How are false negative cases perceived by mammographers? Which abnormalities are misinterpreted and which go undetected?
conference contributionposted on 03.06.2010, 13:16 by Hazel J. Scott, Alastair Gale, Sue Hill
A radiographic ‘false negative’ or a case which has been ‘missed’ can be categorised in terms of errors of search (where gaze does not fall upon the abnormality); detection (a perceptual error where the abnormality may be physically ‘seen’ but remains undetected) and misinterpretation (a perceptual error whereby an abnormality, although detected, is not deemed worthy of further assessment). This study aims to investigate perceptual errors in mammographic film-reading and will focus on the later of the two error types, namely errors of misinterpretation and errors of non-detection. Previous research has shown, on a self-assessment scheme of recent and difficult breast-screening cases, that certain feature types are susceptible to errors of misinterpretation and others to errors of non-detection. This self assessment scheme, ‘PERFORMS’ (Personal Performance in Mammographic Screening), is undertaken by the majority (at present over 90%) of breast-screening mammographers in the UK Breast Screening Programme. The scheme is completed biannually and confidentially and participants receive immediate and detailed feedback on their performance. Feedback from the scheme includes information detailing their false negative decisions including case classifications (benign or malignant), feature type (masses, calcification, asymmetries, architectural distortions and others) and case perception error (percentage of misinterpretation and percentage of non-detection). Results from a recent round of PERFORMS (n=506), revealed that certain feature types had significantly higher percentages of error overall (including architectural distortion and asymmetries), and that these feature types also showed significant differences for error type. Implications for real-life screening practice were explored using real-life self-reported data on years of screening experience.
- Computer Science