status was unrelated to rsFC. However, higher CD4 cell count associated with increased rsFC for the right lateral parietal and PHC seeds in the DMN. Direct associations were noted between NPZ-4 correspond to higher rsFC of the bilateral caudate seed (p?<?0.002). Conclusions:Study findings reveal minimal disruption to structural and functional brain integrity in the earliest stages of HIV. Longitudinal studies are needed to determine if treatment with ART initiated in AHI is sufficient to prevent the evolution of brain dysfunction identified in chronically infected individuals.

Dataset Information

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Publications

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri).

Similar Datasets

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