Could CT Radiomic Analysis of Benign Adrenal Incidentalomas Suggest the Need for Further Endocrinological Evaluation?

Curr Oncol. 2024 Aug 25;31(9):4917-4926. doi: 10.3390/curroncol31090364.

Abstract

We studied the application of CT texture analysis in adrenal incidentalomas with baseline characteristics of benignity that are highly suggestive of adenoma to find whether there is a correlation between the extracted features and clinical data. Patients with hormonal hypersecretion may require medical attention, even if it does not cause any symptoms. A total of 206 patients affected by adrenal incidentaloma were retrospectively enrolled and divided into non-functioning adrenal adenomas (NFAIs, n = 115) and mild autonomous cortisol secretion (MACS, n = 91). A total of 136 texture parameters were extracted in the unenhanced phase for each volume of interest (VOI). Random Forest was used in the training and validation cohorts to test the accuracy of CT textural features and cortisol-related comorbidities in identifying MACS patients. Twelve parameters were retained in the Random Forest radiomic model, and in the validation cohort, a high specificity (81%) and positive predictive value (74%) were achieved. Notably, if the clinical data were added to the model, the results did not differ. Radiomic analysis of adrenal incidentalomas, in unenhanced CT scans, could screen with a good specificity those patients who will need a further endocrinological evaluation for mild autonomous cortisol secretion, regardless of the clinical information about the cortisol-related comorbidities.

Keywords: adenoma; adrenals; hormonal hypersecretion; incidentaloma; machine learning; radiomics.

MeSH terms

  • Adrenal Gland Neoplasms* / diagnostic imaging
  • Aged
  • Female
  • Humans
  • Male
  • Middle Aged
  • Radiomics
  • Retrospective Studies
  • Tomography, X-Ray Computed* / methods

Supplementary concepts

  • Adrenal incidentaloma

Grants and funding

This research received no external funding.