Deep learning approach for differentiating indeterminate adrenal masses using CT imaging.

Journal: Abdominal radiology (New York)
PMID: 37369921

Abstract

PURPOSE: Distinguishing stage 1-2 adrenocortical carcinoma (ACC) and large, lipid poor adrenal adenoma (LPAA) via imaging is challenging due to overlapping imaging characteristics. This study investigated the ability of deep learning to distinguish ACC and LPAA on single time-point CT images.

Authors

  • Yashbir Singh
    Biomedical Engineering, Chung Yuan Christian University, Taoyuan.
  • Zachary S Kelm
    Department of Radiology, Mayo Clinic, Rochester, MN, USA.
  • Shahriar Faghani
    Mayo Clinic Artificial Intelligence Lab, Department of Radiology, Mayo Clinic, 200 1st Street, S.W., Rochester, MN, 55905, USA.
  • Dana Erickson
    Division of Endocrinology, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA.
  • Tal Yalon
    Department of General Surgery, Mayo Clinic, La Crosse, WI, USA.
  • Irina Bancos
    Division of Endocrinology, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA.
  • Bradley J Erickson
    Department of Radiology, Radiology Informatics Lab, Mayo Clinic, Rochester, MN 55905, United States.

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