The prognosis of patients with malignant gliomas remains dismal. In addition, limitations in neuroimaging complicate the clinical management of these patients and impede efficient testing of new therapeutics. While extension of MRI to the cellular and molecular level has introduced new possibilities for imaging malignant gliomas, most molecular MRI studies have been limited to the pre-clinical setting. Recently, a new type of molecular MRI contrast has become available that detects the body's own building blocks: amino acids, proteins and carbohydrates. The magnetic contrast produced by these natural species is due to the presence of groups of protons (NH, NH2, OH) that can exchange with the protons on water and, as such, affect the signal in MRI images. The nomenclature for these compounds is based on their first mechanism of detection with MRI, namely ?Chemical Exchange Saturation Transfer? or ?CEST?. Amide proton transfer weighted (APTw) MRI is an endogenous CEST method with potential for improving cancer diagnosis (identifying and determining the extent of malignant disease), therapeutic monitoring (objective assessment of change in tumor burden), and distinguishing recurrent tumor from treatment effects. However, the current saturation-based approach has low specificity for amide protons due to interference of large confounding background signals from direct water saturation (DS) and conventional magnetization transfer contrast (MTC) from semisolid tissue components, as well as from signals from other endogenous CEST metabolites. We propose to address this by developing pulsed exchange transfer approaches, i.e. not based on RF saturation labeling but on proton excitation and proton frequency evolution labeling, that can remove such confounding effects.
In AIM 1, we will develop pulse sequences that can achieve magnetic labeling of exchangeable protons using trains of RF excitation pulses with variable delays. We use these to encode the exchangeable protons based on their specific chemical shift evolution (frequency encoding) and their exchange transfer properties, which allows removal of the confounding effects mentioned above.
In AIM 2, the goal is quantification of the exchange transfer contrast. Using the editing methods developed in AIM 1, we will design approaches to measure absolute concentrations and validate them using known concentrations in phantoms. In vivo, the water signal used for the detection of exchange transfer will be used as an internal standard. Finally, in AIM 3, we will translate the methodology to fast 3D whole-brain scanning on animal and human systems.
These aims are expected to result in the availability of quantifiable APT contrast MRI in patients with gliomas. While we focus demonstration of the usefulness of the new methods on glioma animal models and patients, the technical developments in this proposal are expected to be important for tumor imaging in general, several other pathologies (e.g. stroke, neurodegeneration), and for the imaging of CEST contrast agents for which the interference of MTC, DS and endogeneous CEST background signals is a major problem.

Public Health Relevance

Limitations in neuroimaging complicate the clinical management of glioma patients and impede efficient testing of new therapeutics. Recently, a new type of MRI contrast has become available that can employ the body's own building blocks: amino acids and proteins, and is detected noninvasively using the body's solvent: water. Our goal is to develop the advanced MRI technology needed to rapidly and quantitatively image such compounds, which has potential for improving cancer diagnosis (identifying and determining the extent of malignant disease), therapeutic monitoring (objective assessment of change in tumor burden), and distinguishing recurrent tumor from treatment effects.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB015032-06
Application #
9352329
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Liu, Guoying
Project Start
2011-08-01
Project End
2020-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
6
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Hugo W. Moser Research Institute Kennedy Krieger
Department
Type
DUNS #
155342439
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Li, Yuguo; Qiao, Yuan; Chen, Hanwei et al. (2018) Characterization of tumor vascular permeability using natural dextrans and CEST MRI. Magn Reson Med 79:1001-1009
Chen, Lin; Xu, Xiang; Zeng, Haifeng et al. (2018) Separating fast and slow exchange transfer and magnetization transfer using off-resonance variable-delay multiple-pulse (VDMP) MRI. Magn Reson Med 80:1568-1576
Chen, Lin; Wei, Zhiliang; Chan, Kannie W Y et al. (2018) Protein aggregation linked to Alzheimer's disease revealed by saturation transfer MRI. Neuroimage 188:380-390
Knutsson, Linda; Xu, Jiadi; Ahlgren, André et al. (2018) CEST, ASL, and magnetization transfer contrast: How similar pulse sequences detect different phenomena. Magn Reson Med 80:1320-1340
Liu, Jing; Bai, Renyuan; Li, Yuguo et al. (2018) MRI detection of bacterial brain abscesses and monitoring of antibiotic treatment using bacCEST. Magn Reson Med 80:662-671
Zhang, Jia; Li, Yuguo; Slania, Stephanie et al. (2018) Phenols as Diamagnetic T2 -Exchange Magnetic Resonance Imaging Contrast Agents. Chemistry 24:1259-1263
Jiang, Shanshan; Eberhart, Charles G; Lim, Michael et al. (2018) Identifying Recurrent Malignant Glioma after Treatment Using Amide Proton Transfer-Weighted MR Imaging: A Validation Study with Image-Guided Stereotactic Biopsy. Clin Cancer Res :
Banerjee, Sangeeta Ray; Song, Xiaolei; Yang, Xing et al. (2018) Salicylic Acid-Based Polymeric Contrast Agents for Molecular Magnetic Resonance Imaging of Prostate Cancer. Chemistry 24:7235-7242
van Zijl, Peter C M; Lam, Wilfred W; Xu, Jiadi et al. (2018) Magnetization Transfer Contrast and Chemical Exchange Saturation Transfer MRI. Features and analysis of the field-dependent saturation spectrum. Neuroimage 168:222-241
Yadav, Nirbhay N; Yang, Xing; Li, Yuguo et al. (2017) Detection of dynamic substrate binding using MRI. Sci Rep 7:10138

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