Vaughan, N., Dubey, V. N., Wee, M.Y.K. and Isaacs, R., 2013. MRI based patient-specific computer models of vertebrae, ligament and soft tissue with various density for epidural needle insertion simulation. In: Proceedings of International Conference of Medical Physics ICMP2013, 1-4 September 2013, Brighton, UK, 657 - 657 (1).
Full text available as:
|
PDF (Abstract)
2013 MEDICAL PHYSICS INTERNATIONAL Journal.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 227kB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: http://www.iomp.org/sites/default/files/mpi_2_with...
Abstract
Epidural simulations previously used layers of synthetic silicate materials to represent tissues. Graphical modelling has enabled visual representation of vertebrae and tissues. The accuracy with which previous simulators modelled the physical properties of tissue layer deformation, density distributions and reaction force during needle insertion has been lacking. Anatomical models are generally static, not considering individual differences between patients especially in obese. Our developed epidural simulator aimed to solve these issues. MRI scans of patients were taken after receiving epidural. The MRI and pressure measurement data was used to reconstruct a density model of the tissues, ligament and vertebrae taking into account the internal structure revealed by MRI intensities. Models were generated from MRI matching individual patients with tissue density varying throughout layers, matching the in vivo tissue. When patient MRI is not available a neural network is alternatively used to estimate the patient's ligament thicknesses with over 92% accuracy. A haptic device is incorporated with the graphics tissue model allowing anaesthetists to practice inserting a needle into the simulated epidural space. Changes in pressure, force and resistance to insertion can be felt as the needle pierces each layer of fat and ligament. The main problem with learning to perform epidural is the inability to see the needle location beneath the skin. MRI reveals the internal tissue structure so that anaesthetists can practice insertions on patient-specific models, visualising epidural space distance and needle obstructions. The developed simulator provides a realistic platform to practice and reduces risks of problems during in-vivo procedures.
Item Type: | Conference or Workshop Item (Poster) |
---|---|
Group: | Faculty of Science & Technology |
ID Code: | 29298 |
Deposited By: | Symplectic RT2 |
Deposited On: | 07 Jun 2017 13:29 |
Last Modified: | 14 Mar 2022 14:04 |
Downloads
Downloads per month over past year
Repository Staff Only - |