The goal of this study is to develop robust tools for acquiring and analyzing in vivo MR metabolic data in patients with recurrent glioma that will be integrated with state of the art MR imaging methods to provide improved metrics for serially monitoring response to therapy. This addresses an important clinical problem, which is confounding the evaluation of novel treatments and making it difficult to make informed decisions about patient care. For subjects with high grade glioma, there is ambiguity between morphological changes that are caused by recurrent tumor and treatment effects such as gliosis and edema. Based on results from the current cycle of this R01, metabolites of interest for mapping out the true extent of recurrent tumor are myo-inositol (myo-I), N-acetylasparate (NAA), creatine (Cr) and choline (Cho). For subjects with an original diagnosis of low grade glioma who have a lesion which is increasing in size, the critical issue is to determine when they have undergone transformation to a more malignant phenotype that requires aggressive therapy. From our ex vivo analysis of tissue samples, additional metabolites of interest in this case are myo-I, glutamate, glutamine, glycine, glutathione and 2-hydroxyglutarate (2HG).
In Specific Aims 1 and 2 we will optimize and then evaluate the test-retest accuracies of automated short TE 3D MRSI, as well as single voxel spectral editing and 2-D COSY sequences that will be used to detect in vivo levels of metabolites with complex coupling patterns and overlapping resonances. This will be done for both 3T and 7T scanners in order to determine which method and field strength will provide the most definitive results for patient studies.
In Specific Aim 3 we will apply methods optimized for detecting 2HG to patients with recurrent low grade glioma to identify metabolic parameters associated with time to progression and overall survival.
In Specific Aim 4, we will perform an analysis in patients with recurrent hig grade glioma using the most reliable strategy for obtaining short TE 3D MRSI data. The results from this study will provide new metrics for assessing response to therapy and for selecting alternative treatments.

Public Health Relevance

The objective of this study is to improve the management of patients with recurrent glioma using novel MR metabolic imaging methods that can distinguish treatment effects from tumor and are able to predict clinical outcome. This is critically important for making decisions about when and how to treat patients with novel therapies, which can provide ambiguous findings using conventional anatomic imaging.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
2R01CA127612-06
Application #
8577002
Study Section
Special Emphasis Panel (ZRG1-DTCS-A (81))
Program Officer
Henderson, Lori A
Project Start
2007-04-01
Project End
2018-05-31
Budget Start
2013-08-13
Budget End
2014-05-31
Support Year
6
Fiscal Year
2013
Total Cost
$344,986
Indirect Cost
$120,429
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Lupo, Janine M; Molinaro, Annette M; Essock-Burns, Emma et al. (2016) The effects of anti-angiogenic therapy on the formation of radiation-induced microbleeds in normal brain tissue of patients with glioma. Neuro Oncol 18:87-95
Akassoglou, Katerina; Agalliu, Dritan; Chang, Christopher J et al. (2016) Neurovascular and Immuno-Imaging: From Mechanisms to Therapies. Proceedings of the Inaugural Symposium. Front Neurosci 10:46
Nelson, Sarah J; Li, Yan; Lupo, Janine M et al. (2016) Serial analysis of 3D H-1 MRSI for patients with newly diagnosed GBM treated with combination therapy that includes bevacizumab. J Neurooncol 130:171-179
Wen, Qiuting; Jalilian, Laleh; Lupo, Janine M et al. (2015) Comparison of ADC metrics and their association with outcome for patients with newly diagnosed glioblastoma being treated with radiation therapy, temozolomide, erlotinib and bevacizumab. J Neurooncol 121:331-9
Li, Yan; Park, Ilwoo; Nelson, Sarah J (2015) Imaging tumor metabolism using in vivo magnetic resonance spectroscopy. Cancer J 21:123-8
Li, Yan; Larson, Peder; Chen, Albert P et al. (2015) Short-echo three-dimensional H-1 MR spectroscopic imaging of patients with glioma at 7 Tesla for characterization of differences in metabolite levels. J Magn Reson Imaging 41:1332-41
Elkhaled, Adam; Jalbert, Llewellyn; Constantin, Alexandra et al. (2014) Characterization of metabolites in infiltrating gliomas using ex vivo ¹H high-resolution magic angle spinning spectroscopy. NMR Biomed 27:578-93
Lupo, Janine M; Nelson, Sarah J (2014) Advanced magnetic resonance imaging methods for planning and monitoring radiation therapy in patients with high-grade glioma. Semin Radiat Oncol 24:248-58
Essock-Burns, Emma; Phillips, Joanna J; Molinaro, Annette M et al. (2013) Comparison of DSC-MRI post-processing techniques in predicting microvascular histopathology in patients newly diagnosed with GBM. J Magn Reson Imaging 38:388-400
Ozhinsky, Eugene; Vigneron, Daniel B; Chang, Susan M et al. (2013) Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging. Magn Reson Med 69:920-30

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