OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

Radiosurgery treatment planning using conformal arc informed volumetric modulated arc therapy.

Linac based radiosurgery to multiple metastases is commonly planned with volumetric modulated arc therapy (VMAT) as it effectively achieves high conformality to complex target arrangements. However, as the number of targets increases, VMAT can struggle to block between targets, which can lead to highly modulated and/or nonconformal multi-leaf collimator (MLC) trajectories that unnecessarily irradiation of healthy tissue. In this study we introduce, describe, and evaluate a treatment planning technique called Conformal Arc Informed VMAT (CAVMAT), which aims to reduce the dose to healthy tissue while generating highly conformal treatment plans. CAVMAT is a hybrid technique which combines the conformal MLC trajectories of dynamic conformal arcs with the MLC modulation and versatility of inverse optimization. CAVMAT has 3 main steps. First, targets are assigned to subgroups to maximize MLC blocking between targets. Second, arc weights are optimized to achieve the desired target dose, while minimizing MU variation between arcs. Third, the optimized conformal arc plan serves as the starting point for limited inverse optimization to improve dose conformity to each target. Twenty multifocal VMAT cases were replanned with CAVMAT with 20Gy applied to each target. The total volume receiving 2.5Gy[cm3], 6Gy[cm3], 12Gy[cm3], and 16Gy[cm3], conformity index, treatment delivery time, and the total MU were used to compare the VMAT and CAVMAT plans. In addition, CAVMAT was compared to a broad range of planning strategies from various institutions (108 linear accelerator based plans, 14 plans using other modalities) for a 5-target case utilized in a recent plan challenge. For the linear accelerator-based plans, a plan complexity metric based on aperture opening area and perimeter, total monitor units (MU), and MU for a given aperture opening was utilized in the plan challenge scoring algorithm to compare the submitted plans to CAVMAT. After re-planning the 20 VMAT cases, CAVMAT reduced the average V2.5Gy[cm3] by 25.25 ± 19.23%, V6Gy[cm3] by 13.68 ± 18.97%, V12Gy[cm3] by 11.40 ± 19.44%, and V16Gy[cm3] by 6.38 ± 19.11%. CAVMAT improved conformity by 3.81 ± 7.57%, while maintaining comparable target dose. MU for the CAVMAT plans increased by 24.35 ± 24.66%, leading to an increased treatment time of 2 minutes. For the plan challenge case, CAVMAT was 1 of 12 linac based plans that met all plan challenge scoring criteria. Compared to the average submitted VMAT plan, CAVMAT increased the V10%Gy[%] of healthy tissue (Brain-PTV) by roughly 3.42%, but in doing so was able to reduce the V25%Gy[%] by roughly 3.73%, while also reducing V50%Gy[%], V75%Gy[%], and V100%Gy[%]. The CAVMAT technique successfully eliminated insufficient MLC blocking between targets prior to the inverse optimization, leading to less complex treatment plans and improved tissue sparing. Tissue sparing, improved conformity, and decreased plan complexity at the cost of slight increase in treatment delivery time indicates CAVMAT to be a promising method to treat brain metastases.

Evaluation of the radiotherapy treatment planning in the presence of a magnetic valve tissue expander.

The combination of radiotherapy treatments and breast reconstruction, using temporary tissue expanders, generates several concerns due to the presence of a magnetic valve inside the radiation field. The objective of this work is to evaluate a radiotherapy treatment planning for a patient using a tissue expander. Isodose curve maps, obtained using radiochromic films, were compared to the ones calculated with two different dose calculation algorithms of the Eclipse radiotherapy Treatment Planning System (TPS), considering the presence or absence of the heterogeneity. The TPS calculation considering the presence of the heterogeneity shows changes around 5% in the isodose curves when they were compared with the calculation without heterogeneity correction. This calculation did not take in account the real density value of the heterogeneity. This limitation was quantified to be around 10% in comparison with the TPS calculation and experimental measurements using the radiochromic film. These results show that the magnetic valve should be taken in account in dose calculations of the TPS. With respect to the AAA and Pencil Beam Convolution algorithms, when the calculation is compared with the real distribution, AAA presents a distribution more similar to experimental dose distribution.