Caroline Chung, M.D., MSc., FRCPC, CIP
Associate Professor, Department of Radiation Oncology, Division of Radiation Oncology
Vice President, Chief Data Officer
Dr. Chung is vice president and chief data officer and director of Data Science Development and Implementation of the Institute of Data Science in Oncology at MD Anderson Cancer Center. She is a clinician-scientist, associate professor in Radiation Oncology and Diagnostic Imaging with a clinical practice focused on CNS malignancies and a computational imaging lab focused on quantitative imaging and modeling to detect and characterize tumors and toxicities of treatment to enable personalized cancer treatment. Motivated by challenges observed in her own clinical and research pursuits, Dr. Chung has developed and leads institutional efforts to enable quantitative measurements for clinically impactful utilization and interpretation of data through a collaborative team science approach, including the Tumor Measurement Initiative (TMI) at MD Anderson. Internationally, Dr. Chung leads several multidisciplinary efforts to improve the generation and utilization of high quality, quantitative data to drive research and impact clinical practice, including her role as Vice Chair of the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance (QIBA), Co-Chair of the Quantitative Imaging for Assessment of Response in Oncology Committee of the International Commission on Radiation Units and Measurements (ICRU) and National Academies of Sciences, Engineering, and Medicine-appointed committee addressing Foundational Research Gaps and Future Directions for DigitalTwins. Beyond her clinical, research and administrative roles, Dr. Chung enjoys serving as an active educator and mentor with a passion to support the growth of diversity, equity and inclusion in STEM, including her role as Chair of Women in Cancer (http://www.womenincancer.org/) , a non-for-profit organization that is committed to advancing cancer care by encouraging the growth, leadership and connectivity of current and future oncologists, trainees and medical researchers.
Andrew Elliott, Ph.D.
Dr. Elliott’s research focuses on developing methodologies and algorithms for medical image analysis. He is testing different machine learning and other computational algorithms for the imaging core lab within the ROSI Advanced Imaging Initiative.
Research Assistant I
Ms. Langshaw operates and scripts RayStation and engages in administrative work for the lab. She also curates and maintains lab databases, and helps facilitate collaborative data sharing.
Research Medical Student
Mr. Tran’s project is focused on improving the detection of radiation necrosis development in melanoma patients with brain metastasis through the identification of predictive clinical variables and radiomic feature analysis.
Research Assistant I
Ms. Erickson’s research efforts focus on curating clinical data for machine learning algorithms and quantitative imaging biomarker analysis. Additionally, her research explores BRAF-mutant metastatic melanoma to identify the optimal treatment sequence for this aggressive disease. Ms. Erickson also works with standardized clinical workflows across radiation oncology to support a strategic alliance.
Clinical Data Abstractor
Ms. White works to abstract information from patient records and collaborates with the Tumor Measurement Initiative (TMI) to advance cancer treatment. She annotates and contours MRI images for use in TMI automation (including normal tissue anatomy and tumor regions), manages image databases to obtain patient records, and maintains appropriate documentation regarding protocols and data. Her research interests include finding non-invasive and innovative treatments for cancer and degenerative diseases, as well as pharmaceutical discovery science to further extend patient longevity.
Clinical Research Program Coordinator
Dr. Talpur is a medical graduate in his third year at MD Anderson and first at Chung Lab. His primary focus of research is studying quality of life outcomes in patients with primary brain tumors. He currently works on enrolling and data gathering for patients on the GBM Adaptive & NASA cognitive protocol.
Dr. Chakrabarty's research interests include machine and deep learning, medical imaging, neuroinformatics, and federated learning. As a Data Scientist at the Institute for Data Science in Oncology (IDSO), his work revolves around building institution-specific and federated AI models for neuro-oncology imaging analysis of intracranial tumors as well as developing informatics frameworks for facilitating their clinical translation.
Samah M. Morsi
Postdoctoral Fellow in Computational Imaging
Dr. Morsi is working around harnessing the power of advanced imaging techniques to enhance cancer treatment. Specializing in Multiparametric and Diffusion Tensor MRI, she collaborates with fellow researchers and mentors aspiring minds, fostering an environment of continuous learning. Driven by a shared vision, she aims to revolutionize cancer research and improve patient outcomes through precise and cutting-edge imaging technologies.
Postdoctoral Fellow, MD Anderson
CPRIT-CURE Summer Student
Undergrad Student, Rice University
Undergrad Student, Rice University
Medical Student, UT Medical School
Summer Student, Duke University
Karine Al Feghali, M.D.
Drew Mitchell, Ph.D.
Neil Chevli, M.D.
Undergraduate Research Student