Estimating age at death by Hausdorff distance analyses of the fourth lumbar vertebral bodies using 3D postmortem CT images.
Age at death
Fourth lumbar vertebral body
Hausdorff distance
Japanese
Postmortem CT
Journal
Forensic science, medicine, and pathology
ISSN: 1556-2891
Titre abrégé: Forensic Sci Med Pathol
Pays: United States
ID NLM: 101236111
Informations de publication
Date de publication:
14 Apr 2023
14 Apr 2023
Historique:
accepted:
24
03
2023
entrez:
14
4
2023
pubmed:
15
4
2023
medline:
15
4
2023
Statut:
aheadofprint
Résumé
The existing methods for determining adult age from human skeletons are mostly qualitative. However, a shift in quantifying age-related skeletal morphology on a quantitative scale is emerging. This study describes an intuitive variable extraction technique and quantifies skeletal morphology in continuous data to understand their aging pattern. A total of 200 postmortem CT images from the deceased aged 25-99 years (130 males, 70 females) who underwent forensic death investigations were used in the study. The 3D volume of the fourth lumbar vertebral body was segmented, smoothed, and post-processed using the open-source software ITK-SNAP and MeshLab, respectively. To measure the extent of 3D shape deformity due to aging, the Hausdorff distance (HD) analysis was performed. In our context, the maximum Hausdorff distance (maxHD) was chosen as a metric, which was subsequently studied for its correlation with age at death. A strong statistically significant positive correlation (P < 0.001) between maxHD and age at death was observed in both sexes (Spearman's rho = 0.742, male; Spearman's rho = 0.729, female). In simple linear regression analyses, the regression equations obtained yielded the standard error of estimates of 12.5 years and 13.1 years for males and females, respectively. Our study demonstrated that age-related vertebral morphology could be described using the HD method. Moreover, it encourages further studies with larger sample sizes and on other population backgrounds to validate the methodology.
Identifiants
pubmed: 37058209
doi: 10.1007/s12024-023-00620-7
pii: 10.1007/s12024-023-00620-7
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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