Defining robustness protocols: a method to include and evaluate robustness in clinical plans

Plan robustness analysis for threshold determination of SGRT-based intrafraction motion control in 3DCRT breast cancer radiation therapy

PURPOSE

The goal of this study was to obtain maximum allowed shift deviations from planning position in six degrees of freedom (DOF), that can serve as threshold values in surface guided radiation therapy (SGRT) of breast cancer patients.

METHODS

The robustness of conformal treatment plans of 50 breast cancer patients against 6DOF shifts was investigated. For that, new dose distributions were calculated on shifted computed tomography scans and evaluated with respect to target volume and spinal cord dose. Maximum allowed shift values were identified by imposing dose constraints on the target volume dose coverage for 1DOF, and consecutively, for 6DOF shifts using an iterative approach and random sampling.

RESULTS

Substantial decreases in target dose coverage and increases of spinal cord dose were observed. Treatment plans showed highly differing robustness for different DOFs or treated area. The sensitivity was particularly high if clavicular lymph nodes were irradiated, for shifts in lateral, vertical, roll or yaw direction, and showed partly pronounced asymmetries. Threshold values showed similar properties with an absolute value range of 0.8 mm to 5 mm and 1.4° to 5°.

CONCLUSION

The robustness analysis emphasized the necessity of taking differences between DOFs and asymmetrical sensitivities into account when evaluating the dosimetric impact of position deviations. It also highlighted the importance of rotational shifts, especially if clavicular lymph nodes were irradiated. A practical approach of determining 6DOF shift limits was introduced and a set of threshold values applicable for SGRT based patient motion control was identified.

Pre-treatment analysis of non-rigid variations can assist robust intensity-modulated proton therapy plan selection for head and neck patients

PURPOSE

To incorporate small non-rigid variations of head and neck patients into the robust evaluation of intensity-modulated proton therapy (IMPT) for the selection of robust treatment plans.

METHODS

A cohort of 20 nasopharynx cancer patients with weekly kilovoltage CT (kVCT) and 15 oropharynx cancer patients with weekly cone-beam CT (CBCT) were retrospectively included. Anatomical variations between week 0/week 1 of treatment were acquired using deformable image registration (DIR) for all 35 patients and then applied to the planning CT of four patients who have kVCT scanned each week to simulate potential small non-rigid variations (sNRVs). The robust evaluations were conducted on IMPT plans with: (1) different number of beam fields from 3-field to 5-field; (2) different beam angles. The robust evaluation before treatment, including the sNRVs and setup uncertainty, referred to as sNRV+R evaluation was compared with the conventional evaluation (without sNRVs) in terms of robustness consistency with the gold standard evaluation based on weekly CT.

RESULTS

Among four patients (490 scenarios), we observed a maximum difference in the sNRV+R evaluation to the nominal dose of: 9.37% dose degradation on D₉₅ of clinical target volumes (CTVs), increase in mean dose (D mean $_{\text{mean}}$ ) of parotid 11.87 Gy, increase in max dose (D max $_{\text{max}}$ ) of brainstem 20.82 Gy. In contrast, in conventional evaluation, we observed a maximum difference to the nominal dose of: 7.58% dose degradation on D₉₅ of the CTVs, increase in parotid D mean $_{\text{mean}}$ by 4.88 Gy, increase in brainstem D max $_{\text{max}}$ by 13.5 Gy. In the measurement of the robustness ranking consistency with the gold standard evaluation, the sNRV+R evaluation was better or equal to the conventional evaluation in 77% of cases, particularly, better on spinal cord, parotid glands, and low-risk CTV.

CONCLUSION

This study demonstrated the additional dose discrepancy that sNRVs can make. The inclusion of sNRVs can be beneficial to robust evaluation, providing information on clinical uncertainties additional to the conventional rigid isocenter shift.

Plan quality assessment in clinical practice: Results of the 2020 ESTRO survey on plan complexity and robustness

PURPOSE

Plan complexity and robustness are two essential aspects of treatment plan quality but there is a great variability in their management in clinical practice. This study reports the results of the 2020 ESTRO survey on plan complexity and robustness to identify needs and guide future discussions and consensus.

METHODS

A survey was distributed online to ESTRO members. Plan complexity was defined as the modulation of machine parameters and increased uncertainty in dose calculation and delivery. Robustness was defined as a dose distribution's sensitivity towards errors stemming from treatment uncertainties, patient setup, or anatomical changes.

RESULTS

A total of 126 radiotherapy centres from 33 countries participated, 95 of them (75%) from Europe and Central Asia. The majority controlled and evaluated plan complexity using monitor units (56 centres) and aperture shapes (38 centres). To control robustness, 98 (97% of question responses) photon and 5 (50%) proton centres used PTV margins for plan optimization while 75 (94%) and 5 (50%), respectively, used margins for plan evaluation. Seventeen (21%) photon and 8 (80%) proton centres used robust optimisation, while 10 (13%) and 8 (80%), respectively, used robust evaluation. Primary uncertainties considered were patient setup (photons and protons) and range calculation uncertainties (protons). Participants expressed the need for improved commercial tools to control and evaluate plan complexity and robustness.

