Satisfaction of Search in Diagnostic Radiology

The long-term objective of this proposal is to understand the perception of multiple abnormalities in an imaging examination and to develop strategies for improved diagnostic accuracy and patient outcome. We are one of the few laboratories in the world pursuing the goal of reducing detection errors through a better understanding of the underlying perceptual processes involved.

Failure to detect an abnormality is the most common class of error in diagnostic imaging and generally is considered the most serious by the medical community. Many of these errors have been attributed to “satisfaction of search,” which occurs when a lesion is not reported because discovery of another abnormality has “satisfied” the goal of the search.

Although we have gained some understanding of the mechanisms of satisfaction of search (SOS), there are significant questions that remain. The failure of human pattern recognition underlying satisfaction of search error has not been explained. Our previous research may offer the key: the clinical importance of abnormalities may determine how much they interfere with detection of other abnormalities.

Helical computed tomography (CT) may replace radiography as the most common and useful radiology examination because it offers more accurate and earlier lesion detection. But the large number of images produced by modern CT and other cross-sectional modalities may quickly overload the radiologists’ perceptual resources, creating increased risk of satisfaction of search error. There have been no experimental studies of SOS error in the advanced imaging.

There are few interventions that hold promise to remedy SOS error. The goal of computer-aided diagnosis is to improve cancer detection. Whether computer-aided diagnosis can reduce SOS error has not been considered or studied until now.

We propose six definitive experiments to approach the complex questions that remain. The research methods will include experiments using analysis of receiver operating characteristic curves, the time course of detection responses and termination of search, and display commands issued by the observer to interrogate the image data array. The knowledge gained from this programmatic research will lead to reduction in observer error.

Software for Satisfaction of Search in Diagnostic Radiology

Lesion Removal Program