BrainLAB Announces 510(k) FDA Clearance of Monte Carlo Dose Engine for Stereotactic Radiosurgery and Radiati...( High Performance Monte Carlo Algorit...),Health

High Performance Monte Carlo Algorithm Generates Precise Dose Calculations

Within Seconds

WESTCHESTER, Ill., July 29 /PRNewswire/ -- BrainLAB, a leader in software-driven systems for targeted, less-invasive medical treatments, has received 510(k) clearance from the U.S. Food and Drug Administration (FDA) for its Monte Carlo Dose Calculation Algorithm, which is already being used at several clinical cooperation sites worldwide.

In the past, clinicians had limited treatment choices or have been unable to include Monte Carlo method calculations into their routine for dose calculation due to numerous factors such as the extreme amount of time needed, restrictions of treatment planning software to a single machine or treatment modality and its integration into available software. Although the Monte Carlo algorithm is widely accepted as the gold standard for calculation in treatment planning accuracy, the aforementioned limitations have inhibited its clinical implementation. To offer superior treatment possibilities for patients and tools that seamlessly integrate into the clinical workflow, BrainLAB has developed new Monte Carlo Dose Calculation software that makes high-precision treatment available in everyday clinical practice.

The BrainLAB Monte Carlo Dose Calculation software is a high performance Monte Carlo algorithm for therapeutic photon beams supporting nearly all linear accelerator and multi-leaf collimator (MLC) types. Monte Carlo is now available as an option on the iPlan(R) RT Dose treatment planning software. Dose calculations can be completed within seconds for conformal beam and dynamic arc treatments and within a few minutes for complex IMRT cases.

"The new BrainLAB Monte Carlo algorithm integrates some of the most advanced image registration and segmentation tools available in the clinical environment, providing a powerful tool to tackle the most challenging radiosurgery cases in lung and
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