CONCLUSION

Clinical implementation of methods to control and evaluate plan complexity and robustness is very heterogeneous. Better tools are needed to manage complexity and robustness in treatment planning systems. International guidelines may promote harmonization.

Efficient uncertainty quantification for Monte Carlo dose calculations using importance (re-)weighting

Objective. To present an efficient uncertainty quantification method for range and set-up errors in Monte Carlo (MC) dose calculations. Further, we show that uncertainty induced by interplay and other dynamic influences may be approximated using suitable error correlation models.Approach. We introduce an importance (re-)weighting method in MC history scoring to concurrently construct estimates for error scenarios, the expected dose and its variance from a single set of MC simulated particle histories. The approach relies on a multivariate Gaussian input and uncertainty model, which assigns probabilities to the initial phase space sample, enabling the use of different correlation models. Through modification of the phase space parameterization, accuracy can be traded between that of the uncertainty or the nominal dose estimate.Main results. The method was implemented using the MC code TOPAS and validated for proton intensity-modulated particle therapy (IMPT) with reference scenario estimates. We achieve accurate results for set-up uncertainties (γ_{2 mm/2%}≥ 99.01% (E[d]),γ_{2 mm/2%}≥ 98.04% (σ(d))) and expectedly lower but still sufficient agreement for range uncertainties, which are approximated with uncertainty over the energy distribution. Here pass rates of 99.39% (E[d])/ 93.70% (σ(d)) (range errors) and 99.86% (E[d])/ 96.64% (σ(d)) (range and set-up errors) can be achieved. Initial evaluations on a water phantom, a prostate and a liver case from the public CORT dataset show that the CPU time decreases by more than an order of magnitude.Significance. The high precision and conformity of IMPT comes at the cost of susceptibility to treatment uncertainties in particle range and patient set-up. Yet, dose uncertainty quantification and mitigation, which is usually based on sampled error scenarios, becomes challenging when computing the dose with computationally expensive but accurate MC simulations. As the results indicate, the proposed method could reduce computational effort while also facilitating the use of high-dimensional uncertainty models.

Proton Therapy for Intracranial Meningioma for the Treatment of Primary/Recurrent Disease Including Re-Irradiation

Meningeal tumors represent approximately 10-25% of primary brain tumors and occur usually in elderly female patients. Most meningiomas are benign (80-85%) and for symptomatic and/or large tumors, surgery, with or without radiation therapy (RT), has been long established as an effective means of local tumor control. RT can be delivered to inoperable lesions or to those with non-benign histology and for Simpson I-III and IV-V resection. RT can be delivered with photons or particles (protons or carbon ions) in stereotactic or non-stereotactic conditions. Particle therapy delivered for these tumors uses the physical properties of charged carbon ions or protons to spare normal brain tissue (i.e. Bragg peak), with or without or a dose-escalation paradigm for non-benign lesions. PT can substantially decrease the dose delivered to the non-target brain tissues, including but not limited to the hippocampi, optic apparatus or cochlea. Only a limited number of meningioma patients have been treated with PT in the adjuvant or recurrent setting, as well as for inoperable lesions with pencil beam scanning and with protons only. Approximately 500 patients with image-defined or WHO grade I meningioma have been treated with protons. The reported outcome, usually 5-year local tumor control, ranges from 85 to 99% (median, 96%). For WHO grade II or III patients, the outcome of only 97 patients has been published, reporting a median tumor local control rate of 52% (range, 38-71.1). Only 24 recurring patients treated previously with photon radiotherapy and re-treated with PT were reported. The clinical outcome of these challenging patients seems interesting, provided that they presented initially with benign tumors, are not in the elderly category and have been treated previously with conventional radiation dose of photons. Overall, the number of meningioma patients treated or-re-irradiated with this treatment modality is small and the clinical evidence level is somewhat low (i.e. 3b-5). In this review, we detail the results of upfront PT delivered to patients with meningioma in the adjuvant setting and for inoperable tumors. The outcome of meningioma patients treated with this radiation modality for recurrent tumors, with or without previous RT, will also be reviewed.

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans

Plan evaluation is a key step in the radiotherapy treatment workflow. Central to this step is the assessment of treatment plan quality. Hence, it is important to agree on what we mean by plan quality and to be fully aware of which parameters it depends on. We understand plan quality in radiotherapy as the clinical suitability of the delivered dose distribution that can be realistically expected from a treatment plan. Plan quality is commonly assessed by evaluating the dose distribution calculated by the treatment planning system (TPS). Evaluating the 3D dose distribution is not easy, however; it is hard to fully evaluate its spatial characteristics and we still lack the knowledge for personalising the prediction of the clinical outcome based on individual patient characteristics. This advocates for standardisation and systematic collection of clinical data and outcomes after radiotherapy. Additionally, the calculated dose distribution is not exactly the dose delivered to the patient due to uncertainties in the dose calculation and the treatment delivery, including variations in the patient set-up and anatomy. Consequently, plan quality also depends on the robustness and complexity of the treatment plan. We believe that future work and consensus on the best metrics for quality indices are required. Better tools are needed in TPSs for the evaluation of dose distributions, for the robust evaluation and optimisation of treatment plans, and for controlling and reporting plan complexity. Implementation of such tools and a better understanding of these concepts will facilitate the handling of these characteristics in clinical practice and be helpful to increase the overall quality of treatment plans in radiotherapy.

