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Novel software could improve treatment accuracy for children with cancer
New, specialized software has shown potential for improving accuracy of pediatric cancer treatment.
“This software may be the missing link in the paradigm of quality assurance processes. We have a very comprehensive quality assurance strategy, and this software is an important addition to our already high standard of care,” Arthur Olch, PhD, FAAPM, chief of physics in the radiation oncology program at Children’s Hospital Los Angeles and professor of clinical pediatrics at the University of Southern California’s Keck School of Medicine, said in a press release.
As one of the only pediatric centers in the U.S. to adopt this new technology, Children’s Hospital Los Angeles gives patients the best chance at fighting their disease, according to the release.
“If your child needs radiation therapy, we are one of very few places around using this system,” Olch said in the release. “It is difficult to say at this point whether this will necessarily cure more children. But, if we can better target their tumors and refine our radiation dosing, we are reducing toxicity and giving children their best possible chance.”
HemOnc Today spoke with Olch about the need the software fills, the study he and colleagues conducted of its clinical utility, and what subsequent research may entail.
Question: What need does the software fill?
Answer : Radiation therapy has historically employed intensive quality assurance practices for all aspects of the process. Any software or hardware device used in the planning or delivery of treatment undergoes periodic testing by the medical physicist to ensure the quality of treatment as well as patient safety. Additional quality assurance procedures are performed on a patient-specific level, such as imaging to confirm patient positioning. We have an architecture of systematic and patient-specific quality assurance measures designed to ensure the highest accuracy of treatment. However, there was no way to test whether the dose delivered to the patient was correct. In the field of radiation therapy, we have come to largely assume that since the systematic tests passed, each treatment would be as correct as it could be. However, until now, we did not have an actual test to prove this.
Q: How did you conduct the study?
A: The system that provides the data to tell us whether the treatment is accurately delivered is a digital imaging panel that is in line with the treatment beam. This digital device captures an image using the treatment beam after it passes through the patient. Our system compares images from every treatment field each day to the initial reference images. In this way, a consistency check can be made of the treatment. In the study, we retrospectively looked at images of 57 patients whose treatments were monitored with this system. These images were acquired for nearly every field for every treatment day and stored in a database. The software automatically queries the database and pulls the images into the system for analysis, which would be impossible to do manually. We also tried to find out why the field may have failed in certain instances.
Q: What did you find?
A: The software provides a comparison of the image for each field on the first day of treatment and any subsequent day of treatment. We used two tolerance limits to conduct the analysis — one very strict and the other more routine. We were then able to compare which values fell outside of each tolerance limit and identify reasons for these values in half of the cases. We concluded that this system was capable of finding variations in a clinically relevant percentage of images. The dosimetric impact of these variations on the patient is not very clear from the data we have, but the information can frequently lead us to take corrective actions to improve treatment accuracy.
Q: What is next for research on this?
A: The dosimetric effect on the patient would have to be determined through another related process. The ability to retrospectively discover the reason for exit dose image variations in half of the cases means a large percentage of these variations can be actionable. However, we do not want to have any differences, and we could potentially mitigate these. We are conducting the next phase of research in this field now.
This system uses the patient’s first fraction images to compare two images on subsequent treatment days. The latest version of this software calculates the absolute dose to the imaging panel and a predicted panel dose from the treatment planning system in which the patient’s plan was developed. This predicted dose is a calculation of what the dose delivered to the imaging panel should be, per the plan. We are going to recalculate the absolute-dose images for these 57 patients and also acquire this information for new patients.
Q: Is there anything else that you would like to mention?
A: This will be a new paradigm in the field of radiation oncology —a number of other commercial systems are on the market. This type of system is being adopted by our field enthusiastically because of the simplicity, automation and feasibility of implementation. – by Jennifer Southall
Reference:
Olch AJ, et al. Adv Radiat Oncol. 2019;doi:10.1016/j.adro.2019.04.001.
For more information:
Arthur J. Olch, PhD, can be reached at Children’s Hospital Los Angeles, 4650 W. Sunset Blvd., Los Angeles, CA 90027; email: aolch@chla.usc.edu.
Disclosure: Olch reports no relevant financial disclosures.