title: Diagnostic accuracy of an iPhone DICOM viewer for the interpretation of magnetic resonance imaging of the knee.
abstract: OBJECTIVE
  To evaluate the diagnostic performance of viewing magnetic resonance (MR) images on a handheld mobile device compared with a conventional radiology workstation for the diagnosis of intra-articular knee pathology.
  
  
  METHODS
  Prospective comparison study.
  
  
  METHODS
  Tertiary care center.
  
  
  METHODS
  Fifty consecutive subjects who had MR imaging of the knee followed by knee arthroscopy were prospectively evaluated.
  
  
  METHODS
  Two musculoskeletal radiologists independently reviewed each MR study using 2 different viewers: the OsiriX DICOM viewer software on an Apple iPhone 3GS device and eFilm Workstation software on a conventional picture archiving and communications system workstation.
  
  
  METHODS
  Sensitivity and specificity of the iPhone and workstation interpretations was performed using knee arthroscopy as the reference standard. Intraobserver concordance and agreement between the iPhone and workstation interpretations were determined.
  
  
  RESULTS
  There was no statistically significant difference between the 2 devices for each paired comparison of diagnostic performance. For the iPhone interpretations, sensitivity ranged from 77% (13 of 17) for the lateral meniscus to 100% (17 of 17) for the anterior cruciate ligament. Specificity ranged from 74% (14 of 19) for cartilage to 100% (50 of 50) for the posterior cruciate ligament. There was a very high level of interobserver and intraobserver agreement between devices and readers. The iPhone reads took longer than the corresponding workstation reads, with a significant mean difference between the iPhone and workstation reads of 3.98 minutes (P < 0.001).
  
  
  CONCLUSIONS
  The diagnostic performance of interpreting MR images on a handheld mobile device for the assessment of intra-articular knee pathology is similar to that of a conventional radiology workstation, however, requires a longer viewing time.
  
  
  CONCLUSIONS
  Timely and accurate interpretation of complex medical images using mobile device solutions could result in new workflow efficiencies and ultimately improve patient care.
authors.affiliation: *Department of Medical Imaging, St. Michael's Hospital University of Toronto, Toronto, Ontario, Canada; †Department of Medical Imaging, Mount Sinai Hospital and the University Health Network, Toronto, Ontario, Canada; ‡Department of Medical Imaging, Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada; and §Department of Surgery, University of Toronto Orthopaedic Sport Medicine Program at Women's College Hospital, Division of Orthopaedic Surgery, Mount Sinai Hospital, Toronto, Ontario, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: De Maio
authors.forename: Lawrence M
authors.initials: LM
authors.lastname: White
authors.forename: Robert
authors.initials: R
authors.lastname: Bleakney
authors.forename: Ravi J
authors.initials: RJ
authors.lastname: Menezes
authors.forename: John
authors.initials: J
authors.lastname: Theodoropoulos
mesh_terms: D000328:Adult; D001182:Arthroscopy; D034201:Computers, Handheld; D005260:Female; D006801:Humans; D007718:Knee Injuries / Q000175:diagnosis*; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies