P16.03 * UNIFYING CLINICAL ROUTINE BRAIN TUMOR MR-SPECTROSCOPY AND MR-IMAGE ANALYSIS: NOVEL JMRUI PLUG-INS FOR BRAIN TUMOR ANALYSIS

INTRODUCTION: Magnetic resonance imaging and spectroscopy are the neuroradiological methods of first choice for the diagnostics of de novo brain tumors, the evaluation tumor response to therapy and the tumor progression. Whereas (i.) T2 and post contrast T1-weighted MRI gives information on the brain tumors' anatomy and integrity of the blood brain barrier, (ii.) perfusion weighted MRI on the perfusion state (important to study processes like neo-angiogenis, apoptosis and necrosis), (iii.) diffusion weighted MRI (evaluation for cellular density, and white matter tract integrity), information on the tumors' metabolism is obtained by MR-spectroscopy. Lactate gives information on the ischemic state, choline/ mobile lipids on the membrane turnover and necrosis/apoptosis. The lactate, as present in many high grade glioma, is an indicator an ischemic condition which can ge regarded as an indicator for tumors resistance to radiation therapy. However, despite the fact that MRS gives valuable additional information to MRI, the available software for clinical routine analysis of MRS data together with MRI data is far from ideal. This abstracts reports on the software, which is currently being developed within an EU-funded Marie Curie Initial Training Network (ITN) (http://www.transact-itn.eu/) named TRANSACT which stands for “Transforming Magnetic Resonance Spectroscopy into a Clinical Tool”. METHODS: Basis for the developed software within the TRANSACT-project is the software package jMRUI, which was developed during former EU-funded projects, and targeted mainly on scientific users of MR-spectroscopy; the current TRANSACT project however focuses on the develop software for clinicians. The novel plug-ins for jMRUI were entirely developed in JAVA. RESULTS: The following important clinical work flow related requirements were incorporated: (a.) full support of DICOM image and spectroscopy data format; (b.) a fully featured integrated patient/study/series examination browser; (c.) automatic projection of spectral voxels within automatically loaded reference image stacks; (d.) DICOM transfer using the standard DICOM network data transfer protocol; (e.) DICOM reporting of spectroscopy results, and possibility to transfer of these results into PACS systems; (f.) absolute quantification of single voxel spectra; (g.) advanced display of spectroscopic SVS and MRSI data; (h.) automated fast metabolite image generation (i.) easy correlation of numeric image data and parametric spectral data. CONCLUSION: An intuitive software has been developed for a clinical setting that allows the simutaneous study of MRI/MRS brain tumor data.