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Modern trends in the radiological diagnostics of adrenal tumors

https://doi.org/10.14341/probl13733

Abstract

The editorial examines modern trends and new technologies in the radiological diagnostics of adrenal tumors, such as dual-energy computed tomography and textural analysis methods utilizing machine learning. Particular attention is paid to the differential diagnosis of adrenal masses, including multi‑class differentiation. Research data demonstrating the high diagnostic efficacy of these approaches are presented, and the importance of an interdisciplinary and personalized approach in patient management is emphasized. The material reflects current achievements and future prospects for the development of radiological methods in endocrinology and oncology.

About the Authors

N. G. Mokrysheva
Endocrinology Research Centre
Russian Federation

Natalia G. Mokrysheva - MD, PhD, Professor,

 11 Dm. Ulyanova street, 117036 Moscow



N. V. Tarbaeva
Endocrinology Research Centre
Russian Federation

Natalia V. Tarbaeva - MD, PhD,

 11 Dm. Ulyanova street, 117036 Moscow



References

1. Bel'tsevich DG, Troshina EA, Mel'nichenko GA, Platonova NM, Ladygina DO, Chevais A. Project of clinical guidelines «Adrenal incidentaloma». Endocrine Surgery. 2021;15(1):4-26. (in Russ). doi: https://doi.org/10.14341/serg12712

2. Fassnacht M, Tsagarakis S, Terzolo M, et al. European Society of Endocrinology clinical practice guidelines on the management of adrenal incidentalomas, in collaboration with the European Network for the Study of Adrenal Tumors. European Journal of Endocrinology. 2023;189:G1-42. doi: https://doi.org/10.1093/ejendo/lvad066

3. Dinnes J, Bancos I, Ferrante di Ruffano L, et al. Management of endocrine disease: imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis. Eur J Endocrinol. 2016;175(2):R51-R64. doi: https://doi.org/10.1530/EJE-16-0461

4. Hindman NM, Megibow AJ. One-stop shopping: dual-energy CT for the confident diagnosis of adrenal adenomas. Radiology. 2020;296(2):333-334. doi: https://doi.org/10.1148/radiol.2020201718

5. Ju Y, Liu A, Dong Y, et al. The value of nonenhanced single source dual energy CT for differentiating metastases from adenoma in adrenal glands. Acad Radiol. 2015;22(7):834-839. doi: https://doi.org/10.1016/j.acra.2015.03.004

6. Tarbaeva NV, Manaev AV, Kornelyuk AYu, et al. Dual-energy CT for differential diagnosis of adrenal lesions. Problems of Endocrinology. 2025;71(5):10-18. (In Russ.). doi: https://doi.org/10.14341/probl13671

7. Khayrieva AV, Tarbaeva NV, Godzenko MV, et al. The possibility of using virtual unenhanced images created by using dual-energy CT data in the differential diagnostic of adrenal tumors: a retrospective study. Diagnostic radiology and radiotherapy. 2025;16(2):56-63. (In Russ.). doi: https://doi.org/10.22328/2079-5343-2025-16-2-56-63

8. Lubner MG, Smith AD, Sandrasegaran K, et al. CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges. RadioGraphics. 2017;37:1483-1503. doi: https://doi.org/10.1148/rg.2017170056

9. Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: The Bridge between Medical Imaging and Personalized Medicine. Nat Rev Clin Oncol. 2017;14:749-762. doi: https://doi.org/10.1038/nrclinonc.2017.141

10. Ferro M, Tataru OS, Carrieri G, et al. Artificial intelligence and radiomics applications in adrenal lesions: a systematic review. Ther Adv Urol. 2025;17. doi: https://doi.org/10.1177/17562872251352553

11. Crimì F, Quaia E, Cabrelle G, et al. Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review. Int J Mol Sci. 2022;23(2):637. doi: https://doi.org/10.3390/ijms23020637

12. Zhang H, Lei H, Pang J. Diagnostic performance of radiomics in adrenal masses: a systematic review and meta-analysis. Front Oncol. 2022;12:975183. doi: https://doi.org/10.3389/fonc.2022.975183 13. Tucci L, Vara G, Morelli V, et al. Prediction of adrenal masses nature through texture analysis and deep learning: preliminary results from ENS@T RADIO-AI multicentric study. Endocr Abstr. 2024;99. doi: https://doi.org/10.1530/endoabs.99.OC11.3

13. Manaev AV, Tarbaeva NV, Buryakina SA, et al. Classification of adrenocortical carcinoma, pheochromocytoma, and adrenal adenomas using contrast-enhanced computed tomography with machine learning and texture features: a cross-sectional study. Digital Diagnostics. 2025;6(4):541-557. (In Russ.). doi: https://doi.org/10.17816/DD659812

14. Manaev AV, Tarbaeva NV, Roslyakova AA, et al. Predicting high proliferative Ki-67 index in patients with adrenocortical carcinoma based on texture analysis of contrast-enhanced computed tomography images: a cross-sectional study. Digital Diagnostics. 2025;6(3):360-372. (In Russ.). doi: https://doi.org/10.17816/DD643532

15. Tarbaeva NV, Manaev AV, Ivashchenko KV, et al. The value of CT texture analysis in predicting mitotic activity and morphological variants of adrenocortical carcinoma. Front Radiol. 2025;5:1635425. doi: https://doi.org/10.3389/fradi.2025.1635425

16. Fassnacht M, Dekkers O, Else T, et al. European Society of Endocrinology Clinical Practice Guidelines on the management of adrenocortical carcinoma in adults, in collaboration with the European Network for the Study of Adrenal Tumors. Eur J Endocrinol. 2018;179(4):G1-G46. doi: https://doi.org/10.1530/eje-18-0608


Supplementary files

1. Figure 1. Flowchart of management tactics for patients with adrenal incidentalomas.
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Type Исследовательские инструменты
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2. Figure 2. Visualization of adrenal incidentalomas.
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Type Исследовательские инструменты
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Review

For citations:


Mokrysheva N.G., Tarbaeva N.V. Modern trends in the radiological diagnostics of adrenal tumors. Problems of Endocrinology. 2026;72(1):8-12. (In Russ.) https://doi.org/10.14341/probl13733

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ISSN 0375-9660 (Print)
ISSN 2308-1430 (Online)