Objective. In head-and-neck cancer intensity modulated proton therapy, adaptive radiotherapy is currently restricted to offline re-planning, mitigating the effect of slow changes in patient anatomies. Daily online adaptations can potentially improve dosimetry. Here, a new, fully automated online re-optimization strategy is presented. In a retrospective study, this online re-optimization approach was compared to our trigger-based offline re-planning (offline _TB re-planning) schedule, including extensive robustness analyses. Approach. The online re-optimization method employs automated multi-criterial re-optimization, using robust optimization with 1 mm setup-robustness settings (in contrast to 3 mm for offline _TB re-planning). Hard planning constraints and spot addition are used to enforce adequate target coverage, avoid prohibitively large maximum doses and minimize organ-at-risk doses. For 67 repeat-CTs from 15 patients, fraction doses of the two strategies were compared for the CTVs and organs-at-risk. Per repeat-CT, 10.000 fractions with different setup and range robustness settings were simulated using polynomial chaos expansion for fast and accurate dose calculations. Main results. For 14/67 repeat-CTs, offline _TB re-planning resulted in <50% probability of D _98% ≥ 95% of the prescribed dose (D _pres) in one or both CTVs, which never happened with online re-optimization. With offline _TB re-planning, eight repeat-CTs had zero probability of obtaining D _98% ≥ 95%D _pres for CTV ₇₀₀₀, while the minimum probability with online re-optimization was 81%. Risks of xerostomia and dysphagia grade ≥ II were reduced by 3.5 ± 1.7 and 3.9 ± 2.8 percentage point [mean ± SD] (p < 10 ⁻⁵ for both). In online re-optimization, adjustment of spot configuration followed by spot-intensity re-optimization took 3.4 min on average. Significance. The fast online re-optimization strategy always prevented substantial losses of target coverage caused by day-to-day anatomical variations, as opposed to the clinical trigger-based offline re-planning schedule. On top of this, online re-optimization could be performed with smaller setup robustness settings, contributing to improved organs-at-risk sparing.

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Background: The steep radiation dose gradients in cervical cancer brachytherapy (BT) necessitate a thorough understanding of the behavior of afterloader source cables or needles in the curved channels of (patient-tailored) applicators. Purpose: The purpose of this study is to develop and validate computer models to simulate: (1) BT source positions, and (2) insertion forces of needles in curved applicator channels. The methodology presented can be used to improve the knowledge of instrument behavior in current applicators and aid the development of novel (3D-printed) BT applicators. Methods: For the computer models, BT instruments were discretized in finite elements. Simulations were performed in SPACAR by formulating nodal contact force and motion input models and specifying the instruments’ kinematic and dynamic properties. To evaluate the source cable model, simulated source paths in ring applicators were compared with manufacturer-measured source paths. The impact of discrepancies on the dosimetry was estimated for standard plans. To validate needle models, simulated needle insertion forces in curved channels with varying curvature, torsion, and clearance, were compared with force measurements in dedicated 3D-printed templates. Results: Comparison of simulated with manufacturer-measured source positions showed 0.5–1.2 mm median and <2.0 mm maximum differences, in all but one applicator geometry. The resulting maximum relative dose differences at the lateral surface and at 5 mm depth were 5.5% and 4.7%, respectively. Simulated insertion forces for BT needles in curved channels accurately resembled the forces experimentally obtained by including experimental uncertainties in the simulation. Conclusion: The models developed can accurately predict source positions and insertion forces in BT applicators. Insights from these models can aid novel applicator design with improved motion and force transmission of BT instruments, and contribute to the estimation of overall treatment precision. The methodology presented can be extended to study other applicator geometries, flexible instruments, and afterloading systems.

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BACKGROUND AND PURPOSE: Although MRI-based image guided adaptive brachytherapy (IGABT) for locally advanced cervical cancer (LACC) has resulted in favorable outcomes, it can be logistically complex and time consuming compared to 2D image-based brachytherapy, and both physically and emotionally intensive for patients. This prospective study aims to perform time-action and patient experience analyses during IGABT to guide further improvements. MATERIALS AND METHODS: LACC patients treated with IGABT were included for the time-action (56 patients) and patient experience (29 patients) analyses. Times per treatment step were reported on a standardized form. For the patient experience analysis, a baseline health status was established with the EQ-5D-5L questionnaire and the perceived pain, anxiety and duration for each treatment step were assessed with the NRS-11. RESULTS: The median total procedure time from arrival until discharge was 530 (IQR: 480–565) minutes. Treatment planning (delineation, reconstruction, optimization) required the most time and took 175 (IQR: 145–195) minutes. Highest perceived pain was reported during applicator removal and treatment planning, anxiety during applicator removal, and duration during image acquisition and treatment planning. Perceived pain, anxiety and duration were correlated. Higher pre-treatment pain and anxiety scores were associated with higher perceived pain, anxiety and duration. CONCLUSION: This study highlights the complexity, duration and impact on patient experience of the current IGABT workflow. Patient reported pre-treatment pain and anxiety can help identify patients that may benefit from additional support. Research and implementation of measures aiming at shortening the overall procedure duration, which may include logistical, staffing and technological aspects, should be prioritized.

