Two-dimensional oxygen-diffusion modelling for FLASH proton therapy with pencil beam scanning - impact of diffusive tissue properties, dose, dose rate and scan patterns.

Oxygen depletion is generally believed to play an important role in the FLASH effect - a differential reduction of the radiosensitivity of healthy tissues, relative to that of the tumour under ultra-high dose-rate (UHDR) irradiation conditions. In proton therapy (PT) with pencil-beam scanning (PBS), the deposition of dose, and, hence, the degree of (radiolytic) oxygen depletion varies both spatially and temporally. Therefore, the resulting oxygen concentration and the healthy-tissue sparing effect through radiation-induced hypoxia varies both spatially and temporally as well. We propose and numerically solve a physical oxygen diffusion model to study these effects and their dependence on tissue parameters and the scan pattern in pencil-beam delivery. Since current clinical FLASH proton therapy (FLASH-PT) is based on 250 MeV shoot-through (transmission) beams, for which dose and dose rate hardly vary with depth compared to the variation transverse to the beam axis, we focus on the two-dimensional case. We numerically integrate the model to obtain the oxygen concentration in each voxel as a function of time and extract voxel-based and spatially and temporarily integrated metrics for oxygen (FLASH) enhanced dose. Furthermore, we evaluate the impact on oxygen enhancement of standard pencil-beam delivery patterns and patterns that were optimised on dose-rate. Our model can contribute to the identification of tissue properties and pencil-beam delivery parameters that are critical for FLASH-PT and it may be used for the optimisation of FLASH-PT treatment plans and their delivery. Our main findings are that: (i) the diffusive properties of oxygen are critical for the steady state concentration and therefore the FLASH effect, even more so in two dimensions when compared to one dimension. (ii) The FLASH effect through oxygen depletion depends primarily on dose and less on other parameters. (iii) At a fixed fraction dose there is a slight dependence on dose rate. (iv) Scan patterns optimised on dose rate slightly increase the oxygen induced FLASH effect.

A fast and robust constraint-based online re-optimization approach for automated online adaptive intensity modulated proton therapy in head and neck cancer.

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 (offlineTBre-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 offlineTBre-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, offlineTBre-planning resulted in <50% probability ofD98%≥ 95% of the prescribed dose (Dpres) in one or both CTVs, which never happened with online re-optimization. With offlineTBre-planning, eight repeat-CTs had zero probability of obtainingD98%≥ 95%Dpresfor CTV7000, 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< 10-5for 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.

Validation of a deep-learning segmentation model for adult and pediatric head and neck radiotherapy in different patient positions.

Background and purpose: Autocontouring for radiotherapy has the potential to significantly save time and reduce interobserver variability. We aimed to assess the performance of a commercial autocontouring model for head and neck (H&N) patients in eight orientations relevant to particle therapy with fixed beam lines, focusing on validation and implementation for routine clinical use. Materials and methods: Autocontouring was performed on sixteen organs at risk (OARs) for 98 adult and pediatric patients with 137 H&N CT scans in eight orientations. A geometric comparison of the autocontours and manual segmentations was performed using the Hausdorff Distance 95th percentile, Dice Similarity Coefficient (DSC) and surface DSC and compared to interobserver variability where available. Additional qualitative scoring and dose-volume-histogram (DVH) parameters analyses were performed for twenty patients in two positions, consisting of scoring on a 0-3 scale based on clinical usability and comparing the mean (Dmean) and near-maximum (D2%) dose, respectively. Results: For the geometric analysis, the model performance in head-first-supine straight and hyperextended orientations was in the same range as the interobserver variability. HD95, DSC and surface DSC was heterogeneous in other orientations. No significant geometric differences were found between pediatric and adult autocontours. The qualitative scoring yielded a median score of ≥ 2 for 13/16 OARs while 7/32 DVH parameters were significantly different. Conclusions: For head-first-supine straight and hyperextended scans, we found that 13/16 OAR autocontours were suited for use in daily clinical practice and subsequently implemented. Further development is needed for other patient orientations before implementation.

