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

• Published in: Frontiers in neuroinformatics Vol. 13; p. 42
• Main Authors: Pallast, Niklas, Diedenhofen, Michael, Blaschke, Stefan, Wieters, Frederique, Wiedermann, Dirk, Hoehn, Mathias, Fink, Gereon R., Aswendt, Markus
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 04.06.2019; Frontiers Media S.A
• Subjects: Algorithms; atlas registration; Automation; Bioinformatics; Brain mapping; Brain research; Data analysis; Data processing; Functional magnetic resonance imaging; MRI; Neural networks; Neuroimaging; Neuroscience; Neurosciences; NMR; Noise; Nuclear magnetic resonance; preclinical neuroimaging; processing pipeline; Rodents; Scanners; Software; Stroke; Structure-function relationships; Germany; processing pipeline; atlas registration; MRI; preclinical neuroimaging; stroke
• ISSN: 1662-5196; 1662-5196
• DOI: 10.3389/fninf.2019.00042

Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive high-resolution microscopy and 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.