Does Breast Imaging Experience During Residency Translate Into Improved Initial Performance in Digital Breast Tomosynthesis?

PURPOSE: To determine the initial digital breast tomosynthesis (DBT) performance of radiology trainees with varying degrees of breast imaging experience. METHODS: To test trainee performance with DBT, we performed a reader study, after obtaining IRB approval. Two medical students, 20 radiology residents, 4 nonbreast imaging fellows, 3 breast imaging fellows, and 3 fellowship-trained breast imagers reviewed 60 unilateral DBT studies (craniocaudal and medio-lateral oblique views). Trainees had no DBT experience. Each reader recorded a final BI-RADS assessment for each case. The consensus interpretations from fellowship-trained breast imagers were used to establish the ground truth. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated. For analysis, first- through third-year residents were classified as junior trainees, and fourth-year residents plus nonbreast imaging fellows were classified as senior trainees. RESULTS: The AUCs were .569 for medical students, .721 for junior trainees, .701 for senior trainees, and .792 for breast imaging fellows. The junior and senior trainee AUCs were equivalent (P < .01) using a two one-sided test for equivalence, with a significance threshold of 0.1. The sensitivities and specificities were highest for breast imaging fellows (.778 and .815 respectively), but similar for junior (.631 and .714, respectively) and senior trainees (.678 and .661, respectively). CONCLUSIONS: Initial performance with DBT among radiology residents and nonbreast imaging fellows is independent of years of training. Radiology educators should consider these findings when developing educational materials.

Duke Scholars

Author Lars Johannes L Grimm Radiology, Breast Imaging

Author Joseph Yuan-Chieh Lo Radiology

Author Karen Schwenk Johnson Radiology, Breast Imaging

Author Sujata Vijay Ghate Radiology, Breast Imaging

Author Maciej A Mazurowski Biostatistics & Bioinformatics, Division of Translational Bi ...