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4D multi-image-based (4DMIB) optimization is a form of robust optimization where different uncertainty scenarios, due to anatomy variations, are considered via multiple image sets (e.g., 4DCT). In this review, we focused on providing an overview of different 4DMIB optimization implementations, introduced various frameworks to evaluate the robustness of scanned particle therapy affected by breathing motion and summarized the existing evidence on the necessity of using 4DMIB optimization clinically. Expected potential benefits of 4DMIB optimization include more robust and/or interplay-effect-resistant doses for the target volume and organs-at-risk for indications affected by anatomical variations (e.g., breathing, peristalsis, etc.). Although considerable literature is available on the research and technical aspects of 4DMIB, clinical studies are rare and often contain methodological limitations, such as, limited patient number, motion amplitude, motion and delivery time structure considerations, number of repeat CTs, etc. Therefore, the data are not conclusive. In addition, multiple studies have found that robust 3D optimized plans result in dose distributions within the set clinical tolerances and, therefore, are suitable for a treatment of moving targets with scanned particle therapy. We, therefore, consider the clinical necessity of 4DMIB optimization, when treating moving targets with scanned particle therapy, as still to be demonstrated., Radiotherapy & Oncology, 169, ISSN:0167-8140, ISSN:1879-0887

PurposeIn the Netherlands, oesophageal cancer (EC) patients are selected for intensity modulated proton therapy (IMPT) using the expected normal tissue complication probability reduction (ΔNTCP) when treating with IMPT compared to volumetric modulated arc therapy (VMAT). In this study, we evaluate the robustness of the first EC patients treated with IMPT in our clinic in terms of target and organs-at-risk (OAR) dose with corresponding NTCP, as compared to VMAT.Materials and MethodsFor 20 consecutive EC patients, clinical IMPT and VMAT plans were created on the average planning 4DCT. Both plans were robustly evaluated on weekly repeated 4DCTs and if target coverage degraded, replanning was performed. Target coverage was evaluated for complete treatment trajectories with and without replanning. The planned and accumulated mean lung dose (MLD) and mean heart dose (MHD) were additionally evaluated and translated into NTCP.ResultsReplanning in the clinic was performed more often for IMPT (15x) than would have been needed for VMAT (8x) (p = 0.11). Both adaptive treatments would have resulted in adequate accumulated target dose coverage. Replanning in the first week of treatment had most clinical impact, as anatomical changes resulting in insufficient accumulated target coverage were already observed at this stage. No differences were found in MLD between the planned dose and the accumulated dose. Accumulated MHD differed from the planned dose (p < 0.001), but since these differences were similar for VMAT and IMPT (1.0 and 1.5 Gy, respectively), the ΔNTCP remained unchanged.ConclusionFollowing an adaptive clinical workflow, adequate target dose coverage and stable OAR doses with corresponding NTCPs was assured for both IMPT and VMAT.

Background and purpose Deformable image registration (DIR) is an important component for dose accumulation and associated clinical outcome evaluation in radiotherapy. However, as an ill-posed problem, the resulting deformation vector field (DVF) is subject to unavoidable discrepancies when different algorithms are applied, leading to dosimetric uncertainties of the accumulated dose. We propose here an approach for proton therapy to estimate dosimetric uncertainties as a consequence of modeled or estimated DVF uncertainties. Materials and methods A patient-specific DVF uncertainty model was built on the first treatment fraction, by correlating the magnitude differences of five DIR results at each voxel to the magnitude of any single reference DIR. In the following fractions, only the reference DIR needs to be applied, and DVF geometric uncertainties were estimated by this model. The associated dosimetric uncertainties were then derived by considering the estimated geometric DVF uncertainty, the dose gradient of fractional recalculated dose distribution and the direction factor from the applied reference DIR of this fraction. This estimated dose uncertainty was respectively compared to the reference dose uncertainty when different DIRs were applied individually for each dose warping. This approach was validated on seven NSCLC patients, each with nine repeated CTs. Results The proposed model-based method is able to achieve dose uncertainty distribution on a conservative voxel-to-voxel comparison within ±5% of the prescribed dose to the 'reference' dosimetric uncertainty, for 77% of the voxels in the body and 66-98% of voxels in investigated structures. Conclusion We propose a method to estimate DIR induced uncertainties in dose accumulation for proton therapy of lung tumor treatments.

Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks. In this study, we compared sCTs based on CBCTs and MRs for head and neck (H&N) cancer patients in terms of image quality and proton dose calculation accuracy. A dataset of 27 H&N-patients, treated with proton therapy (PT), containing planning CTs (pCTs), repeat CTs, CBCTs and MRs were used to train two neural networks to convert either CBCTs or MRs into sCTs. Image quality was quantified by calculating mean absolute error (MAE), mean error (ME) and Dice similarity coefficient (DSC) for bones. The dose evaluation consisted of a systematic non-clinical analysis and a clinical recalculation of actually used proton treatment plans. Gamma analysis was performed for non-clinical and clinical treatment plans. For clinical treatment plans also dose to targets and organs at risk (OARs) and normal tissue complication probabilities (NTCP) were compared. CBCT-based sCTs resulted in higher image quality with an average MAE of 40 ± 4 HU and a DSC of 0.95, while for MR-based sCTs a MAE of 65 ± 4 HU and a DSC of 0.89 was observed. Also in clinical proton dose calculations, sCTCBCT achieved higher average gamma pass ratios (2%/2 mm criteria) than sCTMR (96.1% vs. 93.3%). Dose-volume histograms for selected OARs and NTCP-values showed a very small difference between sCTCBCT and sCTMR and a high agreement with the reference pCT. CBCT- and MR-based sCTs have the potential to enable accurate proton dose calculations valuable for daily adaptive PT. Significant image quality differences were observed but did not affect proton dose calculation accuracy in a similar manner. Especially the recalculation of clinical treatment plans showed high agreement with the pCT for both sCTCBCT and sCTMR.

Background and purposeWhen treating patients for esophageal cancer (EC) with photon or proton radiotherapy (RT), breathing motion of the target and neighboring organs may result in deviations from the planned dose distribution. The aim of this study was to evaluate the magnitude and dosimetric impact of breathing motion. Results were based on comparing weekly 4D computed tomography (4D CT) scans with the planning CT, using the diaphragm as an anatomical landmark for EC.Material and methodsA total of 20 EC patients were included in this study. Diaphragm breathing amplitudes and off-sets (changes in position with respect to the planning CT) were determined from delineated left diaphragm structures in weekly 4D CT-scans. The potential dosimetric impact of respiratory motion was shown in several example patients for photon and proton radiotherapy.ResultsVariation in diaphragm amplitudes were relatively small and ranged from 0 to 0.8 cm. However, the measured off-sets were larger, ranging from -2.1 to 1.9 cm. Of the 70 repeat CT-scans, the off-set exceeded the ITV-PTV margin of 0.8 cm during expiration in 4 CT-scans (5.7%) and during inspiration in 13 CT-scans (18.6%). The dosimetric validation revealed under- and overdosages in the VMAT and IMPT plans.ConclusionsDespite relatively constant breathing amplitudes, the variation in the diaphragm position (off-set), and consequently tumor position, was clinically relevant. These motion effects may result in either treatments that miss the target volume, or dose deviations in the form of highly localized over- or underdosed regions.

Purpose: For locally advanced-stage non-small cell lung cancer (NSCLC), inter-fraction target motion variations during the whole time span of a fractionated treatment course are assessed in a large and representative patient cohort. The primary objective is to develop a suitable motion monitoring strategy for pencil beam scanning proton therapy (PBS-PT) treatments of NSCLC patients during free breathing. Methods: Weekly 4D computed tomography (4DCT; 41 patients) and daily 4D cone beam computed tomography (4DCBCT; 10 of 41 patients) scans were analyzed for a fully fractionated treatment course. Gross tumor volumes (GTVs) were contoured and the 3D displacement vectors of the centroid positions were compared for all scans. Furthermore, motion amplitude variations in different lung segments were statistically analyzed. The dosimetric impact of target motion variations and target motion assessment was investigated in exemplary patient cases. Results: The median observed centroid motion was 3.4 mm (range: 0.2–12.4 mm) with an average variation of 2.2 mm (range: 0.1–8.8 mm). Ten of 32 patients (31.3%) with an initial motion 2 mm, 4DCBCT should be considered for motion monitoring due to substantial motion variations observed.

Background Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton dose calculations. Deep learning can be used to correct CT numbers and generate synthetic CTs (sCTs) that can enable CBCT-based proton dose calculations. Purpose In this work, sparse view 4D-CBCTs were converted into 4D-sCT utilizing a deep convolutional neural network (DCNN). 4D-sCTs were evaluated in terms of image quality and dosimetric accuracy to determine if accurate proton dose calculations for adaptive proton therapy workflows of lung cancer patients are feasible. Methods A dataset of 45 thoracic cancer patients was utilized to train and evaluate a DCNN to generate 4D-sCTs, based on sparse view 4D-CBCTs reconstructed from projections acquired with a 3D acquisition protocol. Mean absolute error (MAE) and mean error were used as metrics to evaluate the image quality of single phases and average 4D-sCTs against 4D-CTs acquired on the same day. The dosimetric accuracy was checked globally (gamma analysis) and locally for target volumes and organs-at-risk (OARs) (lung, heart, and esophagus). Furthermore, 4D-sCTs were also compared to 3D-sCTs. To evaluate CT number accuracy, proton radiography simulations in 4D-sCT and 4D-CTs were compared in terms of range errors. The clinical suitability of 4D-sCTs was demonstrated by performing a 4D dose reconstruction using patient specific treatment delivery log files and breathing signals. Results 4D-sCTs resulted in average MAEs of 48.1 +/- 6.5 HU (single phase) and 37.7 +/- 6.2 HU (average). The global dosimetric evaluation showed gamma pass ratios of 92.3% +/- 3.2% (single phase) and 94.4% +/- 2.1% (average). The clinical target volume showed high agreement in D-98 between 4D-CT and 4D-sCT, with differences below 2.4% for all patients. Larger dose differences were observed in mean doses of OARs (up to 8.4%). The comparison with 3D-sCTs showed no substantial image quality and dosimetric differences for the 4D-sCT average. Individual 4D-sCT phases showed slightly lower dosimetric accuracy. The range error evaluation revealed that lung tissues cause range errors about three times higher than the other tissues. Conclusion In this study, we have investigated the accuracy of deep learning-based 4D-sCTs for daily dose calculations in adaptive proton therapy. Despite image quality differences between 4D-sCTs and 3D-sCTs, comparable dosimetric accuracy was observed globally and locally. Further improvement of 3D and 4D lung sCTs could be achieved by increasing CT number accuracy in lung tissues.

