ISSN: 2251-8762
Accepted Articles (In Press)
2022
Age Estimation from Vertebral Osteophytes Using 3D MDCT Imaging
International Journal of Medical Toxicology and Forensic Medicine,
2022,
,
Page 37813
https://doi.org/10.32598/ijmtfm.vi.37813
Abstract
Background: Age estimation from skeletal measurements is an important step in forensic biological identification. In this study we attempted to benefit from the use of multi-detector computed tomography as an uprising satisfying metric technique. The main aim of this study was to test the hypothesis that osteophytes of the vertebral column are too specific for everyone to develop an age estimation formula from computed tomography images’ measurements. This study used a cross-sectional approach involving thoraco-lumbar multi-detector computed tomography scans from 100 adult volunteers of both sex ranging in age from 20 to 80 years divided into six age groups, and vertebral osteophytes were measured using a specific workstation producing three-dimensional virtual reality images. This involved the lower six thoracic and all lumbar vertebrae, which were scored for degree of osteophyte formation and then classified into six categories.
Results: Statistical analysis of the gathered data showed a statistically significant difference between different age groups and degree of osteophytosis with p value < 0.001, and correlation coefficients resulting from correlation between age and osteophytes’ scores are: 0.75, 0.81, 0.69 for a combination of the sexes, males, and females, respectively. Additionally, a reliable formula for age determination was achieved, regardless of sex y=29.831+ 9.767x; For males y=29.740+ 9.651x; For females y=29.967+ 9.859x (y= age, x= osteophyte index).
Conclusions: The degree of vertebral osteophytosis of an individual can be used as a reliable determinant tool for age identification.
- Age
- Human Identification
- Forensic Radiology
- Anthropology
- Vertebral Osteophytes
How to Cite
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