Deep-learning reconstructed lumbar spine 3D MRI for surgical planning: pedicle screw placement and geometric measurements compared to CT.

Journal: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PMID: 38472429

Abstract

PURPOSE: To test equivalency of deep-learning 3D lumbar spine MRI with "CT-like" contrast to CT for virtual pedicle screw planning and geometric measurements in robotic-navigated spinal surgery.

Authors

  • Frederik Abel
    Department of Spine Surgery, Hospital for Special Surgery, New York, New York, USA.
  • Darren R Lebl
    Department of Spine Surgery, Hospital for Special Surgery, New York, New York, USA.
  • George Gorgy
    Department of Spine Surgery, Hospital for Special Surgery, 535 E 70th Street, New York, NY, 10021, USA.
  • David Dalton
    School of Mathematics & Statistics, University of Glasgow, Glasgow G12 8QQ, United Kingdom.
  • J Levi Chazen
    Department of Radiology and Imaging, Hospital for Special Surgery, 535 E 70th St, New York, NY, 10021, USA.
  • Elisha Lim
    Department of Radiology and Imaging, Hospital for Special Surgery, 535 E 70th Street, New York, NY, 10021, USA.
  • Qian Li
    Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Darryl B Sneag
    Department of Radiology and Imaging, Hospital for Special Surgery, 535 E 70(th) Street, New York, NY 10021, United States of America. Electronic address: sneagd@hss.edu.
  • Ek T Tan
    Department of Radiology and Imaging, Hospital for Special Surgery, 535 E 70(th) Street, New York, NY 10021, United States of America.

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