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

PURPOSE: Evaluation of dose degradation by anatomic changes for head-and-neck cancer (HNC) intensity-modulated proton therapy (IMPT) relative to intensity-modulated photon therapy (IMRT) and identification of potential indicators for IMPT treatment plan adaptation. METHODS: For 31 advanced HNC datasets, IMPT and IMRT plans were recalculated on a computed tomography scan (CT) taken after about 4 weeks of therapy. Dose parameter changes were determined for the organs at risk (OARs) spinal cord, brain stem, parotid glands, brachial plexus, and mandible, for the clinical target volume (CTV) and the healthy tissue outside planning target volume (PTV). Correlation of dose degradation with target volume changes and quality of rigid CT matching was investigated. RESULTS: Recalculated IMPT dose distributions showed stronger degradation than the IMRT doses. OAR analysis revealed significant changes in parotid median dose (IMPT) and near maximum dose (D1ml ) of spinal cord (IMPT, IMRT) and mandible (IMPT). OAR dose parameters remained lower in IMPT cases. CTV coverage (V95% ) and overdose (V107% ) deteriorated for IMPT plans to (93.4 ± 5.4)% and (10.6 ± 12.5)%, while those for IMRT plans remained acceptable. Recalculated plans showed similarly decreased PTV conformity, but considerable hotspots, also outside the PTV, emerged in IMPT cases. Lower CT matching quality was significantly correlated with loss of PTV conformity (IMPT, IMRT), CTV homogeneity and coverage (IMPT). Target shrinkage correlated with increased dose in brachial plexus (IMRT, IMPT), hotspot generation outside the PTV (IMPT) and lower PTV conformity (IMRT). CONCLUSIONS: The study underlines the necessity of precise positioning and monitoring of anatomy changes, especially in IMPT which might require adaptation more often. Since OAR doses remained typically below constraints, IMPT plan adaptation will be indicated by target dose degradations.

Spatial distribution of FMISO in head and neck squamous cell carcinomas during radio-chemotherapy and its correlation to pattern of failure.

BACKGROUND: Tumour hypoxia can be measured by FMISO-PET and negatively impacts local tumour control in patients with head and neck squamous cell carcinoma (HNSCC) undergoing radiotherapy. The aim of this post hoc analysis of a prospective clinical trial was to investigate the spatial variability of FMISO hypoxic subvolumes during radio-chemotherapy and the co-localisation of these volumes with later recurrences as a basis for individualised dose prescription trials with dose escalation defined by FMISO-PET. METHODS: Sequential FMISO scans of 12 (of 25) patients presenting residual hypoxia taken before (FMISOpre) and during (FMISOw1-FMISOw5) radio-chemotherapy were analysed regarding the stability of the FMISO subvolumes and, in case of local failure, their correlation to local relapse. RESULTS: Consecutive FMISO-PET positive volumes could be classified as moderately stable with Dice conformity indices of 62% and 58% up to the second week of treatment. Substantial volumetric variation during treatment was observed, with more than 20% geographic miss in all patients and more than 40% in half of the patients. The localisation of the maximum standardised uptake value (SUVmax) differed with a mean distance of 7.0 mm and 13.5 mm between the pre-therapeutic and first or second FMISO-PET during treatment. A stable hypoxic consensual volume (i.e. overlap of pre-therapeutic FMISO and intra-treatment FMISO subvolumes up to week two, generated by different contouring methods) was determined for six patients with imaging information of local recurrence. Three of these six local recurrences were located within this consensual volume. CONCLUSIONS: Our data suggest that selective dose painting to hypoxic tumour subvolumes requires adaptation during treatment and sufficient margins. An alternative strategy is to escalate the dose to the gross tumour volume, accepting lesser escalation of dose outside hypoxic areas if indicated by constraints for organs at risk.

NTCP reduction for advanced head and neck cancer patients using proton therapy for complete or sequential boost treatment versus photon therapy.

