Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

Carmelia Oloukoi; Anthony Dohan; Martin Gaillard; Christine Hoeffel; Lionel Groussin-Rouiller; Jérome Bertherat; Anne Jouinot; Guillaume Assié; David Fuks; Mathilde Sibony; Philippe Soyer; Anne-Sophie Jannot; Maxime Barat

doi:10.1016/j.diii.2024.03.005

Differentiation between adrenocortical carcinoma and lipid-poor adrenal adenoma using a multiparametric MRI-based diagnostic algorithm

Diagn Interv Imaging. 2024 Oct;105(10):355-363. doi: 10.1016/j.diii.2024.03.005. Epub 2024 Apr 4.

Authors

Affiliations

¹ Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France.
² Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Génomique et Signalisation des Tumeurs Endocrines, Institut Cochin, INSERM U 1016, CNRS UMR8104, Université Paris Cité, 75014 Paris, France.
³ Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Génomique et Signalisation des Tumeurs Endocrines, Institut Cochin, INSERM U 1016, CNRS UMR8104, Université Paris Cité, 75014 Paris, France; Department of Pancreatic and Endocrine Surgery, Hôpital Cochin, AP-HP, 75014 Paris, France.
⁴ Department of Radiology, Hôpital Robert Debré, CRESTIC, URCA, 51000 Reims, France.
⁵ Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Génomique et Signalisation des Tumeurs Endocrines, Institut Cochin, INSERM U 1016, CNRS UMR8104, Université Paris Cité, 75014 Paris, France; Department of Endocrinology, Hôpital Cochin, AP-HP, 75014 Paris, France.
⁶ Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Pancreatic and Endocrine Surgery, Hôpital Cochin, AP-HP, 75014 Paris, France.
⁷ Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Department of Pathology, Hôpital Cochin, AP-HP, 75014 Paris, France.
⁸ AP-HP.Centre- Université Paris Cité, Hôpital Européen Georges Pompidou, Medical Informatics, Biostatistics and Public Health Department, 75015, Paris, France; INSERM, UMR_S1138, Cordeliers Research Center, Université Paris Cité, 75006 Paris, France.
⁹ Department of Radiology, Hôpital Cochin, AP-HP, 75014 Paris, France; Université Paris Cité, Faculté de Médecine, 75006 Paris, France; Génomique et Signalisation des Tumeurs Endocrines, Institut Cochin, INSERM U 1016, CNRS UMR8104, Université Paris Cité, 75014 Paris, France. Electronic address: maxime.barat@aphp.fr.

PMID: 38575426
DOI: 10.1016/j.diii.2024.03.005

Abstract

Purpose: The purpose of this study was to evaluate the capabilities of multiparametric magnetic resonance imaging (MRI) in differentiating between lipid-poor adrenal adenoma (LPAA) and adrenocortical carcinoma (ACC).

Materials and methods: Patients of two centers who underwent surgical resection of LPAA or ACC after multiparametric MRI were retrospectively included. A training cohort was used to build a diagnostic algorithm obtained through recursive partitioning based on multiparametric MRI variables, including apparent diffusion coefficient and chemical shift signal ratio (i.e., tumor signal intensity index). The diagnostic performances of the multiparametric MRI-based algorithm were evaluated using a validation cohort, alone first and then in association with adrenal tumor size using a cut-off of 4 cm. Performances of the diagnostic algorithm for the diagnosis of ACC vs. LPAA were calculated using pathology as the reference standard.

Results: Fifty-four patients (27 with LPAA and 27 with ACC; 37 women; mean age, 48.5 ± 13.3 [standard deviation (SD)] years) were used as the training cohort and 61 patients (24 with LPAA and 37 with ACC; 47 women; mean age, 49 ± 11.7 [SD] years) were used as the validation cohort. In the validation cohort, the diagnostic algorithm yielded best accuracy for the diagnosis of ACC vs. LPAA (75%; 46/61; 95% CI: 55-88) when used without lesion size. Best sensitivity was obtained with the association of the diagnostic algorithm with tumor size (96%; 23/24; 95% CI: 80-99). Best specificity was obtained with the diagnostic algorithm used alone (76%; 28/37; 95% CI: 60-87).

Conclusion: A multiparametric MRI-based diagnostic algorithm that includes apparent diffusion coefficient and tumor signal intensity index helps discriminate between ACC and LPAA with high degrees of specificity and accuracy. The association of the multiparametric MRI-based diagnostic algorithm with adrenal lesion size helps maximize the sensitivity of multiparametric MRI for the diagnosis of ACC.

Keywords: Adrenal gland disease; Adrenal gland neoplasm; Adrenocortical carcinoma; Diagnostic algorithm; Magnetic resonance imaging.

MeSH terms

Adrenal Cortex Neoplasms* / diagnostic imaging
Adrenal Gland Neoplasms / diagnostic imaging
Adrenocortical Adenoma* / diagnostic imaging
Adrenocortical Carcinoma* / diagnostic imaging
Adult
Algorithms*
Diagnosis, Differential
Female
Humans
Lipids
Male
Middle Aged
Multiparametric Magnetic Resonance Imaging* / methods
Retrospective Studies
Sensitivity and Specificity

Substances

Lipids