Quality assurance (QA) plays a central role in every successful breast cancer screening program. At its core, QA ensures that mammography images are accurate, consistent, and clinically reliable, enabling radiologists to detect breast cancer as early and precisely as possible.
But while the importance of quality assurance is universally recognized, the methods used to evaluate image quality vary widely across Europe. These regional differences pose unique challenges for training, comparison, and technology implementation – making flexibility in QA systems not just beneficial, but essential.
The European Landscape: One Goal, Many Systems
Across Europe, countries have developed and adopted distinct QA classification frameworks to evaluate mammographic image quality. While each system aims to uphold high diagnostic standards, their approaches differ significantly:
- 4 classes PGMI (Perfect, Good, Moderate, Inadequate) – e.g. used in Switzerland and Spain
- 3 classes (Stufe 1, 2, 3) – e.g. in Germany
- 2 classes (Acceptable / Inadequate) – e.g. in the Netherlands
- 0 classes (points system) – e.g. in Belgium
Each framework brings its own strengths and limitations:
- PGMI offers granularity and detail, helping identify subtle improvements — but it can be harder to standardize.
- PGI is simplified and efficient, yet may lose nuanced insight.
- AIA provides flexibility and speed, but with limited categories.
This variation reflects the diversity of healthcare systems, professional cultures, and educational standards — but also introduces fragmentation that can impact quality consistency, cross-border training, and innovation adoption.
Why Flexibility Is the Missing Link
As AI and digital tools enter the radiology workflow, the need for interoperable, adaptive QA systems becomes critical.
Rigid QA solutions that only work with one classification system create bottlenecks and complexity:
- Radiographers moving between countries face different evaluation criteria and expectations.
- Centralized training programs are difficult to standardize across borders.
- Innovations in AI-driven quality assurance struggle to scale if every country demands custom configurations.
Flexibility is the answer — and not just as a technical feature, but as a strategic enabler for health systems and policymakers.
By supporting multiple QA frameworks in parallel, screening programs can:
- Maintain their national standards and legal compliance
- Facilitate cross-border learning and mobility
- Enable scalable AI and automation adoption
- Improve consistency in patient outcomes at the European level
How b-rayZ Enables Flexible, Scalable QA
At b-rayZ, we’ve built our b-quality module from the ground up with European diversity in mind.
We recognize that radiographers and quality managers shouldn’t have to choose between standardization and adaptability — and that AI must be a supportive companion, not a restrictive tool.
Here’s how b-quality meets these demands:
- ✅ Framework-agnostic: Compatible with PGMI, PGI, and AIA classification systems
- ✅ Plug-and-play scalability: Easily integrates across multi-site screening programs, regardless of national QA framework
- ✅ Built for quality improvement: Offers real-time feedback and training support tailored to each program’s structure
- ✅ Supports equity and excellence: Helps radiographers achieve consistent high performance, even in underserved or high-pressure environments
With b-quality, healthcare systems no longer have to compromise between local workflows and cross-national progress. They gain a tool that adapts to their needs while driving quality forward.
The Future of QA in Mammography: Adapt to Advance
The conversation around which QA framework is “best” will likely continue for years. But as technology evolves and cross-border collaboration increases, it’s clear that the future of breast screening lies in interoperable, adaptive systems that honor local needs while supporting shared goals.
Tools like b-quality represent a new generation of quality assurance — one that’s built not just for today’s variation, but for tomorrow’s convergence.
It’s time to move beyond rigid definitions and toward a more unified, adaptable, and high-impact approach to breast screening QA.
Discover how b-quality is reshaping image quality assessment across Europe.
Learn more about the module here.
