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Identifying and classifying hyperostosis frontalis interna via computerized tomography
Author(s) -
May Hila,
Peled Nathan,
Dar Gali,
Hay Ori,
Abbas Janan,
Masharawi Youssef,
Hershkovitz Israel
Publication year - 2010
Publication title -
the anatomical record: advances in integrative anatomy and evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.678
H-Index - 62
eISSN - 1932-8494
pISSN - 1932-8486
DOI - 10.1002/ar.21274
Subject(s) - kappa , medicine , reliability (semiconductor) , predictive value , tomography , radiological weapon , nuclear medicine , radiology , mathematics , power (physics) , physics , geometry , quantum mechanics
The aim of this study was to recognize the radiological characteristics of hyperostosis frontalis interna (HFI) and to establish a valid and reliable method for its identification and classification. A reliability test was carried out on 27 individuals who had undergone a head computerized tomography (CT) scan. Intra‐observer reliability was obtained by examining the images three times, by the same researcher, with a 2‐week interval between each sample ranking. The inter‐observer test was performed by three independent researchers. A validity test was carried out using two methods for identifying and classifying HFI: 46 cadaver skullcaps were ranked twice via computerized tomography scans and then by direct observation. Reliability and validity were calculated using Kappa test (SPSS 15.0). Reliability tests of ranking HFI via CT scans demonstrated good results ( K > 0.7). As for validity, a very good consensus was obtained between the CT and direct observation, when moderate and advanced types of HFI were present ( K = 0.82). The suggested classification method for HFI, using CT, demonstrated a sensitivity of 84%, specificity of 90.5%, and positive predictive value of 91.3%. In conclusion, volume rendering is a reliable and valid tool for identifying HFI. The suggested three‐scale classification is most suitable for radiological diagnosis of the phenomena. Considering the increasing awareness of HFI as an early indicator of a developing malady, this study may assist radiologists in identifying and classifying the phenomena. Anat Rec, 2010. © 2010 Wiley‐Liss, Inc.