A collaborative approach to improving prostate magnetic resonance image quality.

OBJECTIVE

Poor magnetic resonance imaging (MRI) quality can lead to missed prostate cancer diagnoses. Our institution had variability in pre-MRI patient preparation, limited collaboration between radiologists and technologists, and no formal, routine image quality auditing process. The Prostate Imaging Quality system version 1 (PI-QUAL v1) is an established framework for assessing prostate MRI quality. Our quality improvement team aimed to increase the percentage of exams that received a PI-QUALv1 score of ≥ 4 and the percentage with at least one Diffusion Weighted Imaging (DWI) sequence rated optimal.

METHODS

In partnership with the American College of Radiology (ACR) Learning Network, we introduced numerous interventions to improve our baseline workflow. During our Intervention Phase (May- September 2023), our team standardized pre-MRI patient instructions and documentation regarding nil by mouth (NPO) status and bladder emptying. MRI technologists received image quality education and were involved in the image scoring process. Our team also used weekly PI-QUALv1 scoring criteria which was later embedded into the reporting system. Interventions were maintained during a Sustainment Phase (October 2023- January 2024).

RESULTS

1206 MRI prostate exams were audited. From the Pre-intervention to Sustainment Phase, the percentage of exams with PI-QUAL score ≥ 4 increased from 90% (95% CI: 87-94%) to 97% (95% CI: 95-99%). The percentage of exams meeting DWI criteria increased from 77% (95% CI: 74-79%) to 83% (95% CI: 78-88%). Team members reported that integrating scoring into the reporting system saved time. Patients and staff reported that standardized instructions led to a better understanding of how patient preparation improves image quality.

CONCLUSIONS

Consistent patient preparation, team collaboration, and standardized quality scoring led to promising quality trends without using enema. PI-QUAL scores and DWI quality reached the upper limits of performance previously described by the ACR Learning Network Prostate MR QI Collaborative.