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Journal of Spine

ISSN: 2165-7939

Open Access

3D Morphometric Analysis of Human Vertebrae C3-T3 Using CT Images Reconstruction

Abstract

Ee Chon Teo, Timothy Holsgrove and Stepanka Haiblikova

Vertebral morphometry is important for spinal analysis, diseases diagnosis and improved implant designs. New technologies available allow us to develop a simple and efficient process of obtaining accurate data of threedimensional (3D) vertebral geometry to create a wide and comprehensive database of vertebral dimension for further research.

The primary aim of this study is to introduce a simple and precise technique of vertebral dimension measurement. The technique involves the segmentation of CT scans of a Caucasian male cadaver’s head and torso specimen to reconstruct 3D images of C1-T3 using 3D imaging processing software (ScanIP Academic, Synopsys Inc.), and 3D modelling software (ANSYS SpaceClaim). A systematic way of defining specific Cartesian coordinate system is done on all reconstructed vertebrae’ images and various standard vertebral parameters are determined accordingly. Finally, the data is compared against previous study to verify the reliability of this method.

The results showed similar trend of vertebral parameters dimensions at vertebral level, except that the dimensions obtained from reconstructed model of CT scans are significantly greater than Asian specimen. The technique applied in this study in the measurement of vertebral parameters is reliable and preferred to other earlier previous methods. The greater dimensions obtained from the specimen can be explained by different specimen ethnic origin, as the vertebral parameters of Caucasian population were reported to be larger than Asian population. To support this latter hypothesis and to create more statistically accurate data, further study on more specimens should be carried out.

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Citations: 2022

Journal of Spine received 2022 citations as per Google Scholar report

Journal of Spine peer review process verified at publons

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