Cochlear-optimized treatment planning in photon and proton radiosurgery for vestibular schwannoma patients.

Objective: To investigate the potential to reduce the cochlear dose with robotic photon radiosurgery or intensity-modulated proton therapy planning for vestibular schwannomas. Materials and Methods: Clinically delivered photon radiosurgery treatment plans were compared to five cochlear-optimized plans: one photon and four proton plans (total of 120). A 1x12 Gy dose was prescribed. Photon plans were generated with Precision (Cyberknife, Accuray) with no PTV margin for set-up errors. Proton plans were generated using an in-house automated multi-criterial planning system with three or nine-beam arrangements, and applying 0 or 3 mm robustness for set-up errors during plan optimization and evaluation (and 3 % range robustness). The sample size was calculated based on a reduction of cochlear Dmean > 1.5 Gy(RBE) from the clinical plans, and resulted in 24 patients. Results: Compared to the clinical photon plans, a reduction of cochlear Dmean > 1.5 Gy(RBE) could be achieved in 11/24 cochlear-optimized photon plans, 4/24 and 6/24 cochlear-optimized proton plans without set-up robustness for three and nine-beam arrangement, respectively, and in 0/24 proton plans with set-up robustness. The cochlea could best be spared in cases with a distance between tumor and cochlea. Using nine proton beams resulted in a reduced dose to most organs at risk. Conclusion: Cochlear dose reduction is possible in vestibular schwannoma radiosurgery while maintaining tumor coverage, especially when the tumor is not adjacent to the cochlea. With current set-up robustness, proton therapy is capable of providing lower dose to organs at risk located distant to the tumor, but not for organs adjacent to it. Consequently, photon plans provided better cochlear sparing than proton plans.

Robustness analysis of CTV and OAR dose in clinical PBS-PT of neuro-oncological tumors: prescription-dose calibration and inter-patient variation with the Dutch proton robustness evaluation protocol.

Objective. The Dutch proton robustness evaluation protocol prescribes the dose of the clinical target volume (CTV) to the voxel-wise minimum (VWmin) dose of 28 scenarios. This results in a consistent but conservative near-minimum CTV dose (D98%,CTV). In this study, we analyzed (i) the correlation between VWmin/voxel-wise maximum (VWmax) metrics and actually delivered dose to the CTV and organs at risk (OARs) under the impact of treatment errors, and (ii) the performance of the protocol before and after its calibration with adequate prescription-dose levels.Approach. Twenty-one neuro-oncological patients were included. Polynomial chaos expansion was applied to perform a probabilistic robustness evaluation using 100,000 complete fractionated treatments per patient. Patient-specific scenario distributions of clinically relevant dosimetric parameters for the CTV and OARs were determined and compared to clinical VWmin and VWmax dose metrics for different scenario subsets used in the robustness evaluation protocol.Main results. The inclusion of more geometrical scenarios leads to a significant increase of the conservativism of the protocol in terms of clinical VWmin and VWmax values for the CTV and OARs. The protocol could be calibrated using VWmin dose evaluation levels of 93.0%-92.3%, depending on the scenario subset selected. Despite this calibration of the protocol, robustness recipes for proton therapy showed remaining differences and an increased sensitivity to geometrical random errors compared to photon-based margin recipes.Significance. The Dutch proton robustness evaluation protocol, combined with the photon-based margin recipe, could be calibrated with a VWmin evaluation dose level of 92.5%. However, it shows limitations in predicting robustness in dose, especially for the near-maximum dose metrics to OARs. Consistent robustness recipes could improve proton treatment planning to calibrate residual differences from photon-based assumptions.

PTV-based VMAT vs. robust IMPT for head-and-neck cancer: A probabilistic uncertainty analysis of clinical plan evaluation with the Dutch model-based selection.

