Proton Scanning Algorithm Precisely Controls how Radiation Dose is Distributed

Varian Medical Systems (Palo Alto, CA, USA) has received U.S. Food and Drug Administration (FDA) 510(k) clearance for the new algorithm, which has been incorporated into Varian's Eclipse treatment planning software. The algorithm now makes it possible to plan for intensity-modulated proton therapy by optimizing dose distributions in three dimensions to protect surrounding healthy tissues.

This proton scanning technique improves on current proton delivery methods that require a therapist to enter and exit the treatment room numerous times throughout a treatment to adjust physical compensators for processing proton beams. "With proton scanning and intensity-modulation, this cumbersome process can be completely eliminated,” said Jeff Amacker, Varian's business manager for treatment planning products.

Proton therapy uses a particle accelerator to generate a beam of protons and deposit them accurately within tumors while sparing adjacent healthy tissues and organs. Unlike the more common photon radiotherapy, with beams that pass all the way through the patient's body, proton therapy beams can be designed to stop and distribute most of their radiation dose at the depth of the tumor. This makes it possible to improve specific cancer treatments by protecting more healthy tissue and thus reduce short- and long-term side effects in cases where surrounding healthy tissues are particularly sensitive to radiation. Radiation oncology experts estimate that about 10% of the patients can benefit from having all or some of their treatment with protons.

With the addition of the proton-scanning dose algorithm, Eclipse, a very fast, versatile, and widely-used radiotherapy treatment planning system, continues to expand on its functionality as a single system for state-of-the-art proton, photon, electron, and brachytherapy treatment planning. Within the Eclipse planning environment, clinicians can combine and compare plans for any and all of these treatment approaches, to arrive at an optimal strategy for helping patients.


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