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Updated: Feb 10, 2026

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
Published on: December 16, 2022
Characteristics of Adrenal Incidentalomas in a Large, Prospective Computed Tomography-Based Multicenter Study: The
Seong Hee Ahn1, Jae Hyeon Kim2, Seung Hee Baek3
1Division of Endocrinology and Metabolism, Inha University Hospital, Inha University School of Medicine, Incheon, Korea.
Purpose:
Previous studies on adrenal incidentalomas (AIs) are limited by their retrospective design, small numbers of patients, Western populations, or use of an outdated imaging technique. We investigated the characteristics of AIs in Korean patients and compared them with those reported in the largest retrospective study in Italy to discover the effects of improved imaging techniques and ethnicity differences.
Materials And Methods:
This was a prospective, multicenter, cross-sectional observational study including 1005 Korean patients. Levels of plasma adrenocorticotrophic hormone, 24-h urinary free cortisol (UFC), serum cortisol after a 1 mg-dexamethasone suppression test, 24-h urinary fractionated metanephrine, and plasma aldosterone and plasma renin activity were measured. All AIs were characterized using computed tomography (CT).
Results:
Compared with the results of the Italian study, AIs in Korean patients were observed more frequently in men and predominantly on the left side. Korean patients with AIs were slightly younger, and fewer patients underwent surgery. Most AIs were nonfunctional in both studies, while fewer subclinical hypercortisolism and more primary aldosteronism (PA) cases were detected in Korean patients. In our study, high UFC levels showed very low sensitivity, compared to those in the Italian study. In pheochromocytoma or PA cases, there were no hormonal differences between the studies. AIs in Korean patients were smaller, such that a lower cutoff size for detecting adrenocortical carcinoma (ACC) could be warranted.
Conclusion:
Recent advances in CT technology were leveraged to provide accurate characteristics of AIs and to detect smaller ACCs.
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