BACKGROUND AND PURPOSE: In the Netherlands, head-and-neck cancer (HNC) patients are referred for proton therapy (PT) through model-based selection (MBS). However, treatment errors may compromise adequate CTV dose. Our aims are: (i) to derive probabilistic plan evaluation metrics on the CTV consistent with clinical metrics; (ii) to evaluate plan consistency between photon (VMAT) and proton (IMPT) planning in terms of CTV dose iso-effectiveness and (iii) to assess the robustness of the OAR doses and of the risk toxicities involved in the MBS. MATERIALS AND METHODS: Sixty HNC plans (30 IMPT/30 VMAT) were included. A robustness evaluation with 100,000 treatment scenarios per plan was performed using Polynomial Chaos Expansion (PCE). PCE was applied to determine scenario distributions of clinically relevant dosimetric parameters, which were compared between the 2 modalities. Finally, PCE-based probabilistic dose parameters were derived and compared to clinical PTV-based photon and voxel-wise proton evaluation metrics. RESULTS: Probabilistic dose to near-minimum volume v = 99.8% for the CTV correlated best with clinical PTV-D98% and VWmin-D98%,CTV doses for VMAT and IMPT respectively. IMPT showed slightly higher nominal CTV doses, with an average increase of 0.8 GyRBE in the median of the D99.8%,CTV distribution. Most patients qualified for IMPT through the dysphagia grade II model, for which an average NTCP gain of 10.5 percentages points (%-point) was found. For all complications, uncertainties resulted in moderate NTCP spreads lower than 3 p.p. on average for both modalities. CONCLUSION: Despite the differences between photon and proton planning, the comparison between PTV-based VMAT and robust IMPT is consistent. Treatment errors had a moderate impact on NTCPs, showing that the nominal plans are a good estimator to qualify patients for PT.

Transarterial Chemoembolization With Drug-Eluting Beads Versus Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma: Outcomes From a Multicenter, Randomized, Phase 2 Trial (the TRENDY Trial).

PURPOSE: To compare transarterial chemoembolization delivered with drug eluting beads (TACE-DEB) with stereotactioc body radiation therapy (SBRT) in patients with hepatocellular carcinoma (HCC) in a multicenter randomized trial. METHODS AND MATERIALS: Patients were included if they were eligible for TACE. They could also be recruited if they required treatment prior to liver transplantation. A maximum of four TACE-DEB procedures and ablation after incomplete TACE-DEB were both allowed. SBRT was delivered in six fractions of 8-9Gy. Primary end point was time to progression (TTP). Secondary endpoints were local control (LC), overall survival (OS), response rate (RR), toxicity, and quality of life (QoL). The calculated sample size was 100 patients. RESULTS: Between May 2015 and April 2020, 30 patients were randomized to the study. Due to slow accrual the trial was closed prematurely. Two patients in the SBRT arm were considered ineligible leaving 16 patients in the TACE-DEB arm and 12 in the SBRT arm. Median follow-up was 28.1 months. Median TTP was 12 months for TACEDEB and 19 months for SBRT (p=0.15). Median LC was 12 months for TACE-DEB and >40 months (not reached) for SBRT (p=0.075). Median OS was 36.8 months for TACEDEB and 44.1 months for SBRT (p=0.36). A post-hoc analysis showed 100% for SBRT 1- and 2-year LC, and 54.4% and 43.6% for TACE-DEB (p=0.019). Both treatments resulted in RR>80%. Three episodes of possibly related toxicity grade ≥3 were observed after TACE-DEB. No episodes were observed after SBRT. QoL remained stable after both treatment arms. CONCLUSIONS: In this trial, TTP after TACE-DEB was not significantly improved by SBRT, while SBRT showed higher local antitumoral activity than TACE-DEB, without detrimental effects on OS, toxicity and QoL. To overcome poor accrual in randomized trials that include SBRT, and to generate evidence for including SBRT in treatment guidelines, international cooperation is needed.

