Validation of the proton range accuracy and optimization of CT calibration curves utilizing range probing

Meijers, Artürs; Free, Jeffrey; Wagenaar, Daniel A.; Deffet, Sylvain; Knopf, A.; Langendijk, Johannes A.; Both, Stefan

doi:10.1088/1361-6560/ab66e1

Cited by 34 publications

(47 citation statements)

References 23 publications

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“…Lastly, optimizing patient positioning to minimize the dose perturbation can improve target coverage without increasing the setup uncertainty setting [34]. Future work on estimation of stopping power ratios using dual-energy CT can help reduce the range errors found in proton radiography and reduce the required range uncertainty setting [23,35]. Additionally, future work should be extended to photon therapy where both robust optimization and a probabilistic assessment of target coverage should be used to further improve treatment [36].…”

Section: Discussionmentioning

confidence: 99%

“…Range errors are systematic in nature and occur depending on tissue type. Common clinical practice is to account for a 2.4% + 1.0 mm range uncertainty error during treatment optimization [22,23]. This recipe was shown to be equal to two SDs in a recent study analyzing the residual range errors in proton radiography validation of our CT calibration curve [23].…”

Section: Error Distributionsmentioning

confidence: 98%

“…Common clinical practice is to account for a 2.4% + 1.0 mm range uncertainty error during treatment optimization [22,23]. This recipe was shown to be equal to two SDs in a recent study analyzing the residual range errors in proton radiography validation of our CT calibration curve [23]. The SD of 1.2% + 0.5 mm was converted to a patient-specific percentage by dividing the absolute component by the monitor unit weighted average range of the clinical treatment plan.…”

Section: Error Distributionsmentioning

confidence: 99%

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Head and neck IMPT probabilistic dose accumulation: Feasibility of a 2 mm setup uncertainty setting

Wagenaar

Kierkels

Schaaf

et al. 2021

Radiotherapy and Oncology

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Objective: To establish optimal robust optimization uncertainty settings for clinical head and neck cancer (HNC) patients undergoing 3D image-guided pencil beam scanning (PBS) proton therapy. Methods: We analyzed ten consecutive HNC patients treated with 70 and 54.25 Gy RBE to the primary and prophylactic clinical target volumes (CTV) respectively using intensity-modulated proton therapy (IMPT). Clinical plans were generated using robust optimization with 5 mm/3% setup/range uncertainties (RayStation v6.1). Additional plans were created for 4, 3, 2 and 1 mm setup and 3% range uncertainty and for 3 mm setup and 3%, 2% and 1% range uncertainty. Systematic and random error distributions were determined for setup and range uncertainties based on our quality assurance program. From these, 25 treatment scenarios were sampled for each plan, each consisting of a systematic setup and range error and daily random setup errors. Fraction doses were calculated on the weekly verification CT closest to the date of treatment as this was considered representative of the daily patient anatomy. Results: Plans with a 2 mm/3% setup/range uncertainty setting adequately covered the primary and prophylactic CTV (V 95 ! 99% in 98.8% and 90.8% of the treatment scenarios respectively). The average organat-risk dose decreased with 1.1 Gy RBE /mm setup uncertainty reduction and 0.5 Gy RBE /1% range uncertainty reduction. Normal tissue complication probabilities decreased by 2.0%/mm setup uncertainty reduction and by 0.9%/1% range uncertainty reduction. Conclusion: The results of this study indicate that margin reduction below 3 mm/3% is possible but requires a larger cohort to substantiate clinical introduction.

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Section: Discussionmentioning

confidence: 99%

Section: Error Distributionsmentioning

confidence: 98%

Section: Error Distributionsmentioning

confidence: 99%

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Head and neck IMPT probabilistic dose accumulation: Feasibility of a 2 mm setup uncertainty setting

Wagenaar

Kierkels

Schaaf

et al. 2021

Radiotherapy and Oncology

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“…In the workflow proposed by Meijers et al, the WEPL error is estimated by calculating the shift to be applied to the simulated IDD to minimize the quadratic error between the simulated and the measured IDDs 14 . This method is, however, not optimal because it does not use the fact that a measured IDD contains information on the WEPL not only at the spot position but also in its vicinity.…”

Section: Methodsmentioning

confidence: 99%

“…In the region of interest D which includes area A, B, and C, this value is 90% for a margin of 0.6 mm + 1.4% which means that the part of the initial margin of 0.6 mm + 2.4% which depends on dose computation was actually overestimated by 71% for 90% of the pixels, or equivalently could be decreased by 42%, which is similar to Meijers conclusions. 14 In the region A which does not have any cavity, the margin corresponding to a 90% confidence interval is 0.6 mm + 0.4%. This means that the part of the initial margin of 0.6 mm + 2.4% which depends on dose computation was overestimated by 500% for 90% of the pixels, or equivalently could be decreased by 83%.…”

