Magnetic Resonance Spectroscopy of Breast Cancer using Model-Based Localization

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DESCRIPTION (provided by applicant): Breast cancer is the most common female cancer, with more than 225,000 new cases and nearly 40,000 deaths per year in the US alone. Magnetic resonance imaging (MRI) has become established as the most accurate imaging modality for characterizing breast cancer, and is now widely used for high-risk screening, diagnosis, and assessing treatment response. Magnetic resonance spectroscopy (MRS) is a technique that can be added to an MRI scan and provide addition metabolic information about a lesion. Studies have shown that measuring the concentration of total choline (tCho) in a breast cancer can provide very valuable clinical information. The tCho concentration is higher in cancers than in benign masses, and therefore tCho can be used to improve diagnostic accuracy. It has also been shown that in patients receiving chemotherapy, a drop in tCho measured as soon as 1 day after starting treatment is associated with good treatment outcomes. There are two techniques currently available to measure tCho in breast cancers. The most commonly used technique is called single-voxel spectroscopy (SVS). SVS generally can produce high-quality data the enables accurate measurement of tCho, but it requires that a specially trained expert is present and making adjustments during the scan. In clinical practice, this is very challenging, and has been a critical barrier to making SVS a practical clinical tool. Another technique is called chemical shift imaging (CSI). This has the advantage of not need an expert at scan time, and it performs very well for studying organs such as the brain and prostate. But in the breast, the presence of large lipid signals from adipose tissue produces artifacts in CSI data, making accurate measurements of tCho less practical. In this grant we propose to use an old technique, called SLIM (spectroscopic localization by imaging), and use it in a new and innovative way to acquire data with the same or better quality as SVS, but without the need for the expert operator. The key to this innovation is combining SLIM with modern water-fat imaging methods, which can acquire high-resolution, quantitative maps of the fat and water in the breast. SLIM can then use this high-resolution information to separate the fat signals from the water signals, and the water contains the tCho that is so clinically valuable. In this grant we will develop the SLIM technique along with several promising variations of SLIM. We will refine and test these methods by performing computer simulations, experiments on phantoms that replicate the breast composition, and in normal female volunteers. Once the techniques are sufficiently refined, we will measure tCho in breast cancer patients who are already receiving MRI scans to test the feasibility of the new methods and compare them CSI and SVS. If successful in this innovative technical development study, we will create a new, non-invasive tool that radiologists and oncologists can use to guide the care and treatment of women with breast cancer.