title: CT angiography of thoracic outlet syndrome: evaluation of imaging protocols for the detection of arterial stenosis.
abstract: OBJECTIVE
  The purpose of this work was to evaluate the results of cross-sectional imaging and multiplanar and 3D reconstructions for the detection of thoracic outlet arterial stenosis on CT angiograms.
  
  
  METHODS
  Eighty-two patients were prospectively evaluated with CT angiography: in the neutral position and after postural maneuver (164 acquisitions); with contralateral injection of a 24% (Group 1; n = 68) or 30% (Group 2; n = 96) contrast agent; and reconstruction of four sets of images from each acquisition, that is, transverse CT scans, sagittal reformations, and 3D [shaded surface displays (SSD) and volume-rendered (VR)] images. A total of 656 sets of images were blindly and independently interpreted by three readers of variable experience. A consensus interpretation of the four sets of images of each acquisition was used as a standard of reference.
  
  
  RESULTS
  The number of examinations coded with an excellent degree of arterial enhancement was significantly higher in Group 2 than in Group 1 [68 (71%) vs. 35 (51%); p < 0.001]. The sensitivity and specificity for detection of arterial stenosis were 67 and 96% for transverse CT scans, 69 and 94% for sagittal reformations, 71 and 99% for 3D-SSDs, and 95 and 100% for VR images. Compared with the standard of reference, a concordant scoring of arterial stenosis severity was found in 54% of transverse CT scans, 84% of sagittal reformations, 78% of 3D-SSDs, and 91% of VR images. Underestimation of stenosis was found in 43% of transverse CT scans and 10% of sagittal reformations; overestimation of stenosis was more frequent on 3D-SSDs (16%) than on VR images (7%). The reader's experience was marked for the interpretation of cross-sectional images but did not influence the interpretation of 3D images.
  
  
  CONCLUSIONS
  Thoracic outlet arterial compression is best depicted with the injection of a 30% contrast agent and reconstruction of VR images.
authors.affiliation: Department of Radiology, University Center Hospital Calmette, Lille, France. mremy-jardin@chru-lille.fr
authors.forename: M
authors.initials: M
authors.lastname: Remy-Jardin
authors.forename: J
authors.initials: J
authors.lastname: Remy
authors.forename: P
authors.initials: P
authors.lastname: Masson
authors.forename: F
authors.initials: F
authors.lastname: Bonnel
authors.forename: P
authors.initials: P
authors.lastname: Debatselier
authors.forename: L
authors.initials: L
authors.lastname: Vinckier
authors.forename: A
authors.initials: A
authors.lastname: Duhamel
mesh_terms: D000293:Adolescent; D000328:Adult; D000792:Angiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011187:Posture; D011446:Prospective Studies; D013901:Thoracic Outlet Syndrome / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*