Deep learning in rib fracture imaging: study quality assessment using the Must AI Criteria-10 (MAIC-10) checklist for artificial intelligence in medical imaging.

Journal: Insights into imaging
Published Date: Aug 9, 2025

Abstract

OBJECTIVES: To analyze the methodological quality of studies on deep learning (DL) in rib fracture imaging with the Must AI Criteria-10 (MAIC-10) checklist, and to report insights and experiences regarding the applicability of the MAIC-10 checklist.

Authors

  • Jonas M Getzmann
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich (USZ), Raemistrasse 100, CH-8091, Zurich, Switzerland.
  • Kitija Nulle
    Radiology Department, Riga East Clinical University Hospital, Riga, Latvia.
  • Cinzia Mennini
    IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
  • Umberto Viglino
    Unit of Radiology, Ospedale Evangelico Internazionale, Genoa, Italy.
  • Francesca Serpi
    IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.
  • Domenico Albano
    IRCCS Istituto Ortopedico Galeazzi, Milano, Italy; Sezione di Scienze Radiologiche, Dipartimento di Biomedicina, Neuroscienze e Diagnostica Avanzata, Università degli Studi di Palermo, Palermo, Italy.
  • Carmelo Messina
    Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy; IRCCS Istituto Ortopedico Galeazzi, Milano, Italy.
  • Stefano Fusco
  • Salvatore Gitto
    Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Milano, Italy. Electronic address: sal.gitto@gmail.com.
  • Luca Maria Sconfienza
    Unit of Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Galeazzi, Milan, Italy.

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