Robustness analysis of dynamic trajectory radiotherapy and volumetric modulated arc therapy plans for head and neck cancer.

Background and purpose: Dynamic trajectory radiotherapy (DTRT) has been shown to improve healthy tissue sparing compared to volumetric arc therapy (VMAT). This study aimed to assess and compare the robustness of DTRT and VMAT treatment-plans for head and neck (H&N) cancer to patient-setup (PS) and machine-positioning uncertainties. Materials and methods: The robustness of DTRT and VMAT plans previously created for 46 H&N cases, prescribed 50-70 Gy to 95 % of the planning-target-volume, was assessed. For this purpose, dose distributions were recalculated using Monte Carlo, including uncertainties in PS (translation and rotation) and machine-positioning (gantry-, table-, collimator-rotation and multi-leaf collimator (MLC)). Plan robustness was evaluated by the uncertainties' impact on normal tissue complication probabilities (NTCP) for xerostomia and dysphagia and on dose-volume endpoints. Differences between DTRT and VMAT plan robustness were compared using Wilcoxon matched-pair signed-rank test (α = 5 %). Results: Average NTCP for moderate-to-severe xerostomia and grade ≥ II dysphagia was lower for DTRT than VMAT in the nominal scenario (0.5 %, p = 0.01; 2.1 %, p < 0.01) and for all investigated uncertainties, except MLC positioning, where the difference was not significant. Average differences compared to the nominal scenario were ≤ 3.5 Gy for rotational PS (≤ 3°) and machine-positioning (≤ 2°) uncertainties, <7 Gy for translational PS uncertainties (≤ 5 mm) and < 20 Gy for MLC-positioning uncertainties (≤ 5 mm). Conclusions: DTRT and VMAT plan robustness to the investigated uncertainties depended on uncertainty direction and location of the structure-of-interest to the target. NTCP remained on average lower for DTRT than VMAT even when considering uncertainties.

Organs-at-risk dose and normal tissue complication probability with dynamic trajectory radiotherapy (DTRT) for head and neck cancer.

We compared dynamic trajectory radiotherapy (DTRT) to state-of-the-art volumetric modulated arc therapy (VMAT) for 46 head and neck cancer cases. DTRT had lower dose to salivary glands and swallowing structure, resulting in lower predicted xerostomia and dysphagia compared to VMAT. DTRT is deliverable on C-arm linacs with high dosimetric accuracy.

Dosimetrically motivated beam-angle optimization for non-coplanar arc radiotherapy with and without dynamic collimator rotation.

BACKGROUND: Non-coplanar techniques have shown to improve the achievable dose distribution compared to standard coplanar techniques for multiple treatment sites but finding optimal beam directions is challenging. Dynamic collimator trajectory radiotherapy (colli-DTRT) is a new intensity modulated radiotherapy technique that uses non-coplanar partial arcs and dynamic collimator rotation. PURPOSE: To solve the beam angle optimization (BAO) problem for colli-DTRT and non-coplanar VMAT (NC-VMAT) by determining the table-angle and the gantry-angle ranges of the partial arcs through iterative 4π fluence map optimization (FMO) and beam direction elimination. METHODS: BAO considers all available beam directions sampled on a gantry-table map with the collimator angle aligned to the superior-inferior axis (colli-DTRT) or static (NC-VMAT). First, FMO is performed, and beam directions are scored based on their contributions to the objective function. The map is thresholded to remove the least contributing beam directions, and arc candidates are formed by adjacent beam directions with the same table angle. Next, FMO and arc candidate trimming, based on objective function penalty score, is performed iteratively until a desired total gantry angle range is reached. Direct aperture optimization on the final set of colli-DTRT or NC-VMAT arcs generates deliverable plans. colli-DTRT and NC-VMAT plans were created for seven clinically-motivated cases with targets in the head and neck (two cases), brain, esophagus, lung, breast, and prostate. colli-DTRT and NC-VMAT were compared to coplanar VMAT plans as well as to class-solution non-coplanar VMAT plans for the brain and head and neck cases. Dosimetric validation was performed for one colli-DTRT (head and neck) and one NC-VMAT (breast) plan using film measurements. RESULTS: Target coverage and conformity was similar for all techniques. colli-DTRT and NC-VMAT plans had improved dosimetric performance compared to coplanar VMAT for all treatment sites except prostate where all techniques were equivalent. For the head and neck and brain cases, mean dose reduction-in percentage of the prescription dose-to parallel organs was on average 0.7% (colli-DTRT), 0.8% (NC-VMAT) and 0.4% (class-solution) compared to VMAT. The reduction in D2% for the serial organs was on average 1.7% (colli-DTRT), 2.0% (NC-VMAT) and 0.9% (class-solution). For the esophagus, lung, and breast cases, mean dose reduction to parallel organs was on average 0.2% (colli-DTRT) and 0.3% (NC-VMAT) compared to VMAT. The reduction in D2% for the serial organs was on average 1.3% (colli-DTRT) and 0.9% (NC-VMAT). Estimated delivery times for colli-DTRT and NC-VMAT were below 4 min for a full gantry angle range of 720°, including transitions between arcs, except for the brain case where multiple arcs covered the whole table angle range. These times are in the same order as the class-solution for the head and neck and brain cases. Total optimization times were 25%-107% longer for colli-DTRT, including BAO, compared to VMAT. CONCLUSIONS: We successfully developed dosimetrically motivated BAO for colli-DTRT and NC-VMAT treatment planning. colli-DTRT and NC-VMAT are applicable to multiple treatment sites, including body sites, with beneficial or equivalent dosimetric performances compared to coplanar VMAT and reasonable delivery times.

Technical note: A collision prediction tool using Blender.

