If you made any changes in Pure, your changes will be visible here soon.

Personal profile


Thomas Yankeelov serves as Director of Cancer Imaging Research in the LIVESTRONG Cancer Institutes of the Dell Medical School. He holds the W.A. "Tex" Moncrief Jr., Simulation-Based Engineering and Sciences Professorship in Computational Oncology and leads the Tumor Modeling Group in the university's Institute for Computational Engineering and Sciences.

He is a computational biomedical engineer and came to The University of Texas at Austin from Vanderbilt University, where he served as the Ingram Professor of Cancer Research; professor of radiology and radiological sciences, physics, biomedical engineering and cancer biology; and director of cancer imaging research. He also served as a co-leader of the Host-Tumor Interactions Research Program for the Vanderbilt-Ingram Cancer Center.

Yankeelov is the recipient of a distinguished $6 million recruitment grant from the Cancer Prevention and Research Institute of Texas (CPRIT).

His clinical research focuses on improving patient care by employing advanced imaging methods for the early identification, assessment and prediction of tumors and their response to therapy. He has developed successful tumor-forecasting methods by combining imaging technologies with patient-specific data to build predictive, multiscale biophysical models of tumor growth. His research emphasizes the importance of offering personalized therapies to cancer patients.

Yankeelov is a fellow of the American Institute of Medical and Biological Engineers and has served on the editorial boards of scientific publications such as Magnetic Resonance Imaging, Medical Physics and Breast Cancer Research. He received his B.A. in mathematics from the University of Louisville, his M.A. in applied mathematics and M.S. in physics, both from Indiana University, and his Ph.D. in biomedical engineering from Stony Brook University.

Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 4 Similar Profiles
Breast Neoplasms Medicine & Life Sciences
Magnetic Resonance Imaging Medicine & Life Sciences
Neoplasms Medicine & Life Sciences
Magnetic resonance Engineering & Materials Science
Tumors Engineering & Materials Science
Diffusion Magnetic Resonance Imaging Medicine & Life Sciences
Imaging techniques Engineering & Materials Science
Breast Medicine & Life Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2003 2019

Magnetic Resonance Imaging
Medical Imaging
Medical imaging
Magnetic resonance
Inverse problems

Assessing metastatic potential of breast cancer cells based on EGFR dynamics

Liu, Y. L., Chou, C. K., Kim, M., Vasisht, R., Kuo, Y. A., Ang, P., Liu, C., Perillo, E. P., Chen, Y. A., Blocher, K., Horng, H., Chen, Y. I., Nguyen, D. T., Yankeelov, T., Hung, M. C., Dunn, A. K. & Yeh, H. C., Dec 1 2019, In : Scientific reports. 9, 1, 3395.

Research output: Contribution to journalArticle

Open Access
Epidermal Growth Factor Receptor
Breast Neoplasms
Cell Membrane
MCF-7 Cells

Characterizing Trastuzumab-Induced Alterations in Intratumoral Heterogeneity with Quantitative Imaging and Immunohistochemistry in HER2+ Breast Cancer

Syed, A. K., Woodall, R., Whisenant, J. G., Yankeelov, T. & Sorace, A. G., Jan 1 2019, In : Neoplasia (United States). 21, 1, p. 17-29 13 p.

Research output: Contribution to journalArticle

Open Access
Xenograft Model Antitumor Assays
ErbB-2 Receptor
Animal Disease Models
Computer-Assisted Image Processing

In vitro vascularized liver and tumor tissue microenvironments on a chip for dynamic determination of nanoparticle transport and toxicity

Ozkan, A., Ghousifam, N., Hoopes, P. J., Yankeelov, T. & Rylander, M. N., May 1 2019, In : Biotechnology and Bioengineering. 116, 5, p. 1201-1219 19 p.

Research output: Contribution to journalArticle

Tumor Microenvironment

Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumors

Wu, C., Pineda, F., Hormuth, D. A., Karczmar, G. S. & Yankeelov, T., Mar 1 2019, In : Magnetic Resonance in Medicine. 81, 3, p. 2147-2160 14 p.

Research output: Contribution to journalArticle

Blood Vessels