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


Journal

Current oncology (Toronto, Ont.)
ISSN: 1718-7729
Titre abrégé: Curr Oncol
Pays: Switzerland
ID NLM: 9502503

Informations de publication

Date de publication:
25 Aug 2024
Historique:
received: 05 07 2024
revised: 14 08 2024
accepted: 24 08 2024
medline: 27 9 2024
pubmed: 27 9 2024
entrez: 27 9 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39329992
pii: curroncol31090364
doi: 10.3390/curroncol31090364
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

4917-4926

Auteurs

Alessandro Toniolo (A)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Elena Agostini (E)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Filippo Ceccato (F)

Endocrinology Unit, Department of Medicine (DIMED), University of Padova, 35122 Padua, Italy.

Irene Tizianel (I)

Endocrinology Unit, Department of Medicine (DIMED), University of Padova, 35122 Padua, Italy.

Giulio Cabrelle (G)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Amalia Lupi (A)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Alessia Pepe (A)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Cristina Campi (C)

Department of Mathematics (DIMA), University of Genova, 16126 Genoa, Italy.

Emilio Quaia (E)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

Filippo Crimì (F)

Department of Medicine (DIMED), Institute of Radiology, University of Padova, 35122 Padua, Italy.

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