Differentiating small (≤1 cm) focal liver lesions as metastases or cysts by means of computed tomography: a case-study to illustrate a fuzzy logic-based method to assess the impact of diagnostic confidence on radiological diagnosis.

PURPOSE: To quantify the impact of diagnostic confidence on radiological diagnosis with a fuzzy logic-based method. MATERIALS AND METHODS: Twenty-two oncologic patients with 20 cysts and 30 metastases ≤1 cm in size found at 64-row computed tomography were included. Two readers (R1/R2) expressed diagnoses as a subjective level of confidence P(d) in malignancy within the interval [0,1] rather than on a "crisp" basis (malignant/benign); confidence in benignancy was 1 - p(d). When cross-tabulating data according to the standard of reference, 2 × 2 table cells resulted from the aggregation between p(d)/1 - p(d) and final diagnosis. We then assessed (i) readers diagnostic performance on a fuzzy and crisp basis; (ii) the "divergence" δ(F, C) (%) as a measure of how confidence impacted on crisp diagnosis. RESULTS: Diagnoses expressed with lower confidence increased fuzzy false positives compared to crisp ones (from 0 to 0.2 for R1; from 1 to 2.4 for R2). Crisp/fuzzy accuracy was 94.0%/93.6% (R1) and 94.0/91.6% (R2). δ(F, C) (%) was larger in the case of the less experienced reader (R2) (up to +7.95% for specificity). According to simulations, δ(F, C) (%) was negative/positive depending on the level of confidence in incorrect diagnoses. CONCLUSION: Fuzzy evaluation shows a measurable effect of uncertainty on radiological diagnoses.