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Innovative Advances in Parallel Computing Open Up the Possibilities of Virtual Cancer Experiments in 3D
The use of supercomputing technology to build realistic 3D models of tumour dynamics could allow us to develop new targeted therapy treatments and advanced medical imaging techniques.
By Paul Darbyshire
Dec. 31, 2015

Over the last decade, high-performance computing has evolved dramatically, in particular because of the accessibility to graphics processing units(GPUs) and the emergence of GPU-CPU heterogeneous architectures, which have led to a huge shift in the available medical applications for supercomputing and parallel programming.A recent paper, by author Dr. P. M. Darbyshire, show the interoperability between a parallel programming model and the graphics hardware allows us to generate dynamic interactive 3D realistic visualisations of tumour dynamics.

“We deploy the compute unified device architecture (CUDA) for the complex parallel calculations and deploy open graphics library (OpenGL) for on-the-fly 3D visualisation of the numerical simulations to continuous-discrete mathematical models of tumour dynamics. Indeed, once we have a model that is validated it is possible to more efficiently predict what should be happening in a particular biological experiment. With such a predictive model it is much easier and faster to perform virtual experiments to test hypotheses and predictions than running time consuming and costly laboratory experiments”, said Darbyshire.

Clearly, being able to link the numerical results of complex mathematical models to interactive 3D visualisations that can literally update instantaneously to varying model parameters, should provide an invaluable tool for clinical physicians and research scientists. Moreover, such rapid and interactive virtual experimental representations can also facilitate oncological research and pharmaceuticals in developing and testing new anti-cancer treatment strategies.

“Implementing more integrative mathematical models that take into, for example blood flow dynamics could make it possible to use such techniques for accelerated 3D image processing, visualisation and dynamic interaction. Significant gaps remain in our understanding of the mechanisms that determine the spatial organisation of angiogenic growth and the topology of the resulting vascular network. Advances in medical imagining technology for studying microcirculatory and hemodynamics at the deepest level will hopefully help close this gap”, said Darbyshire.

Studying the blood flow within the vasculature surrounding atumour whilst also investigating enhanced methods to visualise in 3D the supply of targets to a tumour through the blood vessel superhighway are definitely the way forward. By developing mathematical models with built in factors, such as blood pressure, viscosity, flow rates and other mechanical stress factors, we can further understand angiogenesis has a mechanism for targeting cancer directly. Being able to interact with such models in real time will allows us to experiment with parameters and dynamically change the topology and investigate other strategies for targeted therapy. For example, we could investigate the effects of capillary pruning and clipping along with self-fusion and devise an optimum pathway to the tumour to increase speed of delivery of anti-cancer treatments, all of which can be mapped and tracked in a virtual 3D laboratory.

Darbyshire and his team are currently developing new and innovative algorithms that will realise the goal of having a full interactive 3D virtual laboratory to aid oncologists, researchers and others in the fight against cancer.

Dr P. M. Darbyshire is Technical Director, Computational Biophysics Group, Algenet Cancer Research, Nottingham. UK.

3D Visualisation of Tumour-Induced Angiogenesis Using the CUDA Programming Model and OpenGL Interoperability. doi: 10.11648/j.jctr.20150305.11.

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