Improved Breast Cancer Detection with Artificial Intelligence in a Real-World Digital Breast Tomosynthesis Screening Program.

Journal: Clinical breast cancer
Published Date:

Abstract

OBJECTIVE: The purpose of this study is to compare radiologists' breast cancer screening performance before and after the implementation of an artificial intelligence (AI) detection system for digital breast tomosynthesis (DBT).

Authors

  • Joshua A Nepute
    Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indiana University Health - West Central Region, Avon, IN.
  • Meridith Peratikos
    Biostatistics Consulting LLC, Kensington, MD, USA.
  • Alicia Y Toledano
    Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Biostatistics Consulting, Kensington, Md (A.Y.T.); iCAD, Nashua, NH (S.P., S.V.F., J.G., J.W.H.); and Intrinsic Imaging, Bolton, Mass (J.E.B.).
  • John P Salvas
    Indiana University School of Medicine, Indianapolis, IN.
  • Haley Delks
    Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indiana University Health - West Central Region, Avon, IN.
  • Julie L Shisler
    Hospital of the University of Pennsylvania, 3400 Spruce Street, 1 Silverstein Place, Philadelphia, PA 19104.
  • Jeffrey W Hoffmeister
    Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce St, Philadelphia, PA 19104 (E.F.C.); Biostatistics Consulting, Kensington, Md (A.Y.T.); iCAD, Nashua, NH (S.P., S.V.F., J.G., J.W.H.); and Intrinsic Imaging, Bolton, Mass (J.E.B.).
  • Colleen M Madden
    Department of Radiology and Imaging Sciences, Indiana University School of Medicine, IUH Ball Memorial Hospital, Muncie, IN. Electronic address: comadden@iu.edu.

Keywords

No keywords available for this article.