The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning.

Journal: Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PMID: 37823903

Abstract

PURPOSE: Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has shown promising potential for early and reliable detection of isolated syndesmotic instability using 3D volumetric measurements. While these measurements have been reported to be highly accurate, they are also experience-dependent, time-consuming, and need a particular 3D measurement software tool that leads the clinicians to still show more interest in the conventional diagnostic methods for syndesmotic instability. The purpose of this study was to increase accuracy, accelerate analysis time, and reduce interobserver bias by automating 3D volume assessment of syndesmosis anatomy using WBCT scans.

Authors

  • Alireza Borjali
    Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, Massachusetts.
  • 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.
  • Rohan Bhimani
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: dr.rohanbhimani@gmail.com.
  • 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.
  • Orhun K Muratoglu
    Department of Orthopaedic Surgery, Harris Orthopaedics Laboratory, Massachusetts General Hospital, Boston, Massachusetts.
  • 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.
  • Kartik Mangudi Varadarajan
    Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, USA.
  • Bart Lubberts
    Foot & Ankle Research and Innovation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston 02114, MA, USA. Electronic address: Blubberts@partners.org.

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