TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity

• Main Authors: Guillaume Theaud, Jean-Christophe Houde, Arnaud Boré, François Rheault, Felix Morency, Maxime Descoteaux
• Format: Article
• Language: English
• Published: Elsevier 2020-09-01
• Series: NeuroImage
• Subjects: Diffusion MRI; Pipeline; Tractography; Reproducibility; BIDS; Nextflow
• Online Access: http://www.sciencedirect.com/science/article/pii/S105381192030375X

Diffusion MRI tractography processing pipeline requires a large number of steps (typically 20+ steps). If parameters of these steps, number of threads, and random seed generators are not carefully controlled, the resulting tractography can easily be non-reproducible and non-replicable, even in test-test experiments. To handle these issues, we developed TractoFlow. TractoFlow is fully automatic from raw diffusion weighted images to tractography. The pipeline also outputs classical diffusion tensor imaging measures and several fiber orientation distribution function measures. TractoFlow supports the recent Brain Imaging Data Structure (BIDS) format as input and is based on two engines: Nextflow and Singularity. In this work, the TractoFlow pipeline is evaluated on three databases and shown to be efficient and reproducible from 98% to 100%, depending on parameter choices. Moreover, it is easy to use for non-technical users, with little to no installation requirements. TractoFlow is publicly available for academic research and is an important step forward for better structural brain connectivity mapping.