Diagnosis and treatment of brain tumours is based on clinical symptoms, radiological appearance, and often a histopathological diagnosis of a biopsy. However, treatment response of histologically or radiologically similar tumours can vary widely, particularly so for childhood tumours. Magnetic Resonance Spectroscopy (MRS) is a non-invasive technique for determining tissue biochemicals (the metabolomic profile). The genomic profile of tumours can be determined with DNA microarrays which helps to classify tumour grades and types not easily distinguished by morphologic appearance. Tumour data dealing with clinical information, as well as MRS and DNA microarrays, are made available all over the world and should be used to make better classifications of new tumour cases. To enable this, data will be stored in properly structured databases and clinical centers hosting them will share the data. An approach engendered by mutual benefit (data in return for access to improved diagnostic decision support) will be used to ensure data sharing.We will bring together the expertise required to define a standard ontology incorporating clinical data with genomic and metabolic characteristics of tumours. An agent-based architecture will be built that integrates the disseminated knowledge of clinical data, MRS and gene array analysis of biopsies with the collaboration of multiple centres. We plan to have a local database per local site in some hospitals, rather than collecting all information to a central server. This approach has the advantage that it will overcome some barriers caused by local centres having strict policies of sharing information whilst allowing them to benefit from regular updates of database structure and the global decision support system.
|Effective start/end date||1/01/06 → 31/12/08|
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