BACKGROUND: To determine by treatment plan comparison differences in toxicity risk reduction for patients with head and neck squamous cell carcinoma (HNSCC) from proton therapy either used for complete treatment or sequential boost treatment only. MATERIALS AND METHODS: For 45 HNSCC patients, intensity-modulated photon (IMXT) and proton (IMPT) treatment plans were created including a dose escalation via simultaneous integrated boost with a one-step adaptation strategy after 25 fractions for sequential boost treatment. Dose accumulation was performed for pure IMXT treatment, pure IMPT treatment and for a mixed modality treatment with IMXT for the elective target followed by a sequential boost with IMPT. Treatment plan evaluation was based on modern normal tissue complication probability (NTCP) models for mucositis, xerostomia, aspiration, dysphagia, larynx edema and trismus. Individual NTCP differences between IMXT and IMPT (∆NTCPIMXT-IMPT) as well as between IMXT and the mixed modality treatment (∆NTCPIMXT-Mix) were calculated. RESULTS: Target coverage was similar in all three scenarios. NTCP values could be reduced in all patients using IMPT treatment. However, ∆NTCPIMXT-Mix values were a factor 2-10 smaller than ∆NTCPIMXT-IMPT. Assuming a threshold of ≥ 10% NTCP reduction in xerostomia or dysphagia risk as criterion for patient assignment to IMPT, less than 15% of the patients would be selected for a proton boost, while about 50% would be assigned to pure IMPT treatment. For mucositis and trismus, ∆NTCP ≥ 10% occurred in six and four patients, respectively, with pure IMPT treatment, while no such difference was identified with the proton boost. CONCLUSIONS: The use of IMPT generally reduces the expected toxicity risk while maintaining good tumor coverage in the examined HNSCC patients. A mixed modality treatment using IMPT solely for a sequential boost reduces the risk by 10% only in rare cases. In contrast, pure IMPT treatment may be reasonable for about half of the examined patient cohort considering the toxicities xerostomia and dysphagia, if a feasible strategy for patient anatomy changes is implemented.

The partial adaptation strategy for online-adaptive proton therapy: A proof of concept study in head and neck cancer patients.

BACKGROUND: The accuracy of intensity-modulated proton therapy (IMPT) is greatly affected by anatomy variations that might occur during the treatment course. Online plan adaptations have been proposed as a solution to intervene promptly during a treatment session once the anatomy changes are detected. The implementation of online-adaptive proton therapy (OAPT) is still hindered by time-consuming tasks in the workflow. PURPOSE: The study introduces the novel concept of partial adaptation and aims at investigating its feasibility as a potential solution to parallelize tasks during an OAPT workflow for saving valuable in-room time. METHODS: The proof-of-principle simulation study includes datasets from six head and neck cancer (HNC) patients, each consisting of one planning CT (pCT) and three contoured control CTs (cCTs). Robust 3-field normo-fractionated initial IMPT plans were generated on the pCTs with a standardized field configuration, delivering 66 Gy and 54 Gy to the high-risk and low-risk clinical target volume (CTVHigh and CTVLow), respectively. For each cCT, a dose-mimicking-based partial adaptation was applied: two fields were adapted on the current anatomy taking into account the background dose of the first non-adapted field supposedly delivered in the meantime. Fraction doses on the cCTs resulting from partially adapted plans with different first (non-adapted) field assignments were compared against those from non-adapted and fully adapted plans regarding target coverage and organs at risk (OARs) sparing. The robustness of partially adapted plans was also evaluated. RESULTS: Partially adapted plans showed comparable results to fully adapted plans and were superior to non-adapted plans for both target coverage and OAR sparing. Target coverage degradation in the non-adapted plans (median D98%: 95.9% and 97.5% for CTVLow and CTVHigh, respectively) was recovered by both partial (98.0% and 98.5%) and full adaptation (98.2% and 98.7%) in comparison to the initial plans (98.7% and 98.8%). The initial hotspot dose for the CTVHigh (median D2%: 101.8%) increased in the non-adapted plans (102.9%) and was recovered by the adaptive strategies (partial: 102.5%, full: 101.9%). The near-maximum dose (D0.01cc) to brainstem and spinal cord was within clinical constraints for all investigated dose distributions, but clearly increased for no adaptation and improved in the (both partially and fully) adapted plans with respect to the non-adapted ones. The parotids' median doses (D50) were mainly patient-specific depending on the proximity to the target region, but anyway lower for the partially and fully adapted plans compared to the non-adapted ones. OAR sparing was furthermore improved for the partially adapted plans in comparison to full adaptation. Robustness of the target dose metrics was preserved in all evaluated scenarios. CONCLUSIONS: For OAPT of HNC patients, partial adaptation is able to generate plans of superior conformity to non-adapted plans and of comparable conformity as fully adapted plans, while having the potential to speed up the online-adaptive workflows. Thus, partial adaptation represents an intermediate approach until fast online adaptation workflows become available. Furthermore, it can be applied in workflows where online treatment verification stops the delivery and triggers an online adaptation for the remaining fraction.

