Cross-sectional area and fat infiltration of the lumbar spine muscles in patients with back disorders: a deep learning-based big data analysis.

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:

Abstract

PURPOSE: Validated deep learning models represent a valuable option to perform large-scale research studies aiming to evaluate muscle quality and quantity of paravertebral lumbar muscles at the population level. This study aimed to assess lumbar spine muscle cross-sectional area (CSA) and fat infiltration (FI) in a large cohort of subjects with back disorders through a validated deep learning model.

Authors

  • Jacopo Vitale
    Schulthess Klinik, Lengghalde 2, 8008, Zurich, Switzerland. jacopo.vitale@kws.ch.
  • Luca Maria Sconfienza
    Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
  • Fabio Galbusera
    Laboratory of Biological Structures Mechanics, IRCCS Istituto Ortopedico Galeazzi, Via Galeazzi 4, 20161, Milan, Italy. fabio.galbusera@grupposandonato.it.