Simultaneous optimization of photons and electrons for mixed beam radiotherapy

Mueller, Silvan; Fix, M.K.; Joosten, A.; Henzen, Dominik; Frei, D.; Volken, W.; Kueng, R; Aebersold, Daniel M.; Stampanoni, Marco; Manser, Peter

doi:10.1088/1361-6560/aa70c5

Cited by 28 publications

(58 citation statements)

References 42 publications

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“…The final and beamlet dose distributions are calculated using SMCP integrated beam models and dose calculation algorithms VMC++ (photon beams) and macro MC (electron beams). Measured and calculated dose distributions of single fields generally agree within 2% dose difference (global) or 1 mm distance to agreement for photon beams and 3% dose difference (global) or 2 mm distance to agreement for electron beams . A voxel size of 2.5 × 2.5 × 2.5 mm 3 is used for all final dose calculations in this work.…”

Section: Methodsmentioning

confidence: 83%

“…However, this advantage is not apparent for this case, because a bolus is applied such that photon only plans achieve a sufficient PTV dose homogeneity. The plan quality of DYMBER is expected to be less dependent on using a bolus than photon only techniques, as already indicated for MBRT . On the other hand, the risk for skin toxicity on cases, where the skin is not a part of the target, should be clinically evaluated.…”

Section: Discussionmentioning

confidence: 99%

“…Hence, the optimizer converges potentially to the global minimum of the objective function. Independent of the clinical case, the same parameter values describing the cooling schedules are used as described in a previous work . The objective function given by

f = {false\sum}_{k = 1}^{N_{italicDV}} w_{k} \cdot f_{k}^{DV} + {false\sum}_{j = 1}^{N_{italicgEUD}} w_{j} \cdot f_{j}^{gEUD}

is a weighted sum of N DV dose‐volume and N gEUD generalized equivalent uniform dose (gEUD) objectives, where w k is the weight of the k th dose‐volume objective with its objective function given by

f_{k}^{DV} = {false\sum}_{i = 1}^{M_{k}} \frac{θ false(a_{k} \cdot false(D_{i} - D_{k} false) false) \cdot θ false(a_{k} \cdot false(D (V_{k} false) - D_{i} false) false) \cdot {(D_{i} - D_{k})}^{2}}{N_{i}}

and w j is the weight of the j th gEUD objective with its objective function given by

f_{j}^{gEUD} = θ false(g E U D false(t, j false) - g E U D_{j} false) \cdot {(g E U D (t, j) - g E U D_{j})}^{2}

…”

Section: Methodsmentioning

confidence: 99%

“…If photon beams are added to electron beams, called mixed beam radiotherapy (MBRT), then this restriction in the target depth is removed. It was shown for targets with at least some superficial part that treatment plan quality of coplanar step and shoot MBRT plans with simultaneously optimized photon and electron beams is substantially improved compared to IMRT and VMAT plans, because of the additional DoF of two different particle types . At the same time, clinical workflow could be maintained, because photon and electron beams are usually both available on the same conventional treatment unit and using the pMLC also for electron beam collimation means that no accessory is required to be attached to the treatment unit.…”

Section: Introductionmentioning

confidence: 99%

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Part 2: Dynamic mixed beam radiotherapy (DYMBER): Photon dynamic trajectories combined with modulated electron beams

et al. 2018

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Section: Methodsmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

f = {false\sum}_{k = 1}^{N_{italicDV}} w_{k} \cdot f_{k}^{DV} + {false\sum}_{j = 1}^{N_{italicgEUD}} w_{j} \cdot f_{j}^{gEUD}

f_{k}^{DV} = {false\sum}_{i = 1}^{M_{k}} \frac{θ false(a_{k} \cdot false(D_{i} - D_{k} false) false) \cdot θ false(a_{k} \cdot false(D (V_{k} false) - D_{i} false) false) \cdot {(D_{i} - D_{k})}^{2}}{N_{i}}

and w j is the weight of the j th gEUD objective with its objective function given by

f_{j}^{gEUD} = θ false(g E U D false(t, j false) - g E U D_{j} false) \cdot {(g E U D (t, j) - g E U D_{j})}^{2}

…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Part 2: Dynamic mixed beam radiotherapy (DYMBER): Photon dynamic trajectories combined with modulated electron beams

et al. 2018

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“…By delivering MERT plans with a standard photon MLC, the potential arises for seamless mixed electron–photon delivery without interrupting treatment delivery between modality changes. Indeed, mixed‐beam electron–photon radiotherapy (MBRT) plans have been shown to offer additional degrees of freedom to influence the trade‐off between normal tissue dose and target coverage …”