Early and late contrast enhancing lesions after photon radiotherapy for IDH mutated grade 2 diffuse glioma.

OBJECTIVE: The interpretation of new enhancing lesions after radiotherapy for diffuse glioma remains a clinical challenge. We sought to characterize and classify new contrast enhancing lesions in a historical multicenter cohort of patients with IDH mutated grade 2 diffuse glioma treated with photon therapy. METHODS: We reviewed all follow-up MRI's of all patients treated with radiotherapy for histologically confirmed, IDH mutated diffuse grade 2 glioma between 1-1-2007 and 31-12-2018 in two tertiary referral centers. Disease progression (PD) was defined in accordance with the RANO criteria for progressive disease in low grade glioma. Pseudoprogression (psPD) was defined as any transient contrast-enhancing lesion between the end of radiotherapy and PD, or any new contrast-enhancing lesion that remained stable over a period of 12 months in patients who did not exhibit PD. RESULTS: A total of 860 MRI's of 106 patients were reviewed. psPD was identified in 24 patients (23%) on 76 MRI's. The cumulative incidence of psPD was 13% at 1 year, 22% at 5 years, and 28% at 10 years. The mean of the observed maximal volume of psPD was 2.4 cc. The median Dmin in psPD lesions was 50.1 Gy. The presence of an 1p/19q codeletion was associated with an increased risk of psPD (subhazard ratio 2.34, p = 0.048). psPD was asymptomatic in 83% of patients. CONCLUSION: The cumulative incidence of psPD in grade 2 diffuse glioma increases over time. Consensus regarding event definition and statistical analysis is needed for comparisons between series investigating psPD.

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy.

Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal component analysis (PCA) and are either patient-specific (requiring several scans per patient) or population-based, applying the same set of deformations to all patients. We present a hybrid approach which, based on population data, allows to predict patient-specific inter-fraction variations for an individual patient.Approach. We propose a deep learning probabilistic framework that generates deformation vector fields warping a patient's planning computed tomography (CT) into possible patient-specific anatomies. This daily anatomy model (DAM) uses few random variables capturing groups of correlated movements. Given a new planning CT, DAM estimates the joint distribution over the variables, with each sample from the distribution corresponding to a different deformation. We train our model using dataset of 312 CT pairs with prostate, bladder, and rectum delineations from 38 prostate cancer patients. For 2 additional patients (22 CTs), we compute the contour overlap between real and generated images, and compare the sampled and 'ground truth' distributions of volume and center of mass changes.Results. With a DICE score of 0.86 ± 0.05 and a distance between prostate contours of 1.09 ± 0.93 mm, DAM matches and improves upon previously published PCA-based models, using as few as 8 latent variables. The overlap between distributions further indicates that DAM's sampled movements match the range and frequency of clinically observed daily changes on repeat CTs.Significance. Conditioned only on planning CT values and organ contours of a new patient without any pre-processing, DAM can accurately deformations seen during following treatment sessions, enabling anatomically robust treatment planning and robustness evaluation against inter-fraction anatomical changes.

Pencil-beam Delivery Pattern Optimization Increases Dose Rate for Stereotactic FLASH Proton Therapy.