Analytical probabilistic modeling of dose-volume histograms

PURPOSE

Radiotherapy, especially with charged particles, is sensitive to executional and preparational uncertainties that propagate to uncertainty in dose and plan quality indicators, for example, dose-volume histograms (DVHs). Current approaches to quantify and mitigate such uncertainties rely on explicitly computed error scenarios and are thus subject to statistical uncertainty and limitations regarding the underlying uncertainty model. Here we present an alternative, analytical method to approximate moments, in particular expectation value and (co)variance, of the probability distribution of DVH-points, and evaluate its accuracy on patient data.

METHODS

We use Analytical Probabilistic Modeling (APM) to derive moments of the probability distribution over individual DVH-points based on the probability distribution over dose. By using the computed moments to parameterize distinct probability distributions over DVH-points (here normal or beta distributions), not only the moments but also percentiles, that is, α - DVHs, are computed. The model is subsequently evaluated on three patient cases (intracranial, paraspinal, prostate) in 30- and single-fraction scenarios by assuming the dose to follow a multivariate normal distribution, whose moments are computed in closed-form with APM. The results are compared to a benchmark based on discrete random sampling.

RESULTS

The evaluation of the new probabilistic model on the three patient cases against a sampling benchmark proves its correctness under perfect assumptions as well as good agreement in realistic conditions. More precisely, ca. 90% of all computed expected DVH-points and their standard deviations agree within 1% volume with their empirical counterpart from sampling computations, for both fractionated and single fraction treatments. When computing α - DVH, the assumption of a beta distribution achieved better agreement with empirical percentiles than the assumption of a normal distribution: While in both cases probabilities locally showed large deviations (up to ±0.2), the respective - DVHs for α={0.05,0.5,0.95} only showed small deviations in respective volume (up to ±5% volume for a normal distribution, and up to 2% for a beta distribution). A previously published model from literature, which was included for comparison, exhibited substantially larger deviations.

CONCLUSIONS

With APM we could derive a mathematically exact description of moments of probability distributions over DVH-points given a probability distribution over dose. The model generalizes previous attempts and performs well for both choices of probability distributions, that is, normal or beta distributions, over DVH-points.

Radiation dose-painting with protons vs. photons for head-and-neck cancer

Background: Dose-painting has recently been investigated in early-phase trials in head-and-neck cancer (HNC) with the aim of improving local tumor control. At the same time proton therapy has been reported as potentially capable of decreasing toxicity. Here, we investigate whether protons could be applied in a dose-painting setting by comparing proton dose distributions with delivered photon plans from a phase-I trial of FDG-PET based dose-painting at our institution.Material and methods: Eleven oropharynx (5), hypopharynx (2) and larynx cancer (4) patients from the recently conducted phase I trial were used for comparison of proton and photon dose-painting techniques. Robust optimization (3.5%/3 mm) was used for proton plans. Plan robustness and difference in dose metrics to targets and organs at risk were evaluated.Results: The proton plans met target dose constraints, while having lower non-target dose than photon plans (body-minus-CTV, mean dose 3.9 Gy vs 7.2 Gy, p = .004). Despite the use of robust proton planning for plan max dose, photon plan max doses were more robust (p = .006). Max dose to medulla, brainstem and mandible were lower in the proton plans, while there was no significant difference in mean dose to submandibular- and parotid glands.Conclusion: Proton dose-painting for HNC seems feasible and can reduce the non-target dose overall, however not significantly to certain organs close to the target, such as the salivary glands. Max dose in proton plans had a lower robustness compared to photons, requiring caution to avoid unintended hot spots in consideration of the risk of mucosal toxicity.

Assessment of robustness against setup uncertainties using probabilistic scenarios in lung cancer: a comparison of proton with photon therapy

OBJECTIVE

We compared the sensitivity of intensity modulated proton therapy (IMPT) and photon volumetric modulated arc therapy (VMAT) plans to setup uncertainties in locally advanced non-small cell lung cancer (NSCLC) using probabilistic scenarios.

METHODS

Minimax robust (MM) and planning target volume (PTV) optimised IMPT and VMAT nominal plans were created with physical dose of 70 Gy in 35 fractions in 10 representative patients. Using population data of setup errors, a fractionated treatment course was simulated, summed (Dsum) and compared to the nominal plan. Three treatment-course simulations were done for each plan. Target robustness criteria were: dose deviation of ≤5% to clinical target volume (CTV) D98% and CTV V95% ≥ 99.9%. Voxelwise simulation repeatability was analysed using Bland-Altman plots. Acceptable limits of agreement were 2% of the prescription dose.

RESULTS

All Dsum met target robustness criteria. While fraction VMAT and MM-IMPT doses were excellent, simulated fraction doses in PTV-IMPT were suboptimal. Almost all (>99%) of VMAT and MM-IMPT fraction doses met both target robustness criteria. For PTV-IMPT, only 96.9 and 80.3% of fractions met CTVD98% and V95% criteria respectively. Simulation repeatability was excellent (limits of agreement range: 0.41-1.1 Gy) with strong positive correlations.

