Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review.


Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
07 Jan 2022
Historique:
received: 04 12 2021
revised: 31 12 2021
accepted: 05 01 2022
entrez: 21 1 2022
pubmed: 22 1 2022
medline: 11 2 2022
Statut: epublish

Résumé

Adrenal incidentalomas (AIs) are incidentally discovered adrenal neoplasms. Overt endocrine secretion (glucocorticoids, mineralocorticoids, and catecholamines) and malignancy (primary or metastatic disease) are assessed at baseline evaluation. Size, lipid content, and washout characterise benign AIs (respectively, <4 cm, <10 Hounsfield unit, and rapid release); nonetheless, 30% of adrenal lesions are not correctly indicated. Recently, image-based texture analysis from computed tomography (CT) may be useful to assess the behaviour of indeterminate adrenal lesions. We performed a systematic review to provide the state-of-the-art of texture analysis in patients with AI. We considered 9 papers (from 70 selected), with a median of 125 patients (range 20-356). Histological confirmation was the most used criteria to differentiate benign from the malignant adrenal mass. Unenhanced or contrast-enhanced data were available in all papers; TexRAD and PyRadiomics were the most used software. Four papers analysed the whole volume, and five considered a region of interest. Different texture features were reported, considering first- and second-order statistics. The pooled median area under the ROC curve in all studies was 0.85, depicting a high diagnostic accuracy, up to 93% in differentiating adrenal adenoma from adrenocortical carcinomas. Despite heterogeneous methodology, texture analysis is a promising diagnostic tool in the first assessment of patients with adrenal lesions.

Identifiants

pubmed: 35054823
pii: ijms23020637
doi: 10.3390/ijms23020637
pmc: PMC8776161
pii:
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article Review Systematic Review

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Filippo Crimì (F)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy.

Emilio Quaia (E)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy.

Giulio Cabrelle (G)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy.

Chiara Zanon (C)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy.

Alessia Pepe (A)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy.

Daniela Regazzo (D)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Endocrine Disease Unit, University-Hospital of Padova, 35128 Padua, Italy.

Irene Tizianel (I)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Endocrine Disease Unit, University-Hospital of Padova, 35128 Padua, Italy.

Carla Scaroni (C)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Endocrine Disease Unit, University-Hospital of Padova, 35128 Padua, Italy.

Filippo Ceccato (F)

Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Endocrine Disease Unit, University-Hospital of Padova, 35128 Padua, Italy.

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