title: Size and growth rate of sporadic vestibular schwannoma: predictive value of information available at presentation.
abstract: BACKGROUND
  The current study examines the hypothesis that tumor growth rate in sporadic vestibular schwannoma could be in part predicted by data available at diagnosis, such as tumor volume, patient age, laterality, and sex.
  
  
  METHODS
  Tumor volumes and growth rates were calculated from serial magnetic resonance imaging data in a cohort of 50 patients (26 men and 24 women; mean age at presentation, 64.1 +/- 12.8 yr). Tumor volumes were measured using an algorithm that corrects for partial volume averaging errors and provides accurate estimates of tumor volume with known errors.
  
  
  RESULTS
  Examination of presentation data showed no relationship between tumor size at diagnosis and patient age, sex, or tumor laterality. Two measurements of tumor growth--absolute growth per annum and tumor volume doubling time--were studied, and neither showed any relationship with tumor size at presentation, patient age, tumor laterality, or sex.
  
  
  CONCLUSIONS
  The study represents a typical spectrum of patient ages and is of sufficient size in view of the distribution pattern of the variables to give a calculated statistical power in excess of 90% for each variable. This indicates that the clinical features available at presentation and diagnosis have no power to predict the expected behavior of sporadic vestibular schwannoma.
authors.affiliation: Imaging Science and Biomedical Engineering, School of Medicine, University of Manchester, United Kingdom.
authors.forename: Amit
authors.initials: A
authors.lastname: Herwadker
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Vokurka
authors.forename: D Gareth R
authors.initials: DG
authors.lastname: Evans
authors.forename: Richard T
authors.initials: RT
authors.lastname: Ramsden
authors.forename: Alan
authors.initials: A
authors.lastname: Jackson
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015331:Cohort Studies; D018450:Disease Progression; D004292:Dominance, Cerebral / Q000502:physiology; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009464:Neuroma, Acoustic / Q000175:diagnosis* / Q000473:pathology / Q000532:radiotherapy / Q000601:surgery; D047368:Tumor Burden / Q000502:physiology*