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  • This screenshot of the prostate cancer treatment planning tool developed by researchers at Duke University Medical Center and RENCI shows data from a query case, representing a new prostate cancer case (top images), and a match case taken for comparison from the researchers’ IMRT database (bottom images). At far left is a comparison of CT scans between the query and match cases. A 3D rendering of key structures as “seen” by radiation beams from a particular angle (center) shows the Planning Treatment Volume (PTV), which includes the cancerous tumor (red), bladder (yellow), rectum (brown) and femoral heads (gray). At right, dose volume histograms show the radiation doses received by the PTV (red lines) and the surrounding healthy organs and tissue (yellow, brown and gray lines). The treatment objective is to maximize the radiation dose to the PTV, which moves the red line to the upper right in the graph, while minimizing radiation to the surrounding tissue, which moves those lines to the lower right.“It’s a mathematically complex problem to solve,” says Vorakarn Chanyavanich, a recent Duke Ph.D. recipient in medical physics who conducted his dissertation research on the project. “Each patient comes in with their own geometry and needs to have their treatment plan customized. The process is done manually and takes about four to six hours per patient. What we’d like to do is maintain or improve the dose sparing of critical organs and also reduce the time of treatment planning.”The research team, which includes Chanyavanich, now a resident medical physicist with Emory University; Shiva K. Das, a professor of radiation oncology at Duke School of Medicine; and Joseph Y. Lo, an associate professor of radiology with Duke’s Carl E. Ravin Advanced Imaging Laboratories, developed a knowledge-based approach to streamline the treatment planning process. Their system could also help doctors develop higher quality IMRT treatment plans that spare healthy tissue from the effects of radiation.
    Steve Chall, RENCI, University of North Carolina at Chapel Hill
    This screenshot of the prostate cancer treatment planning tool developed by researchers at Duke University Medical Center and RENCI shows data from a query case, representing a new prostate cancer case (top images), and a match case taken for comparison from the researchers’ IMRT database (bottom images). At far left is a comparison of CT scans between the query and match cases. A 3D rendering of key structures as “seen” by radiation beams from a particular angle (center) shows the Planning Treatment Volume (PTV), which includes the cancerous tumor (red), bladder (yellow), rectum (brown) and femoral heads (gray). At right, dose volume histograms show the radiation doses received by the PTV (red lines) and the surrounding healthy organs and tissue (yellow, brown and gray lines). The treatment objective is to maximize the radiation dose to the PTV, which moves the red line to the upper right in the graph, while minimizing radiation to the surrounding tissue, which moves those lines to the lower right.“It’s a mathematically complex problem to solve,” says Vorakarn Chanyavanich, a recent Duke Ph.D. recipient in medical physics who conducted his dissertation research on the project. “Each patient comes in with their own geometry and needs to have their treatment plan customized. The process is done manually and takes about four to six hours per patient. What we’d like to do is maintain or improve the dose sparing of critical organs and also reduce the time of treatment planning.”The research team, which includes Chanyavanich, now a resident medical physicist with Emory University; Shiva K. Das, a professor of radiation oncology at Duke School of Medicine; and Joseph Y. Lo, an associate professor of radiology with Duke’s Carl E. Ravin Advanced Imaging Laboratories, developed a knowledge-based approach to streamline the treatment planning process. Their system could also help doctors develop higher quality IMRT treatment plans that spare healthy tissue from the effects of radiation.
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