This figure shows the 3-dimensional dose distribution of the prostate upon completion of implanted seeds. Based on patient tests, Lee’s inverse planning system uses 15% fewer seeds. Photo by Eva Lee |
A California medical software company has launched the first “inverse planning” system for helping cancer treatment specialists optimize the placement of radioactive seeds used in the brachytherapy process. Optimization improves the treatment by helping meet physician-set constraints for consistent radiation doses to tumor cells while minimizing effects on nearby structures.Used for treating prostate cancer and other forms of the disease, the new system is based on numerical optimization algorithms licensed from the Georgia Institute of Technology. Beyond improving the overall treatment, the new system dramatically reduces the time required for planning the seed placement.
The Panther Brachy InversePlan system, announced by Prowess Inc. at the annual meeting of the American Society for Therapeutic Radiology and Oncology, improves local tumor control by more consistently focusing radiation while reducing the number of radioactive seeds and needles used. Because the treatment planning can now be done in less than a minute—compared to hours with older systems—planning can be done just prior to seed implantation. That eliminates an extra clinical visit and ensures that the plan is based on the dimensions of the tumor and organ at the time of implantation.
“From the clinical side, this is a significant advance in being able to treat prostate cancer with fewer side effects while providing better local tumor control,” says Eva Lee, a mathematician and associate professor in Georgia Tech’s Stewart School of Industrial and Systems Engineering. “From the clinician’s point of view, this will allow physicians to prescribe how they want the radiation to be applied, and the system will produce an optimized plan to do that. The system will produce a better outcome, reduce the amount of time required to design the plan, and allow patients to recover more quickly.”
The optimization algorithms developed by Lee and Marco Zaider at the Sloan-Kettering Cancer Center in New York account for numerous factors, including the dose provided by each radioactive seed, shape of the organ being treated, location of tumor cells within the organ, location of critical structures for which radiation dose should be limited, sensitivity of tissues to radiation, and expected shrinkage of the organ after treatment. The goals are to provide consistent tumor-killing radiation doses to the tumor cells, while limiting potentially damaging doses to nearby critical structures such as the urethra, bladder, and rectum.
This figure shows the Prowess graphical user interface that displays the dose distribution of a treatment plan obtained from the optimization system. The figure displays the contour of the prostate (red), the urethra (purple), and the rectum (blue). The prescription dose contour is shown in brown; pink and red dots indicate placement of radioactive seeds. Image courtesy of Eva Lee |
This figure shows the culmulative dose-volume histogram resulting from the treatment plan. The lines represent the percentage dose distribution for the prostate (red), urethra (purple), rectum (blue), and bladder (yellow) with respect to the prescribed dose (100%) |
Earlier computer-aided techniques for determining the best locations to place the seeds required many hours of planning, and couldn’t optimize for specific doses specified by physicians. Because so much time was required to plan the treatment, patients had to make two clinic visits—one to obtain information for planning the treatment and a second to actually implant the seeds. Because the size and shape of the prostate can change over time, the time between planning and implantation allowed potential inaccuracies that could reduce tumor control and cause side effects.
“This system can be used in real time,” says Lee. “The patient can come in, the imaging is done, and we can then do the planning and implantation right away. There’s no delay between the imaging, planning, and implantation of the seeds.”
Because the system can quickly reoptimize the placement plan, changes can be made quickly while the patient is on the operating table to deal with difficulties in placing seeds, Lee noted.
John Nguyen, president of Prowess, says the new system gives physicians better control over radiation doses while reducing the time that’s required to treat each patient.
“Physicians can now really impose clinical criteria within the planning process,” he says. “Further, the system is extraordinarily fast, requiring only seconds to design an optimal plan. Having a system so fast means physicians can dynamically adjust and re-optimize the treatment plans as they insert needles. This was impossible to do before.”
The new software should help clinics provide more consistent cancer treatment that doesn’t depend solely on the skills of the treating physicians.
“Right now, the planning varies from physician to physician even though the end goal is the same,” he notes. “Using this system, they can test out different options, varying the dose constraints to see in minutes if they can come up with a better plan. Such a system will help standardize treatment.”
Prowess will add the new algorithms to treatment planning systems it already has in operation at more than 700 clinics in the United States.
The patented system is based on optimization techniques known as mixed integer programming. It was licensed to Prowess in 2004 and converted to a commercial product after clinical trials of more than 100 patients demonstrated its effectiveness at improving treatment plans. The system runs on high-end personal computers.
Beyond prostate cancer therapy, the mixed-integer algorithms can also be used to optimize radioactive seed and external beam radiation treatment for a broad range of other cancers. With support from the National Science Foundation, National Institutes of Health and Whitaker Foundation, Lee has also been working with specialists on improving treatments for breast, lung, cervical, brain, and liver cancers.
“Once the optimization has been determined, we can use this in many different applications, and it works very well for improving local tumor control,” she says. “I feel really good about seeing this applied in the clinic to improve treatment to patients.”
This article was originally published in Georgia Tech Research News.
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