4D multi-image-based (4D

Purpose/objective(s) Calculation of tumor control probability (TCP) and normal tissue complication probability (NTCP) is becoming increasingly relevant for optimizing treatment strategies, for example the selection of patients for proton therapy. While radiobiological models are typically built and evaluated on the planned treatment dose, no consensus exists for their evaluation in the context of varying patient anatomy during treatment. For example, different adaptive strategies can lead to different expected treatment outcomes for the same planned dose. This shows that TCP/NTCP needs to be calculated from the cumulative treatment dose resulting from multiple fraction doses and patient geometries. In this study, different methods of applying TCP and NTCP models to treatments with anatomical changes are developed and compared. These methods were evaluated on an example of locally advanced non-small cell lung cancer (NSCLC) patients using two extreme scenarios: no adaption vs online daily adaptive proton therapy (DAPT). Materials/methods Three methods to calculate TCP/NTCP in the context of anatomical changes were compared: (I) based on the accumulated treatment doses. Six different deformable image registration (DIR) algorithms were used to accumulate the dose, then the TCP/NTCP was calculated on all accumulated doses showing the variation due to the DIR. (II) based on the cumulative effective uniform dose (EUD) of each fraction. (III) based on each fraction dose directly, permitting an evaluation of the mean and variation of TCP/NTCP during treatment. To test and compare these methods, proton therapy treatment plans were generated on deep inspiration breath-hold (DIBH) planning CTs for 5 NSCLC patients (66 Gy-RBE, 33 fractions). Non-adapted and DAPT treatment doses were created by recalculating and reoptimizing these plans on nine repeated CTs. TCP/NTCP calculations were performed with all three methods. Results All methods showed consistent results between no adaption and DAPT. Two patients showed substantial TCP reductions up to 33% without adaption. Three patients, despite anatomical changes and dose differences, did not show a reduced calculated TCP with all methods. For most patients, NTCP differences between DAPT and no adaption were moderate, but one showed improvement in predicted 2-year survival based on heart toxicity with DAPT. Furthermore, the absolute NTCP calculated with method (I) showed variations of up to 7% depending on the DIR algorithm used for dose accumulation. Conclusion The three proposed methods of calculating clinical outcome based on treatment doses showed consistent result between DAPT and non-adapted treatments. Three patients showed benefits with DAPT, so the calculated NTCP could be reduced or calculated TCP maintained. For two patients the dose differences with adaption did not translate in clinically relevant effects. The proposed outcome calculation methods enable a more realistic quantification of TCP/NTCP of different adaptive strategies.

PURPOSE: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone-beam CT (CBCT) can provide these daily images, but x-ray scattering limits CBCT-image quality and hampers dose calculation accuracy. The purpose of this study was to generate CBCT-based synthetic CTs using a deep convolutional neural network (DCNN) and investigate image quality and clinical suitability for proton dose calculations in lung cancer patients.METHODS: A dataset of 33 thoracic cancer patients, containing CBCTs, same-day repeat CTs (rCT), planning-CTs (pCTs) and clinical proton treatment plans, was used to train and evaluate a DCNN with and without a pCT-based correction method. Mean absolute error (MAE), mean error (ME), peak signal-to-noise ratio and structural similarity were used to quantify image quality. The evaluation of clinical suitability was based on recalculation of clinical proton treatment plans. Gamma pass ratios, mean dose to target volumes and organs at risk, and normal tissue complication probabilities (NTCP) were calculated. Furthermore, proton radiography simulations were performed to assess the HU-accuracy of sCTs in terms of range errors.RESULTS: On average, sCTs without correction resulted in a MAE of 34±6 HU and ME of 4±8 HU. The correction reduced the MAE to 31±4HU (ME to 2±4HU). Average 3%/3mm gamma pass ratios increased from 93.7% to 96.8%, when the correction was applied. The patient specific correction reduced mean proton range errors from 1.5 to 1.1 mm. Relative mean target dose differences between sCTs and rCT were below ±0.5% for all patients and both synthetic CTs (with/without correction). NTCP values showed high agreement between sCTs and rCT (CONCLUSION: CBCT-based sCTs can enable accurate proton dose calculations for APT of lung cancer patients. The patient specific correction method increased the image quality and dosimetric accuracy but had only a limited influence on clinically relevant parameters. This article is protected by copyright. All rights reserved.

