Broad long-term objectives: To determine which MR metrics are able to predict time to progression/survival, particularly in low grade gliomas, to provide a second reference standard to histology in glioma therapy triage. Health-relatedness: Current surgical and post-surgical glioma therapy is based on the conventional MRI and histologic features of a glioma. However, there are limitations with both MRI and histology in predicting the true biologic behavior of gliomas. MR metrics, which can provide an indication of the true biologic aggressiveness of an entire lesion in vivo, will be useful in determining the extent of surgical resection, direct tissue specimens for further histologic/ molecular analysis, and the triage of adjuvant chemotherapy and radiation therapy following surgery.
Specific aims : 1) To determine which MR metrics obtained from conventional MRI, perfusion MR and MR spectroscopic imaging in low-grade gliomas are able to predict time to progression/survival. Hypothesis 1: One or more MR metrics will be able to predict tumor biologic behavior. 2) To compare MR metrics with other known prognostic factors (such as histology) in predicting time to progression/survival. Hypothesis 2: Quantitative MR metrics will have added value in and above histopathologic assessment in predicting tumor biologic behavior. 3) To determine if MR metrics can serve as imaging correlates for molecular signatures of chemosensitivity. Hypothesis 3: MR metrics such as rCBV (and others) can be correlated with molecular markers of tumor progression, angiogenesis, invasion, proliferation and chemosensitivity such as HIF-la, FAK, VEGF/VPF, Ipl9q deletions and in turn can be used as marker for guiding further molecular analysis, therapy and predicting prognosis. Research Design: 1) Acquire conventional MRI, perfusion (DSC MRI) and spectroscopic (MRSI) data sets to obtain quantitative MR metrics from study patients. 2) Weibull survival model analysis and Kaplan-Meier survival curves will be used to determine which metrics can predict time to progression/survival. Metrics will be compared with pathology and other prognostic factors in predicting outcome. 3) Finally MR metrics will be correlated with molecular markers of tumor progression, angiogenesis, proliferation and chemosensitivity such as HIF-la, FAK, VEGF/VPF, Ipl9q deletions. Molecular studies will be assessed by loss of heterozygosity using PCR. DNA will be extracted from paraffin curls of brain section and nail clippings and the following primers will be used: 1. D1S1592; 2. D19S219, D19S412. ? ?
|Baete, Steven H; Boada, Fernando E (2018) Accelerated radial diffusion spectrum imaging using a multi-echo stimulated echo diffusion sequence. Magn Reson Med 79:306-316|
|Baete, Steven H; Chen, Jingyun; Lin, Ying-Chia et al. (2018) Low Rank plus Sparse decomposition of ODFs for improved detection of group-level differences and variable correlations in white matter. Neuroimage 174:138-152|
|Baete, Steven H; Yutzy, Stephen; Boada, Fernando E (2016) Radial q-space sampling for DSI. Magn Reson Med 76:769-80|
|Rosenkrantz, Andrew B; Koesters, Thomas; Vahle, Anne-Kristin et al. (2015) Quantitative graphical analysis of simultaneous dynamic PET/MRI for assessment of prostate cancer. Clin Nucl Med 40:e236-40|
|Patil, Vishal; Johnson, Glyn (2013) ?R2 (*) gadolinium-diethylenetriaminepentacetic acid relaxivity in venous blood. Magn Reson Med 69:1104-8|
|Patil, Vishal; Johnson, Glyn (2011) An improved model for describing the contrast bolus in perfusion MRI. Med Phys 38:6380-3|
|Patil, Vishal; Johnson, Glyn; Jensen, Jens H (2009) Robust quantification of contrast agent (CA) concentration with magnetic field correlation (MFC) imaging. Magn Reson Med 62:1002-6|
|Young, Robert; Babb, James; Law, Meng et al. (2007) Comparison of region-of-interest analysis with three different histogram analysis methods in the determination of perfusion metrics in patients with brain gliomas. J Magn Reson Imaging 26:1053-63|
|Law, M; Young, R; Babb, J et al. (2007) Histogram analysis versus region of interest analysis of dynamic susceptibility contrast perfusion MR imaging data in the grading of cerebral gliomas. AJNR Am J Neuroradiol 28:761-6|
|Pivawer, Gabriel; Law, Meng; Zagzag, David (2007) Perfusion MR imaging and proton MR spectroscopic imaging in differentiating necrotizing cerebritis from glioblastoma multiforme. Magn Reson Imaging 25:238-43|
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