CONCLUSION

When considering the whole treatment course, setup errors do not influence robustness irrespective of planning techniques used. However, on a fraction level, VMAT and MM-IMPT plans are superior compared to PTV-IMPT plans.

ADVANCES IN KNOWLEDGE

Probabilistic analysis provides a fast and practical method for evaluating VMAT and IMPT plan sensitivity against setup uncertainty. VMAT and robust-optimised IMPT plans have comparable sensitivity to setup uncertainties in conventionally fractionated treatment for NSCLC.

Inter-fraction robustness of intensity-modulated proton therapy in the post-operative treatment of oropharyngeal and oral cavity squamous cell carcinomas

OBJECTIVE

To evaluate dosimetric consequences of inter-fraction setup variation and anatomical changes in patients receiving multifield optimised (MFO) intensity modulated proton therapy for post-operative oropharyngeal (OPC) and oral cavity (OCC) cancers.

METHODS

Six patients receiving MFO for post-operative OPC and OCC were evaluated. Plans were robustly optimised to clinical target volumes (CTVs) using 3 mm setup and 3.5% range uncertainty. Weekly online cone beam CT (CBCT) were performed. Planning CT was deformed to the CBCT to create virtual CTs (vCTs) on which the planned dose was recalculated. vCT plan robustness was evaluated using a setup uncertainty of 1.5 mm and range uncertainty of 3.5%. Target coverage, D95%, and hotspots, D0.03cc, were evaluated for each uncertainty along with the vCT-calculated nominal plan. Mean dose to organs at risk (OARs) for the vCT-calculated nominal plan and relative % change in weight from baseline were evaluated.

RESULTS

Robustly optimised plans in post-operative OPC and OCC patients are robust against inter-fraction setup variations and range uncertainty. D0.03cc in the vCT-calculated nominal plans were clinically acceptable across all plans. Across all patients D95% in the vCT-calculated nominal treatment plan was at least 100% of the prescribed dose. No patients lost ≥10% weight from baseline. Mean dose to the OARs and max dose to the spinal cord remained within tolerance.

CONCLUSION

MFO plans in post-operative OPC and OCC patients are robust to inter-fraction uncertainties in setup and range when evaluated over multiple CT scans without compromising OAR mean dose.

ADVANCES IN KNOWLEDGE

This is the first paper to evaluate inter-fraction MFO plan robustness in post-operative head and neck treatment.

LOW DOSE BATH FROM IMPT VS. IMXT FOR THE PELVIC AREA WHEN TREATING ADVANCED PROSTATE CANCER

Twenty (10 intensity-modulated proton therapy (IMPT) and 10 intensity-modulated x-ray therapy (IMXT) treatment plans for patients with advanced prostate carcinoma were compared in this study. All chosen patients were indicated for prostate and pelvic lymph nodes irradiation using simultaneous integrated boost technique. These patients represent typical specimen for this diagnose. IMPT irradiates just half of the tissue volume with a low dose (up to 10 cobalt gray equivalent) compared to IMXT without compromise in target volumes coverage and in this way reduces the risk of secondary cancer development or other possible complications.

The impact of proton LET/RBE modeling and robustness analysis on base-of-skull and pediatric craniopharyngioma proton plans relative to VMAT

Purpose: Pediatric craniopharyngioma, adult base-of-skull sarcoma and chordoma cases are all regarded as priority candidates for proton therapy. In this study, a dosimetric comparison between volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) was first performed. We then investigated the impact of physical and biological uncertainties. We assessed whether IMPT plans remained dosimetrically superior when such uncertainty estimates were considered, especially with regards to sparing organs at risk (OARs).Methodology: We studied 10 cases: four chondrosarcoma, two chordoma and four pediatric craniopharyngioma. VMAT and IMPT plans were created according to modality-specific protocols. For IMPT, we considered (i) variable RBE modeling using the McNamara model for different values of (α/β)x, and (ii) robustness analysis with ±3 mm set-up and 3.5% range uncertainties.Results: When comparing the VMAT and IMPT plans, the dosimetric advantages of IMPT were clear: IMPT led to reduced integral dose and, typically, improved CTV coverage given our OAR constraints. When physical robustness analysis was performed for IMPT, some uncertainty scenarios worsened the CTV coverage but not usually beyond that achieved by VMAT. Certain scenarios caused OAR constraints to be exceeded, particularly for the brainstem and optical chiasm. However, variable RBE modeling predicted even more substantial hotspots, especially for low values of (α/β)x. Variable RBE modeling often prompted dose constraints to be exceeded for critical structures.Conclusion: For base-of-skull and pediatric craniopharyngioma cases, both physical and biological robustness analyses should be considered for IMPT: these analyses can substantially affect the sparing of OARs and comparisons against VMAT. All proton RBE modeling is subject to high levels of uncertainty, but the clinical community should remain cognizant possible RBE effects. Careful clinical and imaging follow-up, plus further research on end-of-range RBE mitigation strategies such as LET optimization, should be prioritized for these cohorts of proton patients.