For radiation therapy, it is crucial to ensure that the delivered dose matches the planned dose. Errors in the dose calculations done in the treatment planning system (TPS), treatment delivery errors, other software bugs or data corruption during transfer might lead to significant differences between predicted and delivered doses. As such, patient specific quality assurance (QA) of dose distributions, through experimental validation of individual fields, is necessary. These measurement based approaches, however, are performed with 2D detectors, with limited resolution and in a water phantom. Moreover, they are work intensive and often impose a bottleneck to treatment efficiency. In this work, we investigated the potential to replace measurement-based approach with a simulation-based patient specific QA using a Monte Carlo (MC) code as independent dose calculation engine in combination with treatment log files. Our developed QA platform is composed of a web interface, servers and computation scripts, and is capable to autonomously launch simulations, identify and report dosimetric inconsistencies. To validate the beam model of independent MC engine, in-water simulations of mono-energetic layers and 30 SOBP-type dose distributions were performed. Average Gamma passing ratio 99 ± 0.5% for criteria 2%/2 mm was observed. To demonstrate feasibility of the proposed approach, 10 clinical cases such as head and neck, intracranial indications and craniospinal axis, were retrospectively evaluated via the QA platform. The results obtained via QA platform were compared to QA results obtained by measurement-based approach. This comparison demonstrated consistency between the methods, while the proposed approach significantly reduced in-room time required for QA procedures.

Purpose A major burden of introducing an online daily adaptive proton therapy (DAPT) workflow is the time and resources needed to correct the daily propagated contours. In this study, we evaluated the dosimetric impact of neglecting the online correction of the propagated contours in a DAPT workflow. Material and methods For five NSCLC patients with nine repeated deep-inspiration breath-hold CTs, proton therapy plans were optimised on the planning CT to deliver 60 Gy-RBE in 30 fractions. All repeated CTs were registered with six different clinically used deformable image registration (DIR) algorithms to the corresponding planning CT. Structures were propagated rigidly and with each DIR algorithm and reference structures were contoured on each repeated CT. DAPT plans were optimised with the uncorrected, propagated structures (propagated DAPT doses) and on the reference structures (ideal DAPT doses), non-adapted doses were recalculated on all repeated CTs. Results Due to anatomical changes occurring during the therapy, the clinical target volume (CTV) coverage of the non-adapted doses reduces on average by 9.7% (V95) compared to an ideal DAPT doses. For the propagated DAPT doses, the CTV coverage was always restored (average differences in the CTV V95 < 1% compared to the ideal DAPT doses). Hotspots were always reduced with any DAPT approach. Conclusion For the patients presented here, a benefit of online DAPT was shown, even if the daily optimisation is based on propagated structures with some residual uncertainties. However, a careful (offline) structure review is necessary and corrections can be included in an offline adaption., Radiotherapy & Oncology, 159, ISSN:0167-8140, ISSN:1879-0887

In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods to correct CBCTs and create synthetic CTs that are suitable for proton dose calculations. CBCTs, planning CTs and repeated CTs (rCT) from 33 H&N cancer patients were used to compare a deep convolutional neural network (DCNN), deformable image registration (DIR) and an analytical image-based correction method (AIC) for synthetic CT (sCT) generation. Image quality of sCTs was evaluated by comparison with a same-day rCT, using mean absolute error (MAE), mean error (ME), Dice similarity coefficient (DSC), structural non-uniformity (SNU) and signal/contrast-to-noise ratios (SNR/CNR) as metrics. Dosimetric accuracy was investigated in an intracranial setting by performing gamma analysis and calculating range shifts. Neural network-based sCTs resulted in the lowest MAE and ME (37/2 HU) and the highest DSC (0.96). While DIR and AIC generated images with a MAE of 44/77 HU, a ME of −8/1 HU and a DSC of 0.94/0.90. Gamma and range shift analysis showed almost no dosimetric difference between DCNN and DIR based sCTs. The lower image quality of AIC based sCTs affected dosimetric accuracy and resulted in lower pass ratios and higher range shifts. Patient-specific differences highlighted the advantages and disadvantages of each method. For the set of patients, the DCNN created synthetic CTs with the highest image quality. Accurate proton dose calculations were achieved by both DCNN and DIR based sCTs. The AIC method resulted in lower image quality and dose calculation accuracy was reduced compared to the other methods.

