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Updated: Jun 5, 2026

A Novel Method: Super-selective Adrenal Venous Sampling
Published on: September 15, 2017
Differential diagnosis of ACTH-dependent Cushing's syndrome: Biochemical, imaging, and predictive approaches
Wilfredo Antonio Rivera-Martínez1, Carlos Esteban Builes-Montaño2, Alejandro Román-González3
1Endocrinology Department, IPS Neurum, Medellín, Colombia; Departament of Research and Education Department, Clínica de Occidente S.A., Cali, Colombia.
Abstract:
Endogenous hypercortisolism remains a high-stakes diagnostic challenge in which delays or misclassification drive excess morbidity and mortality. This chapter synthesizes an evidence-based, physiology-anchored approach to the differential diagnosis of ACTH-dependent Cushing's syndrome, integrating clinical phenotyping, first-line biochemistry, dynamic testing, imaging, and invasive confirmation. We first outline bedside features that raise or lower the pre-test probability of Cushing disease (CD) versus ectopic ACTH syndrome (EAS). Then, the initial laboratory tests (nocturnal salivary cortisol, 24-h urinary free cortisol, low-dose dexamethasone suppression, ACTH) and their pathophysiological correlates are reviewed. For dynamic tests, we summarize indications and interpretation of CRH, desmopressin, and high-dose dexamethasone suppression, highlighting their value as composites rather than stand-alone arbiters. The imaging section prioritizes 3 T dynamic pituitary MRI for CD and thin-slice CT for suspected EAS, with targeted use of ^68Ga-SSTRPET/CT (ectopic NETs), ^18F-FDG (high-grade biology), ^18F-DOPA (PPGL), and emerging pituitary-targeted PET tracers as adjuncts. When non-invasive data are discordant or indeterminate, bilateral inferior petrosal sinus sampling (BIPSS) remains the reference: verify selectivity (prolactin IPS:peripheral > 1.8) and apply ACTHIPS:peripheral cut-offs (≥ 2 basal or ≥ 3 post-stimulus), with optional optimized thresholds and prolactin-adjusted ratios in suboptimal flow. Finally, we propose a step-by-step diagnostic algorithm that sequences these elements pragmatically and discuss predictive models as complementary tools to prioritize testing and resource use.
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