A review of the clinical introduction of 4D particle therapy research concepts.

Background and purpose: Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments. Material and methods: This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 4D Treatment Workshops for Particle Therapy as well as a review of the most recent surveys, guidelines and scientific papers dedicated to this topic. Results: Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments. Conclusion: This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.

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.

Comparison of 3D and 4D robustly optimized proton treatment plans for non-small cell lung cancer patients with tumour motion amplitudes larger than 5 mm.

Background and purpose: There is no consensus about an ideal robust optimization (RO) strategy for proton therapy of targets with large intrafractional motion. We investigated the plan robustness of 3D and different 4D RO strategies. Materials and methods: For eight non-small cell lung cancer patients with clinical target volume (CTV) motion >5 mm, different RO approaches were investigated: 3DRO considering the average CT (AvgCT) with a target density override, 4DRO considering three/all 4DCT phases, and 4DRO considering the AvgCT and three/all 4DCT phases. Robustness against setup/range errors, interplay effects based on breathing and machine log file data for deliveries with/without rescanning, and interfractional anatomical changes were analyzed for target coverage and OAR sparing. Results: All nominal plans fulfilled the clinical requirements with individual CTV coverage differences <2pp; 4DRO without AvgCT generated the most conformal dose distributions. Robustness against setup/range errors was best for 4DRO with AvgCT (18% more passed error scenarios than 3DRO). Interplay effects caused fraction-wise median CTV coverage loss of 3pp and missed maximum dose constraints for heart and esophagus in 18% of scenarios. CTV coverage and OAR sparing fulfilled requirements in all cases when accumulating four interplay scenarios. Interfractional changes caused less target misses for RO with AvgCT compared to 4DRO without AvgCT (≤42%/33% vs. ≥56%/44% failed single/accumulated scenarios). Conclusions: All RO strategies provided acceptable plans with equally low robustness against interplay effects demanding other mitigation than rescanning to ensure fraction-wise target coverage. 4DRO considering three phases and the AvgCT provided best compromise on planning effort and robustness.

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.

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.

Experimental validation of 4D log file-based proton dose reconstruction for interplay assessment considering amplitude-sorted 4DCTs.

PURPOSE: The unpredictable interplay between dynamic proton therapy delivery and target motion in the thorax can lead to severe dose distortions. A fraction-wise four-dimensional (4D) dose reconstruction workflow allows for the assessment of the applied dose after patient treatment while considering the actual beam delivery sequence extracted from machine log files, the recorded breathing pattern and the geometric information from a 4D computed tomography scan (4DCT). Such an algorithm capable of accounting for amplitude-sorted 4DCTs was implemented and its accuracy as well as its sensitivity to input parameter variations was experimentally evaluated. METHODS: An anthropomorphic thorax phantom with a movable insert containing a target surrogate and a radiochromic film was irradiated with a monoenergetic field for various 1D target motion forms (sin, sin4 ) and peak-to-peak amplitudes (5/10/15/20/30 mm). The measured characteristic film dose distributions were compared to the respective sections in the 4D reconstructed doses using a 2D γ-analysis (3 mm, 3%); γ-pass rates were derived for different dose grid resolutions (1 mm/3 mm) and deformable image registrations (DIR, automatic/manual) applied during the 4D dose reconstruction process. In an additional analysis, the sensitivity of reconstructed dose distributions against potential asynchronous timing of the motion and machine log files was investigated for both a monoenergetic field and more realistic 4D robustly optimized fields by artificially introduced offsets of ±1/5/25/50/250 ms. The resulting dose distributions with asynchronized log files were compared to those with synchronized log files by means of a 3D γ-analysis (1 mm, 1%) and the evaluation of absolute dose differences. RESULTS: The induced characteristic interplay patterns on the films were well reproduced by the 4D dose reconstruction with 2D γ-pass rates ≥95% for almost all cases with motion magnitudes ≤15 mm. In general, the 2D γ-pass rates showed a significant decrease for larger motion amplitudes and increase when using a finer dose grid resolution but were not affected by the choice of motion form (sin, sin4 ). There was also a trend, though not statistically significant, toward the manually defined DIR for better quality of the reconstructed dose distributions in the area imaged by the film. The 4D dose reconstruction results for the monoenergetic as well as the 4D robustly optimized fields were robust against small asynchronies between motion and machine log files of up to 5 ms, which is in the order of potential network latencies. CONCLUSIONS: We have implemented a 4D log file-based proton dose reconstruction that accounts for amplitude-sorted 4DCTs. Its accuracy was proven to be clinically acceptable for target motion magnitudes of up to 15 mm. Particular attention should be paid to the synchronization of the log file generating systems as the reconstructed dose distribution may vary with log file asynchronies larger than those caused by realistic network delays.

