Can radiologists recognize that a computer has identified cancers that they have overlooked?

Robert M. Nishikawa; Alexandra Edwards; Robert A. Schmidt; John Papaioannou; Michael N. Linver

doi:10.1117/12.656351

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10 March 2006 Can radiologists recognize that a computer has identified cancers that they have overlooked?

Robert M. Nishikawa, Alexandra Edwards, Robert A. Schmidt, John Papaioannou, Michael N. Linver

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Proceedings Volume 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment; 614601 (2006) https://doi.org/10.1117/12.656351
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

For computer-aided detection (CADe) to be effective, the computer must be able to identify cancers that a radiologist misses clinically and the radiologist must be able to recognize that a cancer was missed when he or she reviews the computer output. There are several papers indicating CADe can detected clinically missed cancers. The purpose of this study is to examine whether radiologists can use the CADe output effectively to detect more cancers. Three-hundred mammographic cases, which included current and previous exams, were collected: 66 cases containing a missed cancer that was recognized in retrospect and 234 were normal cases. These were analyzed by a commercial CADe system. An observer study with eight MQSA-qualified radiologists was conducted using a sequential reading method. That is, the radiologist viewed the mammograms and scored the case. Then they reviewed the CADe output and rescored the case. The computer had a sensitivity of 55% with an average of 0.59 false detections per image. For all cancers (n=69), the radiologists had a sensitivity of 58% with no aid and 64% with aid (p=0.002). In cases where the computer detected the cancer in all views that the cancer was visible (n=17), the radiologists had a sensitivity of 74% unaided and increased to 85% aided (p=0.02). In cases where the computer missed the cancer in one view (n=21), the radiologists had a sensitivity of 65% unaided and 72% aided (p<0.001). The radiologists, on average, ignored 20% of all correct computer prompts.

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Robert M. Nishikawa, Alexandra Edwards, Robert A. Schmidt, John Papaioannou, and Michael N. Linver "Can radiologists recognize that a computer has identified cancers that they have overlooked?", Proc. SPIE 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 614601 (10 March 2006); https://doi.org/10.1117/12.656351

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