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

الملخص EN

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.