title: The ribs unfolded - a CT visualization algorithm for fast detection of rib fractures: effect on sensitivity and specificity in trauma patients.
abstract: OBJECTIVE
  To assess a radiologist's detection rate of rib fractures in trauma CT when reading curved planar reformats (CPRs) of the ribs compared to reading standard MPRs.
  
  
  METHODS
  Two hundred and twenty trauma CTs (146 males, 74 females) were retrospectively subjected to a software algorithm to generate CPRs of the ribs. Patients were split into two equal groups. Sixteen patients were excluded due to insufficient segmentation, leaving 107 patients in group A and 97 patients in group B. Two radiologists independently evaluated group A using CPRs and group B using standard MPRs. Two different radiologists reviewed both groups with the inverse methods setting. Results were compared to a standard of reference created by two senior radiologists.
  
  
  RESULTS
  The reference standard identified 361 rib fractures in 61 patients. Reading CPRs showed a significantly higher overall sensitivity (P < 0.001) for fracture detection than reading standard MPRs, with 80.9% (584/722) and 71.5% (516/722), respectively. Mean reading time was significantly shorter for CPRs (31.3 s) compared to standard MPRs (60.7 s; P < 0.001).
  
  
  CONCLUSIONS
  Using CPRs for the detection of rib fractures accelerates the reading of trauma patient chest CTs, while offering an increased overall sensitivity compared to conventional standard MPRs.
  
  
  CONCLUSIONS
  • In major blunt trauma, rib fractures are diagnosed with Computed Tomography. • Image processing can unfold all ribs into a single plane. • Unfolded ribs can be read twice as fast as axial images. • Unfolding the ribs allows a more accurate diagnosis of rib fractures.
authors: Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria, helmut.ringl@meduniwien.ac.at.
authors: Helmut
authors: H
authors: Ringl
authors: Mathias
authors: M
authors: Lazar
authors: Michael
authors: M
authors: Töpker
authors: Ramona
authors: R
authors: Woitek
authors: Helmut
authors: H
authors: Prosch
authors: Ulrika
authors: U
authors: Asenbaum
authors: Csilla
authors: C
authors: Balassy
authors: Daniel
authors: D
authors: Toth
authors: Michael
authors: M
authors: Weber
authors: Stefan
authors: S
authors: Hajdu
authors: Grzegorz
authors: G
authors: Soza
authors: Andreas
authors: A
authors: Wimmer
authors: Thomas
authors: T
authors: Mang
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007223:Infant; D008297:Male; D008875:Middle Aged; D009104:Multiple Trauma / Q000000981:diagnostic imaging; D015588:Observer Variation; D012189:Retrospective Studies; D012253:Rib Fractures / Q000000981:diagnostic imaging*; D012272:Ribs / Q000000981:diagnostic imaging / Q000293:injuries; D012680:Sensitivity and Specificity; D013898:Thoracic Injuries / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014949:Wounds, Nonpenetrating / Q000000981:diagnostic imaging; D055815:Young Adult