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. (27th January 2014)

• Record Type: Journal Article
• Authors: Girometti, Rossano; Fabris, Francesco; Sgarro, Andrea; Zanella, Gloria; Pullini, Serena; Cereser, Lorenzo; Como, Giuseppe; Zuiani, Chiara; Bazzocchi, Massimo
• Other Names: Hall Damien Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2014(2014)
• Publication Date: 2014-01-27
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2014/587976
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : 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.