Can Radiomics Provide Additional Diagnostic Value for Identifying Adrenal Lipid-Poor Adenomas From Non-Adenomas on Unenhanced CT? - Zhang, Binhao; Zhang, Huangqi; Li, Xin; Jin, Shengze; Yang, Jiawen; Pan, Wenting; Dong, Xue; Chen, Jin; Ji, Wenbin (Frontiers in Oncology, 2022)
Background: It is difficult for radiologists to differentiate adrenal lipid-poor adenomas from non-adenomas; nevertheless, this is important, as the clinical interventions required are different. Purpose: To develop an unenhanced computed tomography (CT)-based radiomics model for identifying adrenal lipid-poor adenomas, to assist in clinical decision-making. Materials and methods: Patients with adrenal lesions who underwent CT between January 2015 and August 2021 were retrospectively recruited from two independent institutions. Patients from institution 1 were randomly divided into training and test sets, while those from institution 2 were used as the external validation set. The unenhanced attenuation and tumor diameter were measured to build a conventional model. Radiomics features were extracted from unenhanced CT images and selected features were used to build a radiomics model. A nomogram model combining the conventional and radiomic features was also constructed. All the models were developed in the training set and were validated in the test and external validation sets, and the diagnostic performance of the models for identifying adrenal lipid-poor adenomas was compared. Results: A total of 292 patients with 141 adrenal lipid-poor adenomas and 151 non-adenomas were analyzed. Patients with adrenal lipid-poor adenomas tend to have lower unenhanced attenuation and smoother image textures. The areas under the curve of the conventional, radiomic, and nomogram models were 0.94, 0.93, and 0.96, respectively. There was no difference in diagnostic performance between the conventional and nomogram models in all datasets (all p < 0.05). Conclusions: Our unenhanced CT-based nomogram model could effectively distinguish adrenal lipid-poor adenomas. The diagnostic power of conventional unenhanced CT imaging features may be underestimated and further exploration is worthy.