Section: Introductionmentioning

confidence: 99%

Robust mixed electron–photon radiation therapy optimization

2019

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Purpose Mixed beam electron–photon radiation therapy (MBRT) is an emerging technique that has the potential to reduce dose to normal tissue while improving target coverage for cancer sites with superficial tumors. Advances in optimization algorithms and robotic linear accelerators have made the creation and delivery of complex MBRT plans realistic without the need for special additional collimators, devices, or resetup of the patient. However, no study has been performed on the robustness of MBRT dose distributions to patient setup errors. Intensity‐modulated delivery of other charged particles such as protons have been shown to require robust planning techniques to maintain adequate target coverage under positioning errors. We therefore assess the sensitivity of MBRT treatment plans to positioning uncertainties when created under the traditional planning target volume (PTV)‐based planning paradigm and present a novel optimization model for the creation of robust MBRT plans. Methods The column generation method was applied to robust MBRT treatment planning by deriving the pricing problem for stochastic and “worst case” minimax optimization models, two common formulations of robustness. Robust treatment plans were created for two patient cases representative of the cancer sites which stand to benefit from MBRT: soft tissue sarcoma (STS) irradiation and chest wall irradiation with deep‐seated internal mammary, axillary, and supraclavicular nodes (CW‐N). For both patient cases, beamlet dose distributions for electrons and photons were generated for positioning shifts in six directions, ±5mm(xfalse^,yfalse^,zfalse^) in addition to a nominal unshifted scenario, for a total of seven sets of beamlets. Robust plans were created by specifying dose coverage constraints to the clinical target volume (CTV), as opposed to the PTV. Comparisons were performed against traditional PTV‐based plans created with a single set of unshifted beamlets. Results The dose distributions of traditional PTV‐based MBRT plans showed significant degradation in target coverage homogeneity when patient positioning errors were considered. For both cancer sites, cold spots below 95% and hot spots above 108% of the prescription dose appeared within the CTV when shifting the patient by 5 mm, corresponding to the margin added to the CTV to form the PTV. In contrast, CTV‐based robust plans created with the new optimization model maintained target coverage within the 95%–108% limits, for all positioning errors. Conclusion The quality of MBRT treatment plans created using a traditional PTV‐based optimization model was highly sensitive to patient positioning errors. For both patient cases, positioning errors resulted in perturbations to the nominal dose distributions which would have rendered PTV‐based plans clinically unacceptable. In contrast, CTV‐based robust plans were able to maintain adequate target coverage under all positioning error scenarios considered. We therefore conclude that to ensure the fidelity of the dose distribution delivered to the pat...

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Development of an extended Macro Monte Carlo method for efficient and accurate dose calculation in magnetic fields

et al. 2020

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Motivation Progress in the field of magnetic resonance (MR)‐guided radiotherapy has triggered the need for fast and accurate dose calculation in presence of magnetic fields. The aim of this work is to satisfy this need by extending the macro Monte Carlo (MMC) method to enable dose calculation for photon, electron, and proton beams in a magnetic field. Methods The MMC method is based on the transport of particles in macroscopic steps through an absorber by sampling the relevant physical quantities from a precalculated database containing probability distribution functions. To enable MMC particle transport in a magnetic field, a transformation accounting for the Lorentz force is applied for each macro step by rotating the sampled position and direction around the magnetic field vector. The transformed position and direction distributions on local geometries are validated against full MC for electron and proton pencil beams. To enable photon dose calculation, an in‐house MC algorithm is used for photon transport and interaction. Emerging secondary charged particles are passed to MMC for transport and energy deposition. The extended MMC dose calculation accuracy and efficiency is assessed by comparison with EGSnrc (photon and electron beams) and Geant4 (proton beam) calculated dose distributions of different energies and homogeneous magnetic fields for broad beams impinging on water phantoms with bone and lung inhomogeneities. Results The geometric transformation on the local geometries is able to reproduce the results of full MC for all investigated settings (difference in mean value and standard deviation <1%). Macro Monte Carlo calculated dose distributions in a homogeneous magnetic field are in agreement with EGSnrc and Geant4, respectively, with gamma passing rates >99.6% (global 2%, 2 mm and 10% threshold criteria) for all situations. MMC achieves a substantial efficiency gain of up to a factor of 21 (photon beam), 66 (electron beam), and 356 (proton beam) compared to EGSnrc or Geant4. Conclusion Efficient and accurate dose calculation in magnetic fields was successfully enabled by utilizing the developed extended MMC transport method for photon, electron, and proton beams.

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Simultaneous optimization of photons and electrons for mixed beam radiotherapy

Cited by 28 publications

References 42 publications

Part 2: Dynamic mixed beam radiotherapy (DYMBER): Photon dynamic trajectories combined with modulated electron beams

Part 2: Dynamic mixed beam radiotherapy (DYMBER): Photon dynamic trajectories combined with modulated electron beams

Robust mixed electron–photon radiation therapy optimization

Development of an extended Macro Monte Carlo method for efficient and accurate dose calculation in magnetic fields

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