Exploring the impact of work experience on the detection of specific cancers across different breast density levels on screening mammograms

Abstract

PurposeThis study explores the attributes of true positive and false positive rates in screening mammogram test sets assessed by breast screening radiologists in order to identify the combined impact of prior images, breast density and lesion features with experience factors linked to diagnostic performance. Methods869 radiologists’ first-time readings across nine mammogram BREAST test sets with 361 normal and 179 cancer mammograms were collected between 2014 and 2023. Participants viewed digital mammograms on diagnostic monitors and localized abnormal lesions. The performances of readers in normal and cancer cases were compared with the ground truth and analyzed in four quartiles of breast density, lesion types and the availability of prior images using Man-Whitney U and Kruskal Wallis tests. The general linear model was applied to determine independent and significant covariates that affected the true positives and false positives. The correlation of the readers’ experience with the performances in different case and lesion features was explored using Spearman test. ResultsThe combination of lesion appearance and the availability of prior images had a significant impact on false positive results (P=0.033). The model that included lesion appearance, breast density, and no prior image status significantly influenced case true positives of readers (P=0.026). Meanwhile, the model considering only lesion appearance and breast density (P=0.002) had a significant effect on lesion true positives. There was a positive correlation observed between the number of cases read per week and readers’ performances, including TP rates and lesion sensitivity across various lesion types (P<0.05). Radiologists reading over 100 cases weekly achieved 80 % true positive rate for architectural distortion, asymmetric density, and masses, while this threshold increased to over 150 cases for calcifications. Detecting mixed lesion types required reading more than 60 cases weekly. Radiologists with over 5 years’ experience achieved 70–75 % accuracy in localizing cancer lesions. ConclusionFindings highlight the significant combined impact of breast density, prior image availability, lesion characteristics, and breast screening readers’ experience on breast cancer detection.