A visual deep learning model to predict abnormal versus normal parathyroid glands using intraoperative autofluorescence signals.

Journal: Journal of surgical oncology
PMID: 35416299

Abstract

BACKGROUND: Previous work demonstrated that abnormal versus normal parathyroid glands (PGs) exhibit different patterns of autofluorescence, with former appearing darker and more heterogenous. Our objective was to develop a visual artificial intelligence model using intraoperative autofluorescence signals to predict whether a PG is abnormal (hypersecreting and/or hypercellular) or normal before excision during surgical exploration for primary hyperparathyroidism.

Authors

  • Seyma N Avci
    Department of Endocrine Surgery, Cleveland Clinic, Cleveland, Ohio, USA.
  • Gizem Isiktas
    Department of Endocrine Surgery, Cleveland Clinic, Cleveland, Ohio, USA.
  • Onuralp Ergun
    Department of Endocrine Surgery, Cleveland Clinic, Cleveland, Ohio, USA.
  • Eren Berber
    Professor of Surgery, Department of General Surgery, Cleveland Clinic, Ohio.

Keywords

External Resources

Popular Topics
Recent Journals