AUSTIN, May 10, 2017 — Radiation therapy shoots high-energy particles into the body to destroy or damage cancer cells. Over the last century, the technologies used have constantly improved and it has become a highly effective way to treat cancer. However, physicians must still walk a fine line between delivering enough radiation to kill tumors, while sparing surrounding healthy tissue.

“Historically, radiation has been a blunt tool,” said Matt Vaughn, Director of Life Science Computing at the Texas Advanced Computing Center. “However, it’s become ever more precise because we understand the physics and biology of systems that we’re shooting radiation into, and have improved our ability to target the delivery of that radiation.”

The science of calculating and assessing the radiation dose received by the human body is known as dosimetry – and here, as in many areas of science, advanced computing plays an important role.

Improving Radiation Therapy with Real-Time Imaging

Current radiation treatments rely on imaging from computed tomography (CT) scans taken prior to treatment to determine a tumor’s location. This works well if the tumor lies in an easily detectable and immobile location, but less so if the area is moving, as in the case of lung cancer.

At the University of Texas MD Anderson Cancer Center, scientists are tackling the problem of accurately attacking tumors using a new technology known as an MR-linac that combines magnetic resonance (MR) imaging with linear accelerators (linacs). Developed by Elekta in cooperation with UMC Utrecht and Philips, the MR-linac at MD Anderson is the first of its kind in the U.S.

MR-linacs can image a patient’s anatomy while the radiation beam is being delivered. This allows doctors to detect and visualize any anatomical changes in a patient during treatment. Unlike CT or other x-ray based imaging modalities, which provide additional ionizing radiation, MRI is harmless to healthy tissue.

The MR-linac method offers a potentially significant improvement over current image-guided cancer treatment technology. However, to ensure patients are treated safely, scientists must first correct for the influence of the MRI’s magnetic field on the measurements used to calibrate the radiation dose being delivered.

Researchers use software called Geant4 to simulate radiation within the detectors. Originally developed by CERN to simulate high energy particle physics experiments, the MD Anderson team has adapted Geant4 to incorporate magnetic fields into their computer dosimetry model.

“Since the ultimate aim of the MR-linac is to treat patients, it is important that our simulations be very accurate and that the results be very precise,” said Daniel O’Brien, a postdoctoral fellow in radiation physics at MD Anderson. “Geant4 was originally designed to study radiation at much higher energies than what is used to treat patients. We had to perform tests to make sure that we had the accuracy that we needed.”

Using the Lonestar supercomputer at the Texas Advanced Computing Center (TACC), the research team simulated nearly 17 billion particles of radiation per detector to get the precision that they needed for their study.

In August 2016, they published magnetic field correction factors in Medical Physics for six of the most-used ionization chamber detectors (gas-filled chambers that are used to ensure the dose delivered from a therapy unit is correct). They are now working on verifying these results experimentally.

“The MR-linac is a very promising technology but it also presents many unique challenges from a dosimetry point of view,” O’Brien said. “Over time, our understanding of these effects has improved considerably, but there is still work to be done and resources like TACC are an invaluable asset in making these new technologies safe and reliable.”

“Our computer simulations are important because their results will serve as the foundation to extend current national and international protocols to perform calibration of conventional linacs to MR-linacs,” said Gabriel Sawakuchi, assistant professor of Radiation Physics at MD Anderson. “However, it is important that our results be validated against measurements and independent simulations performed by other groups before used clinically.”

(The project was partially funded by Elekta, a Swedish company that provides radiation therapy equipment and clinical management for the treatment of cancer and brain disorders.)

Read the full release at https://www.tacc.utexas.edu/-/targeted-high-energy-cancer-treatments-get-a-supercomputing-boost

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Source: Aaron Dubrow, TACC