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
References
Benoist, M. (2005). Natural history of the aging spine. In The aging spine (pp. 4-7). Springer, Berlin, Heidelberg.
Chanapa, P. (2011). Osteoporosis in men; more serious than expected. Journal of Public Health, 41(3), pp: 283-294.
Chan YH (2004): Biostatistics 201: linear regression analysis. Singapore Med J.;45(2), pp: 55-61.
Dawson B. and Trapp R. (2001). Basic and clinical biostatistics, 3rd edition; Mcgraw-HillInc: 45-50.
Kacar, E., Unlu, E., Beker-Acay, M., Balcik, C., Gultekin, M. A., Kocak, U., ... and Yucel, A. (2017). Age estimation by assessing the vertebral osteophytes with the aid of 3D CT imaging. Australian Journal of Forensic Sciences, 49(4), pp: 449-458.
Klaassen, Z., Tubbs, R. S., Apaydin, N., Hage, R., Jordan, R., and Loukas, M. (2011). Vertebral spinal osteophytes. Anatomical Science International, 86(1), pp: 1-9.
Listi, G. A., and Manhein, M. H. (2012). The use of vertebral osteoarthritis and osteophytosis in age estimation. Journal of Forensic Sciences, 57(6), pp: 1537-1540.
McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemia medica, 22(3), 276-282.
Namking, M., Buranaurgsa, M., Jeeravipoolvarn, P., and Deesart, M. (2008). The prevalence of vertebral osteophyte formation in Northeast Thais. Srinagarind Medical Journal, 23(1), pp: 81-92.
O’Donnell, C., Iino, M., Mansharan, K., Leditscke, J., and Woodford, N. (2011). Contribution of postmortem multidetector CT scanning to identification of the deceased in a mass disaster: experience gained from the 2009 Victorian bushfires. Forensic Science International, 205(1-3), pp: 15-28
Praneatpolgrang, S., Prasitwattanaseree, S., and Mahakkanukrauh, P. (2019). Age estimation equations using vertebral osteophyte formation in a Thai population: comparison and modified osteophyte scoring method. Anatomy and Cell Biology, 52(2), pp: 149-160.
Rutty, G. N., Robinson, C., Morgan, B., Black, S., Adams, C., and Webster, P. (2009). Fimag: the United Kingdom disaster victim/forensic identification imaging system. Journal of Forensic Sciences, 54(6), pp: 1438-1442.
Siemionow, K., An, H., Masuda, K., Andersson, G., and Cs-Szabo, G. (2011). The Effects of age, gender, ethnicity, and spinal level on the rate of intervertebral disc degeneration. A review of 1712 intervertebral discs. Spine, 36(17), pp: 1333.
Snodgrass, J. J. (2004). Sex differences and aging of the vertebral column. Journal of Forensic Science, 49(3), JFS2003198-6.
Van der Merwe, A. E., Işcan, M. Y., and L'abbé, E. N. (2006). The pattern of vertebral osteophyte development in a South African population. International Journal of Osteoarchaeology, 16(5), pp: 459-464.
Watanabe, S., and Terazawa, K. (2006). Age estimation from the degree of osteophyte formation of vertebral columns in Japanese. Legal Medicine, 8(3), pp: 156-160.
Wong, S. H. J., Chiu, K. Y., & Yan, C. H. (2016). Osteophytes. Journal of Orthopaedic Surgery, 24(3), 403-410.
Yee, A., & Chan, D. (2014). Genetic basis of intervertebral disc degeneration. In The Intervertebral Disc (pp. 157-176). Springer, Vienna.
Zukowski, L. A., Falsetti, A. B., & Tillman, M. D. (2012). The influence of sex, age and BMI on the degeneration of the lumbar spine. Journal of Anatomy, 220(1), 57-66.
- Abstract Viewed: 100 times
- pdf Downloaded: 77 times