Fraction optimization for hybrid proton‐photon treatment planning

Li, Wangyao; Zhang, Weijie; Lin, Yuting; Chen, I‐Chun; Gao, Hao

doi:10.1002/mp.16297

Cited by 7 publications

(5 citation statements)

References 37 publications

(70 reference statements)

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“…Therefore, the uniformity constraint for the fraction dose could potentially increase access to limited proton resources. The optimized plans generated using our method have previously demonstrated robustness to the fractionation effect (Unkelbach et al 2021) in terms of biological effective dose (BED), despite BED not being directly optimized during treatment planning (Li et al 2023b).…”

Section: Discussionmentioning

confidence: 99%

“…Loizeau et al developed a fraction optimization method to minimize normal tissue complication probabilities, based on pre-optimized proton and photon plans (2021). Recently, joint optimization of the number of fractions and plan variables for protons and photons was developed (Li et al 2023b). This method ensures a uniform target dose per proton or photon fraction and can lead to optimized and automatic delivery of hybrid proton-photon RT using existing proton and photon machines.…”

Section: Introductionmentioning

confidence: 99%

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Biological optimization for hybrid proton-photon radiotherapy

Li,

Lin,

et al. 2024

Phys. Med. Biol.

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Objective:Hybrid proton-photon radiotherapy (RT) is a cancer treatment option to broaden access to proton RT. Additionally, with a refined treatment planning method, hybrid RT has the potential to offer superior plan quality compared to proton-only or photon-only RT, particularly in terms of target coverage and sparing organs-at-risk (OAR), when considering robustness to setup and range uncertainties. However, there is a concern regarding the underestimation of the biological effect of protons on OAR, especially those in close proximity to targets. This study seeks to develop a hybrid treatment planning method with biological dose optimization, suitable for clinical implementation on existing proton and photon machines, with each photon or proton treatment fraction delivering a uniform target dose.Approach:The proposed hybrid biological dose optimization method optimizes proton and photon plan variables, along with the number of fractions, minimizing biological dose to OAR and surrounding normal tissues. Hybrid plans are designed to be deliverable separately and robustly on existing proton and photon machines, with enforced uniform target dose constraints for proton and photon fraction doses. Probabilistic formulation is utilized for robust optimization of setup and range uncertainties for protons and photons. The nonconvex optimization problem, arising from minimum monitor unit (MMU) constraint and dose-volume histogram (DVH) constraints, is solved using an iterative convex relaxation method.Main results:Hybrid planning with biological dose optimization effectively eliminated hot spots of biological dose, particularly in normal tissues surrounding the target, outperforming proton-only planning. It also provided superior overall plan quality and OAR sparing compared to proton-only or photon-only planning strategies.Significance:This study presents a novel hybrid biological treatment planning method capable of generating plans with minimized biological hot spots, superior plan quality to proton-only or photon-only plans, and clinical deliverability on existing proton and photon machines, separately and robustly.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biological optimization for hybrid proton-photon radiotherapy

Li,

Lin,

et al. 2024

Phys. Med. Biol.

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“…On the other hand, LET optimization should be considered to lower OAR biological dose 51 . Moreover, the emerging proton arc delivery 52 and the joint use of protons and photons 53 may further improve physical and biological dose distribution and/or delivery robustness for LATTICE. More advanced proton LATTICE studies will be carried out in the future works.…”

