A unified path seeking algorithm for IMRT and IMPT beam orientation optimization.

Objective. Fully automated beam orientation optimization (BOO) for intensity-modulated radiotherapy and intensity modulated proton therapy (IMPT) is gaining interest, since achieving optimal plan quality for an unknown number of fixed beam arrangements is tedious. Fast group sparsity-based optimization methods have been proposed to find the optimal orientation, but manual tuning is required to eliminate the exact number of beams from a large candidate set. Here, we introduce a fast, automated gradient descent-based path-seeking algorithm (PathGD), which performs fluence map optimization for sequentially added beams, to visualize the dosimetric benefit of one added field at a time.Approach. Several configurations of 2-4 proton and 5-15 photon beams were selected for three head-and-neck patients using PathGD, which was compared to group sparsity-regularized BOO solved with the fast iterative shrinkage-thresholding algorithm (GS-FISTA), and manually selected IMPT beams or one coplanar photon VMAT arc (MAN). Once beams were chosen, all plans were compared on computational efficiency, dosimetry, and for proton plans, robustness.Main results. With each added proton beam, Clinical Target Volume (CTV) and organs at risk (OAR) dosimetric cost improved on average across plans by [1.1%, 13.6%], and for photons, [0.6%, 2.0%]. Comparing algorithms, beam selection for PathGD was faster than GS-FISTA on average by 35%, and PathGD matched the CTV coverage of GS-FISTA plans while reducing OAR mean and maximum dose in all structures by an average of 13.6%. PathGD was able to improve CTV [Dmax, D95%] by [2.6%, 5.2%] and reduced worst-case [max, mean] dose in OARs by [11.1%, 13.1%].Significance. The benefit of a path-seeking algorithm is the beam-by-beam analysis of dosimetric cost. PathGD was shown to be most efficient and dosimetrically desirable amongst group sparsity and manual BOO methods, and highlights the sensitivity of beam addition for IMPT in particular.

Ramesh P ，Valdes G ，O'Connor D ，Sheng K ... -  《-》

Quantification of beam size impact on intensity-modulated proton therapy with robust optimization in head and neck cancer-comparison with intensity-modulated radiation therapy.

We assessed the effect of beam size on plan robustness for intensity-modulated proton therapy (IMPT) of head and neck cancer (HNC) and compared the plan quality including robustness with that of intensity-modulated radiation therapy (IMRT). IMPT plans were generated for six HNC patients using six beam sizes (air-sigma 3-17 mm at isocenter for a 70-230 MeV) and two optimization methods for planning target volume-based non-robust optimization (NRO) and clinical target volume (CTV)-based robust optimization (RO). Worst-case dosimetric parameters and plan robustness for CTV and organs-at-risk (OARs) were assessed under different scenarios, assuming a ± 1-5 mm setup error and a ± 3% range error. Statistical comparisons of NRO-IMPT, RO-IMPT and IMRT plans were performed. In regard to CTV-D99%, RO-IMPT with smaller beam size was more robust than RO-IMPT with larger beam sizes, whereas NRO-IMPT showed the opposite (P < 0.05). There was no significant difference in the robustness of the CTV-D99% and CTV-D95% between RO-IMPT and IMRT. The worst-case CTV coverage of IMRT (±5 mm/3%) for all patients was 96.0% ± 1.4% (D99%) and 97.9% ± 0.3% (D95%). For four out of six patients, the worst-case CTV-D95% for RO-IMPT (±1-5 mm/3%) were higher than those for IMRT. Compared with IMRT, RO-IMPT with smaller beam sizes achieved lower worst-case doses to OARs. In HNC treatment, utilizing smaller beam sizes in RO-IMPT improves plan robustness compared to larger beam sizes, achieving comparable target robustness and lower worst-case OARs doses compared to IMRT.

Baba H ，Hotta K ，Takahashi R ，Motegi K ，Sugama Y ，Sakae T ，Tachibana H ... -  《-》

Dosimetric optimization for dynamic mixed beam arc therapy (DYMBARC).

