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Characterization and Quantification of Treatment Response for Patients with Glioblastoma multiforme by Referencing to a multi-scale Atlas of Anatomic and Metabolic Imaging Data

Subject Area Nuclear Medicine, Radiotherapy, Radiobiology
Term Funded in 2016
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 318380466
 
The median survival for adult patients with high-grade glioma (GBM) following standard of care treatment is 14 months. A hallmark of GBM is the presence of abnormal microvasculature, increased vasogenic edema and a high degree of infiltration into normal brain. While anatomic images are widely used for diagnosis and clinical assessment of these features, the changes observed following treatment are non-specific and may represent a combination of tumor with gliosis, edema, necrosis and inflammation. A promising technology for resolving such ambiguities is magnetic resonance spectroscopic imaging (MRSI), which provides information about the biological and metabolic properties of the tissue. Generally, brain diseases like tumors or multiple sclerosis, cause strong metabolic changes in the brain, which makes them very suited for MRSI characterization. However, MR spectroscopic imaging is still not widely used as a standard modality in clinical context. One reason for this discrepancy is that the method is technically challenging, which requires additional training and expertise. In addition, the lack of a standard reference framework, which defines the normal values of metabolic information at different spatial locations, makes it prone to evaluation uncertainties due to the subjective component of the viewer.The objective of this project is to provide a reference framework for the automated analysis of brain MRSI data from patients with GBM by providing reliable and robust metrics that describe the spatial and temporal changes in the lesion and surrounding tissue. The first step will be to obtain MRSI data from healthy volunteers in order to construct a metabolic atlas of the normal human brain, which will be provided to the research community upon validation. Furthermore, the atlas will be used as a reference standard to identify abnormal patterns in MRSI data obtained from over 400 patients at UCSF and link them to histological properties from image-guided tissue samples. The relationships that are established will allow classification algorithms to be developed for assessing response to treatment and evaluating tumor progression in serial patient scans. The methods will provide objective criteria for predicting outcome and characterizing new therapies. The findings will improve diagnosis and assist in selecting appropriate treatments, as well as accelerating the discovery and evaluation of improved treatments.
DFG Programme Research Fellowships
International Connection USA
 
 

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