March 2008
Urgent Computing: Exploring Supercomputing's New Role
Steven Manos
Stefan Zasada
Peter V. Coveney, Centre for Computational Science, Chemistry Department, University College London


HemeLB is intended to yield patient-specific information, which helps plan embolisation of arterio-venous malformations and aneurysms, amongst other neuro-pathologies. Using this methodology, patient-specific models can be used to address issues with pulsatile blood flow, phase differences and the effects of treatment, all of which are potentially very powerful both in terms of understanding neurovascular patho-physiology and in planning patient treatment.

The software environment used in this project aims to bring to the forefront details and processes clinicians need to be aware of, such as (i) the process of image segmentation to obtain a 3D neurovascular model, (ii) the specification of pressure and velocity boundary conditions, and (iii) the real-time rendered image (Figure 2). Clinicians are not concerned with where simulations are running, nor the details of reservations, thus features such as advanced reservations and emergency computing capabilities, job launching and research selection are all done behind the scenes. This environment is particularly important given the time scales involved in the clinical decision making process in the treatment of aterio-venous malformations and aneurysms. From the acquisition of a 3D dataset (which is typically 2 to 4 GB in size), to the next embolisation, a time scale of 15 to 20 minutes is typical, and for such computational approaches to be clinically relevant, we have to fit into this time scale. There are also preventative scenarios that can be envisioned; patients could be subjected to such simulations in advance of vascular pathologies developing, averting future problems with interventional treatments.

Figure 2

Figure 2. The workflow cycle for the simulation of neurovascular blood flow from the viewpoint of a clinician. Patient-specific data is acquired in the form of MRI or X-ray CT scans, and a 3D model of the neurovascular structure is created. Real-time simulation and interactive visualisation is used to examine blood flow through the brain. At this point, new boundaries and other physical changes can be made to the vascular structure, where the clinician can observe changes in pressure and velocity throughout the vasculature prior to operating. Many of the details, such as machine reservations and job submission are completely hidden from the surgeon/clinician/consultant.

Pages: 1 2 3 4 5 6 7 8 9

Reference this article
Manos, S., Zasada, S., Coveney, P. V. "Life or Death Decision-making: The Medical Case for Large-scale, On-demand Grid Computing," CTWatch Quarterly, Volume 4, Number 1, March 2008. http://www.ctwatch.org/quarterly/articles/2008/03/life-or-death-decision-making-the-medical-case-for-large-scale-on-demand-grid-computing/

Any opinions expressed on this site belong to their respective authors and are not necessarily shared by the sponsoring institutions or the National Science Foundation (NSF).

Any trademarks or trade names, registered or otherwise, that appear on this site are the property of their respective owners and, unless noted, do not represent endorsement by the editors, publishers, sponsoring institutions, the National Science Foundation, or any other member of the CTWatch team.

No guarantee is granted by CTWatch that information appearing in articles published by the Quarterly or appearing in the Blog is complete or accurate. Information on this site is not intended for commercial purposes.