Four-dimensional dose calculation (4D-DC) is crucial for predicting the dosimetric outcome in the presence of intra-fractional organ motion. Time-resolved dosimetry can provide significant insights into 4D pencil beam scanning dose accumulation and is therefore irreplaceable for benchmarking 4D-DC. In this study a novel approach of time-resolved dosimetry using five PinPoint ionization chambers (ICs) embedded in an anthropomorphic dynamic phantom was employed and validated against beam delivery details. Beam intensity variations as well as the beam delivery time structure were well reflected with an accuracy comparable to the temporal resolution of the IC measurements. The 4D dosimetry approach was further applied for benchmarking the 4D-DC implemented in the RayStation 6.99 treatment planning system. Agreement between computed values and measurements was investigated for (i) partial doses based on individual breathing phases, and (ii) temporally distributed cumulative doses. For varied beam delivery and patient-related parameters the average unsigned dose difference for (i) was 0.04 +/- 0.03 Gy over all considered IC measurement values, while the prescribed physical dose was 2 Gy. By implementing (ii), a strong effect of the dose gradient on measurement accuracy was observed. The gradient originated from scanned beam energy modulation and target motion transversal to the beam. Excluding measurements in the high gradient the relative dose difference between measurements and 4D-DCs for a given treatment plan at the end of delivery was 3.5% on average and 6.6% at maximum over measurement points inside the target. Overall, the agreement between 4D dose measurements in the moving phantom and retrospective 4D-DC was found to be comparable to the static dose differences for all delivery scenarios. The presented 4D-DC has been proven to be suitable for simulating treatment deliveries with various beam- as well as patient-specific parameters and can therefore be employed for dosimetric validation of different motion mitigation techniques.

PURPOSE: Pencil beam scanned proton therapy (PBS-PT) treatment quality might be compromised by interplay and motion effects. Via fraction-wise reconstruction of 4D dose distributions and dose accumulation, we assess the clinical relevance of motion related target dose degradation in thoracic cancer patients.METHODS AND MATERIALS: For the ten thoracic patients (Hodgkin lymphoma and non-small cell lung cancer) treated at our proton therapy facility, daily breathing pattern records, treatment delivery log-files and weekly repeated 4DCTs were collected. Patients exhibited point-max target motion of up to 20 mm. They received robustly optimized treatment plans, delivered with five-times rescanning in fractionated regimen. Treatment delivery records were used to reconstruct 4D dose distributions and the accumulated treatment course dose per patient. Fraction-wise target dose degradations were analyzed and the accumulated treatment course dose, representing an estimation of the delivered dose, was compared with the prescribed dose.RESULTS: No clinically relevant loss of target dose homogeneity was found in the fraction-wise reconstructed 4D dose distributions. Overall, in 97% of all reconstructed fraction doses, D98 remained within 5% from the prescription dose. The V95 of accumulated treatment course doses was higher than 99.7% for all ten patients.CONCLUSIONS: 4D dose reconstruction and accumulation enables the clinical estimation of actual exhibited interplay and motion effects. In the patients considered here, the loss of homogeneity caused by interplay and organ motion did not show systematic pattern and smeared out throughout the course of fractionated PBS-PT treatment. Dose degradation due to anatomical changes showed to be more severe and triggered treatment adaptations for five patients.

Purpose The treatment of moving targets with scanned proton beams is challenging. For motion mitigation, an Active Breathing Coordinator (ABC) can be used to assist breath-holding. The delivery of pencil beam scanning fields often exceeds feasible breath-hold durations, requiring high breath-hold reproducibility. We evaluated the robustness of scanned proton therapy against anatomical uncertainties when treating nonsmall-cell lung cancer (NSCLC) patients during ABC controlled breath-hold. Methods Four subsequent MRIs of five healthy volunteers (3 male, 2 female, age: 25-58, BMI: 19-29) were acquired under ABC controlled breath-hold during two simulated treatment fractions, providing both intrafractional and interfractional information about breath-hold reproducibility. Deformation vector fields between these MRIs were used to deform CTs of five NSCLC patients. Per patient, four or five cases with different tumor locations were modeled, simulating a total of 23 NSCLC patients. Robustly optimized (3 and 5 mm setup uncertainty respectively and 3% density perturbation) intensity-modulated proton plans (IMPT) were created and split into subplans of 20 s duration (assumed breath-hold duration). A fully fractionated treatment was recalculated on the deformed CTs. For each treatment fraction the deformed CTs representing multiple breath-hold geometries were alternated to simulate repeated ABC breath-holding during irradiation. Also a worst-case scenario was simulated by recalculating the complete treatment plan on the deformed CT scan showing the largest deviation with the first deformed CT scan, introducing a systematic error. Both the fractionated breath-hold scenario and worst-case scenario were dosimetrically evaluated. Results Looking at the deformation vector fields between the MRIs of the volunteers, up to 8 mm median intra- and interfraction displacements (without outliers) were found for all lung segments. The dosimetric evaluation showed a median difference in D-98% between the planned and breath-hold scenarios of -0.1 Gy (range: -4.1 Gy to 2.0 Gy). D-98% target coverage was more than 57.0 Gy for 22/23 cases. The D-1 cc of the CTV increased for 21/23 simulations, with a median difference of 0.9 Gy (range: -0.3 to 4.6 Gy). For 14/23 simulations the increment was beyond the allowed maximum dose of 63.0 Gy, though remained under 66.0 Gy (110% of the prescribed dose of 60.0 Gy). Organs at risk doses differed little compared to the planned doses (difference in mean doses

