Ovarian cancer is the primary cause of mortality resulting from gynecological cancer, and frequently presents at a late stage when it has metastasized throughout the peritoneal cavity. There has been significant progress in the development of new chemotherapeutic strategies to target these metastatic tumors, however pre-clinical studies suffer from an inability to non-invasively and accurately measure the tumor burden. We propose to develop a new imaging technique that combines two emergent and complementary technologies, Magnetic Particle Imaging (MPI) and Magneto- Endosymbionts (MEs). The former is a new type of imaging scanner that enables deep- tissue imaging of iron with zero background, making it valuable in cases where MRI would struggle due to an inability to differentiate iron from normal anatomic features. The latter is a new class of contrast agent for labeling and tracking cells, based on iron-rich magnetotactic bacteria, which has the potential to solve a long-standing issue of contrast agent dilution through cell division. The combination will allow preclinical tumor models based on injection of exogenous tumor cells to be tracked in vivo for several cell generations throughout the body, irrespective of local physiology. First we plan to optimize the MPI hardware to adapt it to the specific properties of magnetotactic bacteria (Aim 1), by changing the excitation frequency (to take into account the longer rotational times of magnetosomes) and detection electronics (to improve sensitivity). Concurrently, we will genetically engineer MEs to produce magnetosomes (iron containing organelles) which are at the optimal size and shape required for efficient MPI (Aim 2). Preliminary results suggest that with these modifications it should be possible to quantitatively monitor cancer implantation, growth, metastases, and pharmaceutical response in a mouse animal model of ovarian cancer, and we plan to evaluate this in Aim 3. We expect that a combination of MRI (for an anatomic reference) and MPI (for high sensitivity detection of the iron) will produce information-rich in vio image data that can be used to quantify metastatic ovarian tumor burden, and which will also be applicable for other preclinical cell tracking applications involving stem or tumor cells.

Public Health Relevance

It is well-known that preclinical imaging techniques play a central-role in the development of new therapies for diseases like cancer. Unfortunately, current preclinical imaging modalities have several limitations that prevent quantitative imaging in various anatomic locations, for example with metastatic ovarian cancer. Such tumors are obscured using current modalities by respiratory motion, difficulty in differentiating them from ai pockets (MRI), limited depth penetration (BLI), and high background signal (PET). In this proposal we aim to combine two relatively new technologies, Magnetic Particle Imaging and Magneto-Endosymbionts to solve these limitations. The resulting imaging technology will enable researchers to non-invasively image previously limited anatomic regions, and accurately measure their response to novel therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB019458-03
Application #
9185975
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Wang, Shumin
Project Start
2015-01-01
Project End
2018-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
3
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
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