Bolch was an assistant professor at Texas A&M University when Xu was a doctoral student there in the early 1990s. They have since become collaborators after Bolch went to UF and Xu joined Rensselaer. In 2001, Bolch invited Xu to give a “Frontiers in Biomedical Engineering” research seminar at UF on tomographic modeling, for which Xu is now recognized as one of the pioneers. Bolch and Xu now collaborate on developing models of children. One of the projects is to study a diagnostic procedure, CT imaging, that allows doctors to visualize internal tissues with high resolution. Multiple, consecutive X-ray images are taken as if slicing the body crosswise to capture the target organ. X-rays carry a risk of causing mutations in a person’s DNA, although the exposure from a single scan is well within safe limits.
However, Xu says, “Most hospitals don’t differentiate [the CT procedures] for patient size,” thus pediatric patients may be receiving unnecessarily high radiation doses. And because children have more years of life ahead of them, they may be more likely to develop long-term effects such as cancer from X-ray exposure. Xu and his Florida colleagues have two aims:
to develop virtual patients based on children and to study X-ray interactions with the virtual body from different intensities of CT imaging. Bolch organized a workshop during the Society of Nuclear Medicine’s annual meeting this June in Toronto and he invited Xu to give a lecture to an audience that included mostly physicians.
At Vanderbilt, Xu’s collaborators, radiology professors Michael Stabin and Randy Brill, work in nuclear medicine. Immunoradiotherapy is like a smart bomb for a cancer tumor. Medicine is administered that contains antibodies (hence “immuno”) that recognize molecules unique to cancer cells and thereby target the delivery of the treatment agent (the radioactivity). This clinical application is becoming “increasingly more important” says Xu, as more drugs are developed to image and destroy specific types of cancers at the molecular level. A major problem, he says, is not knowing how much of the injected dose gets to the target site. “Physicians tend to be overly cautious” when injecting radioactive substances, using lower doses to stay safe from overexposure, says Xu. Using data from virtual patients, doctors can better calculate dose and more aggressively and effectively treat cancers in real patients.
Virtual patients will be used at Massachusetts General Hospital by radiation physicist Harald Paganetti and radiation oncologist Herman Suit to improve proton therapy. In this procedure, a medical accelerator delivers a beam of protons to the target organ. “The clinical problems we are trying to solve,” says Xu, “are how radiation goes into the patients, and how it will cause secondary radiobiological effects” that can result from radiation scatter. The objective is to optimize dose and beam direction to target the tumor while minimizing damage to nearby healthy tissues using the advanced procedures.
Xu and his collaborators plan to have more VIPs, varying in gender, age, size, and ethnicity, as he and his colleagues create a family of virtual patients. Although VIP-Man was the most detailed model when first created, he is, says Xu, “just a single, very tall, very heavy adult male.”
“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,” says 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.”
Toward that end, Xu is leading a worldwide consortium and is creating a Web site as a master depository for virtual patients and applications. Rensselaer computer science faculty Daniel Freedman and Chuck Stewart are working with Xu to develop advanced software to handle the huge datasets, including such computational tools as image segmentation, 3-D and 4-D visualization, and Monte Carlo dose simulations.
The Web site ultimately will allow offsite collaborators to share data and compare results, but it is also a mechanism, says Xu, “to disseminate all the information, all the data, freely to the research community.” Already, the VIP-Man model has been used at Rensselaer by Suvranu De, assistant professor of mechanical, aerospace, and nuclear engineering, to study virtual surgical procedures; by Birsen Yazici, assistant professor of electrical engineering, to analyze medical image quality; and by Jonathan Newell, professor of biomedical engineering, to fabricate prostate phantoms for electric impedance imaging.
As someone who has benefited from open access to a detailed anatomical dataset, Xu knows well the value of making resources available to the public domain.
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