Deep Learning-Driven Abbreviated Shoulder MRI Protocols: Diagnostic Accuracy in Clinical Practice.

Journal: Tomography (Ann Arbor, Mich.)
PMID: 40278715

Abstract

BACKGROUND: Deep learning (DL) reconstruction techniques have shown promise in reducing MRI acquisition times while maintaining image quality. However, the impact of different acceleration factors on diagnostic accuracy in shoulder MRI remains unexplored in clinical practice.

Authors

  • Giovanni Foti
    Department of Radiology, IRCCS Sacro Cuore Hospital, Via Don A. Sempreboni 10, 37024, Negrar (VR), Italy. gfoti81@yahoo.it.
  • Flavio Spoto
    Department of Radiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
  • Thomas Mignolli
    Department of Radiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
  • Alessandro Spezia
    Department of Radiology, Policlinico Universitario GB Rossi, 37134 Verona, Italy.
  • Luigi Romano
    Department of Radiology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.
  • Guglielmo Manenti
    Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.
  • Nicolò Cardobi
    Department of Radiology, G.B. Rossi Hospital, University of Verona, 37134 Verona, Italy.
  • Paolo Avanzi
    Department of Orthopaedic Surgery, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Negrar, Italy.

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