Comput Math Methods Med - Differentiating small (=1cm) 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.

Tópicos

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Resumo

RPOSE: 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 =1cm 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" d(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). d(F, C) (%) was larger in the case of the less experienced reader (R2) (up to +7.95% for specificity). According to simulations, d(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.

Resumo Limpo

rpose quantifi impact diagnost confid radiolog diagnosi fuzzi logicbas methodmateri method twentytwo oncolog patient cyst metastas cm size found row comput tomographi includ two reader rr express diagnos subject level confid pd malign within interv rather crisp basi malignantbenign confid benign pd crosstabul data accord standard refer tabl cell result aggreg pd pd final diagnosi assess reader diagnost perform fuzzi crisp basi ii diverg df c measur confid impact crisp diagnosisresult diagnos express lower confid increas fuzzi fals posit compar crisp one r r crispfuzzi accuraci r r df c larger case less experienc reader r specif accord simul df c negativeposit depend level confid incorrect diagnosesconclus fuzzi evalu show measur effect uncertainti radiolog diagnos

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