Deep Learning Algorithms Improve the Detection of Subtle Lisfranc Malalignments on Weightbearing Radiographs.

Journal: Foot & ankle international
Published Date: May 19, 2022

Abstract

BACKGROUND: Detection of Lisfranc malalignment leading to the instability of the joint, particularly in subtle cases, has been a concern for foot and ankle care providers. X-ray radiographs are the mainstay in the diagnosis of these injuries; thus, improving the performance of clinicians in interpreting radiographs can noticeably affect the quality of health care in these patients. Here we assessed the performance of deep learning algorithms on weightbearing radiographs for detection of Lisfranc joint malalignment in patients with Lisfranc instability.

Authors

  • Soheil Ashkani-Esfahani
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA; Department of Orthopaedic Surgery, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands; Foot & Ankle Service, Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: sashkaniesfahani@mgh.harvard.edu.
  • Reza Mojahed-Yazdi
    Foot & Ankle Research and Innovation Laboratory (FARIL), Department of Orthopaedic Surgery, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA.
  • Rohan Bhimani
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: dr.rohanbhimani@gmail.com.
  • Gino M Kerkhoffs
    Department of Orthopaedic Surgery, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, the Netherlands. Electronic address: g.m.kerkhoffs@amsterdamumc.nl.
  • Mario Maas
    Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, The Netherlands.
  • Christopher W DiGiovanni
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA; Foot & Ankle Service, Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: cwdigiovanni@partners.org.
  • Bart Lubberts
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: Blubberts@partners.org.
  • Daniel Guss
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA; Foot & Ankle Service, Department of Orthopaedic Surgery, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: daniel.guss@mgh.harvard.edu.

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