PURPOSE: FLASH dose rates >40 Gy/s are readily available in proton therapy (PT) with cyclotron-accelerated beams and pencil-beam scanning (PBS). The PBS delivery pattern will affect the local dose rate, as quantified by the PBS dose rate (PBS-DR), and therefore needs to be accounted for in FLASH-PT with PBS, but it is not yet clear how. Our aim was to optimize patient-specific scan patterns for stereotactic FLASH-PT of early-stage lung cancer and lung metastases, maximizing the volume irradiated with PBS-DR >40 Gy/s of the organs at risk voxels irradiated to >8 Gy (FLASH coverage). METHODS AND MATERIALS: Plans to 54 Gy/3 fractions with 3 equiangular coplanar 244 MeV proton shoot-through transmission beams for 20 patients were optimized with in-house developed software. Planning target volume-based planning with a 5 mm margin was used. Planning target volume ranged from 4.4 to 84 cc. Scan-pattern optimization was performed with a Genetic Algorithm, run in parallel for 20 independent populations (islands). Mapped crossover, inversion, swap, and shift operators were applied to achieve (local) optimality on each island, with migration between them for global optimality. The cost function was chosen to maximize the FLASH coverage per beam at >8 Gy, >40 Gy/s, and 40 nA beam current. The optimized patterns were evaluated on FLASH coverage, PBS-DR distribution, and population PBS-DR-volume histograms, compared with standard line-by-line scanning. Robustness against beam current variation was investigated. RESULTS: The optimized patterns have a snowflake-like structure, combined with outward swirling for larger targets. A population median FLASH coverage of 29.0% was obtained for optimized patterns compared with 6.9% for standard patterns, illustrating a significant increase in FLASH coverage for optimized patterns. For beam current variations of 5 nA, FLASH coverage varied between -6.1%-point and 2.2%-point for optimized patterns. CONCLUSIONS: Significant improvements on the PBS-DR and, hence, on FLASH coverage and potential healthy-tissue sparing are obtained by sequential scan-pattern optimization. The optimizer is flexible and may be further fine-tuned, based on the exact conditions for FLASH.

An online adaptive plan library approach for intensity modulated proton therapy for head and neck cancer.

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.

Trade-off in healthy tissue sparing of FLASH and fractionation in stereotactic proton therapy of lung lesions with transmission beams.

PURPOSE AND OBJECTIVE: Besides a dose-rate threshold of 40-100 Gy/s, the FLASH effect may require a dose > 3.5-7 Gy. Even in hypofractioned treatments, with all beams delivered in each fraction (ABEF), most healthy tissue is irradiated to a lower fraction dose. This can be circumvented by single-beam-per-fraction (SBPF) delivery, with a loss of healthy tissue sparing by fractionation. We investigated the trade-off between FLASH and loss of fractionation in SBPF stereotactic proton therapy of lung cancer and determined break-even FLASH-enhancement ratios (FERs). MATERIALS AND METHODS: Treatment plans for 12 patients were generated. GTV delineations were available and a 5 mm GTV-PTV margin was applied. Equiangular arrangements of 3, 5, 7, and 9 244 MeV proton transmission beams were used. To facilitate SBPF, the number of fractions was equal to the number of beams. Iso-effective fractionation schedules with a single field uniform dose prescription were used: D95%,PTV = 100%Dpres per beam. All plans were evaluated in terms of dose to lung and conformity of dose to target of FLASH-enhanced biologically equivalent dose (EQD2). RESULTS: Compared to ABEF, SBPF resulted in a median increase of EQD2mean to healthy lung of 56%, 58%, 55% and 54% in plans with 3, 5, 7 and 9 fractions respectively and of 236%, 78%, 50% and 41% in V100% EQD2, quantifying conformity. This can be compensated for by FERs of at least 1.28, 1.32, 1.30 and 1.23 respectively for EQD2mean and 1.29, 1.18, 1.28 and 1.15 for V100%,EQD2. CONCLUSION: A FLASH effect outweighing the loss of fractionation in SBPF may be achieved in stereotactic lung treatments. The trade-off with fractionation depends on the conditions under which the FLASH effect occurs. Better understanding of the underlying biology and the impact of delivery conditions is needed.

How should we model and evaluate breathing interplay effects in IMPT?

