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Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review
Authors:Filippo Crimì  Emilio Quaia  Giulio Cabrelle  Chiara Zanon  Alessia Pepe  Daniela Regazzo  Irene Tizianel  Carla Scaroni  Filippo Ceccato
Affiliation:1.Department of Medicine DIMED, University of Padova, 35128 Padua, Italy; (F.C.); (E.Q.); (G.C.); (C.Z.); (A.P.); (D.R.); (I.T.); (C.S.);2.Institute of Radiology, University-Hospital of Padova, 35128 Padua, Italy;3.Endocrine Disease Unit, University-Hospital of Padova, 35128 Padua, Italy
Abstract: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.
Keywords:adrenal glands  computed tomography  texture analysis  radiomics
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