Deep learning-enhanced zero echo time MRI for glenohumeral assessment in shoulder instability: a comparative study with CT.

Journal: Skeletal radiology
PMID: 39572485

Abstract

PURPOSE: To evaluate image quality and lesion conspicuity of zero echo time (ZTE) MRI reconstructed with deep learning (DL)-based algorithm versus conventional reconstruction and to assess DL ZTE performance against CT for bone loss measurements in shoulder instability.

Authors

  • Laura Carretero-Gómez
    GE HealthCare, Munich, Germany. laura.carreterogomez@gehealthcare.com.
  • Maggie Fung
    GE Healthcare, Waukesha, Wisconsin, USA.
  • Florian Wiesinger
    GE Global Research, Munich, Germany.
  • Michael Carl
    GE HealthCare, San Diego, CA, USA.
  • Graeme McKinnon
    GE HealthCare, Waukesha, WI, USA.
  • Jose de Arcos
    GE HealthCare, Little Chalfont, Amersham, UK.
  • Sagar Mandava
    GE Healthcare, Atlanta, GA, 30308, USA.
  • Santiago Arauz
    Shoulder Unit, Clínica CEMTRO, Madrid, Spain.
  • Eugenia Sánchez-Lacalle
    Department of Radiology, Clínica CEMTRO, Madrid, Spain.
  • Satish Nagrani
    Department of Radiology, Clínica CEMTRO, Madrid, Spain.
  • Juan Manuel López-Alcorocho
    Research Unit, Clínica CEMTRO, Madrid, Spain.
  • Elena Rodríguez-Íñigo
    Research Unit, Clínica CEMTRO, Madrid, Spain.
  • Norberto Malpica
    Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain.
  • Mario Padrón
    Department of Radiology, Clínica CEMTRO, Madrid, Spain.

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