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Background and purpose: In intensity modulated proton therapy (IMPT), the impact of setup errors and anatomical changes is commonly mitigated by robust optimization with population-based setup robustness (SR) settings and offline replanning. In this study we propose and evaluate an alternative approach based on daily plan selection from patient-specific pre-treatment established plan libraries (PLs). Clinical implementation of the PL strategy would be rather straightforward compared to daily online re-planning. Materials and methods: For 15 head-and-neck cancer patients, the planning CT was used to generate a PL with 5 plans, robustly optimized for increasing SR: 0, 1, 2, 3, 5 mm, and 3% range robustness. Repeat CTs (rCTs) and realistic setup and range uncertainty distributions were used for simulation of treatment courses for the PL approach, treatments with fixed SR (fSR₃) and a trigger-based offline adaptive schedule for 3 mm SR (fSR₃OfA). Daily plan selection in the PL approach was based only on recomputed dose to the CTV on the rCT. Results: Compared to using fSR₃ and fSR₃OfA, the risk of xerostomia grade ≥ II & III and dysphagia ≥ grade III were significantly reduced with the PL. For 6/15 patients the risk of xerostomia and/or dysphagia ≥ grade II could be reduced by > 2% by using PL. For the other patients, adherence to target coverage constraints was often improved. fSR₃OfA resulted in significantly improved coverage compared to PL for selected patients. Conclusion: The proposed PL approach resulted in overall reduced NTCPs compared to fSR₃ and fSR₃OfA at limited cost in target coverage.

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Very high energy electron (VHEE) radiotherapy is being investigated as a potential replacement of photon therapy. VHEE pencil beams have a small penumbra and strong depth dependence for radiotherapy when compared to photons. This allows a lower dose to healthy tissue. Generating these high electron energy beams could be achieved by using laser accelerators. These accelerators allow the equipment to be smaller than currently possible and make it possible to fit them in a standard radiotherapy treatment bunker. This makes VHEE a potential middle ground between photon and proton therapy in relation to equipment costs and treatment quality. The purpose of this project is to compare photon based Intensity Modulated Ra­diation Therapy (IMRT) and VHEE treatment plans for treatment of prostate cancer.  For 10 prostate cancer patients IMRT treatment plans were generated with 23 beams. These plans were optimized using Erasmus MC in-house developed Erasmus-iCycle automated treatment plan optimization tool. The dependence of VHEE plan quality on beam energy (200, 300 and 400 MeV) and number of equi-angular beams (9, 18 and 36) was investigated. The treatment plans were optimized using the multi-criterial optimizer Erasmus-iCycle. For each patient VHEE pencil beam dose distributions were pre-calculated using TOPAS MC, a Monte Carlo simulation program based on Geant4.  Results: VHEE treatment plans show either a reduced or similar mean OAR dose when compared to IMRT treatment plans except for the 9 beam 200 MeV plan which was worse compared to IMRT. All treatment plans were normalized to a PTV coverage of 99 % V57Gy.  It is found that the mean rectum dose reduces from 13.5 Gy for IMRT to between 9.2 and 11.9 (p=0.002-0.004) for the VHEE plans. For the anus dose a reduction in mean dose was found for all VHEE treatment plans except for the 9 beam 200 MeV and the 18 beam 200 MeV VHEE treatment plans. The mean anus dose reduced from 12.4 Gy for IMRT to 7.0 - 10.6 Gy (p=0.002-0.014) for the VHEE treatment plans. The bladder dose reduced from 20.1 Gy to between 15.2 and 18.2 Gy (p=0.002).  Increasing the number of VHEE beams in a treatment plan reduces the OAR dose. Comparing 9, 18 and 36 beam treatment plans with 300 MeV. The mean rectum dose reduces from 14.0 Gy for the 9 beam plan to 11.1 Gy (p=0.002) and 9.9 Gy (p=0.002) for the 18 and 36 beam plan, respectively. The same pattern is found for the anus and bladder.  Treatment plans with a higher beam energy reduces the dose to OAR. The mean rectum dose reduces from 13.4 Gy for the 200 MeV plan to 11.1 (p=0.002) and 10.0 (p=0.002) Gy for the 300 and 400 MeV plans. The same pattern is found in the mean bladder dose with 18.2 Gy, 16.8 Gy (p=0.002) and 15.9 Gy (p=0.002). The right femoral head maximum dose increases from 28.0 Gy for 200 MeV to 29.4 Gy(p=0.002) and 29.6 Gy (p=0.049) for the 300 and 400 MeV treatment plans.  VHEE is a potential replacement for IMRT due to the reduced dose to healthy tissue while maintaining similar target coverage compared to IMRT. By increasing the number of beams and/or the electron beam energy we can further reduce doses to the healthy tissue.  