Clinical necessity of multi-image based (4DMIB) optimization for targets affected by respiratory motion and treated with scanned particle therapy - A comprehensive review.

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.

Optimal Allocation of Proton Therapy Slots in Combined Proton-Photon Radiation Therapy.

PURPOSE: Proton therapy is a limited resource that is not available to all patients who may benefit from it. We investigated combined proton-photon treatments, in which some fractions are delivered with protons and the remaining fractions with photons, as an approach to maximize the benefit of limited proton therapy resources at a population level. METHODS AND MATERIALS: To quantify differences in normal-tissue complication probability (NTCP) between protons and photons, we considered a cohort of 45 patients with head and neck cancer for whom intensity modulated radiation therapy and intensity modulated proton therapy plans were previously created, in combination with NTCP models for xerostomia and dysphagia considered in the Netherlands for proton patient selection. Assuming limited availability of proton slots, we developed methods to optimally assign proton fractions in combined proton-photon treatments to minimize the average NTCP on a population level. The combined treatments were compared with patient selection strategies in which patients are assigned to single-modality proton or photon treatments. RESULTS: There is a benefit of combined proton-photon treatments compared with patient selection, owing to the nonlinearity of NTCP functions; that is, the initial proton fractions are the most beneficial, whereas additional proton fractions have a decreasing benefit when a flatter part of the NTCP curve is reached. This effect was small for the patient cohort and NTCP models considered, but it may be larger if dose-response relationships are better known. In addition, when proton slots are limited, patient selection methods face a trade-off between leaving slots unused and blocking slots for future patients who may have a larger benefit. Combined proton-photon treatments with flexible proton slot assignment provide a method to make optimal use of all available resources. CONCLUSIONS: Combined proton-photon treatments allow for better use of limited proton therapy resources. The benefit over patient selection schemes depends on the NTCP models and the dose differences between protons and photons.

Quantification of plan robustness against different uncertainty sources for classical and anatomical robust optimized treatment plans in head and neck cancer proton therapy.

OBJECTIVE: Classical robust optimization (cRO) in intensity-modulated proton therapy (IMPT) considers isocenter position and particle range uncertainties; anatomical robust optimization (aRO) aims to consider additional non-rigid positioning variations. This work compares the influence of different uncertainty sources on the robustness of cRO and aRO IMPT plans for head and neck squamous cell carcinoma (HNSCC). METHODS: Two IMPT plans were optimized for 20 HNSCC patients who received weekly control CTs (cCT): cRO, using solely the planning CT, and aRO, including 2 additional cCTs. The robustness of the plans in terms of clinical target volume (CTV) coverage and organ at risk (OAR) sparing was analyzed considering stepwise the influence of (1) non-rigid anatomical variations given by the weekly cCT, (2) with fraction-wise added rigid random setup errors and (3) additional systematic proton range uncertainties. RESULTS: cRO plans presented significantly higher nominal CTV coverage but are outperformed by aRO plans when considering non-rigid anatomical variations only, as cRO and aRO plans presented a median target coverage (D98%) decrease for the low-risk/high-risk CTV of 1.8/1.1 percentage points (pp) and -0.2 pp/-0.3 pp, respectively. Setup and range uncertainties had larger influence on cRO CTV coverage, but led to similar OAR dose changes in both plans. Considering all error sources, 10/2 cRO/aRO patients missed the CTV coverage and a limited number exceeded some OAR constraints in both plans. CONCLUSION: Non-rigid anatomical variations are mainly responsible for critical target coverage loss of cRO plans, whereas the aRO approach was robust against such variations. Both plans provide similar robustness of OAR parameters. ADVANCES IN KNOWLEDGE: The influence of different uncertainty sources was quantified for robust IMPT HNSCC plans.

Including anatomical variations in robust optimization for head and neck proton therapy can reduce the need of adaptation.

