This algorithm is used with existing technology to rapidly optimize cancer radiation therapy treatment plans. Also, it has the potential to revolutionize radiation therapy by serving as the platform for adaptive radiation therapy.

Key Words: Radiation Therapy, Optimization, Cancer Treatment Planning

DESCRIPTION OF INVENTION: Fast Inverse Dose Optimization (FIDO) is an algorithm and associated software that does not rely on the current “trial and error” search to find the optimal radiation beam plan for a patient, but instead solves a single algebraic procedure directly. As a result, FIDO delivers an optimal treatment plan in seconds rather than the current standard of minutes to hours (e.g. the TomoTherapy Inc. system uses 32 computers to develop a treatment plan and it can still take overnight for complex plans). Thus, FIDO eliminates the need to settle for sub-optimal treatment plans and sets the stage for adaptive radiation therapy. The FIDO algorithm and the corresponding software are fully developed and simulations using real-life imaging data (CT scans) are complete.

BACKGROUND: According to the National Cancer Institute of Canada, there was an estimated 1.5 million new cases of cancer in North America in 2006. The number of new cases worldwide has increased year on year for the past thirty years and is expected to continue to increase as the population increases and ages. Fifty to sixty percent of cancer patients undergo radiation therapy at some point during their treatment.

The current process involves up-front treatment planning on the basis of three-dimensional images (Computed Tomography (“CT”) scans) of the body obtained prior to treatment. Using these images, a treatment plan is generated through computer simulation of the passage of the radiation beams through the various tissues to determine the optimal radiation dose distribution to strike at the tumour while minimizing collateral damage in nearby healthy organs.
One of the key challenges is that radiation must be delivered in small daily doses over the course of five to seven weeks. During this time, the patient’s anatomy will change compared with the up-front treatment plan (e.g. the status of lung inflation shifts the tumour position). Much research and development is now dedicated to adding CT imaging capabilities to the treatment machine (e.g. tomotherapy) to image and track the “anatomy of the day”. Ideally, the radiation dose distribution should also be re-optimized on a daily basis; however, the problem is that today’s computer hardware and software cannot accomplish this quickly enough (it currently takes several hours to develop a treatment plan and the imaging and treatment session only lasts on average for 15 minutes). This process of developing a new treatment plan for each treatment session is known as adaptive radiation therapy.

In addition, there is currently a trade-off between speed and optimal treatment plans. Therefore, occasionally, sub-optimal treatment plans are accepted because of the excessive time needed to develop an optimal plan. In fact, there is the added detriment in that current non-FIDO algorithms cannot even converge to the true optimal solution.

POTENTIAL ADVANTAGES/USES:
(1) A fast, accurate, and robust technique for planning radiation treatment.
(2) A platform for adaptive radiation therapy.

Reference Number: UWO-AE-011

Applications filed in US, Canada, China, Europe and Japan.