The scope of a radiotherapy treatment is to induce damage to tumor cells by irradiating them with ionizing radiation. The radiation should target the tumor as visible in images, also called the macroscopic disease. There is, however, a risk of small, invisible groups of cancer cells in the area surrounding the macroscopic tumor, the microscopic disease. For an optimal clinical outcome of radiotherapy, the microscopic disease needs to be irradiated as well. In current treatment planning, the macroscopic tumor is extended with a margin to better ensure full disease coverage. Because there is uncertainty in the extent of the microscopic disease, also the margin definition is uncertain. Moreover, in current planning, the same margin is used for all patients, and there is no patient-specific exploration of the trade-offs between dose extensions to cover potentially present microscopic disease vs radiation-induced toxicity because of enhanced dose in organs at risk (OARs) surrounding the tumor. This study aimed to explore whether the margin concept could be replaced by more advanced, individualized approaches for irradiation of volumes just outside the macroscopic tumor. All plans were generated automatically to avoid bias by human planners and to reduce workload. Two novel treatment planning approaches were investigated. The first focused on increasing dose coverage of the microscopic disease while at the same time controlling the resulting increased dose to the healthy tissues surrounding the macroscopic tumor, including OARs. Several treatment plans were generated to explore a range of trade-offs between dose in microscopic disease and dose in OARs. The results showed that for optimal microscopic disease irradiation, both low and high OAR doses needed to worsen. However, the most significant increase in microscopic disease coverage could be obtained when accepting higher OAR low doses, that is generally less important for induction of negative side-effects.
In the second approach, an expected Tumor Control Probability (expected TCP) cost function was used to control dose delivery in areas close to the macroscopic tumor. Basis of the expected TCP model was a function describing the probability of finding microscopic disease at a specific distance from the macroscopic tumor. The results again demonstrated opportunities to increase dose to areas close to the tumor, at the cost of enhanced doses in OARs. In conclusion, both approaches had a positive impact on microscopic disease dose coverage. However, improved irradiation of the microscopic disease was always at a price of enhanced dose in OARs. Complementary studies, involving clinicians, need to be carried out to investigate if and how the approaches could be used to replace the current planning with fixed margins.

Purpose: To develop and evaluate a fast, automated multi-criterial treatment planning approach for adaptive high-dose-rate (HDR) intracavitary + interstitial brachytherapy (BT) for locally advanced cervical cancer. Methods and materials: Twenty-two previously delivered single fraction MRI-based HDR treatment plans (SF_clin) were used to guide training of our in-house system for multi-criterial autoplanning, aiming for an autoplan quality superior to the training plans, while respecting the clinically desired “pear-shaped” dose distribution. Next, the configured algorithm was used to automatically generate treatment plans for 63 other fractions (SF_auto). The SF_auto plans were compared to the corresponding SF_clin plans in blind pairwise comparisons by an expert clinician. Then, the effect of adaptive autoplanning on total treatment (TT) plans (external beam + 3 BT fractions) was evaluated for 16 patients by simulating the clinically applied adaptive strategy to generate TT_auto plans and compare them with the corresponding clinical treatments (TT_clin). Results: In the blind comparisons, all SF_auto plans were considered clinically acceptable. In 62/63 comparisons, SF_auto plans were considered at least as good as, or better than the corresponding SF_clin. The average optimization time for autoplanning was 20.5 ± 19.2 s (range 4.4–106.4 s) per plan. In 14 of 16 TT_auto plans, the desired total dose of 90 Gy (EQD₂) was obtained, compared to only 9 in the corresponding TT_clin, while autoplanning also decreased bladder and rectum doses. Conclusions: Fast, fully-automated multi-criterial treatment planning for adaptive HDR-BT for locally advanced cervical cancer is feasible. Autoplans were superior to corresponding clinical plans.

