Despite remarkable advances in cancer detection and treatment, the disease continues to be a leading cause of mortality in the US accounting for 23% of all deaths in 2011. Cancer of the breast and prostate are by far the most common forms diagnosed in US women and men, respectively, and together are expected to represent more than 450,000 (246,000 prostate, 229,000 breast cancers) new cases and more than 68,000 deaths this year. Since the serious overtreatment of each disease is such a significant issue, improved methods for minimally invasive detection and therapy monitoring are badly needed. Dynamic contrast- enhanced (DCE)-MRI offers substantial promise in this regard. It is a technique acquiring a time-series of T1- weighted MR images before, during, and after intravenous injection of a paramagnetic contrast reagent (CR). The benefits of quantifying the DCE-MRI time-series using a pharmacokinetic model have gained significant interest in recent years and the resulting parametric maps are increasingly important in cancer diagnostics and treatment evaluation. Recent studies demonstrate that quantitative DCE-MRI has the potential to improve accuracy in cancer detection and provide earlier and more accurate evaluation of cancer response to therapy. The overall goal of this SBIR Fast-Track project is to develop and validate a commercial diagnostic software application based on the """"""""Shutter-Speed Model"""""""" (SSM) for quantitative DCE-MRI. The SSM is a novel algorithm that properly accounts for the finite kinetics of water exchange between tissue compartments. This is important because a unique aspect of DCE-MRI is that the CRs are detected indirectly, via their effect on the 1H2O MR signal;CR is the tracer molecule but water is the signal molecule. The SSM approach naturally embraces this feature and has been shown to deliver more reliable discrimination between benign and malignant tissue than the standard tracer DCE pharmacokinetic model.
This proposal will develop a commercial software package that uses the Shutter Speed Dynamic Contrast Enhanced MRI method to aid physicians in breast and prostate cancer diagnosis, presently two of the leading causes of death in the US. The successful outcome of this effort will give physicians greater insight into disease stage and progression, leading to improved patient care and a reduction in cost to the healthcare system.
|Tudorica, Alina; Oh, Karen Y; Chui, Stephen Y-C et al. (2016) Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI. Transl Oncol 9:8-17|
|Li, Xin; Cai, Yu; Moloney, Brendan et al. (2016) Relative sensitivities of DCE-MRI pharmacokinetic parameters to arterial input function (AIF) scaling. J Magn Reson 269:104-12|
|Rooney, William D; Li, Xin; Sammi, Manoj K et al. (2015) Mapping human brain capillary water lifetime: high-resolution metabolic neuroimaging. NMR Biomed 28:607-23|
|Springer Jr, Charles S; Li, Xin; Tudorica, Luminita A et al. (2014) Intratumor mapping of intracellular water lifetime: metabolic images of breast cancer? NMR Biomed 27:760-73|