Visual hindsight bias for abnormal mammograms in radiologists

Abstract

Purpose: Hindsight bias-where people falsely believe they can accurately predict something once they know about it-is a pervasive decision-making phenomenon, including in the interpretation of radiological images. Evidence suggests it is not only a decision-making phenomenon but also a visual perception one, where prior information about an image enhances our visual perception of the contents of that image. The current experiment investigates to what extent expert radiologists perceive mammograms with visual abnormalities differently when they know what the abnormality is (a visual hindsight bias), above and beyond being biased at a decision level.

Approach: $N=40$ experienced mammography readers were presented with a series of unilateral abnormal mammograms. After each case, they were asked to rate their confidence on a 6-point scale that ranged from confident mass to confident calcification. We used the random image structure evolution method, where the images repeated in an unpredictable order and with varied noise, to ensure any biases were visual, not cognitive.

Results: Radiologists who first saw an original image with no noise were more accurate in the max noise level condition [area under the curve $\left(\mathrm{AUC}\right)=0.60$] than those who first saw the degraded images ($\mathrm{AUC}=0.55$; difference: $p=0.005$), suggesting that radiologists' visual perception of medical images is enhanced by prior visual experience with the abnormality.

Conclusions: Overall, these results provide evidence that expert radiologists experience not only decision level but also visual hindsight bias, and have potential implications for negligence lawsuits.

Keywords: expertise; mammograms; medical imaging; radiologists; visual hindsight bias.