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Segmentation can degrade a high-quality dose distribution obtained by fluence map optimisation (FMO). A novel algorithm is proposed for generation of MLC segments to deliver an FMO plan with step-and-shoot IMRT while minimising quality loss. All beams are considered simultaneously while generating MLC segments for reproducing the 3D FMO dose distribution. Segment generation is only steered by the 3D FMO dose distribution, i.e. underlying FMO fluence profiles are not considered. The algorithm features prioritised generation of segments, focusing on accurate reproduction of clinical objectives with the highest priorities. The performance of the segmentation algorithm was evaluated for 20 prostate patients, 15 head-and-neck patients, and 12 liver patients. FMO dose distributions were generated by automated multi-criteria treatment planning (Pareto-optimal plans) and subsequently segmented using the proposed method. Various segmentation strategies were investigated regarding prioritisation of objectives and limitation of the number of segments. Segmented plans were dosimetrically similar to FMO plans and for all patients a clinically acceptable segmented plan could be generated. Substantial differences between FMO and segmented fluence profiles were observed. Avoidance of the usual reconstruction of 2D FMO fluence profiles for segment generation, and instead simultaneously generating segments for all beams to directly reproduce the 3D FMO dose distribution is a likely explanation for the obtained results. For the strategies of limiting the number of segments large reductions in number of segments were observed with minimal impact on plan quality.@en

We developed a fast and fully-automated, multi-criteria treatment planning workflow for high dose rate brachytherapy (HDR-BT). In this workflow, the patient-CT with catheter reconstructions and dwell positions are imported from the clinical TPS into a novel system for automated dwell time optimisation. The optimised dwell times are then imported into the clinical TPS. The aims of automation were (1) planner-independent, enhanced plan quality, (2) short optimisation times. Our in-house developed system for fully automated, multi-criteria external beam radiotherapy (EBRT) treatment planning (Erasmus-iCycle) was adapted for optimisation of HDR-BT dose distributions. The investigations were performed with planning CT scans with catheter reconstructions and delineations of twenty-five low- A nd intermediate-risk prostate cancer patients who were previously treated in our center with 4 × 9.5 Gy HDR-BT. Automatically generated plans (autoplans) were compared to the corresponding clinical plans. All evaluations were performed in the clinical TPS. The requested 95% tumour coverage was obtained for all autoplans, while this was only observed in 23/25 clinical plans. All autoplans showed a consistent reduction of the D1% for the highest prioritised OAR, the urethra. The average and maximum reductions were 6.3%-point and 12.1%-point of the prescribed dose, respectively. In addition, conformality of the autoplans was higher. The autoplans had slightly smaller delivery times. Autoplanning took on average 4.6 s, including computation of the dose kernels.

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Previously, we have proposed Erasmus-iCycle, an algorithm for fully automated IMRT plan generation based on prioritised (lexicographic) multi-objective optimisation with the 2-phase -constraint (2pc) method. For each patient, the output of Erasmus-iCycle is a clinically favourable, Pareto optimal plan. The 2pc method uses a list of objective functions that are consecutively optimised, following a strict, user-defined prioritisation. The novel lexicographic reference point method (LRPM) is capable of solving multi-objective problems in a single optimisation, using a fuzzy prioritisation of the objectives. Trade-offs are made globally, aiming for large favourable gains for lower prioritised objectives at the cost of only slight degradations for higher prioritised objectives, or vice versa. In this study, the LRPM is validated for 15 head and neck cancer patients receiving bilateral neck irradiation. The generated plans using the LRPM are compared with the plans resulting from the 2pc method. Both methods were capable of automatically generating clinically relevant treatment plans for all patients. For some patients, the LRPM allowed large favourable gains in some treatment plan objectives at the cost of only small degradations for the others. Moreover, because of the applied single optimisation instead of multiple optimisations, the LRPM reduced the average computation time from 209.2 to 9.5 min, a speed-up factor of 22 relative to the 2pc method.@en

