Project Summary/Abstract Mammography is the most used imaging-based screening tool, because it is accessible and cost-effective. However, mammography has its limitations. The sensitivity of mammography is only 70-90%, and it has a positive predictive value that ranges widely from 20-80%. Additionally, the accuracy of mammography decreases in dense breasts. In 2015 only 65.3% of women in the United States had had their recommended mammogram. Women opt-out of mammography for several reasons. Individual factors such as inability to tolerate the compression needed for mammographic imaging, concerns about radiation used in mammograms and anxiety about false positives are all barriers to screening mammography. Currently available MRI-based methods can overcome some of these issues. MR imaging does not use compression and does not involve radiation. MR imaging is effective because differences in soft tissues can be visualized without obfuscations from dense tissues. Indeed, quantitative MRI measurements of T1 and T2 relaxation times and Apparent Diffusion Coefficient (ADC) can distinguish healthy and tumor tissues. We propose the use of quantitative magnetic resonance imaging (MRI) for breast cancer at ultra-low magnetic field (ULF) strength (6.5 mT). Specifically, we will use a quantitative MRI technique called T1rho dispersion to generate a map of fat, fibroglandular and tumor tissues at ULF. T1rho dispersion is limited by RF deposition safety concerns at clinical field strengths (1.5 T and 3 T); however, because these safety concerns scale with the square of magnetic field strength, that is not an issue at 6.5 mT. We address the project through two complimentary aims: First, we will collect T1rho dispersion data in vivo using localized spectroscopy to assess the feasibility of this idea (Aim 1). This aim requires constructing breast coils for ULF. Then, we will develop a T1rho dispersion imaging experiment based on an SSFP sequence combined with AI reconstruction (Aim 2). For this aim, we will construct a breast phantom or reference object to mimic the breast tissue properties at ULF. This project will assess the feasibility of using the T1rho SSFP sequence to rapidly distinguish fat, fibroglandular and tumor tissues and will compare T1rho dispersion categorization of tissues (e.g., healthy, benign, malignant) with pathology reports of biopsied tissue. Ultra-low field T1rho dispersion MRI may enable the widespread adoption of an MRI-based screening tool for breast cancer without risk of radiation or contrast agents and with increased certainty in dense tissues. An ultra- low field MRI system would be cheaper than conventional MRI, has greatly reduced siting requirements, like mammography centers, and used as a screening tool, would enable frequent imaging in high-risk populations and may increase compliance for those who currently opt-out of mammography.