BACKGROUND AND PURPOSE: Classical robust optimization considers uncertainties in patient setup and particle range. However, anatomical changes occurring during the treatment are neglected. Our aim was to compare classical robust optimization (cRO) with anatomical robust optimization (aRO), to quantify the influence of anatomical variations during the treatment course, and to assess the need of adaptation. MATERIALS AND METHODS: Planning CT and weekly control CTs (cCTs) from 20 head and neck patients were analysed. Three intensity-modulated proton therapy (IMPT) plans were compared: conventional PTV-based plan; cRO, using solely the planning CT, and aRO, including additionally the first 2 cCTs in the optimization. Weekly and total cumulative doses, considering anatomical variations during the treatment, were calculated and compared with the nominal plans. RESULTS: Nominal plans fulfilled clinical specifications for target coverage (D98% ≥95% of prescribed dose). The PTV-based and cRO approaches were not sufficient to account for anatomical changes during the treatment in 10 and 5 patients, respectively, resulting in the need of plan adaptation. With the aRO approach, in all except one patient the target coverage was conserved, and no adaptations were necessary. CONCLUSION: In 25% of the investigated cases, classical robust optimization is not sufficient to account for anatomical changes during the treatment. Adding additional information of random anatomical variations in the optimization improves plan robustness.

Comparison of different treatment planning approaches for intensity-modulated proton therapy with simultaneous integrated boost for pancreatic cancer.

BACKGROUND: Neoadjuvant radio(chemo)therapy of non-metastasized, borderline resectable or unresectable locally advanced pancreatic cancer is complex and prone to cause side-effects, e.g., in gastrointestinal organs. Intensity-modulated proton therapy (IMPT) enables a high conformity to the targets while simultaneously sparing the normal tissue such that dose-escalation strategies come within reach. In this in silico feasibility study, we compared four IMPT planning strategies including robust multi-field optimization (rMFO) and a simultaneous integrated boost (SIB) for dose-escalation in pancreatic cancer patients. METHODS: For six pancreatic cancer patients referred for adjuvant or primary radiochemotherapy, four rMFO-IMPT-SIB treatment plans each, consisting of two or three (non-)coplanar beam arrangements, were optimized. Dose values for both targets, i.e., the elective clinical target volume [CTV, prescribed dose Dpres = 51Gy(RBE)] and the boost target [Dpres = 66Gy(RBE)], for the organs at risk as well as target conformity and homogeneity indexes, derived from the dose volume histograms, were statistically compared. RESULTS: All treatment plans of each strategy fulfilled the prescribed doses to the targets (Dpres(GTV,CTV) = 100%, D95%,(GTV,CTV) ≥ 95%, D2%,(GTV,CTV) ≤ 107%). No significant differences for the conformity index were found (p > 0.05), however, treatment plans with a three non-coplanar beam strategy were most homogenous to both targets (p < 0.045). The median value of all dosimetric results of the large and small bowel as well as for the liver and the spinal cord met the dose constraints with all beam arrangements. Irrespective of the planning strategies, the dose constraint for the duodenum and stomach were not met. Using the three-beam arrangements, the dose to the left kidney could be significant decreased when compared to a two-beam strategy (p < 0.045). CONCLUSION: Based on our findings we recommend a three-beam configuration with at least one non-coplanar beam for dose-escalated SIB with rMFO-IMPT in advanced pancreatic cancer patients achieving a homogeneous dose distribution in the target while simultaneously minimizing the dose to the organs at risk. Further treatment planning studies on aspects of breathing and organ motion need to be performed.

Superiority in Robustness of Multifield Optimization Over Single-Field Optimization for Pencil-Beam Proton Therapy for Oropharynx Carcinoma: An Enhanced Robustness Analysis.

