Breathing interplay effects during proton beam scanning: simulation and statistical analysis

Seco, Joao; Robertson, Daniel; Trofimov, Alexei V.; Paganetti, Harald

doi:10.1088/0031-9155/54/14/n01

Cited by 156 publications

(212 citation statements)

References 14 publications

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“…This assumption could lead to the possibility of systematic error, as shown by Evans et al 12 Furthermore, since in practice there is no practical way to determine f ( x) for an individual patient, the "weighted average of the dose distribution without motion" is often further approximated by the dose distribution without motion or the 3D static dose. 13 With the availability of 4D respiration-correlated computer tomography (CT) and deformable registration, 4D accumulated dose (4D dose) distribution calculation can be performed with the tumor motion being correlated with time (f ( x, t)) or phase (f ( x, n)). Studies have shown that the 4D dose can differ significantly from the 3D static dose, calculated on any single-phase or average CT, for both photon 14,15 and scanning beam proton 16,17 radiotherapy.…”

Section: Introductionmentioning

confidence: 99%

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Zhang

et al. 2012

Medical Physics

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Purpose: The purpose of this work was to investigate the relationship between dynamically accumulated dose (dynamic dose) and 4D accumulated dose (4D dose) for irradiation of moving tumors, and to quantify the dose uncertainty induced by tumor motion. Methods: The authors established that regardless of treatment modality and delivery properties, the dynamic dose will converge to the 4D dose, instead of the 3D static dose, after multiple deliveries. The bounds of dynamic dose, or the maximum estimation error using 4D or static dose, were established for the 4D and static doses, respectively. Numerical simulations were performed (1) to prove the principle that for each phase, after multiple deliveries, the average number of deliveries for any given time converges to the total number of fractions (K) over the number of phases (N); (2) to investigate the dose difference between the 4D and dynamic doses as a function of the number of deliveries for deliveries of a "pulsed beam"; and (3) to investigate the dose difference between 4D dose and dynamic doses as a function of delivery time for deliveries of a "continuous beam." A Poisson model was developed to estimate the mean dose error as a function of number of deliveries or delivered time for both pulsed beam and continuous beam. Results:The numerical simulations confirmed that the number of deliveries for each phase converges to K/N, assuming a random starting phase. Simulations for the pulsed beam and continuous beam also suggested that the dose error is a strong function of the number of deliveries and/or total deliver time and could be a function of the breathing cycle, depending on the mode of delivery. The Poisson model agrees well with the simulation. Conclusions: Dynamically accumulated dose will converge to the 4D accumulated dose after multiple deliveries, regardless of treatment modality. Bounds of the dynamic dose could be determined using quantities derived from 4D doses, and the mean dose difference between the dynamic dose and 4D dose as a function of number of deliveries and/or total deliver time was also established.

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Section: Introductionmentioning

confidence: 99%

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Zhang

et al. 2012

Medical Physics

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“…scanning repetitively within one fraction [8]. A number of repainting schemes have been investigated previously [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Proton pencil beam scanning for mediastinal lymphoma: treatment planning and robustness assessment

et al. 2016

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Background: Modern radiotherapy (RT) for lymphoma is highly personalized. While advanced imaging is largely employed to define limited treatment volumes, the use of proton pencil beam scanning (PBS) for highly conformal lymphoma RT is still in its infancy. Here, we assess the dosimetric benefits and feasibility of PBS for mediastinal lymphoma (ML). Materials and methods: Ten patients were planned using PBS for involved-site RT. The initial plans were calculated on the average four-dimensional computed tomography (4D-CT). PBS plans were compared with 3D conformal radiotherapy (3D-CRT), intensity-modulated radiotherapy (IMRT), and proton double scattering (DS). In order to evaluate the feasibility of PBS and the plan robustness against interand intra-fractional uncertainties, the 4D dose was calculated on initial and verification CTs. The deviation of planned dose from delivered dose was measured. The same proton beamline was used for all patients, while another beamline with larger spots was employed for patients with large motion perpendicular to the beam. Results: PBS provided the lowest mean lung dose (MLD) and mean heart dose (MHD) for all patients in comparison with 3D-CRT, IMRT, and DS. For eight patients, internal target volume (ITV) D 98% was degraded by <3%; and the MLD and MHD deviated by <10% of prescription over the course of treatment when the PBS field was painted twice in each session. For one patient with target motion perpendicular to the beam (>5 mm), the degradation of ITV D 98% was 9%, which was effectively mitigated by employing large spots. One patient exhibited large dose degradation due to pericardial effusion, which required replanning across all modalities. Conclusions: This study demonstrates that PBS plans significantly reduce MLD and MHD relative to 3D-CRT, IMRT, and DS and identifies requirements for robust free-breathing ML PBS treatments, showing that PBS plan robustness can be maintained with repainting and/or large spots.

