title: Thin-section helical computed tomography of the bladder: initial clinical experience with virtual reality imaging.
abstract: OBJECTIVE
  To evaluate the application of virtual reality imaging of the bladder (virtual cystoscopy) in the detection of bladder masses.
  
  
  METHODS
  Six patients (mean age 61 years, range 43 to 75) with hematuria and positive findings on conventional cystoscopy were studied by means of thin-section helical computed tomography of the air-distended bladder. Using volume-rendering algorithms, interactive intraluminal views of the bladder mucosa were generated (virtual cystoscopy). Results of virtual cystoscopy were compared with those of conventional cystoscopy in each case.
  
  
  RESULTS
  Twenty-six (100%) of 26 masses (mean size 1.7 cm, range 0.3 to 6), detected on conventional cystoscopy, were visualized on virtual cystoscopy. Twelve of 26 masses measured less than 1 cm in maximum diameter. All masses were pathologically proven transitional cell carcinomas. Virtual cystoscopy was well tolerated by all patients, and no complications occurred.
  
  
  CONCLUSIONS
  Our results indicate that virtual cystoscopy is an accurate technique for detection of intrinsic bladder masses. It may represent a radiologic adjunct to conventional cystoscopy for initial evaluation of patients with hematuria and for surveillance of patients after bladder tumor resection.
authors.affiliation: Department of Radiology, Boston University School of Medicine, Massachusetts, USA.
authors.forename: S
authors.initials: S
authors.lastname: Hussain
authors.forename: J A
authors.initials: JA
authors.lastname: Loeffler
authors.forename: R K
authors.initials: RK
authors.lastname: Babayan
authors.forename: H M
authors.initials: HM
authors.lastname: Fenlon
mesh_terms: D000328:Adult; D000368:Aged; D003558:Cystoscopy; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010865:Pilot Projects; D014057:Tomography, X-Ray Computed / Q000379:methods*; D001749:Urinary Bladder Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology