Effect of continuous positive airway pressure administration during lung stereotactic ablative radiotherapy: a comparative planning study.

PURPOSE: By increasing lung volume and decreasing respiration-induced tumour motion amplitude, administration of continuous positive airway pressure (CPAP) during stereotactic ablative radiotherapy (SABR) could allow for better sparing of the lungs and heart. In this study, we evaluated the effect of CPAP on lung volume, tumour motion amplitude and baseline shift, as well as the dosimetric impact of the strategy. METHODS: Twenty patients with lung tumours referred for SABR underwent 4D-computed tomography (CT) scans with and without CPAP (CPAP/noCPAP) at two timepoints (T0/T1). First, CPAP and noCPAP scans were compared for lung volume, tumour motion amplitude, and baseline shift. Next, CPAP and noCPAP treatment plans were computed and compared for lung dose parameters (mean lung dose (MLD), lung volume receiving 20 Gy (V20Gy), 13 Gy (V13Gy), and 5 Gy (V5Gy)) and mean heart dose (MHD). RESULTS: On average, CPAP increased lung volume by 8.0% (p < 0.001) and 6.3% (p < 0.001) at T0 and T1, respectively, but did not change tumour motion amplitude or baseline shift. As a result, CPAP administration led to an absolute decrease in MLD, lung V20Gy, V13Gy and V5Gy of 0.1 Gy (p = 0.1), 0.4% (p = 0.03), 0.5% (p = 0.04) and 0.5% (p = 0.2), respectively, while having no significant influence on MHD. CONCLUSIONS: In patients referred for SABR for lung tumours, CPAP increased lung volume without modifying tumour motion or baseline shift. As a result, CPAP allowed for a slight decrease in radiation dose to the lungs, which is unlikely to be clinically significant.

An individualized radiation dose escalation trial in non-small cell lung cancer based on FDG-PET imaging.

AIM: The aim of the study was to assess the feasibility of an individualized 18F fluorodeoxyglucose positron emission tomography (FDG-PET)-guided dose escalation boost in non-small cell lung cancer (NSCLC) patients and to assess its impact on local tumor control and toxicity. PATIENTS AND METHODS: A total of 13 patients with stage II-III NSCLC were enrolled to receive a dose of 62.5 Gy in 25 fractions to the CT-based planning target volume (PTV; primary turmor and affected lymph nodes). The fraction dose was increased within the individual PET-based PTV (PTVPET) using intensity modulated radiotherapy (IMRT) with a simultaneous integrated boost (SIB) until the predefined organ-at-risk (OAR) threshold was reached. Tumor response was assessed during follow-up by means of repeat FDG-PET/computed tomography. Acute and late toxicity were recorded and classified according to the CTCAE criteria (Version 4.0). Local progression-free survival was determined using the Kaplan-Meier method. RESULTS: The average dose to PTVPET reached 89.17 Gy for peripheral and 75 Gy for central tumors. After a median follow-up period of 29 months, seven patients were still alive, while six had died (four due to distant progression, two due to grade 5 toxicity). Local progression was seen in two patients in association with further recurrences. One and 2-year local progression free survival rates were 76.9% and 52.8%, respectively. Three cases of acute grade 3 esophagitis were seen. Two patients with central tumors developed late toxicity and died due to severe hemoptysis. CONCLUSION: These results suggest that a non-uniform and individualized dose escalation based on FDG-PET in IMRT delivery is feasible. The doses reached were higher in patients with peripheral compared to central tumors. This strategy enables good local control to be achieved at acceptable toxicity rates. However, dose escalation in centrally located tumors with direct invasion of mediastinal organs must be performed with great caution in order to avoid severe late toxicity.

Correlation analysis of [18F]fluorodeoxyglucose and [18F]fluoroazomycin arabinoside uptake distributions in lung tumours during radiation therapy.

BACKGROUND: PET-guided dose painting (DP) aims to target radioresistant tumour regions in order to improve radiotherapy (RT) outcome. Besides the well-known [18F]fluorodeoxyglucose (FDG), the hypoxia positron emission tomography (PET) tracer [18F]fluoroazomycin arabinoside (FAZA) could provide further useful information to guide the radiation dose prescription. In this study, we compare the spatial distributions of FDG and FAZA PET uptakes in lung tumours. MATERIAL AND METHODS: Fourteen patients with unresectable lung cancer underwent FDG and FAZA 4D-PET/CT on consecutive days at three time-points: prior to RT (pre), and during the second (w2), and the third (w3) weeks of RT. All PET/CT were reconstructed in their time-averaged midposition (MidP). The metabolic tumour volume (MTV: FDG standardised uptake value (SUV) > 50% SUVmax), and the hypoxic volume (HV: FAZA SUV > 1.4) were delineated within the gross tumour volume (GTVCT). FDG and FAZA intratumoral PET uptake distributions were subsequently pairwise compared, using both volume-, and voxel-based analyses. RESULTS: Volume-based analysis showed large overlap between MTV and HV: median overlapping fraction was 0.90, 0.94 and 0.94, at the pre, w2 and w3 time-points, respectively. Voxel-wise analysis between FDG and FAZA intratumoral PET uptake distributions showed high correlation: median Spearman's rank correlation coefficient was 0.76, 0.77 and 0.76, at the pre, w2 and w3 time-points, respectively. Interestingly, tumours with high FAZA uptake tended to show more similarity between FDG and FAZA intratumoral uptake distributions than those with low FAZA uptake. CONCLUSIONS: In unresectable lung carcinomas, FDG and FAZA PET uptake distributions displayed unexpectedly strong similarity, despite the distinct pathways targeted by these tracers. Hypoxia PET with FAZA brought very little added value over FDG from the perspective of DP in this population.

Evolution of [18F]fluorodeoxyglucose and [18F]fluoroazomycin arabinoside PET uptake distributions in lung tumours during radiation therapy.

BACKGROUND: Dose painting (DP) aims to improve radiation therapy (RT) outcome by targeting radioresistant tumour regions identified through functional imaging, e.g., positron emission tomography (PET). Importantly, the expected benefit of DP relies on the ability of PET imaging to identify tumour areas which could be consistently targeted throughout the treatment. In this study, we analysed the spatial stability of two potential DP targets in lung cancer patients undergoing RT: the tumour burden surrogate [18F]fluorodeoxyglucose (FDG) and the hypoxia surrogate [18F]fluoroazomycin arabinoside (FAZA). MATERIALS AND METHODS: Thirteen patients with unresectable lung tumours underwent FDG and FAZA 4D-PET/CT before (pre), and during the second (w2) and third (w3) weeks of RT. All PET/CT were reconstructed in their time-averaged midposition (MidP) for further analysis. The metabolic tumour volume (MTV: FDG standardised uptake value (SUV) > 50% SUVmax) and the hypoxic volume (HV: FAZA SUV >1.4) were delineated within the gross tumour volume (GTVCT). The stability of FDG and FAZA PET uptake distributions during RT was subsequently assessed through volume-overlap analysis and voxel-based correlation analysis. RESULTS: The volume-overlap analysis yielded median overlapping fraction (OF) of 0.86 between MTVpre and MTVw2 and 0.82 between MTVpre and MTVw3. In patients with a detectable HV, median OF was 0.82 between HVpre and HVw2 and 0.90 between HVpre and HVw3. The voxel-based correlation analysis yielded median Spearman's correlation coefficient (rS) of 0.87 between FDGpre and FDGw2 and 0.83 between FDGpre and FDGw3. Median rS was 0.78 between FAZApre and FAZAw2 and 0.79 between FAZApre and FAZAw3. CONCLUSIONS: FDG and FAZA PET uptake distributions were spatially stable during the 3 first weeks of RT in patients with unresectable lung cancer, both based on volume- and voxel-based indicators. This might allow for a consistent targeting of high FDG or FAZA PET uptake regions as part of a DP strategy.

Methodology for adaptive and robust FDG-PET escalated dose painting by numbers in head and neck tumors.

OBJECTIVE: To develop a methodology for using FDG PET/CT in adaptive dose painting by numbers (DPBN) in head and neck squamous cell carcinoma (HNSCC) patients. Issues related to noise in PET and treatment robustness against geometric errors are addressed. METHODS: Five patients with locally advanced HNSCC scheduled for chemo-radiotherapy were imaged with FDG-PET/CT at baseline and 2-3 times during radiotherapy (RT). The GTVPET was segmented with a gradient-based method. A double median filter reduces the impact of noise in the PET uptake-to-dose conversion. Filtered FDG uptake values were linearly converted into a voxel-by-voxel prescription from 70 (median uptake) to 86 Gy (highest uptake). A PTVPET was obtained by applying a dilation of 2.5 mm to the entire prescription. Seven iso-uptake thresholds led to seven sub-levels compatible with the Tomotherapy HiArt(®) Treatment Planning System. Planning aimed to deliver a median dose of 56 Gy and 70 Gy in 35 fractions on the elective and therapeutic PTVs, respectively. Plan quality was assessed with quality volume histogram (QVH). At each time point, plans were generated with a total of 3-4 plans for each patient. Deformable image registration was used for automatic contour propagation and dose summation of the 3 or 4 treatment plans (MIMvista(®)). RESULTS: GTVPET segmentations were performed successfully until week 2 of RT but failed in two patients at week 3. QVH analysis showed high conformity for all plans (mean VQ = 0.95 93%; mean VQ = 1.05 3.9%; mean QF 2.2%). Good OAR sparing was achieved while keeping high plan quality. CONCLUSION: Our results show that adaptive FDG-PET-based escalated dose painting in patients with locally advanced HNSCC is feasible while respecting strict dose constraints to organs at risk. Clinical studies must be conducted to evaluate toxicities and tumor response of such a strategy.

Generation of prescriptions robust against geometric uncertainties in dose painting by numbers.

BACKGROUND: In the context of dose painting by numbers delivered with intensity-modulated radiotherapy, the robustness of dose distributions against geometric uncertainties can be ensured by robust optimization. As robust optimization is seldom available in treatment planning systems (TPS), we propose an alternative method that reaches the same goal by modifying the heterogeneous dose prescription (based on (18)FDG-PET) and guarantees coverage in spite of systematic and random errors with known standard deviations Σ and σ, respectively. MATERIAL AND METHODS: The objective was that 95% of all voxels in the GTVPET received at least 95% of the prescribed dose despite geometric errors. The prescription was modified by a geometric dilation of αΣ for systematic errors and a deconvolution by a Gaussian function of width σ for random errors. For a 90% confidence interval, α = 2.5. Planning was performed on a TomoTherapy system, such that 95% of the voxels received at least 95% of the modified prescription and less than 5% of the voxels received more than 105% of the modified prescription. The applicability of the method was illustrated for two head-and-neck tumors. RESULTS: Systematic and random displacements larger than αΣ and σ degraded coverage. Down to 62.8% of the points received at least 95% of prescribed dose for the largest considered displacements (5 mm systematic translation and 3 mm standard deviation for random errors). When systematic and random displacements were smaller than αΣ and σ, no degradation of target coverage was observed. CONCLUSIONS: The method led to treatment plans with target coverage robust against geometric uncertainties without the need to incorporate these in the optimizer of the TPS. The methodology was illustrated for head-and-neck cancer but can be potentially extended to all treatment sites.

Reprogramming of tumor metabolism by targeting mitochondria improves tumor response to irradiation.

BACKGROUND: The Warburg phenotype identified decades ago describes tumor cells with increased glycolysis and decreased mitochondrial respiration even in the presence of oxygen. This particular metabolism also termed 'aerobic glycolysis' reflects an adaptation of tumor cells to proliferation in a heterogeneous tumor microenvironment. Although metabolic alterations in cancer cells are common features, their impact on the response to radiotherapy is not yet fully elucidated. This study investigated the impact of cellular oxygen consumption inhibition on the tumor response to radiotherapy. MATERIAL AND METHODS: Warburg-phenotype tumor cells with impaired mitochondrial respiration (MD) were produced and compared in respect to their metabolism to the genetically matched parental cells (WT). After characterization of their metabolism we compared the response of MD cells to irradiation in vivo and in vitro to the genetically matched parental cells (WT). RESULTS: We first confirmed that MD cells were exclusively glycolytic while WT cells exhibited mitochondrial respiration. We then used these cells for assessing the response of WT and MD tumors to a single dose of radiation and showed that the in vivo tumor growth delay of the MD group was increased, indicating an increased radiosensitivity compared to WT while the in vitro ability of both cell lines to repair radiation-induced DNA damage was similar. CONCLUSION: Taken together, these results indicate that in addition to intrinsic radiosensitivity parameters the tumor response to radiation will also depend on their metabolic rate of oxygen consumption.

Assessment of tumor motion reproducibility with audio-visual coaching through successive 4D CT sessions.

This study aimed to compare combined audio-visual coaching with audio coaching alone and assess their respective impact on the reproducibility of external breathing motion and, one step further, on the internal lung tumor motion itself, through successive sessions. Thirteen patients with NSCLC were enrolled in this study. The tumor motion was assessed by three to four successive 4D CT sessions, while the breathing signal was measured from magnetic sensors positioned on the epigastric region. For all sessions, the breathing was regularized with either audio coaching alone (AC, n = 5) or combined with a real-time visual feedback (A/VC, n = 8) when tolerated by the patients. Peak-to-peak amplitude, period and signal shape of both breathing and tumor motions were first measured. Then, the correlation between the respiratory signal and internal tumor motion over time was evaluated, as well as the residual tumor motion for a gated strategy. Although breathing and tumor motions were comparable between AC and AV/C groups, A/VC approach achieved better reproducibility through sessions than AC alone (mean tumor motion of 7.2 mm ± 1 vs. 8.6 mm ± 1.8 mm, and mean breathing motion of 14.9 mm ± 1.2 mm vs. 13.3mm ± 3.7 mm, respectively). High internal/external correlation reproducibility was achieved in the superior-inferior tumor motion direction for all patients. For the anterior posterior tumor motion direction, better correlation reproducibility has been observed when visual feedback has been used. For a displacement-based gating approach, A/VC might also be recommended, since it led to smaller residual tumor motion within clinically relevant duty cycles. This study suggests that combining real-time visual feedback with audio coaching might improve the reproducibility of key characteristics of the breathing pattern, and might thus be considered in the implementation of lung tumor radiotherapy.

Secondary cancer risk in six anatomical sites when using PAT, IMPT, and VMAT/IMRT radiotherapy.

BACKGROUND AND PURPOSE: Compared to intensity modulated proton therapy (IMPT), proton arc therapy (PAT) is expected to improve dose conformality, delivery efficiency, and provide a more favorable LET distribution. Alternatively, the low-dose bath is potentially spread over larger volumes, which could impact the likelihood of developing a radiation-induced, secondary cancer (SC). The goal of this study was to evaluate this risk in several anatomical sites using newly developed commercial tools. MATERIALS AND METHODS: Treatment plans encompassing six anatomical sites, five patients per site, and three techniques per patient were created using RayStation. Techniques included PAT and IMPT for protons, and either volumetrically modulated radiotherapy (VMAT) or intensity modulated radiotherapy (IMRT) for photons. Risk estimates were based on the organ-equivalent dose (OED) concept using both Schneider's mechanistic dose-response model for carcinoma induction and a linear dose-response model. RESULTS: With few exceptions, mean and integral dose were lowest with PAT. For protons, the factor OEDIMPT/OEDPAT ranged from 0.7 to 1.8 with both the mechanistic and linear model, while for photons OEDphoton/OEDPAT ranged from 1.5 to 10 using the mechanistic model and 1.3 to using the linear model. A strong correlation was found between mean dose and OED for organs with significant repopulation/repair (high R value) and less cell death from single hit interactions (low α value). CONCLUSION: Based on results from both mechanistic and linear risk models, the transition from IMPT to PAT should not substantially affect SC risk in patients treated with proton therapy. Additionally, when using Schneider's model, the shapes of the dose-response curves can be used as a good predictor of how SC risk will respond to shifts from intermediate dose to low dose as anticipated when moving from IMPT to PAT.

Efficient proton arc optimization and delivery through energy layer pre-selection and post-filtering.

BACKGROUND: Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time. PURPOSE: This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering, and comparing its performance to a baseline approach without filtering. METHODS: Three methods of EL filtering were developed: unrestricted, switch-up (SU), and switch-up gap (SU gap) filtering. The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework energy layer selection and spot assignment (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and normal tissue complication probability evaluations, as well as comparisons to intensity-modulated proton therapy (IMPT) plans, were used to assess plan quality. RESULTS: The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients. CONCLUSIONS: This study provides insights to accelerate PAT delivery without compromising plan quality. These advancements could enhance treatment efficiency and patient throughput.

An experimental validation of a filtering approach for prompt gamma prediction in a research proton treatment planning system.

Objective.Prompt gamma (PG) radiation generated from nuclear reactions between protons and tissue nuclei can be employed for range verification in proton therapy. A typical clinical workflow for PG range verification compares the detected PG profile with a predicted one. Recently, a novel analytical PG prediction algorithm based on the so-called filtering formalism has been proposed and implemented in a research version of RayStation (RaySearch Laboratories AB), which is a widely adopted treatment planning system. This work validates the performance of the filtering PG prediction approach.Approach.The said algorithm is validated against experimental data and benchmarked with another well-established PG prediction algorithm implemented in a MATLAB-based software REGGUI. Furthermore, a new workflow based on several PG profile quality criteria and analytical methods is proposed for data selection. The workflow also calculates sensitivity and specificity information, which can help practitioners to decide on irradiation course interruption during treatment and monitor spot selection at the treatment planning stage. With the proposed workflow, the comparison can be performed on a limited number of selected high-quality irradiation spots without neighbouring-spot aggregation.Main results.The mean shifts between the experimental data and the predicted PG detection (PGD) profiles (ΔPGD) by the two algorithms are estimated to be1.5±2.1mm and-0.6±2.2mm for the filtering and REGGUI prediction methods, respectively. The ΔPGD difference between two algorithms is observed to be consistent with the beam model difference within uncertainty. However, the filtering approach requires a much shorter computation time compared to the REGGUI approach.Significance.The novel filtering approach is successfully validated against experimental data and another widely used PG prediction algorithm. The workflow designed in this work selects spots with high-quality PGD shift calculation results, and performs sensitivity and specificity analyses to assist clinical decisions.

Particle arc therapy: Status and potential.

There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook.

Automatic detection and classification of treatment deviations in proton therapy from realistically simulated prompt gamma imaging data.

BACKGROUND: A clinical study regarding the potential of range verification in proton therapy (PT) by prompt gamma imaging (PGI) is carried out at our institution. Manual interpretation of the detected spot-wise range shift information is time-consuming, highly complex, and therefore not feasible in a broad routine application. PURPOSE: Here, we present an approach to automatically detect and classify treatment deviations in realistically simulated PGI data for head-and-neck cancer (HNC) treatments using convolutional neural networks (CNNs) and conventional machine learning (ML) approaches. METHODS: For 12 HNC patients and 1 anthropomorphic head phantom (n = 13), pencil beam scanning (PBS) treatment plans were generated, and 1 field per plan was assumed to be monitored with a PGI slit camera system. In total, 386 scenarios resembling different relevant or non-relevant treatment deviations were simulated on planning and control CTs and manually classified into 7 classes: non-relevant changes (NR) and relevant changes (RE) triggering treatment intervention due to range prediction errors (±RP), setup errors in beam direction (±SE), anatomical changes (AC), or a combination of such errors (CB). PBS spots with reliable PGI information were considered with their nominal Bragg peak position for the generation of two 3D spatial maps of 16 × 16 × 16 voxels containing PGI-determined range shift and proton number information. Three complexity levels of simulated PGI data were investigated: (I) optimal PGI data, (II) realistic PGI data with simulated Poisson noise based on the locally delivered proton number, and (III) realistic PGI data with an additional positioning uncertainty of the slit camera following an experimentally determined distribution. For each complexity level, 3D-CNNs were trained on a data subset (n = 9) using patient-wise leave-one-out cross-validation and tested on an independent test cohort (n = 4). Both the binary task of detecting RE and the multi-class task of classifying the underlying error source were investigated. Similarly, four different conventional ML classifiers (logistic regression, multilayer perceptron, random forest, and support vector machine) were trained using five previously established handcrafted features extracted from the PGI data and used for performance comparison. RESULTS: On the test data, the CNN ensemble achieved a binary accuracy of 0.95, 0.96, and 0.93 and a multi-class accuracy of 0.83, 0.81, and 0.76 for the complexity levels (I), (II), and (III), respectively. In the case of binary classification, the CNN ensemble detected treatment deviations in the most realistic scenario with a sensitivity of 0.95 and a specificity of 0.88. The best performing ML classifiers showed a similar test performance. CONCLUSIONS: This study demonstrates that CNNs can reliably detect relevant changes in realistically simulated PGI data and classify most of the underlying sources of treatment deviations. The CNNs extracted meaningful features from the PGI data with a performance comparable to ML classifiers trained on previously established handcrafted features. These results highlight the potential of a reliable, automatic interpretation of PGI data for treatment verification, which is highly desired for a broad clinical application and a prerequisite for the inclusion of PGI in an automated feedback loop for online adaptive PT.

Potential margin reduction in prostate cancer proton therapy with prompt gamma imaging for online treatment verification.

The potential of proton therapy is currently limited due to large safety margins. We estimated the potential reduction of clinical margins when using prompt gamma imaging (PGI) for online treatment verification of prostate cancer. For two adaptive scenarios a potential reduction relative to clinical practice was evaluated. The use of a trolley-mounted PGI system for online treatment verification to trigger an adaptation reduced the current range margins from 7 mm to 3 mm. In a case example, the dose reduction due to reduced range margins was substantially larger compared to reduced setup margins when using pre-treatment volumetric imaging.

Spot scanning proton arc therapy reduces toxicity in oropharyngeal cancer patients.

BACKGROUND: Proton arc technology has recently shown dosimetric gains for various treatment indications. The increased number of beams and energy layers (ELs) in proton arc plans, increases the degrees of freedom in plan optimization and thereby flexibility to spare dose in organs at risk (OARs). A relationship exists between dosimetric plan quality, delivery efficiency, the number of ELs -and beams in a proton arc plan. PURPOSE: This work aims to investigate the effect of the number of beams and ELs in a proton arc plan, on toxicity and delivery time for oropharyngeal cancer patients (OPC) selected for intensity modulated proton therapy (IMPT) based on the Dutch model-based approach. METHODS: The EL reduction algorithm iteratively selects ELs from beams equidistantly spaced over a 360° arc. The beams in the final plan may contain multiple ELs, making them suited for static delivery on the studied treatment machine. The produced plans can therefore be called "step and shoot" proton arc plans. The number of beams and ELs were varied to determine the relationship with the planning cost function value, normal tissue complication probability (NTCP) and delivery time. Proton arc plans with robust target coverage and optimal energy layer reduction (ELR) settings to reduce NTCP, were generated for 10 OPC patients. Proton arc plans were compared to clinical volumetric modulated arc therapy (VMAT) and IMPT plans in terms of integral dose, OAR dose, NTCP for xerostomia and dysphagia and delivery time. Furthermore, dose-weighted average linear energy transfer (LETd ) distributions were compared between the IMPT and proton arc plans. A dry run delivery of a plan containing 20 beams and 360 ELs was performed to evaluate delivery time and accuracy. RESULTS: We found 360 ELs distributed over 30 beams generated proton arc plans with near minimal expected plan toxicity. Relative to corresponding IMPT and VMAT plans, an average reduction of 21 ± 3% and 58 ± 10% in integral dose was observed. D m e a n $_{mean}$ was reduced most in the pharyngeal constrictor muscle (PCM) medius structure, with on average 9.0 ± 4.2 Gy(RBE) (p = 0.0002) compared to the clinical IMPT plans. The average NTCP for grade≥2 and grade≥3 xerostomia at 6 months after treatment significantly decreased with 4.7 ± 1.8% (p = 0.002) and 1.7 ± 0.8% (p = 0.002), respectively, while the average NTCP for grade≥2 and grade≥3 dysphagia decreased with 4.4 ± 2.9% (p = 0.002) and 0.9 ± 0.4% (p = 0.002), respectively, increasing the benefit of protons relative to VMAT. For a "step and shoot" proton arc delivery with auto beam sequencing the estimated delivery time is 11 min, similar to the delivery time of a 6-field IMPT treatment. Gamma analysis between the planned and delivered dose distribution resulted in a 99.99% pass rate using 1mm/1% dose difference/distance to agreement criteria. CONCLUSIONS: "Step and shoot" proton arc demonstrates potential to further reduce toxicity compared to IMPT and VMAT in OPC treatment. By employing 360 ELs and 30 beams in the proposed ELR method, delivery time can reach clinically acceptable levels without compromising plan toxicity when automatic beam sequencing is available.

Scatter correction of 4D cone beam computed tomography to detect dosimetric effects due to anatomical changes in proton therapy for lung cancer.

