A CT Radiomics Analysis of the Adrenal Masses: Can We Discriminate Lipid-poor Adenomas from the Pheochromocytoma and Malignant Masses?

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dc.authoridMendi, Bokebatur Ahmet Rasit/0000-0002-6102-2188
dc.contributor.authorMendi, Bokebatur Ahmet Rasit
dc.contributor.authorGulbay, Mutlu
dc.date.accessioned2024-11-07T13:32:03Z
dc.date.available2024-11-07T13:32:03Z
dc.date.issued2023
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractAims: The aim of the study is to demonstrate a non-invasive alternative method to aid the decision making process in the management of adrenal masses. Background: Lipid-poor adenomas constitute 30% of all adrenal adenomas. When discovered incidentally, additional dynamic adrenal examinations are required to differentiate them from an adrenal malignancy or pheochromocytoma. Objective: In this retrospective study, we aimed to discriminate lipid-poor adenomas from other lipid-poor adrenal masses by using radiomics analysis in single contrast phase CT scans. Materials and Methods: A total of 38 histologically proven lipid-poor adenomas (Group 1) and 38 cases of pheochromocytoma or malignant adrenal mass (Group 2) were included in this retrospective study. Lesions were segmented volumetrically by two independent authors, and a total of 63 sizes, shapes, and first- and second-order parameters were calculated. Among these parameters, a logit-fit model was produced by using 6 parameters selected by the LASSO (least absolute shrinkage and selection operator) regression. The model was cross-validated with LOOCV (leave-one-out cross-validation) and 1000-bootstrap sampling. A random forest model was also generated in order to use all parameters without the risk of multicollinearity. This model was examined with the nested cross-validation method. Results: Sensitivity, specificity, accuracy and AUC were calculated in test sets as 84.2%, 81.6%, 82.9% and 0.829 in the logit fit model and 91%, 80%, 82.8% and 0.975 in the RF model, respectively. Conclusion: Predictive models based on radiomics analysis using single-phase contrast-enhanced CT can help characterize adrenal lesions.
dc.identifier.doi10.2174/1573405619666221115124352
dc.identifier.endpage1030
dc.identifier.issn1573-4056
dc.identifier.issn1875-6603
dc.identifier.issue9
dc.identifier.pmid36380444
dc.identifier.scopus2-s2.0-85148756171
dc.identifier.scopusqualityQ3
dc.identifier.startpage1018
dc.identifier.urihttps://doi.org/10.2174/1573405619666221115124352
dc.identifier.urihttps://hdl.handle.net/11480/15191
dc.identifier.volume19
dc.identifier.wosWOS:001040664100005
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherBentham Science Publ Ltd
dc.relation.ispartofCurrent Medical Imaging
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectRadiomics
dc.subjectadrenal
dc.subjectcomputed tomography
dc.subjecttexture analysis
dc.subjectlogit fit
dc.subjectrandom forest
dc.titleA CT Radiomics Analysis of the Adrenal Masses: Can We Discriminate Lipid-poor Adenomas from the Pheochromocytoma and Malignant Masses?
dc.typeArticle

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