Data Grid Announced for UK Mammography Research
- 16 October 2002
IBM, Oxford University and the U.K. government have announced plans to build a distributed computing network, or next generation ‘data grid’, to share and store mammograms among health care providers and researchers
The aim is to enable early screening and diagnosis of breast cancer, and to allow medical professionals to collaborate and share information that will help treat the disease.
The network, called eDiamond, is similar to a project IBM launched last year with the University of Pennsylvania.
The data grid will initially link the mammogram databases of several hospitals in the UK, with the potential to include all 92 screening centres in the UK. Project leaders expect the network to be operational at its initial six UK sites within two years and nationally a few years later.
Researchers at any of the six sites will be able to access mammograms stored in the online database and compare them to earlier mammograms for that patient, regardless of where the procedure was completed.
Advanced data mining capabilities will allow physicians to study the effects of environment, heredity and lifestyle on breast cancer. The eDiamond data grid will provide federated data access for radiologists sharing and comparing digital mammogram images distributed in hospitals throughout the UK.
The eDiamond project is part of the United Kingdom’s e-Science initiative. Investments in the project by the U.K. government and IBM are estimated at approximately £4 million.
Future plans also offer the potential to create a worldwide digital mammography grid, linking programs in France, Germany, Japan, as well as the US.
One of the most significant characteristics of this grid is that it will be comprised entirely of commercially available technology. In addition, the grid will be based on open standards including OGSA (the Open Grid Services Architecture).
As well as delivering benefits to mammography research and treatment, the project may prove significant in demonstrating the viability of these next generation ‘data grids’ in healthcare, which has requirements for collaboration and data-sharing capabilities.
Grid computing is a method of harnessing the power of many computers in a network to solve problems requiring a large number of processing cycles and involving huge amounts of data, rather than using a network of computers simply to communicate and transfer data.
Two of the best known examples of Grid computing include the Search for Extra Terrestrial Intelligence (SETI@home) and Oxford University’s Centre for Computational Drug Discovery’s project that, both of which involve PC users worldwide donating unused processing capacity.