BACKGROUND: The treatment of moving tumor entities is expected to have superior clinical outcomes, using image-guided adaptive intensity-modulated proton therapy (IMPT). PURPOSE: For 21 lung cancer patients, IMPT dose calculations were performed on scatter-corrected 4D cone beam CTs (4DCBCTcor ) to evaluate their potential for triggering treatment adaptation. Additional dose calculations were performed on corresponding planning 4DCTs and day-of-treatment 4D virtual CTs (4DvCTs). METHODS: A 4DCBCT correction workflow, previously validated on a phantom, generates 4DvCT (CT-to-CBCT deformable registration) and 4DCBCTcor images (projection-based correction using 4DvCT as a prior) with 10 phase bins, using day-of-treatment free-breathing CBCT projections and planning 4DCT images as input. Using a research planning system, robust IMPT plans administering eight fractions of 7.5 Gy were created on a free-breathing planning CT (pCT) contoured by a physician. The internal target volume (ITV) was overridden with muscle tissue. Robustness settings for range and setup uncertainties were 3% and 6 mm, and a Monte Carlo dose engine was used. On every phase of planning 4DCT, day-of-treatment 4DvCT, and 4DCBCTcor , the dose was recalculated. For evaluation, image analysis as well as dose analysis were performed using mean error (ME) and mean absolute error (MAE) analysis, dose-volume histogram (DVH) parameters, and 2%/2-mm gamma pass rate analysis. Action levels (1.6% ITV D98 and 90% gamma pass rate) based on our previous phantom validation study were set to determine which patients had a loss of dosimetric coverage. RESULTS: Quality enhancements of 4DvCT and 4DCBCTcor over 4DCBCT were observed. ITV D98% and bronchi D2% had its largest agreement for 4DCBCTcor -4DvCT, and the largest gamma pass rates (>94%, median 98%) were found for 4DCBCTcor -4DvCT. Deviations were larger and gamma pass rates were smaller for 4DvCT-4DCT and 4DCBCTcor -4DCT. For five patients, deviations were larger than the action levels, suggesting substantial anatomical changes between pCT and CBCT projections acquisition. CONCLUSIONS: This retrospective study shows the feasibility of daily proton dose calculation on 4DCBCTcor for lung tumor patients. The applied method is of clinical interest as it generates up-to-date in-room images, accounting for breathing motion and anatomical changes. This information could be used to trigger replanning.

The first investigation of spot-scanning proton arc (SPArc) delivery time and accuracy with different delivery tolerance window settings.

Objective. To investigate the impact of various delivery tolerance window settings on the treatment delivery time and dosimetric accuracy of spot-scanning proton arc (SPArc) therapy.Approach. SPArc plans were generated for three representative disease sites (brain, lung, and liver cancer) with an angle sampling frequency of 2.5°. An in-house dynamic arc controller was used to simulate the arc treatment delivery with various tolerance windows (±0.25, ±0.5, ±1, and ±1.25°). The controller generates virtual logfiles during the arc delivery simulation, such as gantry speed, acceleration and deceleration, spot position, and delivery sequence, similar to machine logfiles. The virtual logfile was then imported to the treatment planning system to reconstruct the delivered dose distribution and compare it to the initial SPArc nominal plan. A three-dimensional gamma index was used to quantitatively assess delivery accuracy. Total treatment delivery time and relative lost time (dynamic arc delivery time-fix beam delivery time)/fix beam delivery time) were reported.Main Results. The 3D gamma passing rate (GPR) was greater than 99% for all cases when using 3%/3 mm and 2%/2 mm criteria and the GPR (1%/1 mm criteria) degraded as the tolerance window opens. The total delivery time for dynamic arc delivery increased with the decreasing delivery tolerance window length. The average delivery time and the relative lost time (%) were 630 ± 212 s (253% ± 68%), 322 ± 101 s (81% ± 31%), 225 ± 60 s (27% ± 16%), 196 ± 41 s (11% ± 6%), 187 ± 29 s (6% ± 1%) for tolerance windows ±0.25, ±0.5, ±1, and ±1.25° respectively.Significance. The study quantitatively analyzed the dynamic SPArc delivery time and accuracy with different delivery tolerance window settings, which offer a critical reference in the future SPArc plan optimization and delivery controller design.

Detectability of Anatomical Changes With Prompt-Gamma Imaging: First Systematic Evaluation of Clinical Application During Prostate-Cancer Proton Therapy.

