EYES2023 ESE Young Endocrinologists and Scientists (EYES) 2023 Oral communication 3: Adrenal Tumors and Neuroendocrine Tumors (7 abstracts)
Identification of adrenocortical masses malignancy through radiomics: A pilot study
Lorenzo Tucci 1 , Giulio Vara 2 , Ilaria Improta 3 , Antonio De Leo 4 , Saverio Selva 5 , Caterina Balacchi 2 , Donatella Santini 6 , Cristina Mosconi 2 , Valentina Vicennati 3 , Uberto Pagotto 7 & Guido Di Dalmazi 8
1Alma Mater Studiorum University of Bologna, Irccs Sant’orsola Polyclinic Endocrinology Unit, Medical and Surgical Sciences, Bologna, Italy; 2Alma Mater Studiorum University of Bologna, Irccs Sant’orsola Polyclinic Radiology Unit, Italy; 3Alma Mater Studiorum University of Bologna, Irccs Sant’orsola Polyclinic Endocrinology Unit, Italy; 4Alma Mater Studiorum University of Bologna, Irccs Sant’orsola Polyclinic Anatomic Pathology Unit, Italy; 5Irccs Sant’orsola Polyclinic General and Endocrine Surgery Unit, Italy; 6Irccs Sant’orsola Polyclinic Anatomic Pathology Unit, Italy; 7St. Orsola General Hospital, Internal Medicin/Endocr Unit, Bologna, Italy; 8Division of Endocrinology, Dept. of Medical and Surgical Sciences, Division of Endocrinology, Department of Medical and Surgical Sciences, Alma Mater University of Bologna, S. Orsola-Malpighi Hospital, Bologna, Italy, Bologna, Italy.
Background: Adrenal lipid poor adenoma (LPA) and adrenocortical cancer (ACC) may overlap in computerized tomography (CT). Radiomics recently emerged as new tool for malignant behavior identification.
Aim: To assess radiomics utility for identification of ACC and LPA in adrenocortical masses with unenhanced (UE) CT scan attenuation≥10 Hounsfield Unit (HU).
Methods: We retrospectively enrolled 50 patients, 38 radiologically defined LPA with 6–12 months of radiologic stability or benign histological exam (n=11), and 12 ACC with histological exam (2 patients with Weiss score=3; 4 patient with ki67≥10%). All patients underwent CT with UE scan, arterial (ACE), venous (VCE) and 15’ delayed (DCE) contrast enhanced phases, on which radiomics was performed with LIFEx software (©LITO 2022–2023). We performed a two-steps multivariate analysis for each CT phase to evaluate predictors of malignancy (Weiss score≥3). Multivariate analysis first-step was completed within single radiomics feature classes, then first-step predictors were altogether employed for multivariate analysis second-step. Second-step predictors were utilized for receiver operating characteristic curve analysis and estimation of positive (PPV) and negative predictive value (NPV).
Results: In UE, surface to volume ratio (SVR) and Run Length Non-Uniformity (RLNU) predicted malignancy (Odds Ratio (OR)=2.718; 95% Confidence Interval (CI)=1.56–4.75; P<0.001), with 83.3% sensitivity, 94.3% specificity, 83.3% PPV, 94.7% NPV. In ACE, SVR and Feret diameter predicted malignancy [OR=2.718; 95% CI=1.57–4.745; P<0.001], with 83.3% sensitivity, 92.1% specificity, 76.9% PPV, 94.6% NPV. In VCE, SVR and compacity predicted malignancy [OR=2.719; 95% CI=1.54–4.79; P<0.001], with 83.3% sensitivity, 92.1% specificity, 76.9% PPV, 94.5% NPV. In DCE, SVR and RLNU predicted malignancy [OR=2.718; 95% CI=1.54–4.79; P<0.001], with 83.3% sensitivity, 91.9% specificity, 76.9% PPV, 94.5% NPV.
Conclusion: Radiomics seems useful to identify adrenal masses nature, even without CT contrast enhanced phases. SVR and RLNU seem to be powerful predictors of adrenocortical masses malignancy.
Volume 93
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