Harmonization of proton treatment planning for head and neck cancer using pencil beam scanning: first report of the IPACS collaboration group

Background and purpose: A collaborative network between proton therapy (PT) centres in Trento in Italy, Poland, Austria, Czech Republic and Sweden (IPACS) was founded to implement trials and harmonize PT. This is the first report of IPACS with the aim to show the level of harmonization that can be achieved for proton therapy planning of head and neck (sino-nasal) cancer.Methods: CT-data sets of five patients were included. During several face-to-face and online meetings, a common treatment planning protocol was developed. Each centre used its own treatment planning system (TPS) and planning approach with some restrictions specified in the treatment planning protocol. In addition, volumetric modulated arc therapy (VMAT) photon plans were created.Results: For CTV1, the average D_median was 59.3 ± 2.4 Gy(RBE) for protons and 58.8 ± 2.0 Gy(RBE) for VMAT (aim was 56 Gy(RBE)). For CTV2, the average D_median was 71.2 ± 1.0 Gy(RBE) for protons and 70.6 ± 0.4 Gy(RBE) for VMAT (aim was 70 Gy(RBE)). The average D_2% for the spinal cord was 25.1 ± 8.5 Gy(RBE) for protons and 47.6 ± 1.4 Gy(RBE) for VMAT. The average D_2% for chiasm was 46.5 ± 4.4 Gy(RBE) for protons and 50.8 ± 1.4 Gy(RBE) for VMAT, respectively. Robust evaluation was performed and showed the least robust plans for plans with a low number of beams.Discussion: In conclusion, several influences on harmonization were identified: adherence/interpretation to/of the protocol, available technology, experience in treatment planning and use of different beam arrangements. In future, all OARs that should be included in the optimization need to be specified in order to further harmonize treatment planning.

Practical robustness evaluation in radiotherapy - A photon and proton-proof alternative to PTV-based plan evaluation

BACKGROUND AND PURPOSE

A planning target volume (PTV) in photon treatments aims to ensure that the clinical target volume (CTV) receives adequate dose despite treatment uncertainties. The underlying static dose cloud approximation (the assumption that the dose distribution is invariant to errors) is problematic in intensity modulated proton treatments where range errors should be taken into account as well. The purpose of this work is to introduce a robustness evaluation method that is applicable to photon and proton treatments and is consistent with (historic) PTV-based treatment plan evaluations.

MATERIALS AND METHODS

The limitation of the static dose cloud approximation was solved in a multi-scenario simulation by explicitly calculating doses for various treatment scenarios that describe possible errors in the treatment course. Setup errors were the same as the CTV-PTV margin and the underlying theory of 3D probability density distributions was extended to 4D to include range errors, maintaining a 90% confidence level. Scenario dose distributions were reduced to voxel-wise minimum and maximum dose distributions; the first to evaluate CTV coverage and the second for hot spots. Acceptance criteria for CTV D98 and D2 were calibrated against PTV-based criteria from historic photon treatment plans.

RESULTS

CTV D98 in worst case scenario dose and voxel-wise minimum dose showed a very strong correlation with scenario average D98 (R² > 0.99). The voxel-wise minimum dose visualised CTV dose conformity and coverage in 3D in agreement with PTV-based evaluation in photon therapy. Criteria for CTV D98 and D2 of the voxel-wise minimum and maximum dose showed very strong correlations to PTV D98 and D2 (R² > 0.99) and on average needed corrections of -0.9% and +2.3%, respectively.

CONCLUSIONS

A practical approach to robustness evaluation was provided and clinically implemented for PTV-less photon and proton treatment planning, consistent with PTV evaluations but without its static dose cloud approximation.

Robustness Analysis for External Beam Radiation Therapy Treatment Plans: Describing Uncertainty Scenarios and Reporting Their Dosimetric Consequences

PURPOSE

With external beam radiation therapy, uncertainties in treatment planning and delivery can result in an undesirable dose distribution delivered to the patient that can compromise the benefit of treatment. Techniques including geometric margins and probabilistic optimization have been used effectively to mitigate the effects of uncertainties. However, their broad application is inconsistent and can compromise the conclusions derived from cross-technique and cross-modality comparisons.

METHODS AND MATERIALS

Conventional methods to deal with treatment planning and delivery uncertainties are described, and robustness analysis is presented as a framework that is applicable across treatment techniques and modalities.

RESULTS

This report identifies elements that are imperative to include when conducting a robustness analysis and describing uncertainties and their dosimetric effects.

CONCLUSION

The robustness analysis approach described here is presented to promote reliable plan evaluation and dose reporting, particularly during clinical trials conducted across institutions and treatment modalities.

Proton therapy for brain tumours in the area of evidence-based medicine

ADVANCES IN KNOWLEDGE

This review details the indication of brain tumors for proton therapy and give a list of the open prospective trials for these challenging tumors.