Proton therapy is affected by range uncertainty, which is partly caused by an ambiguous conversion from x-ray attenuation to proton stopping power. CT calibration curves, or Hounsfield look-up tables (HLUTs), are institution-specific and may be a source of systematic errors in treatment planning. A range probing method to verify, optimize and validate HLUTs for proton treatment is proposed. An initial HLUT was determined according to the stoichiometric approach. For HLUT validation, three types of animal tissue phantoms were prepared: a pig's head, 'thorax' and femur. CT scans of the phantoms were taken and a structure, simulating a water slab, was added on the scan distal to the phantoms to mimic the detector used for integral depth-dose measurements. The CT scans were imported into the TPS to calculate individual pencil beams directed through the phantoms. The phantoms were positioned at the therapy system isocenter using x-ray imaging. Shoot-through pencil beams were delivered, and depth-dose profiles were measured using a multi-layer ionization chamber. Measured depth-dose curves were compared to the calculated curves and the range error per spot was determined. Based on the water equivalent path length (WEPL) of individual spot, a range error margin was defined. Ratios between measured error and theoretical margin were calculated per spot. The HLUT optimization was performed by identifying systematic shifts of the mean range error per phantom and minimizing the ratios between range errors and uncertainty margins. After optimization, the ratios of the actual range error and the uncertainty margin over the complete data set did not exceed 0.75 (1.5 SD), indicating that the actual errors are covered by the theoretical uncertainty recipe. The feasibility of using range probing to assess range errors was demonstrated. The theoretical uncertainty margins in the institution-specific setting potentially may be reduced by ∼25%.

Purpose: The introduction of advanced treatment techniques in proton therapy, such as intensity-modulated proton therapy, leads to an increased need for patient-specific quality assurance, especially an accurate treatment plan verification becomes inevitable. In this study, signal theoretical analysis of dose distributions in scanned proton therapy is performed to investigate the feasibility and limits of two-dimensional (2D) detector arrays for treatment plan verification. Methods: 2D detector arrays are characterized by two main aspects: the distance between the single detectors on the array or the sampling frequency; and the lateral response functions of a single detector. The analysis is based on single spots, reference fields and on measured and calculated dose distributions of typical intensity-modulated proton therapy treatment plans with and without range shifter. Measurements were performed with Gafchromic EBT3 films (Ashland Speciality Ingredients G.P., Bridgewater, NJ, USA), the MatriXX PT detector array (IBA Dosimetry, Schwarzenbruck, Germany) and the OCTAVIUS detector array 1500XDR (PTW-Freiburg, Germany) at an IBA Proteus PLUS proton therapy system (Ion Beam Applications, Louvain-la-Neuve, Belgium). Dose calculations were performed with the treatment planning system RayStation 6 or 8 (RaySearch Laboratories, Sweden). Results: The Fourier analysis of the data of the treatment planning system and film measurements show maximum frequencies of 0.06/mm for the plan with range shifter and 0.083/mm for the plan without range shifter. According to the Nyquist theorem, this corresponds to minimum required sampling distances of 8.3 and 6 mm, respectively. By comparison, the sampling distances of the arrays of 7.6 mm (MatriXX PT) and 7.1 mm (OD1500XDR) are sufficient to reconstruct the dose distributions adequately from measurements if range shifters are used, whereas some fields of the plans without range shifter violated the Nyquist requirement. The lateral dose response functions of the single detectors within the arrays have clearly higher frequencies than the treatment plans and thus the volume effect only slightly influences the measurements. Consequently, the array measurements show high gamma passing rates with at least 96 % and a good agreement between the investigated line profiles. Conclusion: The results indicate that the detector dimensions and sampling distances of the arrays are in most studied cases adequate not to substantially influence the measurement process when they are used for analyzing typical intensity-modulated proton therapy treatment plans. Nevertheless, clinical conditions have been identified, for instance treatment plans without range shifter, under which the Nyquist theorem is violated such that a full representation of the dose distributions with the measurements is not feasible. In these cases, analysis of measurements is limited to pointwise comparisons.

The purpose of this study was to develop a method enabling synthetic computed tomography (sCT) generation of the whole abdomen using magnetic resonance imaging (MRI) images of pediatric patients with abdominal tumors. The proposed method relies on an automatic atlas-based segmentation of bone and lungs followed by an MRI intensity to synthetic Hounsfield unit conversion. Separate conversion algorithms were used for bone, lungs and soft-tissue. Rigidly registered CT and T2-weighted MR images of 30 patients in treatment position and with the same field of view were used for the evaluation of the atlas and the conversion algorithms. The dose calculation accuracy of the generated sCTs was verified for volumetric modulated arc therapy (VMAT) and pencil beam scanning (PBS). VMAT and PBS plans were robust optimized on an internal target volume (ITV) against a patient set-up uncertainty of 5 mm. Average differences between CT and sCT dose calculations for the ITV V95% were 0.5% (min 0.0%; max 5.0%) and 0.0% (min -0.1%; max 0.1%) for VMAT and PBS dose distributions, respectively. Average differences for the mean dose to the organs at risk were

