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Laboratory of Analytical Chemistry, Nijmegen University

MV Scientific short echo time prototype Demo of most important features. Arjan Simonetti, Joshua Underwood, Willem Melssen, Geert Postma, Lutgarde Buydens. Laboratory of Analytical Chemistry, Nijmegen University. Main goals

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Laboratory of Analytical Chemistry, Nijmegen University

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  1. MV Scientific short echo time prototype Demo of most important features Arjan Simonetti, Joshua Underwood, Willem Melssen, Geert Postma, Lutgarde Buydens Laboratory of Analytical Chemistry, Nijmegen University

  2. Main goals • Development of a classification model based on short echo MRSI and MRI data. • Construction of a user friendly demo in cooperation with Joshua. Laboratory of Analytical Chemistry, Nijmegen University

  3. Research questions • Predict the patients tumor type with the highest degree of reliability. • Identify the tumor location. • Provide an indication of the tumors heterogeneity. • Present information to the clinician. Laboratory of Analytical Chemistry, Nijmegen University

  4. Approach • Acquisition of short echo MRI and MRSI data; performed by UMCN. • Pre-process the data in the same unique way. • Segment the brain into 3, 4, 5 and 6 segments. • Select the best segmentation through criterion or clinician. • Classify each segment using a classification model. • Construct spatial probability maps to assess the heterogeneity of the tissue. - Distribution of classes in space. • Classify each voxel. • Present the succesive steps by means of images to the clinicians. Laboratory of Analytical Chemistry, Nijmegen University

  5. Distribution of classes in space treshold treshold % of objects r Laboratory of Analytical Chemistry, Nijmegen University

  6. Distribution of classes in space normal grade II Laboratory of Analytical Chemistry, Nijmegen University

  7. Probability plots and classification of UMCN005 normal CSF grade II grade III GBM classification Laboratory of Analytical Chemistry, Nijmegen University

  8. conclusion - We developed a classification model which achieves a robust classification and which gives an insight in the heterogeneity of the tissue by probability maps. - Classificaton of segmented area’s can be compared with classification of voxels, providing a consensus diagnosis. Laboratory of Analytical Chemistry, Nijmegen University

  9. Lessons learned - What is the relation between pathologic classes and spectroscopic classes? - More information from pathology is desirable, e.g., fractions of cell type. - Putting effort into spectral pre-processing and combination of MRI and MRSI might be more important than trying to find the best classification model. - Future of MV and SV system?? Laboratory of Analytical Chemistry, Nijmegen University

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