Abstract
Abstract Purpose The aim of this study is to investigate an implementation method and the results of a voxel-based self-adaptive prescription dose optimization algorithm for intensity-modulated radiotherapy. Materials and methods The self-adaptive prescription dose optimization algorithm used a quadratic objective function, and the optimization engine was implemented using the molecular dynamics. In the iterative optimization process, the optimization prescription dose changed with the relationship between the initial prescription dose and the calculated dose. If the calculated dose satisfied the initial prescription dose, the optimization prescription dose was equal to the calculated dose; otherwise, the optimization prescription dose was equal to the initial prescription dose. We assessed the performance of the self-adaptive prescription dose optimization algorithm with two cases: a mock head and neck case and a breast case. Isodose lines, dose–volume histogram, and dosimetric parameters were compared between the conventional molecular dynamics optimization algorithm and the self-adaptive prescription dose optimization algorithm. Results The self-adaptive prescription dose optimization algorithm produces the different optimization results compared with the conventional molecular dynamics optimization algorithm. For the mock head and neck case, the planning target volume (PTV) dose uniformity improves, and the dose to organs at risk is reduced, ranging from 1 to 4%. For the breast case, the use of self-adaptive prescription dose optimization algorithm also leads to improvements in the dose distribution, with the dose to organs at risk almost unchanged. Conclusion The self-adaptive prescription dose optimization algorithm can generate an ideal clinical plan more effectively, and it could be integrated into a treatment planning system after more cases are studied.
Highlights
Compared with conventional conformal radiotherapy, intensity modulated radiotherapy (IMRT) increases the dose of tumor and decreases the dose of organs by adjusting the intensity distribution of radiation field [1,2,3,4]
The self-adaptive prescription dose optimization algorithm (SAPDOA) used the weighted quadratic objective function, which was the same as the conventional molecular dynamics optimization algorithm (CMDOA) we have implemented, but the objective function was redefined as follows: We evaluated the SAPDOA algorithm with two cases, one of them was from the AAPM TG-119 [22], and the other one was a clinical case
Organ-based inverse optimization is widely used in clinical practice at present, the quality of the plan obtained by organ-based optimization heavily depends on the experience of the planner
Summary
Compared with conventional conformal radiotherapy, intensity modulated radiotherapy (IMRT) increases the dose of tumor and decreases the dose of organs by adjusting the intensity distribution of radiation field [1,2,3,4]. Inverse planning is the foundation of IMRT, and its performance determines the success of IMRT [5,6]. There are two kinds of inverse optimization techniques in IMRT: organ-based optimization and voxel-based optimization. In the organ-based optimization, the prescription dose and weight parameters are given to the organ, and all the voxels in an organ are combined and treated in the objective function. Because there is no clear relationship between the dose and weight parameters and the final dose distribution, the determination of these parameters is essentially a “guessing game;”
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