As TG-101 suggests, and as anyone who does SRS knows, there are multiple steps between simulating a patient and finally delivering a stereotactic treatment.
Because of the interdependencies of these steps, end-to-end testing is crucial in order to identify and quantify dose discrepancies between what is prescribed and what is delivered.
Like several other institutions and facilities, we used to have a jerry-rigged end-to-end solution that went back and forth between our clinic and machine shop, enduring several slight changes in design and engineering.
Once upon a time, the Medical Physicist was a partner with the RadiationOncologist and other members of the clinical team. He or she was seen as someone with the intellectual capital to improve the diagnosis and treatment of the patient.
Today, the physicist is viewed more as a technician, relegated to the back room, and not taking an active role in the imaging and treatment process.
Physicists are partially to blame. Many of us were quite content to sit in that back room, interacting only with our computers.
Whereas TG-142 is primarily performance-based QA, comparing test results with historical results, TG-198 is more prescriptive. The goal is to increase the quality of the QA process itself, taking into account the evolution of technology.
My QADS presentation will introduce some of the concepts from TG-198, which is a work in progress. I will also touch on some of the new technologies that come into play when we think about imaging and machine QA.
After nearly two decades of research, has the stage been set for transit dosimetry to emerge as a common tool in radiotherapy? Or, will it continue to be relegated to use mainly in large academic centers? How can innovation be leveraged to meet common challenges in the regular useof transit dosimetry? Two seasoned transit dosimetry experts give their take on these questions, drawing from their own extensive experience with transit dosimetry.
In today's clinic, you'd expect all your systems —imaging, treatment planning systems (TPS), treatment management systems (TMS), and so on— to easily transfer and accept data within the clinical workflow. A little more than a decade ago, this was not a given.
Every year, the PLAN Challenge helps advance best practices in medical dosimetry because we are able to learn from each other—lessons we can apply in real clinical practice. This year was no different. Here are the top three things we learned from this Challenge's brain case:
If you've contemplated using transit dosimetry in your clinic, most likely, a handful of concerns and objections immediately come to mind. You might think, "My current process works great! There's absolutely no need for all the added time transit dosimetry would cost me." In this video, I offer a different way to think about transit dosimetry, and how you can use existing technology to make your patient QA even more robust.