Affiliation:
1. Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
2. Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
Abstract
Objectives: To investigate performance of adrenal CT-derived multivariate prediction models in differentiating adenomas with cortisol hypersecretion from the other subtypes. Methods: This retrospective study included 127 patients who underwent adrenal CT and had a surgically proven adrenal adenoma. Adenoma subtypes were defined according to biochemical test results: Group A, overt cortisol hypersecretion; Group B, mild cortisol hypersecretion; Group C, aldosterone hypersecretion; and Group D, non-function. Two independent readers analyzed size, attenuation, and washout properties of adenomas, and performed quantitative and qualitative analyses for assessing contralateral adrenal atrophy. Actual and internally validated areas under the curves (AUCs) of adrenal CT-derived multivariate prediction models for differentiating adenomas with cortisol hypersecretion from the other subtypes were assessed Results: In differentiating Group A from the other groups, the actual and internally validated AUCs of the prediction model were 0.856 (95% confidence interval [CI]: 0.786, 0.926) and 0.847 (95% CI: 0.695, 0.999) for Reader 1, respectively, and 0.901 (95% CI: 0.845, 0.956) and 0.897 (95% CI: 0.783, 1.000) for Reader 2, respectively. In differentiating Group B from groups C and D, the actual and internally validated AUCs of the prediction model were 0.777 (95% CI: 0.687, 0.866) and 0.760 (95% CI: 0.552, 0.969) for Reader 1, respectively, and 0.783 (95% CI: 0.690, 0.875) and 0.765 (95% CI: 0.553, 0.977) for Reader 2, respectively. Conclusion: Adrenal CT may be useful in differentiating adenomas with cortisol hypersecretion from the other subtypes. Advances in knowledge: Adrenal CT may benefit in adrenal adenoma subtyping.
Publisher
Oxford University Press (OUP)
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Cited by
1 articles.
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