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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
Background
Scoliosis is a 3-dimensional deformity of the spine that develops in child/adolescent life and can deteriorate during skeletal growth and especially in periods of rapid skeletal development such as around puberty. The overall prevalence has been has been reported to be between 0.5-5%. Scoliosis can severely affect the quality of life of many patients; it may lead to multiple impairments and creates a heath inequality, requiring treatment. Females are 8 times more likely to progress to a curve that requires treatment in comparison to males. There is no consensus among spinal surgeons on the use of correction techniques in the treatment of scoliosis. For example, some many surgeons prefer approaches which are thought to provide good scoliosis correction though they may pose long-term risks in comparison to low risk approaches that may provide comparable results (e.g. all pedicle screw correction rather than hybrid instrumentation)(Tsirikos and Subramanian 2012). Similarly there are many other questions related to treatment and instrumentation (Tsirikos 2019) that remain debated and can be answered using computational modelling (Pankaj 2013; Scott et al. 2020)
Aims
-Develop computational models using the imaging data (CT and MRI) to simulate the anatomy of an adolescent scoliotic spine across the different types of curves which represent the common patterns seen in clinical practice.
-Undertake a modelling studies to evaluate intra-operative corrective forces required in scoliosis correction of the spine to answer a range of clinical questions.
-Compare the computational results with patient reported outcomes using the Scoliosis Research Society (SRS)-22 validated questionnaire for adolescent idiopathic scoliosis.
-Develop software to recommend an optimum correction approach for a given clinical scenario.
Training Outcomes
-Present and critique the state-of-art with respect to scoliosis and its treatment approaches.
-Develop complex geometry of the scoliotic spines from 3D scan data.
-Describe the mathematical constitutive models of components involved in modelling.
-Describe loadings experienced by the spine due to different correction approaches and instrumentations.
-Learn to generate, curate and analyse large datasets.
-Master techniques for data analysis obtained from computational modelling, imaging and patient reported outcomes.
-Work in a team and become self reliant for acquiring resources required for research.
-Present research in international conferences and write journal papers.
Q&A Session
If you have any questions regarding this project, you are invited to attend a Q&A session hosted by the Supervisor(s) on 5th December at 11am via Microsoft Teams. Click here to join the meeting.
About the Programme
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the following link:
https://www.ed.ac.uk/usher/precision-medicine/app-process-eligibility-criteria
For more information about Precision Medicine visit:
Funding Notes
Qualifications criteria: Applicants applying for an MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area. The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £17,668 (UKRI rate 2022/23).
Full eligibility details are available: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
Enquiries regarding programme: [Email Address Removed]
References
2. Tsirikos AI (2019). Correction of adolescent idiopathic scoliosis using a convex pedicle screw technique: A novel technique for deformity correction. J Bone Joint Surg Essential Surg Tech, 9(1):e9(1-13).
3. Pankaj P (2013). Patient-specific modelling of bone and bone-implant systems: the challenges. Int J Num Meth Biomed Eng, 29:233-49.
4. Scott CEH, Simpson AHRW, Pankaj P (2020). Distinguishing Fact from Fiction in Finite Element Analysis: A guide for clinicians, Editorial in Bone Joint J, 102-B:1271-73.

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