Breathing interplay effects in Intensity Modulated Proton Therapy (IMPT) arise from the interaction between target motion and the scanning beam. Assessing the detrimental effect of interplay and the clinical robustness of several mitigation techniques requires statistical evaluation procedures that take into account the variability of breathing during dose delivery. In this study, we present such a statistical method to model intra-fraction respiratory motion based on breathing signals and assess clinical relevant aspects related to the practical evaluation of interplay in IMPT such as how to model irregular breathing, how small breathing changes affect the final dose distribution, and what is the statistical power (number of different scenarios) required for trustworthy quantification of interplay effects. First, two data-driven methodologies to generate artificial patient-specific breathing signals are compared: a simple sinusoidal model, and a precise probabilistic deep learning model generating very realistic samples of patient breathing. Second, we investigate the highly fluctuating relationship between interplay doses and breathing parameters, showing that small changes in breathing period result in large local variations in the dose. Our results indicate that using a limited number of samples to calculate interplay statistics introduces a bigger error than using simple sinusoidal models based on patient parameters or disregarding breathing hysteresis during the evaluation. We illustrate the power of the presented statistical method by analyzing interplay robustness of 4DCT and Internal Target Volume (ITV) treatment plans for a 8 lung cancer patients, showing that, unlike 4DCT plans, even 33 fraction ITV plans systematically fail to fulfill robustness requirements.

Accurate assessment of a Dutch practical robustness evaluation protocol in clinical PT with pencil beam scanning for neurological tumors.

BACKGROUND AND PURPOSE: Scenario-based robust optimization and evaluation are commonly used in proton therapy (PT) with pencil beam scanning (PBS) to ensure adequate dose to the clinical target volume (CTV). However, a statistically accurate assessment of the clinical application of this approach is lacking. In this study, we assess target dose in a clinical cohort of neuro-oncological patients, planned according to the DUPROTON robustness evaluation consensus, using polynomial chaos expansion (PCE). MATERIALS AND METHODS: A cohort of the first 27 neuro-oncological patients treated at HollandPTC was used, including realistic error distributions derived from geometrical and stopping-power prediction (SPP) errors. After validating the model, PCE-based robustness evaluations were performed by simulating 100.000 complete fractionated treatments per patient to obtain accurate statistics on clinically relevant dosimetric parameters and population-dose histograms. RESULTS: Treatment plans that were robust according to clinical protocol and treatment plansin which robustness was sacrificed are easily identified. For robust treatment plans on average, a CTV dose of 3 percentage points (p.p.) more than prescribed was realized (range +2.7 p.p. to +3.5 p.p.) for 98% of the sampled fractionated treatments. For the entire patient cohort on average, a CTV dose of 0.1 p.p. less than prescribed was achieved (range -2.4 p.p. to +0.5 p.p.). For the 6 treatment plans in which robustness was clinically sacrificed, normalized CTV doses of 0.98, 0.94(7)1, 0.94, 0.91, 0.90 and 0.89 were realized. The first of these was clinically borderline non-robust. CONCLUSION: The clinical robustness evaluation protocol is safe in terms of CTV dose as all plans that fulfilled the clinical robustness criteria were also robust in the PCE evaluation. Moreover, for plans that were non-robust in the PCE-based evaluation, CTV dose was also lower than prescribed in the clinical evaluation.

Fiducial marker motion relative to the tumor bed has a significant impact on PTV margins in partial breast irradiation.

INTRODUCTION: With the introduction of accelerated partial breast irradiation (APBI) and the trend of reducing the number of fractions, the geometric accuracy of treatment delivery becomes critical. APBI patient setup is often based on fiducials, as the seroma is frequently not visible on pretreatment imaging. We assessed the motion of fiducials relative to the tumor bed between planning CT and treatment, and calculated margins to compensate for this motion. METHODS: A cohort of seventy patients treated with APBI on a Cyberknife was included. Planning and in-room pretreatment CT scans were registered on the tumor bed. Residual motion of the centers of mass of surgical clips and interstitial gold markers was calculated. We calculated the margins required per desired percentage of patients with 100% CTV coverage, and the systematic and random errors for fiducial motion. RESULTS: For a single fraction treatment, a margin of 1.8 mm would ensure 100% CTV coverage in 90% of patients when using surgical clips for patient set-up. When using interstitial markers, the margin should be 2.2 mm. The systematic and random errors were 0.46 mm for surgical clip motion and 0.60 mm for interstitial marker motion. No clinical factors were found predictive for fiducial motion. CONCLUSIONS: Fiducial motion relative to the tumor bed between planning CT and APBI treatment is non-negligible and should be included in the PTV margin calculation to prevent geographical miss. Systematic and random errors of fiducial motion were combined with other geometric uncertainties to calculate comprehensive PTV margins for different treatment techniques.