Impact of treatment planning using a structure block function on the target and organ doses related to patient movement in cervical esophageal cancer: A phantom study

Helical tomotherapy (HT) can restrict beamlets passing through the virtual contour on computed tomography (CT) image in dose optimization, reducing the dose to organs at risk (OARs). Beamlet restriction limits the incident beamlet angles; thus, the proper planning target volume (PTV) margin may differ from that of the standard treatment plan without beamlet restriction, depending on the patient's movement during dose delivery. Dose distribution changes resulting from patient movement have not been described for treatment plans with beamlet restriction. This study quantified changes in dose distribution to the target and OARs when beamlet restriction is applied to cervical esophageal cancer treatment plan using HT by systematically shifting a phantom. Treatment plans for cervical esophageal cancers with and without beamlet restriction modes [directional block (DB) and nonblock (NB), respectively] were designed for CT images of the RANDO phantom. The PTV margin for the DB mode was set to be the same as that for the NB mode (5 mm). The CT image was intentionally shifted by ±1, ±2, and ±3 voxels in the left–right, anterior–posterior, and superior–inferior directions, and the dose distribution was recalculated for each position using the fluence for the NB or DB mode. When the phantom shift was within the same PTV margin as the NB mode, changes in doses to the targets, lungs, heart, and spinal cord in the DB mode were small as those in the NB mode. In conclusion, the virtual contour shape used in this study would provide safe delivery even with patient movement within the same PTV margin as for the NB mode.

Robust optimization to reduce the impact of biological effect variation from physical uncertainties in intensity-modulated proton therapy

Robust optimization (RO) methods are applied to intensity-modulated proton therapy (IMPT) treatment plans to ensure their robustness in the face of treatment delivery uncertainties, such as proton range and patient setup errors. However, the impact of those uncertainties on the biological effect of protons has not been specifically considered. In this study, we added biological effect-based objectives into a conventional RO cost function for IMPT optimization to minimize the variation in biological effect. One brain tumor case, one prostate tumor case and one head & neck tumor case were selected for this study. Three plans were generated for each case using three different optimization approaches: planning target volume (PTV)-based optimization, conventional RO, and RO incorporating biological effect (BioRO). In BioRO, the variation in biological effect caused by IMPT delivery uncertainties was minimized for voxels in both target volumes and critical structures, in addition to a conventional voxel-based worst-case RO objective function. The biological effect was approximated by the product of dose-averaged linear energy transfer (LET) and physical dose. All plans were normalized to give the same target dose coverage, assuming a constant relative biological effectiveness (RBE) of 1.1. Dose, biological effect, and their uncertainties were evaluated and compared among the three optimization approaches for each patient case. Compared with PTV-based plans, RO plans achieved more robust target dose coverage and reduced biological effect hot spots in critical structures near the target. Moreover, with their sustained robust dose distributions, BioRO plans not only reduced variations in biological effect in target and normal tissues but also further reduced biological effect hot spots in critical structures compared with RO plans. Our findings indicate that IMPT could benefit from the use of conventional RO, which would reduce the biological effect in normal tissues and produce more robust dose distributions than those of PTV-based optimization. More importantly, this study provides a proof of concept that incorporating biological effect uncertainty gap into conventional RO would not only control the IMPT plan robustness in terms of physical dose and biological effect but also achieve further reduction of biological effect in normal tissues.

A novel and individualized robust optimization method using normalized dose interval volume constraints (NDIVC) for intensity-modulated proton radiotherapy

PURPOSE

Intensity-modulated proton therapy (IMPT) is known to be sensitive to patient setup and range uncertainty issues. Multiple robust optimization methods have been developed to mitigate the impact of these uncertainties. Here, we propose a new robust optimization method, which provides an alternative way of robust optimization in IMPT, and is clinically practical, which will enable users to control the balance between nominal plan quality and plan robustness in a user-defined fashion.

METHOD

We calculated nine individual dose distributions which corresponded to one nominal and eight extreme scenarios caused by patient setup and proton beam's range uncertainties. For each voxel, the normalized dose interval (NDI) is defined as the full dose range variation divided by the maximum dose in all uncertainty scenarios (NDI = [max - min dose]/max dose), which was then used to calculate the normalized dose interval volume histogram (NDIVH) curves. The areas under the NDIVH curves were used to quantify plan robustness. A normalized dose interval volume constraint (NDIVC) applied to the target was incorporated to specify the desired robustness which was user-defined. Users could then explore the trade-off between nominal plan quality and plan robustness by adjusting the position of the NDIVCs on the NDIVH curves freely. We benchmarked our method using one lung, five head and neck (H&N), and three prostate cases by comparing our results to those derived using the voxel-wise worst-case robust optimization.

RESULTS

Using the benchmark cases, our new method achieved quality IMPT plans comparable to those derived from the voxel-wise worst-case robust optimization for both nominal plan quality and plan robustness in general; even more conformal and more homogeneous target dose distributions in some cases, if proper NDIVCs were applied. The AUC under NDIVH, as a precise quantitative index of plan robustness, was consistent with DVH bandwidths. Additionally, we demonstrated the feasibility of adjusting the position of NDIVCs in the NDIVH curves which allowed users to explore the trade-off between nominal plan quality and plan robustness.

CONCLUSIONS

The NDIVH-based robust optimization method provided a novel and individualized way of robust optimization in IMPT, and enables users to adjust the balance between nominal plan quality and plan robustness in a user-defined fashion. This method is applicable for continued improvement and developing the next generation of IMPT planning algorithms in the future.

