SBIR-STTR Award

This project will produce a method for constructing treatment plans with a guarantee on the quality of the solution. The plans produced by current techniques can fall short of the optimum or needlessly fail to satisfy constraints. As a result, the search for an improved solution is open-ended, exhausting hospital resources and manpower, and providing no assurance to patient or physician that a better plan was not overlooked. This application proposes to use the theory of mixed integer programming to provide a solution whose objective lies within a defined range of the highest possible value obtainable under the constraints (e.g., one fraction size, 1.8 Gy). The method will accept absolute dose limits, dose volume limits and dose homogeneity limits and will be applied to both conformal therapy and intensity modulated therapy. The effect on the objective of making small changes to the constraints will be found, giving the physician and patient better control of the competing risks of treatment. It will also find the minimum number of beams needed, significantly reducing treatment cost. If successful, the method will be patented and marketed to the radiotherapy community. It will provide improved outcomes, reduce provider risks and make planning more efficient. PROPOSED COMMERCIAL APPLICATIONS: This work will develop a software algorithm that can be marketed for treatment planning. The software will reduce the costs of radiotherapy planning, improve achievable tumor doses, provide assurance that inferior plans are not created and reveal information to physicians on the tradeoffs among the risks and benefits of treatment

This project will develop a package of planning products for radiation treatment that will introduce a measure of quality assurance now lacking, provide clinicians the opportunity to raise tumor dose, and expose the tradeoffs among the treatment constraints and objectives. The new approach based on mixed integer programming (MIP) will ensure that the dose distributions prepared for patients do not fail to meet the conditions specified because of inferior performance in a planning routine. The result will be a package for picking beams and beam angles, constructing intensity profiles, and evaluating the effect of uncertainties in treatment objectives or in target and organ positions. Constraints can include dose, dosevolume, and homogeneity limits, and restrictions on beam number. Phase I demonstrated the feasibility of using MIP to optimize tumor dose to within a known error of the best possible while enforcing prescribed constraints, and revealed the tradeoffs among the objective and constraints. Phase II aims to speed performance by customizing a proprietary solver to the developed algorithms and adding new formulations, to integrate the processes of intensity optimization and treatment delivery in order to limit the dose distortions users now face, and to engineer displays of the multidimensional tradeoffs present.

Thesaurus Terms:
mathematical model, method development, neoplasm /cancer radiation therapy, patient care planning, radiation therapy dosage, therapy design /development computer assisted patient care, computer graphics /printing, computer system design /evaluation, information display, neutron radiation, three dimensional imaging /topography bioengineering /biomedical engineering, human data