title: Orthopedic hardware complications diagnosed with multi-detector row CT.
abstract: OBJECTIVE
  To retrospectively evaluate multi-detector row computed tomography (CT) for the depiction of orthopedic hardware complications in the spine and appendicular skeleton.
  
  
  METHODS
  This HIPAA-compliant study had institutional review board approval; patient informed consent was not required. Results of 114 multi-detector row CT studies performed because of possible hardware complications in 109 patients (57 men, 52 women; mean age, 44 years; age range, 12-82 years) were available for analysis. The CT studies were retrospectively reviewed and compared with clinical or surgical outcomes, which were used as the reference standard. In another experiment, detection of hardware complications on radiographs and multi-detector row CT images was compared between two readers for selected cases (18 positive and 26 negative) by using receiver operating characteristic (ROC) methods.
  
  
  RESULTS
  For 91 (80%) of 114 multi-detector row CT studies, the complication status could be determined on the basis of clinical or surgical outcomes. Twenty-three multi-detector row CT studies were confirmed to be positive (revealing 10 cases of nonunion, five cases of hardware malplacement, three cases of hardware loosening, three perihardware fractures, and two chronic infections), and 57 were confirmed to be negative. There were three false-positive and eight false-negative multi-detector row CT studies. With clinical or surgical outcomes as the reference standard, the sensitivity, specificity, and positive and negative predictive values of multi-detector row CT were 74% (23 of 31 studies), 95% (57 of 60 studies), 88% (23 of 26 studies), and 88% (57 of 65 studies), respectively. Results of ROC analysis indicated that detection of hardware complications was much lower with radiography than with multi-detector row CT (area under ROC curve, 0.84 vs 1.00; F = 4.69, df = 1, 43; P < .05).
  
  
  CONCLUSIONS
  Multi-detector row CT is an effective tool for depicting orthopedic hardware complications.
authors.affiliation: Department of Radiology, University of Iowa Roy J. and Lucille A. Carver College of Medicine, IA 52242, USA. kenjirou-ohashi@uiowa.edu
authors.forename: Kenjirou
authors.initials: K
authors.lastname: Ohashi
authors.forename: Georges Y
authors.initials: GY
authors.lastname: El-Khoury
authors.forename: D Lee
authors.initials: DL
authors.lastname: Bennett
authors.forename: José M
authors.initials: JM
authors.lastname: Restrepo
authors.forename: Kevin S
authors.initials: KS
authors.lastname: Berbaum
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D009984:Orthopedic Fixation Devices; D011183:Postoperative Complications / Q000000981:diagnostic imaging*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed