title: [Performance of different CT angiography imaging modalities in detecting renal artery stenoses].
abstract: OBJECTIVE
  Purpose of the study was to compare the sensitivity and specificity of various display modalities in the detection of renal artery stenosis. In particular, the difference between hard-copy reading and interactive analysis at the workstation was assessed.
  
  
  METHODS
  Selected patients (n = 31) with expected suboptimal conditions for CT angiography due to long-standing hypertension and compromised renal function were included. Six radiologists evaluated independently a total of 77 renal arteries with 49 renal artery stenoses proven by angiography. Image analysis included: mode A: interactive display, analysis of multiplanar reformats and axial sections at the workstation, mode B: visualization of MIPs in the coronal and axial planes as hard copies only, mode C: visualization of MIPs and axial sections as hard copies only.
  
  
  RESULTS
  The following sensitivities and specificities were found for internal readers and (readers from outside institutions): mode A: 94.8%, 87.9%, mode B: 97.7% (95.1%), 80.3% (75.4%); mode C: 97.0% (95.3%), 78.8% (76.6%). The differences were statistically not significant (p > 0.05).
  
  
  CONCLUSIONS
  Standardized hard copies of MIPs plus axial CT provide sufficient accuracy to detect renal artery stenosis compared to interactive imaging even in this highly selected group of patients.
authors.affiliation: Abt. Diagnostische Radiologie, Medizinische Hochschule Hannover. galanski.m@mh-hannover.de
authors.forename: M
authors.initials: M
authors.lastname: Galanski
authors.forename: L
authors.initials: L
authors.lastname: Hoogestraat-Lufft
authors.forename: D
authors.initials: D
authors.lastname: Högemann
authors.forename: S
authors.initials: S
authors.lastname: Baus
authors.forename: A
authors.initials: A
authors.lastname: Schmidt
authors.forename: A
authors.initials: A
authors.lastname: Koehler
authors.forename: I P
authors.initials: IP
authors.lastname: Arlart
authors.forename: P
authors.initials: P
authors.lastname: Landwehr
authors.forename: P
authors.initials: P
authors.lastname: Huppert
authors.forename: H
authors.initials: H
authors.lastname: Hecker
authors.forename: A
authors.initials: A
authors.lastname: Chavan
mesh_terms: D000328:Adult; D000368:Aged; D000792:Angiography / Q000295:instrumentation*; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation; D005103:Expert Systems; D005260:Female; D006801:Humans; D006978:Hypertension, Renovascular / Q000000981:diagnostic imaging; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008297:Male; D008875:Middle Aged; D012078:Renal Artery Obstruction / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000295:instrumentation*