Proton therapy for low-grade gliomas in adults: A systematic review

For adult patients with diffuse low-grade glioma (LGG) proton therapy is an emerging radiotherapy modality. The number of proton facilities is rapidly increasing. However, there is a shortage of published data concerning the clinical effectiveness compared to photon radiotherapy and potential proton-specific toxicity. This study aimed to systematically review and summarize the relevant literature on proton therapy for adult LGG patients, including dosimetric comparisons, the type and frequency of acute and long-term toxicity and the clinical effectiveness. A systematic search was performed in several medical databases and 601 articles were screened for relevance. Nine articles were deemed eligible for in-depth analysis using a standardized data collection form by two independent researchers. Proton treatment plans compared favorably to photon-plans regarding dose to uninvolved neural tissue. Fatigue (27-100%), alopecia (37-85%), local erythema (78-85%) and headache (27-75%) were among the most common acute toxicities. One study reported no significant long-term cognitive impairments. Limited data was available on long-term survival. One study reported a 5-year overall survival of 84% and 5-year progression-free survival of 40%. We conclude that published data from clinical studies using proton therapy for adults with LGG are scarce. As the technique becomes more available, controlled clinical studies are urgently warranted to determine if the potential benefits based on comparative treatment planning translate into clinical benefits.

An evaluation method of clinical impact with setup, range, and radiosensitivity uncertainties in fractionated carbon-ion therapy

In light ion therapy, the dose concentration is highly sensitive to setup and range errors. Here we propose a method for evaluating the effects of these errors by using the correlation between fractions on tumour control probability (TCP) in carbon-ion therapy. This method incorporates the concept of equivalent stochastic dose (Cranmer-Sargison and Zavgorodni 2005 Phys. Med. Biol. 50 4097-109), which was defined as a dose that gives the mean expected survival fraction (SF) for the stochastically variable dose. The mean expected SFs were calculated while considering the correlation between fractions for setup and range errors. By using this SF, equivalent stochastic clinical doses (ESCD), which are weighted by relative biological effectiveness, of lung and prostate cases with varying errors were derived. To account for spatial dose heterogeneity, equivalent uniform stochastic clinical doses (EUSCD) were obtained by using the mean expected SF in the volume of interest. TCP curves were calculated for each assumed error considering inter-patient sensitivity variation with a fractionation effect. ESCD distributions, EUSCD, and TCP curves were affected by the inter-fraction correlation and the contribution of setup and range errors. Irradiated areas that could be affected by these errors can be visualized quantitatively by using the ESCD distribution. TCP curves for the errors of various conditions converged around the TCP curve in nominal conditions by using the EUSCD. EUSCD correlated well with TCP in setup and range errors when the errors were not large and was comparatively stably insensitive to uncertain biological parameters. The proposed evaluation method with EUSCD and TCP calculations will be useful to indicate tumour doses to improve realistic dose distributions in carbon-ion therapy.

Robust optimization in lung treatment plans accounting for geometric uncertainty

Robust optimization generates scenario‐based plans by a minimax optimization method to find optimal scenario for the trade‐off between target coverage robustness and organ‐at‐risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D₉₉, D₉₈, and D₉₅ were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume‐based robust optimization plans (ITV‐IMRT and ITV‐VMAT) and conventional PTV margin‐based plans (PTV‐IMRT and PTV‐VMAT). The dosimetric comparison parameters were: ITV target mean dose (D_mean), R₉₅(D₉₅/D_prescription), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D_mean, V_{20 Gy} and V_{15 Gy}), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin‐based plans. Plan robustness evaluation showed that the perturbed doses of D₉₉, D₉₈, and D₉₅ were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin‐based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study.

A method for acquiring random range uncertainty probability distributions in proton therapy

In treatment planning we depend upon accurate knowledge of geometric and range uncertainties. If the uncertainty model is inaccurate then the plan will produce under-dosing of the target and/or overdosing of OAR. We aim to provide a method for which centre and site-specific population range uncertainty due to inter-fraction motion can be quantified to improve the uncertainty model in proton treatment planning. Daily volumetric MVCT data from previously treated radiotherapy patients has been used to investigate inter-fraction changes to water equivalent path-length (WEPL). Daily image-guidance scans were carried out for each patient and corrected for changes in CTV position (using rigid transformations). An effective depth algorithm was used to determine residual range changes, after corrections had been applied, throughout the treatment by comparing WEPL within the CTV at each fraction for several beam angles. As a proof of principle this method was used to quantify uncertainties for inter-fraction range changes for a sample of head and neck patients of [Formula: see text] mm, [Formula: see text] mm and overall [Formula: see text] mm. For prostate [Formula: see text] mm, [Formula: see text] mm and overall [Formula: see text] mm. The choice of beam angle for head and neck did not affect the inter-fraction range error significantly; however this was not the same for prostate. Greater range changes were seen using a lateral beam compared to an anterior beam for prostate due to relative motion of the prostate and femoral heads. A method has been developed to quantify population range changes due to inter-fraction motion that can be adapted for the clinic. The results of this work highlight the importance of robust planning and analysis in proton therapy. Such information could be used in robust optimisation algorithms or treatment plan robustness analysis. Such knowledge will aid in establishing beam start conditions at planning and for establishing adaptive planning protocols.

