ANNALS OF NUCLEAR MEDICINE, 2026 (SCI-Expanded, Scopus)
Objective Adrenal lesions encompass a wide spectrum ranging from benign, non-functional adenomas to potentially metastatic tumors such as pheochromocytoma (PHEO). In addition to clinical and biochemical evaluation, imaging plays a pivotal role in their characterization. This study aimed to investigate the diagnostic contribution of quantitative parameters obtained from Ga-6(8)-DOTATATE PET/CT (DOTA PET) in the differential diagnosis of adrenal lesions. Methods Patients who underwent DOTA PET between 2013 and 2025 for adrenal lesion characterization, as well as those with incidentally detected adrenal lesions on DOTA PET performed for other indications, were retrospectively analyzed. Patients without adrenal pathology on DOTA PET constituted the control group. The final diagnoses was established using histopathology or radiological imaging. Quantitative parameters, including SUVmax of the lesion, liver, and normal adrenal gland, as well as volumetric indices -somatostatin receptor expressing tumor volume (SSTR-TV) and total lesion somatostatin receptor expression (SSTR-TL)- were calculated to assess lesion volume and receptor density. Results PHEO demonstrated significantly higher SUVmax and volumetric parameters compared with adrenal adenomas and normal adrenal glands (p < 0.05). ROC analysis yielded a sensitivity of 77% and specificity of 80% for SUVmax, using a threshold of 13. Volumetric parameters showed superior diagnostic accuracy: median SSTR-TV2.5 was markedly greater in PHEO than adenoma, and a threshold of 3.8 provided 94% sensitivity and 95% specificity (AUC = 0.97, p < 0.05). DeLong analysis confirmed that SSTR-TV2.5 outperformed SUVmax and lesion size (p < 0.05). Conclusion Volumetric parameters derived from DOTA PET, particularly SSTR-TV, provided high diagnostic accuracy in differentiating PHEOs from adrenal adenomas. These results indicate that quantitative assessment can serve as a valuable, non-invasive approach in characterizing adrenal lesions.