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“…This effect is the same for both scattering and scanning delivery techniques. In addition, for active scanning, the major effect of intrafield motion is ''interplay'', which relates to motion, usually respiratory motion, with a frequency similar to that of the scanned beam, and which can lead to overand underdosage in the target volume [34][35][36][37].…”

Section: Motionmentioning

confidence: 99%

“…The problem of organ motion and rescanning synchronism has also been tackled by several groups, including Furukawa et al [45] and Seco et al [37]. Solutions include: N using random modulations, e.g.…”

Section: Rescanningmentioning

confidence: 99%

Treatment planning optimisation in proton therapy

McGowan¹,

Burnet²,

Lomax³

2013

BJR

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ABSTRACT. The goal of radiotherapy is to achieve uniform target coverage while sparing normal tissue. In proton therapy, the same sources of geometric uncertainty are present as in conventional radiotherapy. However, an important and fundamental difference in proton therapy is that protons have a finite range, highly dependent on the electron density of the material they are traversing, resulting in a steep dose gradient at the distal edge of the Bragg peak. Therefore, an accurate knowledge of the sources and magnitudes of the uncertainties affecting the proton range is essential for producing plans which are robust to these uncertainties. This review describes the current knowledge of the geometric uncertainties and discusses their impact on proton dose plans. The need for patient-specific validation is essential and in cases of complex intensity-modulated proton therapy plans the use of a planning target volume (PTV) may fail to ensure coverage of the target. In cases where a PTV cannot be used, other methods of quantifying plan quality have been investigated. A promising option is to incorporate uncertainties directly into the optimisation algorithm. A further development is the inclusion of robustness into a multicriteria optimisation framework, allowing a multi-objective Pareto optimisation function to balance robustness and conformity. The question remains as to whether adaptive therapy can become an integral part of a proton therapy, to allow re-optimisation during the course of a patient's treatment. The challenge of ensuring that plans are robust to range uncertainties in proton therapy remains, although these methods can provide practical solutions. The ability to create and deliver the ideal treatment plan, where the target volume receives 100% of the prescribed dose and normal tissue receives 0%, is the holy grail of radiation therapy [1]. It is, however, impossible to achieve this perfect balance. Instead, multiple trade-offs are required to achieve a clinically acceptable plan, so the problem becomes one of optimisation. There are many factors that can affect how ''optimised'' a patient's treatment can be. This review focuses on the challenges of proton therapy plan optimisation, particularly in regard to range uncertainties, and how to incorporate them into the plan evaluation and verification process.The nature of proton therapy makes the aim of cure without complications potentially more achievable, owing to the highly localised deposition of dose in the characteristic Bragg peak [2]. This relates predominantly to the ability to deliver high doses of radiation close to normal tissue structures, which would be dose limiting in conventional X-ray treatments, and to the finite range of protons, which results in a reduced integral dose to surrounding normal tissues.From a clinical perspective, the exact role of proton therapy has yet to be defined. However, for childhood cancers, proton therapy delivers a lower dose to tissues around the tumour than X-rays, resulting in less growth disturbance and l...

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Breathing interplay effects during proton beam scanning: simulation and statistical analysis

Cited by 156 publications

References 14 publications

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Dynamically accumulated dose and 4D accumulated dose for moving tumors

Proton pencil beam scanning for mediastinal lymphoma: treatment planning and robustness assessment

Treatment planning optimisation in proton therapy

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