Improving Prostate MR Image Quality in Practice - Initial results from the ACR Prostate MR Image Quality Improvement Collaborative

Andrei S Purysko; Kay Zacharias-Andrews; Kandice Garcia Tomkins; Ismail Baris Turkbey; Francesco Giganti; Mythreyi Bhargavan-Chatfield; David B Larson; ACR Prostate MR Image Quality Improvement Collaborative

doi:10.1016/j.jacr.2024.04.008

Improving Prostate MR Image Quality in Practice - Initial results from the ACR Prostate MR Image Quality Improvement Collaborative

J Am Coll Radiol. 2024 May 8:S1546-1440(24)00416-2. doi: 10.1016/j.jacr.2024.04.008. Online ahead of print.

Authors

Andrei S Purysko¹, Kay Zacharias-Andrews², Kandice Garcia Tomkins³, Ismail Baris Turkbey⁴, Francesco Giganti⁵, Mythreyi Bhargavan-Chatfield⁶, David B Larson⁷; ACR Prostate MR Image Quality Improvement Collaborative

Collaborators

ACR Prostate MR Image Quality Improvement Collaborative:
Jeffrey Weinreb, Clare Tempany, Christopher Smith, Ann Hester, Kevin Chang, Sara Martin, Rajan Gupta, Erica Owenby, Logan McLean, Linda Campbell, Alessandro Furlan, Andrew Grills

Affiliations

¹ Section of Abdominal Imaging, Imaging Institute, Cleveland Clinic, Cleveland, OH, USA. Electronic address: puryska@ccf.org.
² American College of Radiology, Reston, VA, USA.
³ Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
⁴ Molecular Imaging Program, National Cancer Institute, Bethesda, MD, USA. Electronic address: https://twitter.com/radiolobt.
⁵ Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK; Division of Surgery & Interventional Science, University College London, London, UK. Electronic address: https://twitter.com/giga_fra.
⁶ American College of Radiology, Reston, VA, USA. Electronic address: https://twitter.com/MythreyiC.
⁷ Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA. Electronic address: https://twitter.com/larson_david_b.

PMID: 38729590
DOI: 10.1016/j.jacr.2024.04.008

Abstract

Objective: Variability in prostate MRI quality is an increasingly recognized problem that negatively affects patient care. This report aims to describe the results and key learnings of the first cohort of the ACR Learning Network Prostate MR Image Quality Improvement Collaborative.

Methods: Teams from five organizations in the U.S. were trained on a structured improvement method. After reaching a consensus on image quality and auditing their images using the Prostate Imaging Quality (PI-QUAL) system, teams conducted a current state analysis to identify barriers to obtaining high-quality images. Through plan-do-study-act cycles involving frontline staff, each site designed and tested interventions targeting image quality key drivers. The percentage of exams meeting quality criteria (i.e., PI-QUAL score ≥ 4) was plotted on a run chart, and project progress was reviewed in weekly meetings. At the collaborative level, the goal was to increase the percentage of exams with PI-QUAL ≥ 4 to at least 85%.

Results: Across 2380 exams audited, the mean weekly rates of prostate MR exams meeting image quality criteria increased from 67% (range: 60-74%) at baseline to 87% (range: 80-97%) upon program completion. The most commonly employed interventions were MR protocol adjustments, development and implementation of patient preparation instructions, personell training and development of an auditing process mechanism.

Conclusion: A Learning Network model, where organizations share knowledge and work together toward a common goal, can improve prostate MR image quality at multiple sites simultaneously. The inaugural cohort's key learnings provide a roadmap for improvement on a broader scale.

Keywords: Learning Network; Magnetic Resonance Imaging; Prostate Cancer; Quality improvement.