PURPOSE: The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system. METHODS AND MATERIALS: For 15 patients with prostate cancer, PGI measurements were performed during 105 fractions (201 fields) with in-room control computed tomography (CT)acquisitions. Field-wise doses on control CT scans were manually classified as whether showing relevant or non-relevant anatomical changes. This manual classification of the treatment fields was then used to establish an automatic field-wise ground truth based on spot-wise dosimetric range shifts, which were retrieved from integrated depth-dose (IDD) profiles. To determine the detection capability of anatomical changes with PGI, spot-wise PGI-based range shifts were initially compared with corresponding dosimetric IDD range shifts. As final endpoint, the agreement of a developed field-wise PGI classification model with the field-wise ground truth was determined. Therefore, the PGI model was optimized and tested for a subcohort of 131 and 70 treatment fields, respectively. RESULTS: The correlation between PGI and IDD range shifts was high, ρpearson = 0.67 (p < 0.01). Field-wise binary PGI classification resulted in an area under the curve of 0.72 and 0.80 for training and test cohorts, respectively. The model detected relevant anatomical changes in the independent test cohort, with a sensitivity and specificity of 74% and 79%, respectively. CONCLUSIONS: For the first time, evidence of the detection capability of anatomical changes in prostate-cancer PT from clinically acquired PGI data is shown. This emphasizes the benefit of PGI-based range verification and demonstrates its potential for online-adaptive PT.

Proton arc therapy increases the benefit of proton therapy for oropharyngeal cancer patients in the model based clinic.

BACKGROUND AND PURPOSE: In the model-based approach, patients qualify for proton therapy when the reduction in risk of toxicity (ΔNTCP) obtained with IMPT relative to VMAT is larger than predefined thresholds as defined by the Dutch National Indication Protocol (NIPP). Proton arc therapy (PAT) is an emerging technology which has the potential to further decrease NTCPs compared to IMPT. The aim of this study was to investigate the potential impact of PAT on the number of oropharyngeal cancer (OPC) patients that qualify for proton therapy. MATERIALS AND METHODS: A prospective cohort of 223 OPC patients subjected to the model-based selection procedure was investigated. 33 (15%) patients were considered unsuitable for proton treatment before plan comparison. When IMPT was compared to VMAT for the remaining 190 patients, 148 (66%) patients qualified for protons and 42 (19%) patients did not. For these 42 patients treated with VMAT, robust PAT plans were generated. RESULTS: PAT plans provided better or similar target coverage compared to IMPT plans. In the PAT plans, integral dose was significantly reduced by 18% relative to IMPT plans and by 54% relative to VMAT plans. PAT decreased the mean dose to numerous organs-at-risk (OARs), further reducing NTCPs. The ΔNTCP for PAT relative to VMAT passed the NIPP thresholds for 32 out of the 42 patients treated with VMAT, resulting in 180 patients (81%) of the complete cohort qualifying for protons. CONCLUSION: PAT outperforms IMPT and VMAT, leading to a further reduction of NTCP-values and higher ΔNTCP-values, significantly increasing the percentage of OPC patients selected for proton therapy.

Bi-criteria Pareto optimization to balance irradiation time and dosimetric objectives in proton arc therapy.

Objective. Proton arc therapy (PAT) is a new delivery technique that exploits the continuous rotation of the gantry to distribute the therapeutic dose over many angular windows instead of using a few static fields, as in conventional (intensity-modulated) proton therapy. Although coming along with many potential clinical and dosimetric benefits, PAT has also raised a new optimization challenge. In addition to the dosimetric goals, the beam delivery time (BDT) needs to be considered in the objective function. Considering this bi-objective formulation, the task of finding a good compromise with appropriate weighting factors can turn out to be cumbersome.Approach. We have computed Pareto-optimal plans for three disease sites: a brain, a lung, and a liver, following a method of iteratively choosing weight vectors to approximate the Pareto front with few points. Mixed-integer programming (MIP) was selected to state the bi-criteria PAT problem and to find Pareto optimal points with a suited solver.Main results. The trade-offs between plan quality and beam irradiation time (staticBDT) are investigated by inspecting three plans from the Pareto front. The latter are carefully picked to demonstrate significant differences in dose distribution and delivery time depending on their location on the frontier. The results were benchmarked against IMPT and SPArc plans showing the strength of degrees of freedom coming along with MIP optimization.Significance. This paper presents for the first time the application of bi-criteria optimization to the PAT problem, which eventually permits the planners to select the best treatment strategy according to the patient conditions and clinical resources available.