Clinical Scorecard: Enhancing the Efficacy of Breast Radiographers in Tomosynthesis Screening through Automated Software Assessment

At a Glance

Key Highlights

• Proper breast positioning and compression are critical for high-quality mammography and DBT images, impacting cancer detection accuracy and patient comfort.
• Automated software tools like Volpara Analytics enable systematic, objective, and comprehensive assessment of positioning and compression, overcoming limitations of visual methods such as sampling bias and inter-observer variability.
• Use of automated assessment in a quality improvement project demonstrated potential to enhance individual radiographer performance and increase the proportion of high-quality mammograms.

Guideline-Based Recommendations

Diagnosis

• Use digital breast tomosynthesis (DBT) with double reading by breast radiologists for screening women at age 45 with personalized protocols based on breast density and risk.
• Assess breast positioning quality using standardized criteria such as the PGMI Image Evaluation System adapted internationally.

Management

• Implement automated software tools (e.g., Volpara Analytics) to evaluate breast positioning and compression parameters systematically during DBT screening.
• Set target compression pressure range between 7 and 15 kPa to optimize image quality and patient comfort.

Monitoring & Follow-up

• Continuously collect and analyze positioning and compression data via automated software to provide feedback and quality assurance for radiographers.
• Monitor the percentage of images classified as perfect or good (% P + G) as a key performance metric.

Risks

• Inadequate breast positioning or compression can reduce image quality, increase radiation dose, and impair cancer detection accuracy.
• Visual assessment methods alone may be insufficient due to time constraints and inter-observer variability.

Patient & Prescribing Data

Women aged 45 undergoing personalized breast cancer screening with DBT based on breast density and risk profile

Automated software assessment supports personalized screening by improving image quality and potentially enhancing early cancer detection through better radiographer performance.

Clinical Best Practices

• Ensure comprehensive training and personalized feedback for radiographers using automated positioning and compression assessment tools.
• Adopt standardized international positioning criteria (e.g., PGMI) integrated into automated software for objective quality evaluation.
• Maintain compression pressure within the recommended range (7–15 kPa) to balance image quality and patient comfort.
• Use double reading by breast radiologists to improve diagnostic accuracy in DBT screening.
• Incorporate automated quality assurance data into continuous professional development and quality improvement initiatives.

References

• National Health System Breast Screening Program PGMI Image Evaluation System
• American College of Radiology Mammography Quality Control Manual
• Volpara Health Volpara Analytics Software
• RIBBS Study ClinicalTrials.gov NCT05675085
• Tyrer-Cuzick Breast Cancer Risk Model