Medicineworld.org: Speed up radiation therapy
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Speed up radiation therapy
The automatic radiation planning algorithm results in beamlet intensities that produce equal-dose contours.A new computer-based technique could eliminate hours of manual adjustment linked to a popular cancer therapy. In a paper reported in the Feb. 7 issue of Physics in Medicine and Biology, scientists from Rensselaer Polytechnic Institute and Memorial Sloan-Kettering Cancer Center describe an approach that has the potential to automatically determine acceptable radiation plans in a matter of minutes, without compromising the quality of therapy.
Credit: Rensselaer/Richard Radk
"Intensity Modulated Radiation Therapy (IMRT) has exploded in popularity, but the technique can require hours of manual tuning to determine an effective radiation therapy for a given patient," said Richard Radke, assistant professor of electrical, computer, and systems engineering at Rensselaer. Radke is leading a team of engineers and medical physicists to develop a "machine learning" algorithm that could cut hours from the process.
A subfield of artificial intelligence, machine learning is based on the development of algorithms that allow computers to learn relationships in large datasets from examples. Radke and his colleagues have tested their algorithm on 10 patients with prostate cancer at Memorial Sloan-Kettering. They observed that for 70 percent of the cases, the algorithm automatically determined an appropriate radiation treatment plan in about 10 minutes.
"The main goal of radiation treatment is to irradiate a tumor with a very high dose, while avoiding all of the healthy organs," Radke said. He described early versions of radiation treatment as a "fire hose" approach, applying a uniform stream of particles to overwhelm cancer cells with radiation.
IMRT adds nuance and flexibility to radiation treatment, increasing the likelihood of treating a tumor without endangering surrounding healthy tissue. Each IMRT beam is composed of thousands of tiny "beamlets" that can be individually modulated to deliver the right level of radiation precisely where it is needed.
But the semi-automatic process of developing a therapy plan can be extremely time-consuming -- up to about four hours for prostate cancer and up to an entire day for more complicated cancers in the head and neck, as per Radke.
A radiation planner must perform a Computerized axial tomography scan, analyze the image to determine the exact locations of the tumor and healthy tissues, and define the radiation levels that each area should receive. Then the planner must give weight to various constraints set by a doctor, such as allowing no more than a certain level of radiation to hit a nearby organ, while assuring that the tumor receives enough to kill the malignant cells.
This is currently achieved by manually determining the settings of up to 20 different parameters, or "knobs," deriving the corresponding radiation plan, and then repeating the process if the plan does not meet the clinical constraints. "Our goal is to automate this knob-turning process, saving the planner's time by removing decisions that don't require their expert intuition," said Radke.
The scientists first performed a sensitivity analysis, which showed that a number of of the parameters could be eliminated completely because they had little effect on the outcome of the therapy. They then showed that an automatic search over the smaller set of sensitive parameters could theoretically lead to clinically acceptable plans.
The procedure was put to the test by developing radiation plans for 10 prostate cancer patients. In all 10 cases the process took between five and 10 minutes, Radke said. Four cases would have been immediately acceptable in the clinic; three needed only minor "tweaking" by an expert to achieve an acceptable radiation plan; and three would have demanded more attention from a radiation planner.
Radke and his colleagues plan to develop a more robust prototype that can be installed on hospital computers and reviewed in a clinical setting. He hopes to see a clinical prototype in place at Memorial Sloan-Kettering in the next few years. The scientists also plan to test the approach on tumors that are more difficult to treat with radiation treatment, such as head and neck cancers.
In a related project, Radke is collaborating with colleagues at Boston's Massachusetts General Hospital to create computer vision algorithms that offer accurate estimates of the locations of tumors. This automatic modeling and segmentation process could help radiation planning at an earlier stage by automatically outlining organs of interest in each image of a Computerized axial tomography scan, which is another time-consuming manual step. Learn more about this project here: http://news.rpi.edu/update.do?artcenterkey=134
Posted by: Janet Source
Did you know?
A new computer-based technique could eliminate hours of manual adjustment linked to a popular cancer therapy. In a paper reported in the Feb. 7 issue of Physics in Medicine and Biology, scientists from Rensselaer Polytechnic Institute and Memorial Sloan-Kettering Cancer Center describe an approach that has the potential to automatically determine acceptable radiation plans in a matter of minutes, without compromising the quality of therapy.
Medicineworld.org: Speed up radiation therapy
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