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Published on: August 30, 2013
Australia's Three System Approach to Mammographic Image Quality Assessment
Kelly Bentley-Spuur1, Minh T Chau1
1School of Dentistry and Medical Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia.
None:
Breast cancer is the most commonly diagnosed cancer among Australian women, and mammography remains the gold standard for early detection. The effectiveness of mammography relies on the consistent production of high-quality images, making image evaluation systems (IES) central to quality assurance and accreditation. This narrative review examines the three different IES currently used in Australia: the acceptable/repeatable IES used in diagnostic settings as a part of the Royal Australian and New Zealand College of Radiologists (RANZCR) Mammography Quality Assurance Program (MQAP), the BreastScreen Australia (BSA) Perfect (P), Good (G), Moderate (M), Inadequate (I) or PGMI IES, and emerging automated evaluation tools such as Volpara TruPGMI. Each IES has evolved from different clinical contexts, resulting in inconsistencies in application, criteria, and benchmarking across diagnostic and screening settings. The widely used PGMI IES has been heavily criticised for its subjectivity, poor reproducibility, and lack of a body of evidence linking image grades to diagnostic outcomes; indeed, there is a distinct lack of outcome-based evidence in the literature. Automated approaches offer objective and reproducible analysis but remain inconsistently integrated into accreditation frameworks and lack correlation to improvements in diagnostic outcomes. The coexistence of these three systems has led to fragmented image quality assessment practices that challenge both radiographer performance evaluation and program-level quality assurance. This narrative review highlights the need for a unified, evidence-based, and technologically aligned framework that reflects contemporary imaging practice. Standardising image evaluation across diagnostic and screening environments would enhance reliability, support professional development, and ensure that image quality monitoring meaningfully contributes to diagnostic accuracy and patient care.
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