In radiation therapy treatment planning, generating a treatment plan is a multi-objective optimisation problem. The decision-making strategy is uniform for each group of cancer patients, e.g. prostate cancer, and can thus be automated. Predefined priorities and aspiration levels are assigned to each objective, and the strategy is to attain these levels in order of priority. Therefore, a straightforward lexicographic approach is sequential ϵ-constraint programming where objectives are sequentially optimised and constrained according to predefined rules, mimicking human decision-making. The clinically applied 2-phase ϵ-constraint (2pϵc) method captures this approach and generates clinically acceptable treatment plans. However, the number of optimisation problems to be solved for the 2pϵc method, and hence the computation time, scales linearly with the number of objectives. To improve the daily planning workload and to further enhance radiation therapy, it is extremely important to reduce this time. Therefore, we developed the lexicographic reference point method (LRPM), a lexicographic extension of the reference point method, for generating a treatment plan by solving a single optimisation problem. The LRPM processes multiple a priori defined reference points into modified partial achievement functions. In addition, a priori bounds on a subset of the partial trade-offs can be imposed using a weighted sum component. The LRPM was validated for 30 randomly selected prostate cancer patients. While the treatment plans generated using the LRPM were of similar clinical quality to those generated using the 2pϵc method, the LRPM decreased the average computation time from 12.4 to 1.2 minutes, a speed-up factor of 10.

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Purpose To quantify the impact of the degree of robustness against setup errors and range errors on organ-at-risk (OAR) dose and normal tissue complication probabilities (NTCPs) in intensity-modulated proton therapy for oropharyngeal cancer patients. Material and methods For 20 oropharyngeal cases (10 unilateral and 10 bilateral), robust treatment plans were generated using ‘minimax’ worst-case optimization. We varied the robustness against setup errors (‘setup robustness’) from 1 to 7 mm and the robustness against range errors (‘range robustness’) from 1% to 7% (+1 mm). We evaluated OAR doses and NTCP-values for xerostomia, dysphagia and larynx edema. Results Varying the degree of setup robustness was found to have a considerably larger impact than varying the range robustness. Increasing setup robustness from 1 mm to 3, 5, and 7 mm resulted in average NTCP-values to increase by 1.9, 4.4 and 7.5 percentage point, whereas they increased by only 0.4, 0.8 and 1.2 percentage point when increasing range robustness from 1% to 3%, 5% and 7%. The degree of setup robustness was observed to have a clinically significant impact in bilateral cases in particular. Conclusions For oropharyngeal cancer patients, minimizing setup errors should be given a higher priority than minimizing range errors.

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Purpose We aimed to derive a "robustness recipe" giving the range robustness (RR) and setup robustness (SR) settings (ie, the error values) that ensure adequate clinical target volume (CTV) coverage in oropharyngeal cancer patients for given Gaussian distributions of systematic setup, random setup, and range errors (characterized by standard deviations of Σ, σ, and ρ, respectively) when used in minimax worst-case robust intensity modulated proton therapy (IMPT) optimization. Methods and Materials For the analysis, contoured computed tomography (CT) scans of 9 unilateral and 9 bilateral patients were used. An IMPT plan was considered robust if, for at least 98% of the simulated fractionated treatments, 98% of the CTV received 95% or more of the prescribed dose. For fast assessment of the CTV coverage for given error distributions (ie, different values of Σ, σ, and ρ), polynomial chaos methods were used. Separate recipes were derived for the unilateral and bilateral cases using one patient from each group, and all 18 patients were included in the validation of the recipes. Results Treatment plans for bilateral cases are intrinsically more robust than those for unilateral cases. The required RR only depends on the ρ, and SR can be fitted by second-order polynomials in Σ and σ. The formulas for the derived robustness recipes are as follows: Unilateral patients need SR = -0.15Σ² + 0.27σ² + 1.85Σ - 0.06σ + 1.22 and RR=3% for ρ = 1% and ρ = 2%; bilateral patients need SR = -0.07Σ² + 0.19σ² + 1.34Σ - 0.07σ + 1.17 and RR=3% and 4% for ρ = 1% and 2%, respectively. For the recipe validation, 2 plans were generated for each of the 18 patients corresponding to Σ = σ = 1.5 mm and ρ = 0% and 2%. Thirty-four plans had adequate CTV coverage in 98% or more of the simulated fractionated treatments; the remaining 2 had adequate coverage in 97.8% and 97.9%. Conclusions Robustness recipes were derived that can be used in minimax robust optimization of IMPT treatment plans to ensure adequate CTV coverage for oropharyngeal cancer patients.

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