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Erschienen in: Forensic Science, Medicine and Pathology 2/2020

12.03.2020 | Original Article

Odontological identification dental charts based upon postmortem computed tomography compared to dental charts based upon postmortem clinical examinations

verfasst von: Niels Dyrgaard Jensen, Pilar Cornejo Ulloa, Sara Arge, Dorthe Arenholt Bindslev, Niels Lynnerup

Erschienen in: Forensic Science, Medicine and Pathology | Ausgabe 2/2020

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Abstract

Since the beginning of this century, the use of postmortem computed tomography (PMCT) in forensic autopsies has increased. In this study we examined how similar dental charts created using PMCT as a solitary examination mode were to dental charts created using the conventional method of a clinical inspection including intraoral radiographs. A total of 100 previously performed dental identification cases were retrospectively included in the study. For each case, a dental chart was created solely based upon PMCT. The PMCT based dental chart was subsequently compared with the chart created from the previous conventional identification examination. Based upon the accuracy, sensitivity and specificity values PMCT performed very well compared to the conventional method in the identification concerning presence or absence of teeth, the presence of crowns, bridges and endodontic treatments as well as the presence and types of fillings. PMCT performed poorly concerning the extension of fillings and identification of small, tooth-colored fillings. The use of PMCT is a valuable supplement to the conventional methods available for forensic odontologists and may be of great value for initial screening in mass fatalities.
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Metadaten
Titel
Odontological identification dental charts based upon postmortem computed tomography compared to dental charts based upon postmortem clinical examinations
verfasst von
Niels Dyrgaard Jensen
Pilar Cornejo Ulloa
Sara Arge
Dorthe Arenholt Bindslev
Niels Lynnerup
Publikationsdatum
12.03.2020
Verlag
Springer US
Erschienen in
Forensic Science, Medicine and Pathology / Ausgabe 2/2020
Print ISSN: 1547-769X
Elektronische ISSN: 1556-2891
DOI
https://doi.org/10.1007/s12024-020-00217-4

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