Literature DB >> 27083691

Contribution of the computed tomography of the anatomical aspects of the sphenoid sinuses to forensic identification.

Mathieu Auffret1, Marc Garetier2, Idris Diallo1, Serge Aho3, Douraied Ben Salem4.   

Abstract

INTRODUCTION: Body identification is the cornerstone of forensic investigation. It can be performed using radiographic techniques, if antemortem images are available. This study was designed to assess the value of visual comparison of the computed tomography (CT) anatomical aspects of the sphenoid sinuses, in forensic individual identification, especially if antemortem dental records, fingerprints or DNA samples are not available.
MATERIAL AND METHODS: This retrospective work took place in a French university hospital. The supervisor of this study randomly selected from the picture archiving and communication system (PACS), 58 patients who underwent one (16 patients) or two (42 patients) head CT in various neurological contexts. To avoid bias, those studies were prepared (anonymized, and all the head structures but the sphenoid sinuses were excluded), and used to constitute two working lists of 50 (42+8) CT studies of the sphenoid sinuses. An anatomical classification system of the sphenoid sinuses anatomical variations was created based on the anatomical and surgical literature. In these two working lists, three blinded readers had to identify, using the anatomical system and subjective visual comparison, 42 pairs of matched studies, and 16 unmatched studies. Readers were blinded from the exact numbers of matching studies.
RESULTS: Each reader correctly identified the 42 pairs of CT with a concordance of 100% [97.5% confidence interval: 91-100%], and the 16 unmatched CT with a concordance of 100% [97.5% confidence interval: 79-100%]. Overall accuracy was 100%.
CONCLUSION: Our study shows that establishing the anatomical concordance of the sphenoid sinuses by visual comparison could be used in personal identification. This easy method, based on a frequently and increasingly prescribed exam, still needs to be assessed on a postmortem cohort.
Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Computed tomography; Identification; Sphenoid sinus

Mesh:

Year:  2016        PMID: 27083691     DOI: 10.1016/j.neurad.2016.03.007

Source DB:  PubMed          Journal:  J Neuroradiol        ISSN: 0150-9861            Impact factor:   3.447


  6 in total

1.  Antemortem identification by fusion of MR and CT of the paranasal sinuses.

Authors:  Jakob Heimer; Dominic Gascho; Simon Gentile; Gary M Hatch; Michael J Thali; Thomas D Ruder
Journal:  Forensic Sci Med Pathol       Date:  2017-05-20       Impact factor: 2.007

2.  Automated contour detection in spine radiographs and computed tomography reconstructions for forensic comparative identification.

Authors:  Julien Ognard; Lucile Deloire; Claire Saccardy; Valerie Burdin; Douraied Ben Salem
Journal:  Forensic Sci Med Pathol       Date:  2019-11-25       Impact factor: 2.007

3.  Automatic forensic identification using 3D sphenoid sinus segmentation and deep characterization.

Authors:  Kamal Souadih; Ahror Belaid; Douraied Ben Salem; Pierre-Henri Conze
Journal:  Med Biol Eng Comput       Date:  2019-12-17       Impact factor: 2.602

4.  Cardiac conduction devices in the radiologic comparative identification of decedents.

Authors:  Vasiliki Chatzaraki; Garyfalia Ampanozi; Michael J Thali; Wolf Schweitzer
Journal:  Forensic Sci Med Pathol       Date:  2019-11-14       Impact factor: 2.007

5.  Three-dimensional analysis of sphenoid sinus uniqueness for assessing personal identification: a novel method based on 3D-3D superimposition.

Authors:  Annalisa Cappella; Daniele Gibelli; Michaela Cellina; Debora Mazzarelli; Antonio Giancarlo Oliva; Danilo De Angelis; Chiarella Sforza; Cristina Cattaneo
Journal:  Int J Legal Med       Date:  2019-08-08       Impact factor: 2.686

6.  Forensic Identification from Three-Dimensional Sphenoid Sinus Images Using the Iterative Closest Point Algorithm.

Authors:  Xiaoai Dong; Fei Fan; Wei Wu; Hanjie Wen; Hu Chen; Kui Zhang; Ji Zhang; Zhenhua Deng
Journal:  J Digit Imaging       Date:  2022-04-04       Impact factor: 4.903

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.