title: Relationship between the thickness of the roof of glenoid fossa, condyle morphology and remaining teeth in asymptomatic European patients based on cone beam CT data sets.
abstract: OBJECTIVE
  The aim of this study was to examine the relationship between the roof of the glenoid fossa (RGF) thickness and condyle morphology and the influence of the number of remaining teeth and age.
  
  
  METHODS
  Cone beam CT data sets from 77 asymptomatic European patients were analysed retrospectively in this study. The thinnest area of RGF was identified among the sagittal and coronal slices on a computer screen; distance measurement software was used to measure the thickness. Moreover, we applied a free digital imaging and communications in medicine viewer for classification of condyle head type. It was also used to analyse any relation between RGF thickness and the number of remaining teeth. We performed a correlation analysis for RGF, age and missing teeth. Finally, we investigated combining sagittal condyle morphological characterization with coronal condyle morphology in relation to the number of joints and RGF thickness.
  
  
  RESULTS
  The Kruskal-Wallis test revealed no significant differences in RGF thickness among any of the coronal condyle head morphology groups (p > 0.05). There were significant differences in the thinnest part of RGF in relation to the sagittal plane for condyle morphological characterization, because we observed increased RGF thickness in joints with osteoarthritis features (p < 0.05). There is a non-significant correlation between the thinnest part of the RGF and the number of remaining teeth (p > 0.05).
  
  
  CONCLUSIONS
  We found that the RGF thickness is unaffected by the coronal condyle head morphology and the number of remaining teeth. Osteoarthritic changes (sagittal condyle morphology) have an effect on RGF.
authors.affiliation: Department of Oral and Maxillofacial Radiology, Nihon University School of Dentistry, Tokyo, Japan.
authors.forename: K
authors.initials: K
authors.lastname: Ejima
authors.forename: D
authors.initials: D
authors.lastname: Schulze
authors.forename: A
authors.initials: A
authors.lastname: Stippig
authors.forename: K
authors.initials: K
authors.lastname: Matsumoto
authors.forename: D
authors.initials: D
authors.lastname: Rottke
authors.forename: K
authors.initials: K
authors.lastname: Honda
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D054893:Cone-Beam Computed Tomography; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D008335:Mandibular Condyle / Q000000981:diagnostic imaging / Q000473:pathology*; D008875:Middle Aged; D010003:Osteoarthritis / Q000000981:diagnostic imaging / Q000473:pathology*; D012189:Retrospective Studies; D018709:Statistics, Nonparametric; D013701:Temporal Bone / Q000000981:diagnostic imaging / Q000473:pathology*; D013704:Temporomandibular Joint / Q000000981:diagnostic imaging / Q000473:pathology*; D013705:Temporomandibular Joint Disorders / Q000000981:diagnostic imaging / Q000473:pathology; D016388:Tooth Loss / Q000503:physiopathology*; D055815:Young Adult