Non-coplanarity and mixed beam modality could be combined to further enhance dosimetric treatment plan quality. We introduce dynamic mixed beam arc therapy (DYMBARC) as an innovative technique that combines non-coplanar photon and electron arcs, dynamic gantry and collimator rotations, and intensity modulation with photon multileaf collimator (MLC). However, finding favorable beam directions for DYMBARC is challenging due to the large solution space, machine component constraints, and optimization parameters, posing a highly non-convex optimization problem. To establish DYMBARC and solve the pathfinding challenge by employing direct aperture optimization (DAO) to determine the table angles and gantry angle ranges of photon and electron arcs for different clinically motivated cases. The method starts by generating a grid of beam directions based on user-defined resolutions along the gantry and table angle axes for each beam quality considered. Beam directions causing collisions or entering through the end of CT are excluded. For electrons, a fixed source-to-surface distance of 80 cm is used to reduce in-air scatter. Electron beam energies with insufficient range to reach the target or beam directions impinging on the table before reaching the patient are excluded. The remaining beam directions form the pathfinding solution space. Promising photon and electron MLC-defined apertures, with associated monitor unit (MU) weights, are iteratively added using a hybrid-DAO algorithm. This algorithm combines column generation to add apertures and simulated annealing to further refine aperture shapes and weights. Apertures are added until the requested number of paths are formed and the user-defined maximum total gantry angle range is reached. Paths are resampled to a finer gantry angle resolution and subject to DAO for simultaneous optimization of beam intensities along the photon/electron arcs. Subsequent final dose calculation and MU weight reoptimization result in a deliverable DYMBARC plan. DYMBARC plans are created for three clinically motivated cases (brain, breast, and pelvis) and compared to DYMBARC variants: colli-DTRT (dynamic collimator trajectory radiotherapy) using non-coplanar photon arcs; and Arc-MBRT (mixed beam radiotherapy) using photons and electrons but restricted to coplanar setup. Additionally, a manually defined volumetric modulated arc therapy (VMAT) setup serves as a reference clinical technique. Dose distributions, dose-volume histograms, and dosimetric endpoints are evaluated. Dosimetric validation with radiochromic film measurements (gamma evaluation, 3% / 2 mm (global), 10% dose threshold) is performed on a TrueBeam system in developer mode for one case. While maintaining similar target coverage and homogeneity, DYMBARC reduced mean doses to organs-at-risk compared to VMAT by an average of 3.2, 0.5, and 2.9 Gy for the brain, breast, and pelvis cases, respectively. Similar or smaller mean dose reductions were observed for Arc-MBRT or colli-DTRT, compared to VMAT. Electron contributions to the mean planning target volume dose ranged from 2% to 34% for DYMBARC and from 11% to 40% for Arc-MBRT. Measurement validation showed >99.7% gamma passing rate. DYMBARC was successfully established using a dosimetrically optimized pathfinding approach, combining non-coplanarity with mixed beam modality. DYMBARC facilitated the determination of photon and electron contributions on a case-by-case basis, enhancing more personalized treatment modalities.

Zhu C ，Guyer G ，Bertholet J ，Mueller S ，Loebner HA ，Volken W ，Arnold J ，Aebersold DM ，Stampanoni MFM ，Fix MK ，Manser P ... -  《-》

An orthogonal matching pursuit optimization method for solving minimum-monitor-unit problems: Applications to proton IMPT, ARC and FLASH.

The intensities (i.e., number of protons in monitor unit [MU]) of deliverable proton spots need to be either zero or meet a minimum-MU (MMU) threshold, which is a nonconvex problem. Since the dose rate is proportionally associated with the MMU threshold, higher-dose-rate proton radiation therapy (RT) (e.g., efficient intensity modulated proton therapy (IMPT) and ARC proton therapy, and high-dose-rate-induced FLASH effect needs to solve the MMU problem with larger MMU threshold, which however makes the nonconvex problem more difficult to solve. This work will develop a more effective optimization method based on orthogonal matching pursuit (OMP) for solving the MMU problem with large MMU thresholds, compared to state-of-the-art methods, such as alternating direction method of multipliers (ADMM), proximal gradient descent method (PGD), or stochastic coordinate descent method (SCD). The new method consists of two essential components. First, the iterative convex relaxation (ICR) method is used to determine the active sets for dose-volume planning constraints and decouple the MMU constraint from the rest. Second, a modified OMP optimization algorithm is used to handle the MMU constraint: the non-zero spots are greedily selected via OMP to form the solution set to be optimized, and then a convex constrained subproblem is formed and can be conveniently solved to optimize the spot weights restricted to this solution set via OMP. During this iterative process, the new non-zero spots localized via OMP will be adaptively added to or removed from the optimization objective. The new method via OMP is validated in comparison with ADMM, PGD and SCD for high-dose-rate IMPT, ARC, and FLASH problems of large MMU thresholds, and the results suggest that OMP substantially improved the plan quality from PGD, ADMM and SCD in terms of both target dose conformality (e.g., quantified by max target dose and conformity index) and normal tissue sparing (e.g., mean and max dose). For example, in the brain case, the max target dose for IMPT/ARC/FLASH was 368.0%/358.3%/283.4% respectively for PGD, 154.4%/179.8%/150.0% for ADMM, 134.5%/130.4%/123.0% for SCD, while it was <120% in all scenarios for OMP; compared to PGD/ADMM/SCD, OMP improved the conformity index from 0.42/0.52/0.33 to 0.65 for IMPT and 0.46/0.60/0.61 to 0.83 for ARC. A new OMP-based optimization algorithm is developed to solve the MMU problems with large MMU thresholds, and validated using examples of IMPT, ARC, and FLASH with substantially improved plan quality from ADMM, PGD, and SCD.

Zhu YN ，Zhang X ，Lin Y ，Lominska C ，Gao H ... -  《-》

Erratum: Eyestalk Ablation to Increase Ovarian Maturation in Mud Crabs.

《Jove-Journal of Visualized Experiments》