Potential proton and photon dose degradation in advanced head and neck cancer patients by intratherapy changes

Purpose

Evaluation of dose degradation by anatomic changes for head‐and‐neck cancer (HNC) intensity‐modulated proton therapy (IMPT) relative to intensity‐modulated photon therapy (IMRT) and identification of potential indicators for IMPT treatment plan adaptation.

Methods

For 31 advanced HNC datasets, IMPT and IMRT plans were recalculated on a computed tomography scan (CT) taken after about 4 weeks of therapy. Dose parameter changes were determined for the organs at risk (OARs) spinal cord, brain stem, parotid glands, brachial plexus, and mandible, for the clinical target volume (CTV) and the healthy tissue outside planning target volume (PTV). Correlation of dose degradation with target volume changes and quality of rigid CT matching was investigated.

Results

Recalculated IMPT dose distributions showed stronger degradation than the IMRT doses. OAR analysis revealed significant changes in parotid median dose (IMPT) and near maximum dose (D_1ml) of spinal cord (IMPT, IMRT) and mandible (IMPT). OAR dose parameters remained lower in IMPT cases. CTV coverage (V_95%) and overdose (V_107%) deteriorated for IMPT plans to (93.4 ± 5.4)% and (10.6 ± 12.5)%, while those for IMRT plans remained acceptable. Recalculated plans showed similarly decreased PTV conformity, but considerable hotspots, also outside the PTV, emerged in IMPT cases. Lower CT matching quality was significantly correlated with loss of PTV conformity (IMPT, IMRT), CTV homogeneity and coverage (IMPT). Target shrinkage correlated with increased dose in brachial plexus (IMRT, IMPT), hotspot generation outside the PTV (IMPT) and lower PTV conformity (IMRT).

Conclusions

The study underlines the necessity of precise positioning and monitoring of anatomy changes, especially in IMPT which might require adaptation more often. Since OAR doses remained typically below constraints, IMPT plan adaptation will be indicated by target dose degradations.

Quantification of the uncertainties of a biological model and their impact on variable RBE proton treatment plan optimization

PURPOSE

In proton radiation therapy, a relative biological effectiveness (RBE) equal to 1.1 is currently assumed, although biological experiments show that it is not constant. The purpose of this study was to quantify the uncertainties of a published biological model and explore their impact on variable RBE treatment plan (TP) optimization.

METHODS

Two patient cases with a high and a low (α/β)_x tumor were investigated. Firstly, intensity modulated proton therapy TPs assuming constant RBE were derived, and subsequently the variable RBE weighted dose (RWD), including the uncertainty originating in the fit to the experimental data and the uncertainty of the (α/β)_x, were calculated. Secondly, TPs optimized for uniform biological effect assuming a variable RBE were created using the worst case tissue specific (α/β)_x.

RESULTS

For the nasopharyngeal cancer patient, the uncertainty of (α/β)_x corresponded to a CTV D₉₈ confidence interval (CI) of (-2, +4)% while for the fit parameter CI was (-2,+1)%. For the standard fractionation prostate case the (α/β)_x CI was (-7,+5)% and the fit parameter CI was (-3,+3)%. For the hypofractionated case both CIs were (-1,+1)%. In both patient cases, the RBE in most organs at risk (OARs) was significantly underestimated by the constant RBE approximation, whereas the situation was not as definite in the target volumes. Overdosage of OARs was reduced by using the biological effect optimization.

CONCLUSION

For the two patient cases, the RWD uncertainty from the fit parameter in the biological model contributed non-negligibly to the total uncertainty, depending on the patient case and the organ. The presented optimization strategy is a basic method for robust biological effect optimization to reduce potential consequences caused by the (α/β)_x uncertainty.

Fast and accurate sensitivity analysis of IMPT treatment plans using Polynomial Chaos Expansion

The highly conformal planned dose distribution achievable in intensity modulated proton therapy (IMPT) can severely be compromised by uncertainties in patient setup and proton range. While several robust optimization approaches have been presented to address this issue, appropriate methods to accurately estimate the robustness of treatment plans are still lacking. To fill this gap we present Polynomial Chaos Expansion (PCE) techniques which are easily applicable and create a meta-model of the dose engine by approximating the dose in every voxel with multidimensional polynomials. This Polynomial Chaos (PC) model can be built in an automated fashion relatively cheaply and subsequently it can be used to perform comprehensive robustness analysis. We adapted PC to provide among others the expected dose, the dose variance, accurate probability distribution of dose-volume histogram (DVH) metrics (e.g. minimum tumor or maximum organ dose), exact bandwidths of DVHs, and to separate the effects of random and systematic errors. We present the outcome of our verification experiments based on 6 head-and-neck (HN) patients, and exemplify the usefulness of PCE by comparing a robust and a non-robust treatment plan for a selected HN case. The results suggest that PCE is highly valuable for both research and clinical applications.