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• W2045359905 abstract "Objectives To differentiate among atypical adenomatous hyperplasia (AAH), bronchioloalveolar carcinoma (BAC), and adenocarcinoma showing ground-glass opacity (GGO) on CT scans, we conducted a study to determine the optimal parameter on CT number analysis using three-dimensional (3D) computerized quantification. Methods From the CT numbers of GGO lesions obtained by 3D computerized quantification, CT number histogram pattern, peak CT number on the histogram, mean CT number, and the 5th to 95th percentile CT numbers were analyzed to determine the optimal parameter for differentiation among AAH (n = 10), BAC (n = 21), and adenocarcinoma (n = 12). Results While the CT number histogram showed one peak in all 10 of the AAH lesions (100%), it showed two peaks in 8 of 21 BAC lesions (38%), and in 5 of 12 adenocarcinoma lesions (42%). For differentiation between AAH and BAC, the 75th percentile CT number with a cutoff value of −584 Hounsfield units (HU) was optimal, with a sensitivity of 0.90 and a specificity of 0.81. For differentiation between BAC and adenocarcinoma, a mean CT number with a cutoff value of −472 HU was optimal, with a sensitivity of 0.75 and a specificity of 0.81. Conclusions From the analysis of CT numbers of GGO lesions obtained by 3D computerized quantification, we conclude the following: (1) two peaks on the CT number histogram can rule out AAH; (2) the 75th percentile is the optimal CT number for differentiating between AAH and BAC; and (3) the mean CT number is the optimal CT number for differentiating between BAC and adenocarcinoma. To differentiate among atypical adenomatous hyperplasia (AAH), bronchioloalveolar carcinoma (BAC), and adenocarcinoma showing ground-glass opacity (GGO) on CT scans, we conducted a study to determine the optimal parameter on CT number analysis using three-dimensional (3D) computerized quantification. From the CT numbers of GGO lesions obtained by 3D computerized quantification, CT number histogram pattern, peak CT number on the histogram, mean CT number, and the 5th to 95th percentile CT numbers were analyzed to determine the optimal parameter for differentiation among AAH (n = 10), BAC (n = 21), and adenocarcinoma (n = 12). While the CT number histogram showed one peak in all 10 of the AAH lesions (100%), it showed two peaks in 8 of 21 BAC lesions (38%), and in 5 of 12 adenocarcinoma lesions (42%). For differentiation between AAH and BAC, the 75th percentile CT number with a cutoff value of −584 Hounsfield units (HU) was optimal, with a sensitivity of 0.90 and a specificity of 0.81. For differentiation between BAC and adenocarcinoma, a mean CT number with a cutoff value of −472 HU was optimal, with a sensitivity of 0.75 and a specificity of 0.81. From the analysis of CT numbers of GGO lesions obtained by 3D computerized quantification, we conclude the following: (1) two peaks on the CT number histogram can rule out AAH; (2) the 75th percentile is the optimal CT number for differentiating between AAH and BAC; and (3) the mean CT number is the optimal CT number for differentiating between BAC and adenocarcinoma." @default.
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• W2045359905 date "2007-09-01" @default.
• W2045359905 modified "2023-10-05" @default.
• W2045359905 title "Differential Diagnosis of Ground-Glass Opacity Nodules" @default.
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• W2045359905 doi "https://doi.org/10.1378/chest.07-0793" @default.
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