Section: C Range Uncertainty Analysismentioning

confidence: 96%

openPR — A computational tool for CT conversion assessment with proton radiography

et al. 2020

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Purpose One of the main sources of uncertainty in proton therapy is the conversion of the Hounsfield Units of the planning CT to (relative) proton stopping powers. Proton radiography provides range error maps but these can be affected by other sources of errors as well as the CT conversion (e.g., residual misalignment). To better understand and quantify range uncertainty, it is desirable to measure the individual contributions and particularly those associated to the CT conversion. Methods A workflow is proposed to carry out an assessment of the CT conversion solely on the basis of proton radiographs of real tissues measured with a multilayer ionization chamber (MLIC). The workflow consists of a series of four stages: (a) CT and proton radiography acquisitions, (b) CT and proton radiography registration in postprocessing, (c) sample‐specific validation of the semi‐empirical model both used in the registration and to estimate the water equivalent path length (WEPL), and (d) WEPL error estimation. The workflow was applied to a pig head as part of the validation of the CT calibration of the proton therapy center PARTICLE at UZ Leuven, Belgium. Results The CT conversion‐related uncertainty computed based on the well‐established safety margin rule of 1.2 mm + 2.4% were overestimated by 71% on the pig head. However, the range uncertainty was very much underestimated where cavities were encountered by the protons. Excluding areas with cavities, the overestimation of the uncertainty was 500%. A correlation was found between these localized errors and HUs between −1000 and −950, suggesting that the underestimation was not a consequence of an inaccurate conversion but was probably rather due to the resolution of the CT leading to material mixing at interfaces. To reduce these errors, the CT calibration curve was adapted by increasing the HU interval corresponding to the air up to −950. Conclusion The application of the workflow as part of the validation of the CT conversion to RSPs showed an overall overestimation of the expected uncertainty. Moreover, the largest WEPL errors were found to be related to the presence of cavities which nevertheless are associated with low WEPL values. This suggests that the use of this workflow on patients or in a generalized study on different types of animal tissues could shed sufficient light on how the contributions to the CT conversion‐related uncertainty add up to potentially reduce up to several millimeters the uncertainty estimations taken into account in treatment planning. All the algorithms required to perform the workflow were implemented in the computational tool named openPR which is part of openREGGUI, an open‐source image processing platform for adaptive proton therapy.

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An evaluation of the use of DirectSPR images for proton planning in the RayStation treatment planning software

Sarkar

Paxton

et al. 2023

J Applied Clin Med Phys

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An important source of uncertainty in proton therapy treatment planning is the assignment of stopping-power ratio (SPR) from CT data. A commercial product is now available that creates an SPR map directly from dual-energy CT (DECT). This paper investigates the use of this new product in proton treatment planning and compares the results to the current method of assigning SPR based on a single-energy CT (SECT). Two tissue surrogate phantoms were CT scanned using both techniques. The SPRs derived from single-energy CT and by Direct-SPR™ were compared to measured values. SECT-based values agreed with measurements within 4% except for low density lung and high density bone, which differed by 13% and 8%, respectively. DirectSPR™ values were within 2% of measured values for all tissues studied. Both methods were also applied to scanned containers of three types of animal tissue, and the expected range of protons of two different energies was calculated in the treatment planning system and compared to the range measured using a multi-layer ion chamber. The average difference between range measurements and calculations based on SPR maps from dual-and single-energy CT, respectively, was 0.1 mm (0.07%) versus 2.2 mm (1.5%). Finally, a phantom was created using a layer of various tissue surrogate plugs on top of a 2D ion chamber array. Dose measurements on this array were compared to predictions using both single-and dual-energy CTs and SPR maps. While standard gamma pass rates for predictions based on DECT-derived SPR maps were slightly higher than those based on singleenergy CT, the differences were generally modest for this measurement setup. This study showed that SPR maps created by the commercial product from dual-energy CT can successfully be used in RayStation to generate proton dose distributions and that these predictions agree well with measurements.

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Validation of the proton range accuracy and optimization of CT calibration curves utilizing range probing

Abstract: Validation of the proton range accuracy and optimization of CT calibration curves utilizing range probing. Physics in Medicine and Biology, 65(3), [03NT02].

Cited by 34 publications

References 23 publications

Head and neck IMPT probabilistic dose accumulation: Feasibility of a 2 mm setup uncertainty setting

Head and neck IMPT probabilistic dose accumulation: Feasibility of a 2 mm setup uncertainty setting

openPR — A computational tool for CT conversion assessment with proton radiography

An evaluation of the use of DirectSPR images for proton planning in the RayStation treatment planning software

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