Knowledge-Based Software Can Significantly Expedite Creation of High-Quality Radiotherapy Treatment Plans for Precise Tumor Targeting

PALO ALTO, Calif., Oct. 22, 2015 /PRNewswire/ -- Studies presented earlier this week at the 2015 annual meeting of the American Society for Radiation Oncology (ASTRO) confirmed that knowledge-based treatment planning software can dramatically improve the speed and quality of cancer care.   One award-winning study by a team using RapidPlan™ software from Varian Medical Systems (NYSE: VAR) showed that radiotherapy treatment planning for cervical cancer can be done in minutes rather than hours, with superior quality. 

In a presentation that was named among the "Best of ASTRO" and won the Basic/ Translational Science Abstract Award in the physics category, Nan Li, PhD, postdoctoral fellow at the University of California, San Diego (UCSD), and her team¹ reported on their use of a RapidPlan model that was based on a refined sample of 86 previously-treated cervical cancer cases.  They found that treatment planning time for intensity-modulated radiation therapy took an average of 6.85 minutes.[1]  According to Kevin Moore, PhD, senior author on the study, UCSD dosimetrists estimate that manual GYN planning would require anywhere from 2-6 hours of optimization.  "The use of knowledge-based planning represents a considerable time savings and reduced personnel costs," he said. 

RapidPlan also improved plan quality compared to conventionally generated plans by minimizing the impact on normal surrounding tissues. "With both dramatic efficiency gains and improved normal tissue sparing, the final automated planning module was validated as both a clinical trial quality control system and a valuable tool for high-quality clinical planning in cervical cancer," observed Li.

Moore and his physician colleagues from UCSD also described work where stereotactic radiosurgery (SRS) treatment plans created using automated knowledge-based planning algorithms that they developed were set against manually-created clinical plans in a blinded comparison study.[2] 

"In a clear majority of the cases, automated SRS planning demonstrated superior or equivalent plan quality to existing manual planning processes," Moore said.  "Further refinement of algorithms to balance the complex clinical tradeoffs for high-priority organs-at-risk . . . will likely improve this technique further."

Researchers from Duke University evaluated a "rapid learning approach" in which clinicians "train" the RapidPlan tool by establishing a base knowledge model and continuously evaluate and update this knowledge model using subsequent cases. In their research on pelvic cancer cases, Jackie Wu, PhD, professor of radiation oncology, and her colleagues compared the RapidPlan rapid learning approach to the batch training method: knowledge modeling based on a static set of training cases.[3]

"The rapid learning approach is able to learn knowledge models for multiple cancer types in the pelvic region with comparable accuracy to the batch training method and with improved efficiency," Dr. Wu said. "This approach will facilitate the implementation of the knowledge based radiation therapy planning in clinics."

Knowledge-based planning enables clinicians to extract information from past clinical experience and use it to generate mathematical models that expedite the creation of new treatment plans. The software helps the planner quickly generate a new treatment plan that achieves the physician's tumor coverage and normal tissue sparing goals, greatly reducing the need for time-consuming, manual trial-and-error processes while still optimizing quality. 

"Varian's RapidPlan software is a very robust knowledge-based planning solution that was developed to help clinical teams enhance quality, consistency, and efficiency in radiotherapy treatment planning," said Kolleen Kennedy, president of Varian Oncology Systems.  "We are gratified to see research being conducted and presented, affirming the value of this tool for enhancing access to quality cancer treatment around the world.  With the publication in the Lancet, last month, of a special report on the need to expand global access to radiotherapy, Varian is pleased to be offering tools like RapidPlan designed to improve utilization of radiotherapy around the world." [4]     

[1] Li, N et al. Validation of a knowledge-based automated planning system in cervical cancer as a clinical trial quality system [abstract]. Presented at: American Society for Radiation Oncology (ASTRO) 57^th Annual Meeting: October 18-21, 2015; San Antonio, Texas.

[2] Moore, K, et al. Single-blind trial of knowledge-based automated planning versus manually planned stereotactic radiosurgery [abstract]. Presented at: American Society for Radiation Oncology (ASTRO) 57^th Annual Meeting: October 18-21, 2015; San Antonio, Texas.

[3] Wu, J et al. A rapid learning approach for the knowledge modeling of radiation therapy plan [abstract]. Presented at: American Society for Radiation Oncology (ASTRO) 57^th Annual Meeting: October 18-21, 2015; San Antonio, Texas.

[4] Atun R, et al. Expanding global access to radiotherapy. Lancet Oncol. 2015 Sep;16(10):1153-86. http://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(15)00222-3/fulltext  

About Varian Medical Systems

Varian Medical Systems, Inc., of Palo Alto, California, focuses energy on saving lives by equipping the world with advanced technology for fighting cancer and for X-ray imaging.  The company is the world's leading manufacturer of medical devices and software for treating cancer and other medical conditions with radiation. The company provides comprehensive solutions for radiotherapy, radiosurgery, proton therapy and brachytherapy. The company supplies informatics software for managing comprehensive cancer clinics, radiotherapy centers and medical oncology practices. Varian is also a premier supplier of X-ray imaging components, including tubes, digital detectors, and image processing software and workstations for use in medical, scientific, and industrial settings, as well as for security and non-destructive testing.  Varian Medical Systems employs approximately 6,900 people who are located at manufacturing sites in North America, Europe, and China and approximately 70 sales and support offices around the world.  For more information, visit www.varian.com or follow us on Twitter.

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