An open-source repository-based tool for quality control of imaging protocol compliance: demonstration in a multicentre MRI study

Objectives
Clinical translation of advanced MRI techniques can be hindered by the challenges of performing standardized multicentre imaging trials. This work aims to develop and demonstrate an automated tool for monitoring imaging protocol deviations, enabling corrective action to be taken.

Methods
A Python-based tool, integrated into the imaging repository XNAT, was developed to compare DICOM series with an agreed imaging protocol, highlighting missing series and parameter deviations. This was demonstrated through retrospective analysis of a prospectively acquired dataset from a ten-site whole-body (WB) MRI study of patients with multiple myeloma. The acquired data were compared to the relevant radiological guidelines and to the site-specific imaging protocols agreed for the study.

Results
The rate of technical software failure was 0% across 174 examinations from 10 sites. The clinical guidelines were followed in 87.9% of examinations and compliance with the site-specific imaging protocol was greater than 75.0% for all parameters. Common deviations included number of averages for diffusion-weighted imaging (DWI) and repetition time for DWI and Dixon: 85.2%, 81.7%, and 75.1%, respectively. There was a statistically significant correlation between protocol compliance and overall exam radiological image quality.

Conclusions
Repository-integrated software is presented for automated monitoring of imaging protocol compliance to support standardization in multicentre studies and clinical translation.

Advances in knowledge
This study presents a novel open-source repository-integrated software tool for automatically monitoring compliance with the expected imaging protocol. Standardized acquisition protocols are crucial in multicentre imaging studies and this tool has the potential to enhance research outcomes and support clinical translation.