Web accessible MR decision support system for brain tumour diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data (eTUMOUR)

Diagnosis and treatment of brain tumors is based on clinical symptoms, the radiological appearance by Magnetic Resonance Imaging (MRI), and frequently a histopathological diagnosis of a biopsy. However, treatment response of histological or radiologically similar tumors can vary widely, particularly for childhood tumors. New technologies have become available that may greatly improve tumor classification in terms of diagnosis and prognosis, and may allow individually optimized treatments. 1H MR Spectroscopy (MRS) is a non-invasive technique providing information on the biochemicals present (the metabolomic profile) in a tumor. 1H MRS is performed in conjunction with a clinical MRI but widespread use is hampered by specialised analysis requirements and poor dissemination of the skills needed to interpret the data. The genomic profile of tumors can be deteremined with DNA microarrays. Early studies have demonstrated differences in gene expression between tumor grades, as well as between tumour types not easily distinguished by morphologic appearance. We will bring together the expertise required for a large-scale study of the genomic and metabolomic characteristics of brain tumors,with a multi-centre collaboration to acquire statistically significant data,particularly for rare tumor types. In vivo clinical MRS, high-resolution magic angle spinning(HR MAS) 1H MRS of biopsy samples,and gene array analysis, will be used to investigate how metabolomic and genomic profiles relate to clinically relevant factors such as survival time and treatment response. As well as providing new scientific data on the biology of tumors,we intend to develop the technology for this information to be readily and easily used to help radiologists in the management of brain tumors and help the neurosurgeon to establish an accurate prognosis and treatment protocol for the patient.We will build upon previous expertise obtained with INTERPRET EU project(IST-1999-10310),which created a MR