PURPOSE: To compare the difference in robustness of single-field optimized (SFO) and robust multifield optimized (rMFO) proton plans for oropharynx carcinoma patients by an improved robustness analysis. METHODS AND MATERIALS: We generated rMFO proton plans for 11 patients with oropharynx carcinoma treated with SFO intensity modulated proton therapy with simultaneous integrated boost prescription. Doses from both planning approaches were compared for the initial plans and the worst cases from 20 optimization scenarios of setup errors and range uncertainties. Expected average dose distributions per range uncertainty were obtained by weighting the contributions from the respective scenarios with their expected setup error probability, and the spread of dose parameters for different range uncertainties were quantified. Using boundary dose distributions created from 56 combined setup error and range uncertainty scenarios and considering the vanishing influence of setup errors after 30 fractions, we approximated realistic worst-case values for the total treatment course. Error bar metrics derived from these boundary doses are reported for the clinical target volumes (CTVs) and organs at risk (OARs). RESULTS: The rMFO plans showed improved CTV coverage and homogeneity while simultaneously reducing the average mean dose to the constrictor muscles, larynx, and ipsilateral middle ear by 5.6 Gy, 2.0 Gy, and 3.9 Gy, respectively. We observed slightly larger differences during robustness evaluation, as well as a significantly higher average brainstem maximum and ipsilateral parotid mean dose for SFO plans. For rMFO plans, the range uncertainty-related spread in OAR dose parameters and many error bar metrics were found to be superior. The SFO plans showed a lower global maximum dose for single-scenario worst cases and a slightly lower mean oral cavity dose throughout. CONCLUSIONS: An enhanced robustness analysis has been proposed and implemented into clinical systems. The benefit of better CTV coverage and OAR dose sparing in oropharynx carcinoma patients by rMFO compared with SFO proton plans is preserved in a robustness analysis with consideration of setup error and range uncertainty.

Dual-energy CT based proton range prediction in head and pelvic tumor patients.

BACKGROUND AND PURPOSE: To reduce range uncertainty in particle therapy, an accurate computation of stopping-power ratios (SPRs) based on computed tomography (CT) is crucial. Here, we assess range differences between the state-of-the-art CT-number-to-SPR conversion using a generic Hounsfield look-up table (HLUT) and a direct patient-specific SPR prediction (RhoSigma) based on dual-energy CT (DECT) in 100 proton treatment fields. MATERIAL AND METHODS: For 25 head-tumor and 25 prostate-cancer patients, the clinically applied treatment plan, optimized using a HLUT, was recalculated with RhoSigma as CT-number-to-SPR conversion. Depth-dose curves in beam direction were extracted for both dose distributions in a regular grid and range deviations were determined and correlated to SPR differences within the irradiated volume. RESULTS: Absolute (relative) mean water-equivalent range shifts of 1.1mm (1.2%) and 4.1mm (1.7%) were observed in the head-tumor and prostate-cancer cohort, respectively. Due to the case dependency of a generic HLUT, range deviations within treatment fields strongly depend on the tissues traversed leading to a larger variation within one patient than between patients. CONCLUSIONS: The magnitude of patient-specific range deviations between HLUT and the more accurate DECT-based SPR prediction is clinically relevant. A clinical application of the latter seems feasible as demonstrated in this study using medically approved systems from CT acquisition to treatment planning.

Impact of robust treatment planning on single- and multi-field optimized plans for proton beam therapy of unilateral head and neck target volumes.

BACKGROUND: Proton beam therapy is promising for the treatment of head and neck cancer (HNC), but it is sensitive to uncertainties in patient positioning and particle range. Studies have shown that the planning target volume (PTV) concept may not be sufficient to ensure robustness of the target coverage. A few planning studies have considered irradiation of unilateral HNC targets with protons, but they have only taken into account the dose on the nominal plan, without considering anatomy changes occurring during the treatment course. METHODS: Four pencil beam scanning (PBS) proton therapy plans were calculated for 8 HNC patients with unilateral target volumes: single-field (SFO) and multi-field optimized (MFO) plans, either using the PTV concept or clinical target volume (CTV)-based robust optimization. The dose was recalculated on computed tomography (CT) scans acquired during the treatment course. Doses to target volumes and organs at risk (OARs) were compared for the nominal plans, cumulative doses considering anatomical changes, and additional setup and range errors in each fraction. If required, the treatment plan was adapted, and the dose was compared with the non-adapted plan. RESULTS: All nominal plans fulfilled the clinical specifications for target coverage, but significantly higher doses on the ipsilateral parotid gland were found for both SFO approaches. MFO PTV-based plans had the lowest robustness against range and setup errors. During the treatment course, the influence of the anatomical variation on the dose has shown to be patient specific, mostly independent of the chosen planning approach. Nine plans in four patients required adaptation, which led to a significant improvement of the target coverage and a slight reduction in the OAR dose in comparison to the cumulative dose without adaptation. CONCLUSIONS: The use of robust MFO optimization is recommended for ensuring plan robustness and reduced doses in the ipsilateral parotid gland. Anatomical changes occurring during the treatment course might degrade the target coverage and increase the dose in the OARs, independent of the chosen planning approach. For some patients, a plan adaptation may be required.