Intrafraction motion during partial breast irradiation depends on treatment time.

INTRODUCTION: As the prognosis of early-stage breast cancer patients is excellent, prevention of radiation-induced toxicity has become crucial. Reduction of margins compensating for intrafraction motion reduces non-target dose. We assessed motion of the tumor bed throughout APBI treatment fractions and calculated CTV-PTV margins for breathing and drift. METHODS: This prospective clinical trial included patients treated with APBI on a Cyberknife with fiducial tracking. Paired orthogonal kV images made throughout the entire fraction were used to extract the tumor bed position. The images used for breathing modelling were used to calculate breathing amplitudes. The margins needed to compensate for breathing and drift were calculated according to Engelsman and Van Herk respectively. RESULTS: Twenty-two patients, 110 fractions and 5087 image pairs were analyzed. The margins needed for breathing were 0.3-0.6 mm. The margin for drift increased with time after the first imaging for positioning. For a total fraction duration up to 8 min, a margin of 1.0 mm is sufficient. For a fraction of 32 min, 2.5 mm is needed. Techniques that account for breathing motion can reduce the margin by 0.1 mm. There was a systematic trend in the drift in the caudal, medial and posterior direction. To compensate for this, 0.7 mm could be added to the margins. CONCLUSIONS: The margin needed to compensate for intrafraction motion increased with longer fraction duration due to drifting of the target. It doubled for a fraction of 24 min compared to 8 min. Breathing motion has a limited effect.

Model based patient pre-selection for intensity-modulated proton therapy (IMPT) using automated treatment planning and machine learning.

BACKGROUND AND PURPOSE: Patient selection for intensity modulated proton therapy (IMPT), using comparative photon therapy planning, is workload-intensive and time-consuming. Pre-selection aims at avoidance of manual IMPT planning for patients that are in the end ineligible. We investigated the use of machine learning together with automated IMPT treatment planning for pre-selection of head and neck cancer patients, and validated the methodology for the Dutch model based selection (MBS) approach. MATERIALS & METHODS: For forty-five head and neck patients with a previous MBS, an IMPT plan was generated with non-clinical, fully-automated planning. Dosimetric differences of these plans with the corresponding previously generated photon plans, and the outcomes of the former MBS, were used to train a Gaussian naïve Bayes classifier for MBS outcome prediction. During training, strong emphasis was placed on avoiding misclassification of IMPT eligible patients (i.e. false negatives). RESULTS: Pre-selection with the classifier resulted in 0 false negatives, 12 (27%) true negatives, 27 (60%) true positives, and only 6 (13%) false positive predictions. Using this pre-selection, the number of formal selection procedures with involved manual IMPT planning that resulted in a negative outcome could be reduced by 67%. CONCLUSION: With pre-selection, using machine learning and automated treatment planning, the percentage of patients with unnecessary manual IMPT planning for MBS could be drastically reduced, thereby saving costs, labor and time. With the developed approach, larger patient populations can be screened, and likely bias in pre-selection of patients can be mitigated by assisting the physician during patient pre-selection.

Reducing the Risk of Secondary Lung Cancer in Treatment Planning of Accelerated Partial Breast Irradiation.

