PURPOSE: To evaluate the interobserver variability and accuracy of an algorithm for anatomic localization of small nodules evident on thin-section computed tomographic (CT) images of the lungs. MATERIALS AND METHODS: Four experienced chest radiologists independently evaluated thin-section CT images in 58 patients by using an algorithm and a standard score sheet. Nodules were placed into four possible anatomic locations or categories: perilymphatic, random, associated with small airways disease, or centrilobular. Algorithm accuracy was assessed by comparing the localization by the observers to that expected for each specific disease in the study group on the basis of reports in the literature. Interobserver variability was assessed by placing cases into one of three groups: (a) complete concordance, (b) triple concordance, and (c) discordant. RESULTS: All observers agreed in 79% (46 of 58) of the cases with regard to nodule localization; three of the four concurred in an additional 17% (10 of 58). The observers were correct in 218 (94%) of 232 localizations in the 58 cases. There were no apparent differences in the number of either discordant or incorrect localizations between the observers. The most noteworthy source of error and of disagreement between observers was the confusion of perilymphatic and small airways disease-associated nodules in a small number of cases. CONCLUSION: The proposed algorithm is reproducible and accurate in the majority of cases and facilitates nodule localization at thin-section CT.
PURPOSE: To evaluate the interobserver variability and accuracy of an algorithm for anatomic localization of small nodules evident on thin-section computed tomographic (CT) images of the lungs. MATERIALS AND METHODS: Four experienced chest radiologists independently evaluated thin-section CT images in 58 patients by using an algorithm and a standard score sheet. Nodules were placed into four possible anatomic locations or categories: perilymphatic, random, associated with small airways disease, or centrilobular. Algorithm accuracy was assessed by comparing the localization by the observers to that expected for each specific disease in the study group on the basis of reports in the literature. Interobserver variability was assessed by placing cases into one of three groups: (a) complete concordance, (b) triple concordance, and (c) discordant. RESULTS: All observers agreed in 79% (46 of 58) of the cases with regard to nodule localization; three of the four concurred in an additional 17% (10 of 58). The observers were correct in 218 (94%) of 232 localizations in the 58 cases. There were no apparent differences in the number of either discordant or incorrect localizations between the observers. The most noteworthy source of error and of disagreement between observers was the confusion of perilymphatic and small airways disease-associated nodules in a small number of cases. CONCLUSION: The proposed algorithm is reproducible and accurate in the majority of cases and facilitates nodule localization at thin-section CT.
Authors: George A Margaritopoulos; Athanasia Proklou; Eleni Lagoudaki; Argiro Voloudaki; Nikos M Siafakas; Katerina M Antoniou Journal: J Med Case Rep Date: 2012-08-31