A Fully Automated Pipeline for the Determination of the Iron Microstructure Coefficient (IMC) from Multi-Echo GRE Data

Motivation: This work aims to automate analysis of the newly introduced Iron Microstructure Coefficient (IMC) to facilitate understanding of iron cellular distribution in neurological diseases for large cohort studies. Goal(s): The goal is to develop and test an automated and widely applicable pipeline for IMC analysis using quantitative susceptibility and R2* maps obtained from the same multi-echo GRE sequence. Approach: The pipeline inputs magnetic susceptibility and R2* maps, T1-w data, templates, and regions of interest (ROIs). The output is the IMC value per ROI per subject. Results: The pipeline successfully executed in 50 minutes without segmentation failure for a cohort of 28 test subjects. Impact: The automated pipeline accelerates data processing for IMC, providing enhanced standardization in a robust, reproducible, and user-friendly manner. It facilitates large-scale research, driving significant advancements in our understanding of neurological diseases, with the goal of improving accurate diagnosis for patients.