Modeling tumor control probability for spatially inhomogeneous risk of failure based on clinical outcome data.

PURPOSE: Objectives of this work are (1) to derive a general clinically relevant approach to model tumor control probability (TCP) for spatially variable risk of failure and (2) to demonstrate its applicability by estimating TCP for patients planned for photon and proton irradiation. METHODS AND MATERIALS: The approach divides the target volume into sub-volumes according to retrospectively observed spatial failure patterns. The product of all sub-volume TCPi values reproduces the observed TCP for the total tumor. The derived formalism provides for each target sub-volume i the tumor control dose (D50,i) and slope (γ50,i) parameters at 50% TCPi. For a simultaneous integrated boost (SIB) prescription for 45 advanced head and neck cancer patients, TCP values for photon and proton irradiation were calculated and compared. The target volume was divided into gross tumor volume (GTV), surrounding clinical target volume (CTV), and elective CTV (CTVE). The risk of a local failure in each of these sub-volumes was taken from the literature. RESULTS: Convenient expressions for D50,i and γ50,i were provided for the Poisson and the logistic model. Comparable TCP estimates were obtained for photon and proton plans of the 45 patients using the sub-volume model, despite notably higher dose levels (on average +4.9%) in the low-risk CTVE for photon irradiation. In contrast, assuming a homogeneous dose response in the entire target volume resulted in TCP estimates contradicting clinical experience (the highest failure rate in the low-risk CTVE) and differing substantially between photon and proton irradiation. CONCLUSIONS: The presented method is of practical value for three reasons: It (a) is based on empirical clinical outcome data; (b) can be applied to non-uniform dose prescriptions as well as different tumor entities and dose-response models; and (c) is provided in a convenient compact form. The approach may be utilized to target spatial patterns of local failures observed in patient cohorts by prescribing different doses to different target regions. Its predictive power depends on the uncertainty of the employed established TCP parameters D50 and γ50 and to a smaller extent on that of the clinically observed pattern of failure risk.

Evaluation of motion mitigation using abdominal compression in the clinical implementation of pencil beam scanning proton therapy of liver tumors.

PURPOSE: To determine whether individual liver tumor patients can be safely treated with pencil beam scanning proton therapy. This study reports a planning preparation workflow that can be used for beam angle selection and the evaluation of the efficacy of abdominal compression (AC) to mitigate motion. METHODS: Four-dimensional computed tomography scans (4DCT) with and without AC were available from 10 liver tumor patients with fluoroscopy-proven motion reduction by AC, previously treated using photons. For each scan, the motion amplitudes and the motion-induced variation of water-equivalent thickness (ΔWET) in each voxel of the target volume were evaluated during treatment plan preparation. Optimal proton beam angles were selected after volume analysis of the respective beam-specific planning target volume (BSPTV). M⊥80 and ΔWET80 derived from the 80th percentiles of perpendicular motion amplitude (M⊥ ) and ΔWET were compared with and without AC. Proton plans were created on the average CT to achieve target coverage similar to that of the conventional photon treatments. 4D dynamic dose calculation was performed postplan by synchronizing proton beam delivery timing patterns to the 4DCT phases to assess interplay and fractionation effects, and to determine motion criteria for subsequent patient treatment. RESULTS: Selected coplanar beam angles ranged between 180° and 39°, primarily from right lateral (oblique) and posterior (oblique) directions. While AC produced a significant reduction in mean Liver-GTV dose, any reduction in mean heart dose was patient dependent and not significant. Similarly, AC resulted in reductions in M⊥ , ΔWET, and BSPTV volumes and improved dose degradation (ΔD95 and ΔD1 ) within the CTV. For small motion (M⊥80 < 7 mm and ΔWET80 < 5 mm), motion mitigation was not needed. For moderate motion (M⊥80 7-10 mm or ΔWET80 5-7 mm), AC produced a modest improvement. For large motion (M⊥80 > 10 mm or ΔWET80 > 7 mm), AC and/or some other form of mitigation strategies were required. CONCLUSION: A workflow for screening patients' motion characteristics and optimizing beam angle selection was established for the pencil beam scanning proton therapy treatment of liver tumors. Abdominal compression was found to be useful at mitigation of moderate and large motion.