Open Access 01-08-2012 | Breast
The Breast Imaging Reporting and Data System (BI-RADS) in the Dutch breast cancer screening programme: its role as an assessment and stratification tool
Published in: European Radiology | Issue 8/2012
Login to get accessAbstract
Objectives
To assess the suitability of the Breast Imaging Reporting and Data System (BI-RADS) as a quality assessment tool in the Dutch breast cancer screening programme.
Methods
The data of 93,793 screened women in the Amsterdam screening region (November 2005–July 2006) were reviewed. BI-RADS categories, work-up, age, final diagnosis and final TNM classification were available from the screening registry. Interval cancers were obtained through linkage with the cancer registry. BI-RADS was introduced as a pilot in the Amsterdam region before the nationwide introduction of digital mammography (2009–2010).
Results
A total of 1,559 women were referred to hospital (referral rate 1.7 %). Breast cancer was diagnosed in 485 women (detection rate 0.52 %); 253 interval cancers were reported, yielding a programme sensitivity of 66 % and specificity of 99 %. BI-RADS 0 had a lower positive predictive value (PPV, 14.1 %) than BI-RADS 4 (39.1 %) and BI-RADS 5 (92.9 %; P < 0.0001). The number of invasive procedures and tumour size also differed significantly between BI-RADS categories (P < 0.0001).
Conclusion
The significant differences in PPV, invasive procedures and tumour size match with stratification into BI-RADS categories. It revealed inter-observer variability between screening radiologists and can thus be used as a quality assessment tool in screening and as a stratification tool in diagnostic work-up.
Key Points
• The BI-RADS atlas is widely used in breast cancer screening programmes.
• There were significant differences in results amongst different BI-RADS categories.
• Those differences represented the radiologists’ degree of suspicion for malignancy, thus enabling stratification of referrals.
• BI-RADS can be used as a quality assessment tool in screening.
• Training should create more uniformity in applying the BI-RADS lexicon.