Field size dependence of the output factor in passively scattered proton therapy: Influence of range, modulation, air gap, and machine settings

Daartz, Juliane; Engelsman, Martijn; Paganetti, Harald; Bussière, Marc R.

doi:10.1118/1.3152111

Cited by 34 publications

(52 citation statements)

References 13 publications

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“…Additional range margins would not improve tumor coverage for these sites. Underdosage in lung patients cannot be prevented by larger range margins either as has been shown elsewhere (27). …”

Section: Discussionmentioning

confidence: 72%

“…The most clinically significant differences between the calculation algorithms were seen in lung, where the largest differences in mean dose, D50, D95 and TCP were observed (figure 1). Apart from inaccurate modeling of MCS, the low density of lung tissue is an additional source of discrepancies in these cases due to inaccuracies in dose calculations based on water-equivalent path-lengths (27). …”

Section: Discussionmentioning

confidence: 99%

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Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

Schuemann

Giantsoudi

Grassberger

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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Purpose To assess the impact of approximations in current analytical dose calculation methods (ADCs) on tumor control probability (TCP) in proton therapy. Methods Dose distributions planned with ADC were compared to delivered dose distributions (as determined by Monte Carlo simulations). A total of 50 patients were investigated in this analysis with 10 patients per site for 5 treatment sites (head-and-neck, lung, breast, prostate, liver). Differences were evaluated using dosimetric indices based on a dose-volume-histogram analysis, a γ-index analysis and estimations of TCP. Results We find that ADC overestimates the target doses on average by 1–2% for all patients considered. The mean dose, D95, D50 and D02 (the dose value covering 95%, 50% and 2% of the target volume, respectively) are predicted within 5% of the delivered dose. The γ-index passing rate for target volumes was above 96% for a 3%/3mm criteria. Differences in TCP were up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head-and-neck and lung patients, respectively. Differences in normal tissue complication probabilities for bladder and anterior-rectum of prostate patients were less than 3%. Conclusion Our results indicate that current dose calculation algorithms lead to underdosage of the target by as much as 5%, resulting in differences in TCP of up to 11%. In order to ensure full target coverage, advanced dose-calculation methods like Monte Carlo simulations may be necessary in proton therapy. Monte Carlo simulations may also be required in order to avoid biases due to systematic discrepancies in calculated dose distributions for clinical trials comparing proton therapy to conventional radiotherapy.

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Section: Discussionmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

Schuemann

Giantsoudi

Grassberger

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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“…The opening area of the aperture is 10.5 cm 2 because this field is only treating a subset of the GTV. It has previously been found (Bueno et al 2013, Bednarz et al 2010) that the analytical algorithm does not model the doses for small fields correctly, even for very homogeneous patient geometries (Daartz et al 2009). For the field in figure 3, this results in an overestimation of the delivered dose and thus a systematically longer range predicted by XiO as compared to TOPAS.…”

Section: Resultsmentioning

confidence: 99%

Site-specific range uncertainties caused by dose calculation algorithms for proton therapy

et al. 2014

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The purpose of this study was to investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for 7 disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head & neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and Monte Carlo algorithms to obtain the average range differences (ARD) and root mean square deviation (RMSD) for each field for the distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation (ADD) of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing Monte Carlo dose calculations. We recommend range margins of 2.8% + 1.2 mm for liver and prostate treatments and 3.1% + 1.2 mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head & neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3% + 1.2 mm would be needed for breast, lung and head & neck treatments. We conclude that currently used generic range uncertainty margins in proton therapy should be redefined site specific and that complex geometries may require a field specific adjustment. Routine verifications of treatment plans using Monte Carlo simulations are recommended for patients with heterogeneous geometries.

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“…This effect is related to the well-known field-size-effect (14), which is exacerbated in low-density lung tissue. This is demonstrated by the liver fields also shown in Fig.…”

Section: Discussionmentioning

confidence: 99%

Quantification of Proton Dose Calculation Accuracy in the Lung

Grassberger

Daartz

Dowdell

et al. 2014

International Journal of Radiation Oncology*Biology*Physics

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Purpose Quantify the accuracy of a clinical proton treatment planning system (TPS) as well as Monte Carlo (MC) based dose calculation through measurements. Assess the clinical impact in a cohort of patients with tumors located in the lung. Methods A lung phantom and ion chamber array were used to measure the dose to a plane through a tumor embedded in lung and to determine the distal fall-off of the proton beam. Results were compared with TPS and MC calculations. Dose distributions in 19 patients (54 fields total) were simulated using MC and compared to the TPS algorithm. Results MC increases dose calculation accuracy in lung tissue compared to the TPS and reproduces dose measurements in the target to within ±2%. The average difference between measured and predicted dose in a plane through the center of the target is 5.6% for the TPS and 1.6% for MC. MC recalculations in patients show a mean dose to the clinical target volume on average 3.4% lower than the TPS, exceeding 5% for small fields. For large tumors MC also predicts consistently higher V5 and V10 to the normal lung, due to a wider lateral penumbra, which was also observed experimentally. Critical structures located distal to the target can show large deviations, though this effect is very patient-specific. Range measurements show that MC can reduce range uncertainty by a factor ~2: the average(maximum) difference to the measured range is 3.9mm(7.5mm) for MC and 7mm(17mm) for the TPS in lung tissue. Conclusion Integration of Monte Carlo dose calculation techniques into the clinic would improve treatment quality in proton therapy for lung cancer by avoiding systematic overestimation of target dose and underestimation of dose to normal lung. Additionally, the ability to confidently reduce range margins would benefit all patients through potentially lower toxicity.

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Field size dependence of the output factor in passively scattered proton therapy: Influence of range, modulation, air gap, and machine settings

Cited by 34 publications

References 13 publications

Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

Site-specific range uncertainties caused by dose calculation algorithms for proton therapy

Quantification of Proton Dose Calculation Accuracy in the Lung

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