Benefits of Automation in Radiation Oncology

Abstract

automation; radiation oncology: automation; radiation oncologyA utomation, at maturity, could be the conduit to higher quality, safer treatments, all harnessed to a more rapid and accurate delivery system of radiation oncology. The potential exists for technology to inform and execute treatment plans with minimum human intervention and its attendant errors. Automation could also provide physicians with an escape from time-consuming, repetitious tasks, while providing them with more time to do what they do best—interact with patients. While the gallop toward the automation of increasingly more processes is moving at a thoroughbred's pace, the field is really only “semi-automated” at this point, remarked Meral Reyhan, PhD, Assistant Professor, Division of Medical Physics, Thomas Jefferson University, Philadelphia. “I say ‘semi-automated’ because even though many processes are ‘automated’ they still require a human to check that the process has been carried out correctly. For example, even when using the best image registration algorithm, a physician still must go through all of the images and make sure the registrations are correct.” With that clarification in mind, however, Reyhan said automation is making an impact in a multitude of areas, such as contouring, treatment planning, image registration, transferring of treatment fields from the treatment planning system to the treatment delivery system, recording and verifying radiation delivered, aggregating data for analysis of radiation treatment, and many of the quality assurance measurements for the treatment machines. Yan Yu, PhD, MBA, FAAPM, FASTRO, Professor and Vice Chair Director of Jefferson's Division of Medical Physics, Department of Radiation Oncology, emphasized, “Dosimetric treatment planning occupies a central stage in every radiation therapy treatment course. This is a highly skilled and time-consuming step, during which patients wait anxiously for their first day of treatment, often with tumor still growing in the body.” Understandably, any reliable shortcuts would benefit both clinicians and patients. Contouring “In its present state, automation in radiation oncology is helpful in the contouring of imaging,” offered Bruce Minsky, MD, FASTRO, Professor of Radiation Oncology at MD Anderson Cancer Center, Houston, and Immediate Past Chair of the American Society for Radiation Oncology's (ASTRO) Board of Directors. “When we design radiation fields, we need to contour many organs in the radiation field to make sure that we treat the tumor and spare the normal tissues,” he continued. “This is tedious and time-consuming. Now we have contouring programs that will automatically contour normal structures—making this step much more rapid.” Keeping caution in mind, Reyhan remarked that while several companies have come out with software using sophisticated computer vision algorithms/machine learning to automate the contouring process, “most of these programs work excellently the majority of the time, but no one is ready to trust patient care to something that works excellently the ‘majority’ of the time. It needs to work perfectly 100 percent of the time before it is truly ‘automated’ in radiation oncology.” Treatment Planning The entirety of treatment planning indeed will see significant changes as a result of automation, added Todd Pawlicki, PhD, FAAPM, FASTRO, Professor of Radiation Oncology at the University of California, San Diego, and a member of ASTRO's Board of Directors. “Currently, treatment planning is done by a trial-and-error process and the ‘optimal’ treatment plan is largely dependent on the knowledge and experience of the person creating the treatment plan,” Pawlicki explained, adding that there are a number of publications in peer-reviewed literature showing there is variability in treatment plan quality not only across centers, but even in the same center where there are several different treatment planners. “Knowledge-based treatment planning is an autom