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Abstract #5001

Digging deeper into the pervasive problem of non-compliance in MR datasets

Harsh Sinha1 and Pradeep Reddy Raamana1
1University of Pittsburgh, Pittsburgh, PA, United States

Synopsis

Keywords: Data Acquisition, Software Tools, Protocol Compliance

Motivation: Large MRI datasets from multiple sites are not monitored for protocol compliance and dataset integrity.

Goal(s): We previously demonstrated the pervasiveness of protocol non-compliance in MR datasets using our open source tool mrQA. We aim to produce deeper insights with vertical audit and analyze the common patterns of non-compliance.

Approach: We processed the large and open ABCD study verifying relationships between sequences in their protocol.

Results: We observed issues on non-compliance in coil, shim setting, and pixel spacing. We also observed significant disparities across vendors, scanners and sites. This underscores the necessity for tools such as mrQA that can identify non-compliance across vendors/sites.

Impact: Non-compliance in acquisition parameters is a pervasive problem in MR datasets. It is impractical to “hope” for protocol compliance across sites, and scanners. Our tool, mrQA can enable researchers to continuously monitor and identify non-compliant scans in a practical manner.

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