title: The thickness of the temporal squama and its implication for transcranial sonography.
abstract: OBJECTIVE
  The difficult transtemporal ultrasound window is a relatively frequent occurrence. The authors assessed if the thickness of the temporal bone squama as measured in the "bone window" of the head computerized tomography (CT) scan can predict the transtemporal acoustic window.
  
  
  METHODS
  The authors retrospectively reviewed the head CTs on their bone window setting of patients in which nonimaging transcranial Dopplers (TCDs) had been performed. The thickness of the temporal squama in its thinnest portion was measured. The temporal TCD windows were graded in three classes: class 1 as good, class 2 when only a partial study is possible, and class 3 as an impossible ultrasonic window. In a case-control design, for every patient with any class 2 and 3 TCD temporal window, a patient with a class 1 window was randomly included from the same time period.
  
  
  RESULTS
  Fifty-five temporal bones (56%) were class 1, 17 (17%) were class 2, and 27 (27%) were class 3. Bone thicknesses (in mm, mean +/- SD) were greater in those with poorer windows: class 1 = 2.67 +/- 0.70, class 2 = 4.06 +/- 0.56, and class 3 = 5.04 +/- 1.06, P < or = .0001 by Cusick's nonparametric test of trend. Temporal squama thickness of > or = 5 mm portends 86% sensitivity, 90% specificity, 70% positive predictive value, and a positive likelihood ratio of 8.6 for a class 3 transtemporal ultrasound window.
  
  
  CONCLUSIONS
  Measurement of temporal bone thickness on the bone window setting of the head CT scan may be useful in identifying patients who are poor candidates for transcranial ultrasound.
authors.affiliation: Department of Neurology, Division of Neurocritical Care, Vascular Ultrasound Laboratory, University of California, San Francisco, USA. adrian.a.jarquin-valdivia@vanderbilt.edu
authors.forename: A A
authors.initials: AA
authors.lastname: Jarquin-Valdivia
authors.forename: J
authors.initials: J
authors.lastname: McCartney
authors.forename: D
authors.initials: D
authors.lastname: Palestrant
authors.forename: S C
authors.initials: SC
authors.lastname: Johnston
authors.forename: D
authors.initials: D
authors.lastname: Gress
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001921:Brain / Q000098:blood supply; D001927:Brain Diseases / Q000000981:diagnostic imaging*; D019544:Equipment Failure Analysis; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D015576:Hyperostosis / Q000000981:diagnostic imaging* / Q000473:pathology; D007091:Image Processing, Computer-Assisted; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D010022:Osteopetrosis / Q000000981:diagnostic imaging* / Q000473:pathology; D012372:ROC Curve; D012016:Reference Values; D012039:Regional Blood Flow / Q000502:physiology; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013701:Temporal Bone / Q000000981:diagnostic imaging* / Q000473:pathology; D014057:Tomography, X-Ray Computed; D017585:Ultrasonography, Doppler, Transcranial