Purpose: Adjuvant accelerated partial breast irradiation (APBI) results in low local recurrence risks. However, the survival benefit of adjuvant radiotherapy APBI for low-risk breast cancer might partially be offset by the risk of radiation-induced lung cancer. Reducing the lung dose mitigates this risk, but this could result in higher doses to the ipsilateral breast. Different external beam APBI techniques are equally conformal and homogenous, but the intermediate to low dose distribution differs. Thus, the risk of toxicity is different. The purpose of this study is to quantify the trade-off between secondary lung cancer risk and breast dose in treatment planning and to compare an optimal coplanar and non-coplanar technique. Methods: A total of 440 APBI treatment plans were generated using automated treatment planning for a coplanar VMAT beam-setup and a non-coplanar robotic stereotactic radiotherapy beam-setup. This enabled an unbiased comparison of two times 11 Pareto-optimal plans for 20 patients, gradually shifting priority from maximum lung sparing to maximum ipsilateral breast sparing. The excess absolute risks of developing lung cancer and breast fibrosis were calculated using the Schneider model for lung cancer and the Avanzo model for breast fibrosis. Results: Prioritizing lung sparing reduced the mean lung dose from 2.2 Gy to as low as 0.3 Gy for the non-coplanar technique and from 1.9 Gy to 0.4 Gy for the coplanar technique, corresponding to a 7- and 4-fold median reduction of secondary lung cancer risk, respectively, compared to prioritizing breast sparing. The increase in breast dose resulted in a negligible 0.4% increase in fibrosis risk. The use of non-coplanar beams resulted in lower secondary cancer and fibrosis risks (p < 0.001). Lung sparing also reduced the mean heart dose for both techniques. Conclusions: The risk of secondary lung cancer of external beam APBI can be dramatically reduced by prioritizing lung sparing during treatment planning. The associated increase in breast dose did not lead to a relevant increase in fibrosis risk. The use of non-coplanar beams systematically resulted in the lowest risks of secondary lung cancer and fibrosis. Prioritizing lung sparing during treatment planning could increase the overall survival of early-stage breast cancer patients by reducing mortality due to secondary lung cancer and cardiovascular toxicity.

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.

The TRENDY multi-center randomized trial on hepatocellular carcinoma - Trial QA including automated treatment planning and benchmark-case results.

BACKGROUND AND PURPOSE: The TRENDY trial is an international multi-center phase-II study, randomizing hepatocellular carcinoma (HCC) patients between transarterial chemoembolization (TACE) and stereotactic body radiation therapy (SBRT) with a target dose of 48-54 Gy in six fractions. The radiotherapy quality assurance (QA) program, including prospective plan feedback based on automated treatment planning, is described and results are reported. MATERIALS AND METHODS: Scans of a single patient were used as a benchmark case. Contours submitted by nine participating centers were compared with reference contours. The subsequent planning round was based on a single set of contours. A total of 20 plans from participating centers, including 12 from the benchmark case, 5 from a clinical pilot and 3 from the first study patients, were compared to automatically generated VMAT plans. RESULTS: For the submitted liver contours, Dice Similarity Coefficients (DSC) with the reference delineation ranged from 0.925 to 0.954. For the GTV, the DSC varied between 0.721 and 0.876. For the 12 plans on the benchmark case, healthy liver normal-tissue complication probabilities (NTCPs) ranged from 0.2% to 22.2% with little correlation between NCTP and PTV-D95% (R2 < 0.3). Four protocol deviations were detected in the set of 20 treatment plans. Comparison with co-planar autoVMAT QA plans revealed these were due to too high target dose and suboptimal planning. Overall, autoVMAT resulted in an average liver NTCP reduction of 2.2 percent point (range: 16.2 percent point to -1.8 percent point, p = 0.03), and lower doses to the healthy liver (p < 0.01) and gastrointestinal organs at risk (p < 0.001). CONCLUSIONS: Delineation variation resulted in feedback to participating centers. Automated treatment planning can play an important role in clinical trials for prospective plan QA as suboptimal plans were detected.