This research and training program will enable me to apply a new kind of magnetic resonance (MR) signal to get noninvasive chemical information about tumors, which could ultimately aid diagnosis and treatment decisions.
The research aims outline the progression of two methods into clinically useful diagnostics. A) A proven method that noninvasively measures the chemical composition of fat will be applied to improve the specificity of breast cancer diagnoses. B) We will also develop a related MR method to noninvasively measure metabolites related to cancer, which will be applicable to a larger number of organs than current techniques Because the lipid-specific method has been demonstrated in mice, our aims for that sequence focus on establishing the significance of that data. After initializing and optimizing the sequence our studies will validate the connection between our data, i.e., peaks in a spectrum, and the chemical composition of adipose tissue in obese mice. Next, human studies will measure the fat in breast tissue to determine whether fat surrounding MR-identified lesions correlates to malignancy or delineates the extent of disease. The proposal also presents a new method that can noninvasively measure chemical components in the body besides fat, including metabolites known to be important markers of cancer. Such measurements have become crucial for diagnosing brain and prostate cancer, but standard techniques yield poor quality data when applied to other organs. We will show that our method works in other organs, such as breast. Since my training is as an MR physicist, completing this work will also require significant amounts of biomedical training, which will be accomplished through a combination of class work, mentorship, and hands- on experience. There are four major training goals in this proposal. 1) Training in molecular biology and cancer biology will begin with a course in molecular biology followed by one in cancer biology. Courses will be supplemented by discussions with my co-mentors, renowned experts in cancer biology and tumor microenvironments, and attendance at national meetings on cancer research. 2) Training in advanced in vivo magnetic resonance techniques will include both formal coursework as well as hands-on training, which will be guided by Dr. Robin De Graaf, author of the leading textbook on the subject. 3) Training in human research studies and biostatistics will include semester long courses in biostatistics and in the ethics of clinical investigations, as well as an intensive workshop on clinical skills for researchers. Hands-on training will be under the guidance of my clinical collaborators, a breast radiologist and a cancer pathologist, both distinguished clinicians who boast extensive research accomplishments. 4) Scientific and career guidance to develop my independent career path are explicitly outlined in the proposal, including a structured mentoring plan and interaction with the broader scientific community.
This project will develop new MRI methods that noninvasively measure chemical composition in organs where conventional methods give low quality data. A proven method that noninvasively measures the chemical composition of fat will be validated and applied to improve the specificity of breast cancer diagnoses. We will also pilot a related MR method to noninvasively measure metabolites related to cancer, which will be applicable to a larger number of organs than current techniques, including breast.
| Wang, Haifeng; Tam, Leo; Kopanoglu, Emre et al. (2017) O-space with high resolution readouts outperforms radial imaging. Magn Reson Imaging 37:107-115 |
| Wang, Haifeng; Tam, Leo K; Constable, R Todd et al. (2016) Fast rotary nonlinear spatial acquisition (FRONSAC) imaging. Magn Reson Med 75:1154-65 |
| Wang, Haifeng; Tam, Leo; Kopanoglu, Emre et al. (2016) Experimental O-space turbo spin echo imaging. Magn Reson Med 75:1654-61 |
| Tam, Leo K; Galiana, Gigi; Stockmann, Jason P et al. (2015) Pseudo-random center placement O-space imaging for improved incoherence compressed sensing parallel MRI. Magn Reson Med 73:2212-24 |
| Li, Shu; Chan, Cheong; Stockmann, Jason P et al. (2015) Algebraic reconstruction technique for parallel imaging reconstruction of undersampled radial data: application to cardiac cine. Magn Reson Med 73:1643-53 |
| Galiana, Gigi; Peters, Dana; Tam, Leo et al. (2014) Multiecho acquisition of O-space data. Magn Reson Med 72:1648-57 |
| Galiana, Gigi; Constable, R Todd (2014) Single echo MRI. PLoS One 9:e86008 |
