Clinicoradiological Characteristics of Adrenal Incidentaloma: An Eight-Year Data From a Tertiary Center

Abstract

Background: There is a rise in the incidence of adrenal incidentaloma (AI) cases owing to routine cross-sectional imaging; however, the actual practice of handling patients with AI often differs from the current international guidelines that are evidence-based. The aim of the study was to describe the clinicoradiological presentation and biochemical profile of patients with AI at a tertiary health institution in Saudi Arabia.

Methods: This retrospective cohort study involved 418 adults who had an AI of at least 1 cm in diameter for a period of 8 years. Analysis was performed regarding their clinical presentations, radiology images, hormonal assessment, and management using SPSS version 27.0. Chi-square and associated P-value were used to analyze demographics by gender.

Results: There was a predominance of females (66.5%) and high prevalence of obesity. The majority of tumors were identified incidentally (94.3%), were unilateral (92.9%), ranged between 1 to 2 cm (62.2%) in size, and exhibited a constant morphological pattern with an average follow-up period of 2.19 ± 1.56 years. On the other hand, 89.5% of baseline computed tomography studies lacked a specific protocol for the adrenal gland. Biochemically, 38.1% of patients did not pass the 1-mg overnight dexamethasone test ≥ 50 nmol/L, thus having a high incidence of mild autonomous cortisol secretion (MACS). Other types of hormonal excess were less common. Unexpectedly, only 9.3% of the total patient population was referred to the endocrinology department. Observation was chosen in 91.0% of patients, whereas 9.0% had their tumors surgically removed.

Conclusion: While most AIs were smaller and morphologically static, there were significant deficiencies in terms of guideline compliance, especially in imaging performed according to guidelines and specialist endocrinology referral. Considering that the MACS prevalence rate is quite high, it is necessary for all healthcare organizations to develop automated, multidisciplinary care pathways.