Bassant Mowafey1, Elke Van de Casteele1, Jilan M Youssef2, Ahmed R Zaher3, Hany Omar4, Constantinus Politis1, Reinhilde Jacobs1. 1. OMFS IMPATH research group, Dept. Imaging & Pathology, Faculty of Medicine, KU Leuven and Oral and Maxillofacial Surgery, University Hospitals Leuven, Leuven, Belgium. 2. Periodontology, Oral Medicine, Diagnosis, and Oral Radiology Department, Faculty of Dentistry, Mansoura University, Egypt. 3. Oral Biology Department, Faculty of Dentistry, Mansoura University, Egypt. 4. Oral Radiology Department, Faculty of Oral and Dental Medicine, Cairo University, Egypt.
Abstract
OBJECTIVES: This study aimed to identify whether the lingual canals of the mandible can be used as a unique fingerprint when dealing with forensic victim identification. MATERIALS AND METHODS: The study consisted of two parts; an observational part and an objective image analysis part. In the observational part a total of 100 in vivo high resolution CBCT datasets of human mandibles were included in the process of simulated matching of ante-mortem (AM) and post-mortem (PM) data. For the objective image analysis part 10 dry human mandibles were scanned with 2 different Cone Beam Computed tomography (CBCT) machines. In the observational part of the study trained observers attempted to correctly identify matching pairs of images taken from the same mandible out of a series of 100 mandibles. The aim was to simulate matching of the neurovascular structures on AM and PM mandibular midline images and determine the percentage of mandibles identified correctly. In the objective image analysis part, simulated matching was carried out using a specific CBCT dataset acquired to mimic a PM dataset and 10 datasets acquired from a different CBCT device which served as the source of potential AM cases. Comparison between AM and PM datasets resulted in the matching of the AM data and PM data obtained from the same mandible, leading to an assumed correct identification. RESULTS: The observational part of the study showed an average 95% correct identification of the mandibular midline neurovascular structures. Registration of mandibles resulted in perfect overlap of the same mandible from 2 different CBCT machine with an error distance equalling zero, while the registration of different mandibles deviated on average error distance 0.13 mm to 0.18 mm. CONCLUSION: The percentage of fit for the simulated AM and PM data of the same mandible was 100%. This finding together with the significant deviations noted for the non-matching cases, may have a potential role in forensic identification in the same way that fingerprints are recognised as being a unique identifying feature.
OBJECTIVES: This study aimed to identify whether the lingual canals of the mandible can be used as a unique fingerprint when dealing with forensic victim identification. MATERIALS AND METHODS: The study consisted of two parts; an observational part and an objective image analysis part. In the observational part a total of 100 in vivo high resolution CBCT datasets of human mandibles were included in the process of simulated matching of ante-mortem (AM) and post-mortem (PM) data. For the objective image analysis part 10 dry human mandibles were scanned with 2 different Cone Beam Computed tomography (CBCT) machines. In the observational part of the study trained observers attempted to correctly identify matching pairs of images taken from the same mandible out of a series of 100 mandibles. The aim was to simulate matching of the neurovascular structures on AM and PM mandibular midline images and determine the percentage of mandibles identified correctly. In the objective image analysis part, simulated matching was carried out using a specific CBCT dataset acquired to mimic a PM dataset and 10 datasets acquired from a different CBCT device which served as the source of potential AM cases. Comparison between AM and PM datasets resulted in the matching of the AM data and PM data obtained from the same mandible, leading to an assumed correct identification. RESULTS: The observational part of the study showed an average 95% correct identification of the mandibular midline neurovascular structures. Registration of mandibles resulted in perfect overlap of the same mandible from 2 different CBCT machine with an error distance equalling zero, while the registration of different mandibles deviated on average error distance 0.13 mm to 0.18 mm. CONCLUSION: The percentage of fit for the simulated AM and PM data of the same mandible was 100%. This finding together with the significant deviations noted for the non-matching cases, may have a potential role in forensic identification in the same way that fingerprints are recognised as being a unique identifying feature.
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