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DE SALIS, Alexandra Fane, SAATCHI, Reza and DIMITRI, Paul (2018). Evaluation of High Resolution Thermal Imaging to Determine the Effect of Vertebral Fractures on Associated Skin Surface Temperature in Children with Osteogenesis Imperfecta. Medical & Biological Engineering & Computing, 56 (9), 1633-1643.
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Abstract
Vertebral fractures are common in children with osteogenesis imperfecta (OI). Current imaging methods for fracture detection (X-ray and DXA) use ionising radiation. This pilot study explored whether the alteration in blood flow in vertebral fractures results in skin temperature changes that may be detected using high resolution thermal imaging (HRTI) and thus assist diagnosis and monitoring of fractures in OI patients. Eleven participants aged 5-18 years with OI and known vertebral fractures were enrolled. Small metal discs were placed on the skin surface alongside the vertebrae before participants had DXA and X-ray scans and thermal imaging of their backs. Visibility of the discs on the DXA and X-ray scans and thermal images allowed the temperatures of the skin surface above vertebrae without (healthy) and with fractures to be compared to their respective adjacent skin surface regions (Region of Reference, ROR) by calculating the temperature percentage change (TPC). The TPC between the skin temperature over the fractured thoracic vertebrae (n=11) and the ROR was significant (1.44%, p=0.002, 95% confidence). TPC between the skin temperature over healthy thoracic vertebrae and ROR was not (0.97%, p=0.15, 95% confidence). HRTI may provide a novel tool for assisting in detection of vertebral fractures in OI. Keywords: Computerised medical diagnosis, thermal imaging, vertebral fracture detection, osteogenesis imperfecta.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Computerised medical diagnosis, thermal imaging, vertebral fracture detection, osteogenesis imperfecta. |
| Research Institute, Centre or Group - Does NOT include content added after October 2018: | Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory |
| Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Engineering and Mathematics |
| Identification Number: | https://doi.org/10.1007/s11517-018-1806-3 |
| Page Range: | 1633-1643 |
| Depositing User: | Reza Saatchi |
| Date Deposited: | 16 Feb 2018 11:48 |
| Last Modified: | 18 Mar 2021 07:30 |
| URI: | https://shura.shu.ac.uk/id/eprint/18669 |
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