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The neuroimaging community is steering towards increasingly large and diverse datasets acquired by multisite consortia. Pooling data across diverse sources requires consistency and compliance with the acquisition protocols i.e., ensuring different sites and scanners for a given project have used identical or compatible MR physics parameter values. Conventionally, protocol compliance has been an ad-hoc and manual process that is easily error-prone. Moreover, this is often overlooked for lack of realization that parameter values are routinely improvised locally at various sites in different ways. Ensuring compliance is an arduous process for many reasons, including difficulties in working with the complicated DICOM standard and lack of resources allocated towards protocol compliance and data management. The overlooked inconsistencies across acquisition protocols can reduce SNR, statistical power, and in the worst case, may invalidate the results altogether due to incompatible values. To address this issue, we developed an assistive tool to interface with multiple dataset formats (DICOM, BIDS) and automatically generate protocol compliance reports. In this paper, we describe the origins of the issue and demonstrate its prevalence based on our analysis of the ABCD dataset and, over 20 open neuroimaging datasets. We found that many of these datasets exhibit non-compliance in acquisition parameters. We propose a practical quality assurance (QA) solution to address the issue and offer an open-source tool mrQAto monitor protocol compliance in neuroimaging datasets. |
