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To combine the technologies, the Alberta researchers had to reengineer both components. “The whole machine is designed differently,” says Fallone. Special shielding is employed. And instead of using a high-strength magnetic field generated by superconducting-wire coils, as in clinical MRI, the machine uses a weak permanent magnet. The weak magnet interferes much less with the accelerator and is smaller and less expensive to operate. This December, Fallone’s group published the results of imaging studies that showed it was possible to generate MRI images while running the linear accelerator without interference.

The weak magnet imposes a different challenge, however: the image quality is much lower. So researchers at Stanford University are working on computational methods for getting the necessary information from these lower-resolution images. “Diagnostic MRI requires a very high image quality, but for radiotherapy you don’t need to see the tumor in exquisite detail,” says Amit Sawant, an instructor in radiation oncology at the Stanford School of Medicine. “You can afford to lose [image] signal, and still get enough information to know when the tumor is moving.” What’s important to see during radiotherapy, says Fallone, are the edges of the tumor.

Fallone and Sawant will present initial results of image-tracking studies done with the prototype combined device at the conference in Anaheim. Sawant’s group will describe imaging software that allows the machine to acquire five two-dimensional MRI images per second–much faster than conventional MRI. The Stanford researchers increased the imaging speed by decreasing the imaging area and using a technique called compressive sensing. When images are stored, about 90 percent of the data is thrown out; using compressive sensing, it’s possible to acquire only the most important 10 percent of the image data in the first place.

Fallone will present results demonstrating that such real-time guidance can be used to redirect the prototype device’s x-ray beam. “So far, only CT has been available for image guidance,” says Bhadrasain Vikram, chief of the clinical radiation oncology branch of the National Cancer Institute’s Radiation Research Program. “It’s exciting that [MRI] is becoming available to start asking whether it can provide more accurate information.” Better guidance for radiotherapy, says Vikram, might speed up the treatments or even “cure some cancers you can’t cure today.”

But before the system can be tested on patients, the researchers caution that the image-acquisition process needs to be sped up even more, so that it’s possible to make 3-D images. The device will also need to be tested on animals. Fallone estimates that human tests are at least five years away.

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Credit: University of Alberta Cross Cancer Institute

Tagged: Computing, Biomedicine, cancer, imaging, radiation, physics

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