Solving the Pervasive Problem of Protocol Non-Compliance in MRI using an Open-Source toolmrQA

Abstract

AbstractPooling data across diverse sources acquired by multisite consortia requires compliance with a predefined reference protocol i.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Traditionally, this has been an arduous and manual process due to difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance. Moreover, issues of protocol compliance is often overlooked for lack of realization that parameter values are routinely improvised/modified locally at various sites. The inconsistencies in acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether. We developed an open-source tool called mrQA to automatically assess protocol compliance on standard dataset formats such as DICOM and BIDS, and study the patterns of non-compliance in over 20 open neuroimaging datasets, including the large ABCD study. We demonstrate that the lack of compliance is rather pervasive. The frequent sources of non-compliance include but not limited to deviations in Repetition Time (TR), Echo Time (TE), Flip Angle (FA), and Phase Encoding Direction (PED). We also noticed that GE and Philips scanners exhibited higher rates of non-compliance relative to the Siemens scanners in the ABCD dataset. We strongly recommend continuous monitoring of datasets for protocol compliance before any pre-or post-processing, ideally right after the acquisition, to avoid the silent propagation of severe/subtle issues. While we focus our analysis on neuroimaging datasets, our tool mrQA is domain-agnostic and can work with any DICOM-based datasets.