Decompressive craniectomy (DC) is a surgical procedure in which the neurosurgeon removes a section of skull in order to reduce uncontrolled raised intra-cranial pressure (ICP) post traumatic brain injury. DC has seen renewed interest in recent years, however, there remains doubt as to the efficacy of the procedure. Engineering models of DC can aid the surgeon in furthering their understanding of the procedure and its likely effects on the brain during surgery. These models may provide useful insight into the procedure and regions where the methods may be optimised. Current work includes a parametric finite element study of a simplified brain model and further experimental and FE work in order to validate the models. The PhD project is being undertaken by Tim Fletcher, co-supervised by Peter Hutchinson at the Department of Neurosurgery and in collaboration with colleagues there on the RescueICP project. [Picture acknowledgement F Servadei]

Cardiovascular disease is a major cause of death. Rupture of diseased atherosclerotic plaque leads to stroke, while the benefits of lowering high blood pressure using drugs are well established. The project aims to develop new coupled mechanical-pharmacological models of arteries to describe plaque rupture and arterial response to drugs. This will lead to more effective ways for clinicians to treat vulnerable plaque and identify novel pharmacological treatments. The pharmacological response of healthy and diseased coronary arteries is measured by inserting artery rings into an organ bath. Appropriate drugs are introduced and the force of contraction of the artery measured. These constituent components can be combined in a mathematical model of the mechanical-pharmacological response of the artery. Chen Yen Ooi is currently working on a PhD in this area, in collaboration with Anthony Davenport and Janet Maguire at the Department of Clinical Parmacology. There are also close links with Jonathan Gillard and Zhongzhao Teng at the Department of Radiology, measuring material properties and linking modelling with MRI data and clinical trial results.

Radiotherapy remains one of the most potent curative treatments for cancer. For many common cancers, up to half of patients treated experience some degree of toxicity. Current dose escalation strategies are based on static models of the patient anatomy, and do not take into account variation in patient position, shape and location of mobile internal organs. This research project aims to provide bio-engineering models and analysis tools to predict tissue-tracked dosage mapping and hence guide development of appropriate patient-specific radiotherapy protocols. The project is being undertaken by Robin Boudsocq co-supervised by Dr Sutcliffe at Engineering and Dr Burnett at Oncology, with support from his colleague Dr Jena at Oncology. The work is funded by the Armstrong Trust and is part of the Voxtox project. [Picture acknowledgement Brook et al, 2010]

I have been involved with various projects in collaboration with colleagues at Addenbrooke's Hospital and the Department of Veterinary Medicine, predominantly working on mechanical and materials testing, with help from Alan Heaver and Anne Bahnweg in the Department. Projects include: (i) testing of suture configurations for use in repairing cruciate disease in canine stifle joints, (ii) strength of hand tendon repairs, (iii) assessment of different techniques for treating feline talocrural luxation using suture prostheses and bone tunnels, (iv) assessment of different fixation plate configurations for stabilising canine tibia fracture.

This project investigated brain compliance and deformation associated with various neuro-pathologies (head injury and hydrocephalus), focussing on two different modelling approaches: global and structural. In the global approach, the relationship between added volume and pressure response was analysed in terms of cerebrospinal volume-pressure compensatory reserve or brain compartmental compliances. For the structural approach, magnetic resonance imaging data were processed to generate meshes for finite element analysis. For hydrocephalus, the resulting models can be used to help define the degree of pathogenesis by considering the size of ventricles and the extent of cerebral oedema and to discriminate between hydrocephalus and other neurological disorders. These hold the potential to improve treatment outcomes for individual patients by making pragmatic treatment decisions in clinical practice. The PhD project was undertaken undertaken by DongJoo Kim, co-supervised by Marek Czosnyka at the Department of Neurosurgery and in collaboration with colleagues there.