TROY, N.Y., Aug. 11 -- Rensselaer Polytechnic Institute (RPI) is leading a team of researchers awarded a three-year, $2.1 million grant from the National Institutes of Health (NIH) to develop 3-D virtual patient models that will more accurately compute radiation doses for computed tomography (CT) imaging, nuclear medicine and radiation treatment of cancer patients. The grant is funded by the National Cancer Institute, which is part of NIH.
X. George Xu, associate professor of nuclear and biomedical engineering at RPI, is the principal investigator of the project. Researchers from RPI and from Vanderbilt University Medical Center, University of Florida and Massachusetts General Hospital are participating in the multidisciplinary project and will contribute their expertise in computer science, CT imaging, nuclear medicine and proton therapy.
In 2000, Xu and his students at RPI created Visible Photographic Man (VIP-Man), an advanced computer model that simulates in 3-D how radiation affects the organs and tissues in the human body. The project combined precise organ and tissue anatomy with the Monte Carlo statistical method to simulate the interactions of radiation types in the body such as photons, electrons, neutrons and protons. The research on VIP-Man, which was funded by the National Science Foundation and the National Library of Medicine, contained three billion voxels of medical image data in a computer code that formulates a virtual patient. A voxel is a 3-D volume of the patient body, similar to a pixel measuring a piece of 2-D image data.
Xu's team plans to expand on VIP-Man by creating a library of additional 3-D models of female and male patients of various ages and body sizes. They will also develop advanced 4-D patient models that simulate organ motions. Xu is also leading an international effort to form a consortium on computational patient models as a key resource for biomedical research.
"Currently accepted methods in radiation protection and nuclear medicine do not realistically consider patient variations in age and body size, resulting in very large miscalculations in the true radiation dose to the patient," said Xu. "Our project aims to bring about a paradigm change by creating a realistic patient model library and related computational tools that will facilitate image processing, simulation and radiation dose measurement for various clinical diagnostic and therapeutic procedures."
For more information, visit: www.rpi.edu