Research Scientist, Radiation Oncology Department, Beaumont Health Research Institute
Making a Mathematical Diagnosis: How Combining Medical Imaging with Computational Science can Improve Patient Outcomes
Medical imaging is essential for diagnosing and treating many diseases. While imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT) provide a visualization of internal anatomy, functional imaging modalities provide information on physiological activity. For instance, positron emission tomography (PET) quantifies metabolic activity and pulmonary ventilation scans measure breathing. However, in comparison to CT imaging, functional imaging requires a longer acquisition time, has a lower spatial resolution, and is often susceptible to motion artifacts, particularly in the lungs. With the goal of addressing these shortcomings, my research team and I developed 4DCT-derived functional imaging (CT-FI). CT-FI is an image processing based modality that uses numerical optimization methods to quantify pulmonary function from dynamic computed tomography (often referred to as 4DCT). In this talk, I will present the mathematical derivation and numerical implementation of CT-FI, as well as how its application within cancer radiotherapy, diagnostic imaging, and emergency room medicine can improve patient outcomes.
Edward Castillo is currently a Research Scientist in the Radiation Oncology Department at the Beaumont Health Research Institute. He is also an Adjunct Assistant Professor in the Computational and Applied Mathematics Department at Rice University, as well as an Adjunct Assistant Professor of Medical Physics at Oakland University (Rochester Hills, MI).
Dr. Castillo is originally from San Antonio, TX, where in 2001 he graduated as an Honors Scholar from St. Mary’s University with a B.S. degree in mathematics. He went on to earn M.A. (2005) and Ph.D (2007) degrees from the Computational and Applied Mathematics department at Rice University for his work on medical image processing and then continued this line of research as a postdoctoral scholar in the Mathematics Department at the University of California, Irvine. In 2009, Dr. Castillo joined the department of Radiation Oncology research staff at the University of Texas MD Anderson Cancer Center and in 2012 was promoted to Assistant Professor. During this time, Dr. Castillo became well known for his work on medical image processing and, in collaboration with his research team, for pioneering the CT-derived ventilation imaging modality.
In 2014, Dr. Castillo joined the Beaumont Health Research Institute where he continues his work on the mathematical development, numerical implementation, and clinical application of novel methods for medical image analysis. His current research projects include radiotherapy dose response modeling, numerical methods for computing CT-derived functional imaging, and computer-aided diagnostics. During his career, Dr. Castillo has coauthored over 35 research publications and over 30 conference abstracts. He is a co-investigator and principal investigator on numerous funded projects, including grant awards from the National Institutes of Health, the University of Michigan MTRAC for Life Sciences, and the Beaumont Research Institute’s Nederlander Family Seed Grant Award for Cancer Research.