Section: Discussionmentioning

confidence: 99%

Lattice position optimization for LATTICE therapy

et al. 2023

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BackgroundLATTICE radiation therapy delivers 3D heterogenous dose of high peak‐to‐valley dose ratio (PVDR) to the tumor target, with peak dose at lattice vertices inside the target and valley dose for the rest of the target. Although the lattice vertex positions can impact PVDR inside the target and sparing of organs‐at‐risk (OAR), they are fixed as constants and not optimized during treatment planning in current clinical practice.PurposeThis work proposes a new LATTICE plan optimization method that can optimize lattice vertex positions during LATTICE treatment planning, which is the first lattice position optimization study to the best of our knowledge.MethodsThe new LATTICE treatment planning method optimizes lattice vertex positions as well as other plan variables (e.g., photon fluences or proton spot weights), with optimization objectives for target PVDR and OAR sparing. To satisfy mathematical differentiability, the lattice vertices are approximated in sigmoid functions. For geometric feasibility, proper geometry constraints are enforced onto lattice vertex positions. The lattice position optimization problem is solved by iterative convex relaxation (ICR) method and alternating direction method of multipliers (ADMM), and lattice vertex positions and photon/proton plan variables are jointly updated via the Quasi‐Newton method.ResultsBoth photon and proton LATTICE RT were considered, and the optimal lattice vertex positions in terms of plan objectives were found by solving all possible combinations on given discrete positions via exhaustive searching based on standard IMRT/IMPT, which served as the ground truth for validating the new LATTICE method. The results show that the new method indeed provided the optimal lattice vertex positions with the smallest optimization objective, the largest target PVDR, and the best OAR sparing.ConclusionsA new LATTICE treatment planning method is proposed and validated that can optimize lattice vertex positions as well as other photon or proton plan variables for improving target PVDR and OAR sparing.

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“…Multi-modality treatments combining PBT and XRT have been proposed to utilise the benefits of each treatment modality. 6 However, there are significant logistical challenges in co-ordinating the required scheduling for different machines and reimbursement challenges in multimodality treatments. In this scenario, one would ideally cooptimise the XRT dose distribution and the PBT dose distribution concurrently and deliver both modalities in the same treatment appointment.…”

Section: Introductionmentioning

confidence: 99%

“…Multi‐modality treatments combining PBT and XRT have been proposed to utilise the benefits of each treatment modality 6 . However, there are significant logistical challenges in co‐ordinating the required scheduling for different machines and reimbursement challenges in multi‐modality treatments.…”

Section: Introductionmentioning

confidence: 99%

Single high‐energy arc proton therapy with Bragg peak boost (SHARP)

Penfold,

Santos,

Penfold

et al. 2024

J of Medical Radiation Sci

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IntroductionBecause of the co‐location of critical organs at risk, base of skull tumours require steep dose gradients to achieve the prescribed dosimetric criteria. When available, proton beam therapy (PBT) is often considered a desirable modality for these cases, but in many instances, compromises in target coverage are still required to achieve critical organ at risk (OAR) tolerance doses. A number of techniques have been proposed to further improve the penumbra of PBT. In the current study, we propose a novel, collimator‐free treatment planning technique that combines high‐energy shoot‐through proton beams with conventional Bragg peak spot placement. The small spot size of the high‐energy pencil beams provides a sharp penumbra at the target boundary, and the Bragg peak spots provide a higher linear energy transfer (LET) boost to the target centre.MethodsThree base of skull chordoma patients were retrospectively planned with three different PBT treatment planning techniques: (1) conventional intensity‐modulated proton therapy (IMPT); (2) high‐energy proton arc therapy (HE‐PAT); and (3) the novel technique combining HE‐PAT and IMPT, referred to as single high‐energy arc with Bragg peak boost (SHARP). The Monaco 6 treatment planning system was used.ResultsSHARP was found to improve the PBT penumbra in the plane perpendicular to the HE‐PAT beams. Minimal penumbra differences were observed in the plane of the HE‐PAT beams. SHARP reduced dose‐averaged LET to surrounding organs at risk.ConclusionA novel PBT treatment planning technique was successfully implemented. Initial results indicate the potential for SHARP to improve the penumbra of PBT treatments for base of skull tumours.

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Fraction optimization for hybrid proton‐photon treatment planning

Cited by 7 publications

References 37 publications

Biological optimization for hybrid proton-photon radiotherapy

Biological optimization for hybrid proton-photon radiotherapy

Lattice position optimization for LATTICE therapy

Single high‐energy arc proton therapy with Bragg peak boost (SHARP)

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