摘要
This paper uses a molecular dynamics (MD) method for intensity-modulated proton therapy treatment planning optimization to overcome the problem of gradient-based optimization methods such as quasi-Newton, which is sensitive to starting conditions and is easily trapped in local minima. We implemented a molecular dynamics (MD) method and a quasi-Newton method for plan optimization. Three types of cancer cases, prostate, head-and-neck and lung cancer, were tested with three starting different initial conditions. Overall, the MD method consistently resulted in solutions with lower objective function values (OFVs) compared to those from the quasi-Newton algorithm. Furthermore, the MD method converged on the same OFV regardless of its initial starting points used for the prostate cancer case.
This paper uses a molecular dynamics (MD) method for intensity-modulated proton therapy treatment planning optimization to overcome the problem of gradient-based optimization methods such as quasi-Newton, which is sensitive to starting conditions and is easily trapped in local minima. We implemented a molecular dynamics (MD) method and a quasi-Newton method for plan optimization. Three types of cancer cases, prostate, head-and-neck and lung cancer, were tested with three starting different initial conditions. Overall, the MD method consistently resulted in solutions with lower objective function values (OFVs) compared to those from the quasi-Newton algorithm. Furthermore, the MD method converged on the same OFV regardless of its initial starting points used for the prostate cancer case.