Motion-induced range changes and incorrectly placed dose spots strongly affect the quality of pencil-beam-scanned (PBS) proton therapy, especially in thoracic tumour sites, where density changes are large. Thus motion-mitigation techniques are necessary, which must be validated in a realistic patient-like geometry. We report on the development and characterisation of a dynamic, anthropomorphic, thorax phantom that can realistically mimic thoracic motions and anatomical features for verifications of proton and photon 4D treatments. The presented phantom is of an average thorax size, and consists of inflatable, deformable lungs surrounded by a skeleton and skin. A mobile 'tumour' is embedded in the lungs in which dosimetry devices (such as radiochromic films) can be inserted. Motion of the tumour and deformation of the thorax is controlled via a custom made pump system driving air into and out of the lungs. Comprehensive commissioning tests have been performed to evaluate the mechanical performance of the phantom, its visibility on CT and MR imaging and its feasibility for dosimetric validation of 4D proton treatments. The phantom performed well on both regular and irregular pre-programmed breathing curves, reaching peak-to-peak amplitudes in the tumour of 90% in the central planes of the target. The results of this study demonstrate that this anthropomorphic thorax phantom is suitable for imaging and dosimetric studies in a thoracic geometry closely-matched to lung cancer patients under realistic motion conditions.

Purpose The safe clinical implementation of pencil beam scanning (PBS) proton therapy for lung tumors is complicated by the delivery uncertainties caused by breathing motion. The purpose of this feasibility study was to investigate whether a voluntary breath-hold technique could limit the delivery uncertainties resulting from interfractional motion. Methods and Materials Data from 15 patients with peripheral lung tumors previously treated with stereotactic radiation therapy were included in this study. The patients had 1 computed tomographic (CT) scan in voluntary breath-hold acquired before treatment and 3 scans during the treatment course. PBS proton treatment plans with 2 fields (2F) and 3 fields (3F), respectively, were calculated based on the planning CT scan and subsequently recalculated on the 3 repeated CT scans. Recalculated plans were considered robust if the V 95% (volume receiving ≥95% of the prescribed dose) of the gross target volume (GTV) was within 5% of what was expected from the planning CT data throughout the simulated treatment. Results A total of 14/15 simulated treatments for both 2F and 3F met the robustness criteria. Reduced V 95% was associated with baseline shifts (2F, P =.056; 3F, P =.008) and tumor size (2F, P =.025; 3F, P =.025). Smaller tumors with large baseline shifts were also at risk for reduced V 95% (interaction term baseline/size: 2F, P =.005; 3F, P =.002). Conclusions The breath-hold approach is a realistic clinical option for treating lung tumors with PBS proton therapy. Potential risk factors for reduced V 95% are small targets in combination with large baseline shifts. On the basis of these results, the baseline shift of the tumor should be monitored (eg, through image guided therapy), and appropriate measures should be taken accordingly. The intrafractional motion needs to be investigated to confirm that the breath-hold approach is robust.

Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams' eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric and layered rescanning have been observed as a function of increasing number of re-scans. However, once gating and rescanning is combined, HI to within 2% of the static plan could be achieved in the clinical target volume, with only moderately prolonged treatment times, irrespective of the rescanning strategy used. Moreover, these results are independent of the motion surrogate used. In conclusion, our results suggest image guided beam gating, combined with rescanning, is a feasible, effective and efficient motion mitigation approach for PBS-based liver tumour treatments.

The treatment of mobile targets with scanned particle beams is challenging, and the effects of motion will be especially pronounced in hypo-fractionated treatment regimes due to the lack of statistical smoothing through fractionation and the prolonged delivery times per session. Therefore, motion mitigation techniques will play a major role for radiosurgery approaches. This article concentrates on the motion mitigation technique called rescanning. It alludes the existence of many scanning/rescanning flavors and raises awareness of the importance of an optimized flavor choice. Furthermore, it is discussed that rescanning can compensate for the lack of statistical wash-out, target dose conformity, however, will remain degraded. Therefore, especially in the context of radiosurgery, rescanning should be combined with other motion mitigation techniques like breath hold, gating and/or tracking.

In this review article we emphasize the importance of "imaging" and "image guidance" in advanced particle therapy from a clinical point of view. Although the image-guided radiotherapy (IGRT) technology used for photon and particle therapy is closely similar, the focus of its application in the two modalities differs. Here, we emphasize the challenges of IGRT for charged particle beams. Radiological Physics and Technology (RTPE) readers interested in the common technologies of IGRT for photons and protons are referred to the plentiful articles already published. Our present deeper insight into IGRT arose through the collaboration of two particle therapy centers, the National Institute of Radiological Sciences (NIRS) in Japan and the Paul Scherrer Institute (PSI) in Switzerland. We believe that international collaboration in rapidly developing fields such as IGRT provides a broad perspective over a wide range of the uses of such technology.

International audience; Accurate knowledge of organ location and tissue attenuation properties are the two essential components to perform radiotherapy treatment planning (RTP). Computed tomography (CT) has been the modality of choice for RTP as it easily provides electron density information. However, its low soft tissue contrast limits the accuracy of organ delineation. On the contrary, magnetic resonance (MR) provides images with excellent soft tissue contrast but its use for RTP is limited by the fact that it does not readily provide tissue attenuation information.In this work we propose a multi-atlas information propagation scheme that jointly segments the organs at risk and generates pseudo CT data from MR images. We demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, bypassing the need for CT scan for accurate RTP.

