Injae Hong¹ (), Chirag Maheshwari², Jeremy Wolfe^1,3; ¹Brigham & Women's Hospital, ²Cypress Ridge High School, ³Harvard Medical School

Radiologists, screening mammograms for breast cancer, are required to search for different signs of cancer such as masses, calcifications, and structural distortions. This search should be fast, accurate, and complete. Search for more than one type of target is known as “hybrid search”. Hybrid search can impose a cost on performance that increases with the number of different types of possible targets. Accuracy might be improved by splitting a hybrid search into multiple simple searches for a single target type. This study investigated whether splitting search might be a useful intervention to improve target detection in breast cancer screening. Non-experts searched for either masses or calcifications or both in simulated 2D mammograms (Experiment 1) or while scrolling through 3D volumes of simulated digital breast tomosynthesis images (Experiment 2). Masses and calcifications were independently present with 60 % prevalence. If the target was present, participants clicked on the target and labeled the item as a mass or a calcification using a key press. They received feedback after pressing the space bar to complete the trial. There were four types of task: search for calcifications alone, search for masses alone, search for both types of targets simultaneously, or both types but one after the other, sequentially. The results showed that sequential search was advantageous compared to simultaneous search. In particular, there was a reduced level of “satisfaction of search” errors in rare cases when more than one target was present. SoS errors declined from 60% to 22% (Experiment 1) and 67% to 32% (Experiment 2). However, reduction of SoS errors on a few trials comes at substantial 20% and 28% increase in time for all trials. The standard simultaneous method of searching might be adequate, but splitting hybrid search into several simple searches may reduce errors in some, important cases.

Acknowledgements: CA207490