Christopher Pericak and Caitlin Visek
Despite buzz at the recent ASTRO meeting about new radiation therapy technology, the ViewRay platform, we've seen a sharp falloff in chatter about this innovative technology. Our research team has spoken to several early adopters, but questions from interested buyers have been few and far between. This is somewhat unexpected, since the technology gets us closer than ever to the “holy grail” of radiation therapy: real-time adaptive treatment.
The ViewRay system, which received FDA clearance last spring, uses continuously acquired MRI images to optimize radiation therapy as it is being delivered. However, ViewRay’s system is expensive and will be restricted to the research setting for the foreseeable future. Researchers still need to solve several challenges related to tumor tracking and adaptive dose delivery.
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An innovative alternative to ViewRay
Institutions that have a high interest in innovation but a low appetite for risk may find MRI simulation more appealing. MRI simulation is a technique whereby MRI—typically 3T—replaces CT for radiation therapy planning. Currently, most radiation therapy planning workflows feature CT, and some institutions also fuse MR images to incorporate both datasets. However, a handful of institutions have begun to replace CT with MR entirely in recent years, sparing patients the ionizing radiation and precluding the fusion errors that often occur when MR data is merged with CT.
Further, MRI offers better resolution than CT where it counts: soft tissue tumors, such as found in the prostate, or tumors found in complex anatomy, like the brain. MRI simulation has been successfully performed independent of CT for these sites. Other exciting applications include breast, liver, and pancreas among other sites where MRI has traditionally proven itself to be superior to CT.
Physical limitations of MRI technology
Still, MRI technology does have some inherent physical limitations. It lacks electron density and bony detail information, and geometric distortions reduce the spatial accuracy of treatment plans and cause variance in dose calculation. However, researchers have developed a number of techniques to solve these problems. Assigning bulk electron densities to tissues and using atlas-reconstruction method have resulted in dosimetric calculations that often differ by less than 1% from CT-based calculations.
Implementation can also be difficult because patients undergoing treatment planning MRI exams require special accommodations. To reduce errors from motion, immobilization devices are frequently employed to hold the patient still during the exam. The MRI scanner must be able to accommodate these bulky devices, often through flexible coils or open-bore designs. Though many MRI exam tables are concave—to improve patient comfort—flat-top exam tables are needed for simulation in order to ensure reliable patient set-up.
MRI simulation most suitable for institutions with strong, diverse case mixes
In light of its present limitations, MR-only planning is best suited for high-volume academic medical centers and pediatric hospitals. Researchers continue to hone MRI simulation techniques and expand applications to other tumor sites.
Though still far off from replacing CT on a large scale, MRI simulation presents an opportunity for progressive oncology programs to continue their efforts to improve precision in treatment planning and delivery.
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