The most advanced delivery technique for proton radiotherapy is active spot scanning. So far, predominantly static targets have been treated with active spot scanning, since mobile targets in combination with dynamic treatment delivery can lead to interplay effects, causing inhomogeneous dose distributions. One way to mitigate motion effects is re-scanning. In this study we investigate the effectiveness of re-scanning in relation to different plan parameters (number of fields, field directions, number of re-scans) as well as in respect to different motion parameters (motion amplitude, motion starting phase). A systematic study was performed for three liver patients, for which ten different plans have been calculated, respectively. The treatment plans were evaluated for three different scenarios (static, motion/single-scan-delivery, motion/re-scanned-delivery). The choice of motion parameters was based on an evaluation of the 4D CT data sets of the three patients. It is shown that the effect of motion/re-scanning per fraction is largest the fewer fields per plan are used and the more the field direction differs from the main motion direction. For amplitudes up to 6 mm, re-scanning may not be required if multiple fields are used, since only dose blurring effects appear that cannot be compensated by re-scanning. For larger motion amplitudes two planning strategies are proposed.

International audience

Since 2009, a 4D treatment planning workshop has taken place annually, gathering researchers working on the treatment of moving targets, mainly with scanned ion beams. Topics discussed during the workshops range from problems of time resolved imaging, the challenges of motion modelling, the implementation of 4D capabilities for treatment planning, up to different aspects related to 4D dosimetry and treatment verification.This report gives an overview on topics discussed at the 4D workshops in 2014 and 2015. It summarizes recent findings, developments and challenges in the field and discusses the relevant literature of the recent years. The report is structured in three parts pointing out developments in the context of understanding moving geometries, of treating moving targets and of 4D quality assurance (QA) and 4D dosimetry.The community represented at the 4D workshops agrees that research in the context of treating moving targets with scanned ion beams faces a crucial phase of clinical translation. In the coming years it will be important to define standards for motion monitoring, to establish 4D treatment planning guidelines and to develop 4D QA tools. These basic requirements for the clinical application of scanned ion beams to moving targets could e.g. be determined by a dedicated ESTRO task group.Besides reviewing recent research results and pointing out urgent needs when treating moving targets with scanned ion beams, the report also gives an outlook on the upcoming 4D workshop organized at the University Medical Center Groningen (UMCG) in the Netherlands at the end of 2016. (C) 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Several recent developments in linear accelerator-based radiation therapy (RT) such as fast multileaf collimators, accelerated intensity modulation paradigms like volumeric modulated arc therapy and flattening filter-free (FFF) high-dose-rate therapy have dramatically shortened the duration of treatment fractions. Deliverable photon dose distributions have approached physical complexity limits as a consequence of precise dose calculation algorithms and online 3-dimensional image guided patient positioning (image guided RT). Simultaneously, beam quality and treatment speed have continuously been improved in particle beam therapy, especially for scanned particle beams. Applying complex treatment plans with steep dose gradients requires strategies to mitigate and compensate for motion effects in general, particularly breathing motion. Intrafractional breathing-related motion results in uncertainties in dose delivery and thus in target coverage. As a consequence, generous margins have been used, which, in turn, increases exposure to organs at risk. Particle therapy, particularly with scanned beams, poses additional problems such as interplay effects and range uncertainties. Among advanced strategies to compensate breathing motion such as beam gating and tracking, deep inspiration breath hold (DIBH) gating is particularly advantageous in several respects, not only for hypofractionated, high single-dose stereotactic body RT of lung, liver, and upper abdominal lesions but also for normofractionated treatment of thoracic tumors such as lung cancer, mediastinal lymphomas, and breast cancer. This review provides an in-depth discussion of the rationale and technical implementation of DIBH gating for hypofractionated and normofractionated RT of intrathoracic and upper abdominal tumors in photon and proton RT.

International audience; In this work, we propose to tackle the problem of magnetic resonance (MR)-based radiotherapy treatment planning in the head & neck area by synthesising computed tomography (CT) from MR images using an iterative multi-atlas approach. The proposed method relies on pre-acquired pairs of non-rigidly aligned T2-weighted MRI and CT images of the neck. To synthesise a pseudo CT, all the MRIs in the database are first registered to the target MRI using a robust affine followed by a deformable registration. An initial pseudo CT is obtained by fusing the mapped atlases according to their morphological similarity to the target. This initial pseudo CT is then combined with the target MR image in order to improve both the registration and fusion stages and refine the synthesis in the bone region.Results showed that the proposed iterative CT synthesis algorithm is able to generate pseudo CT images in a challenging region for registration algorithms. We demonstrate that the robust affine decreases the overall absolute error compared to a single affine transformation, mainly in images with small axial field-of-view, whilst the bone refinement process further reduces the error in the bone region, increasing image sharpness.