Project 1: Self-Triage by 2D Full-field Digital Mammography or Synthetic Images

One method of breast cancer screening involves radiologists reading digital tomosynthesis (DBT) images. DBT consists of a 3D stack of x-ray "slices" through the breast. The exam is accompanied by a 2D image like a standard mammogram, a single x-ray of the breast. In a screening setting, most cases are normal. Sometimes it is obvious that a case is normal from a quick look at the 2D image. It would speed up the process of screening if readers could dismiss a clearly normal case on the basis of the 2D image, alone, without looking at the DBT images. Obviously, the investigators would only want to "triage" cases in this way if the investigators were almost perfectly sure that no cancers would be missed. In this study, the investigators look at radiologist's willingness to triage cases and on the accuracy of their answers. In addition, the investigators ask about the impact of an Artificial Intelligence (AI) opinion. Would it be possible to triage an image on the basis of the AI opinion, alone? Radiologists will look at each case for up to five seconds and offer an opinion (on a 1-10 scale) about how sure they are that a case is normal. Next, they will see the opinion of the AI. Finally, they will say (using a 1-10) scale, how willing they would be for the AI to triage this case without human intervention. This study is the start of an effort to understand the conditions under which radiologists might be willing to declare a case "normal" with little or no human examination.

Sex

All

Minimum age

18 Years

Inclusion Criteria:

* Must be Radiologists or radiology trainees
* some experience reading mammography.

Exclusion Criteria:

* acuity less than 20/25 with correction