Non-coplanar radiotherapy treatment techniques on C-arm linear accelerators have the potential to reduce dose to organs-at-risk in comparison with coplanar treatment techniques. Accurately predicting possible collisions between gantry, table and patient during treatment planning is needed to ensure patient safety. We offer a freely available collision prediction tool using Blender, a free and open-source 3D computer graphics software toolset. A geometric model of a C-arm linear accelerator including a library of patient models is created inside Blender. Based on the model, collision predictions can be used both to calculate collision-free zones and to check treatment plans for collisions. The tool is validated for two setups, once with and once without a full body phantom with the same table position. For this, each gantry-table angle combination with a 2° resolution is manually checked for collision interlocks at a TrueBeam system and compared to simulated collision predictions. For the collision check of a treatment plan, the tool outputs the minimal distance between the gantry, table and patient model and a video of the movement of the gantry and table, which is demonstrated for one use case. A graphical user interface allows user-friendly input of the table and patient specification for the collision prediction tool. The validation resulted in a true positive rate of 100%, which is the rate between the number of correctly predicted collision gantry-table combinations and the number of all measured collision gantry-table combinations, and a true negative rate of 89%, which is the ratio between the number of correctly predicted collision-free combinations and the number of all measured collision-free combinations. A collision prediction tool is successfully created and able to produce maps of collision-free zones and to test treatment plans for collisions including visualisation of the gantry and table movement.

Delivery time reduction for mixed photon-electron radiotherapy by using photon MLC collimated electron arcs.

Objective. Electron arcs in mixed-beam radiotherapy (Arc-MBRT) consisting of intensity-modulated electron arcs with dynamic gantry rotation potentially reduce the delivery time compared to mixed-beam radiotherapy containing electron beams with static gantry angle (Static-MBRT). This study aims to develop and investigate a treatment planning process (TPP) for photon multileaf collimator (pMLC) based Arc-MBRT.Approach. An existing TPP for Static-MBRT plans is extended to integrate electron arcs with a dynamic gantry rotation and intensity modulation using a sliding window technique. The TPP consists of a manual setup of electron arcs, and either static photon beams or photon arcs, shortening of the source-to-surface distance for the electron arcs, initial intensity modulation optimization, selection of a user-defined number of electron beam energies based on dose contribution to the target volume and finally, simultaneous photon and electron intensity modulation optimization followed by full Monte Carlo dose calculation. Arc-MBRT plans, Static-MBRT plans, and photon-only plans were created and compared for four breast cases. Dosimetric validation of two Arc-MBRT plans was performed using film measurements.Main results. The generated Arc-MBRT plans are dosimetrically similar to the Static-MBRT plans while outperforming the photon-only plans. The mean heart dose is reduced by 32% on average in the MBRT plans compared to the photon-only plans. The estimated delivery times of the Arc-MBRT plans are similar to the photon-only plans but less than half the time of the Static-MBRT plans. Measured and calculated dose distributions agree with a gamma passing rate of over 98% (3% global, 2 mm) for both delivered Arc-MBRT plans.Significance. A TPP for Arc-MBRT is successfully developed and Arc-MBRT plans showed the potential to improve the dosimetric plan quality similar as Static-MBRT while maintaining short delivery times of photon-only treatments. This further facilitates integration of pMLC-based MBRT into clinical practice.

Deep-Learning-Based Dose Predictor for Glioblastoma-Assessing the Sensitivity and Robustness for Dose Awareness in Contouring.

External beam radiation therapy requires a sophisticated and laborious planning procedure. To improve the efficiency and quality of this procedure, machine-learning models that predict these dose distributions were introduced. The most recent dose prediction models are based on deep-learning architectures called 3D U-Nets that give good approximations of the dose in 3D almost instantly. Our purpose was to train such a 3D dose prediction model for glioblastoma VMAT treatment and test its robustness and sensitivity for the purpose of quality assurance of automatic contouring. From a cohort of 125 glioblastoma (GBM) patients, VMAT plans were created according to a clinical protocol. The initial model was trained on a cascaded 3D U-Net. A total of 60 cases were used for training, 15 for validation and 20 for testing. The prediction model was tested for sensitivity to dose changes when subject to realistic contour variations. Additionally, the model was tested for robustness by exposing it to a worst-case test set containing out-of-distribution cases. The initially trained prediction model had a dose score of 0.94 Gy and a mean DVH (dose volume histograms) score for all structures of 1.95 Gy. In terms of sensitivity, the model was able to predict the dose changes that occurred due to the contour variations with a mean error of 1.38 Gy. We obtained a 3D VMAT dose prediction model for GBM with limited data, providing good sensitivity to realistic contour variations. We tested and improved the model's robustness by targeted updates to the training set, making it a useful technique for introducing dose awareness in the contouring evaluation and quality assurance process.

Impact of the gradient in gantry-table rotation on dynamic trajectory radiotherapy plan quality.

BACKGROUND: To improve organ at risk (OAR) sparing, dynamic trajectory radiotherapy (DTRT) extends VMAT by dynamic table and collimator rotation during beam-on. However, comprehensive investigations regarding the impact of the gantry-table (GT) rotation gradient on the DTRT plan quality have not been conducted. PURPOSE: To investigate the impact of a user-defined GT rotation gradient on plan quality of DTRT plans in terms of dosimetric plan quality, dosimetric robustness, deliverability, and delivery time. METHODS: The dynamic trajectories of DTRT are described by GT and gantry-collimator paths. The GT path is determined by minimizing the overlap of OARs with planning target volume (PTV). This approach is extended to consider a GT rotation gradient by means of a maximum gradient of the path ( G m a x ${G}_{max}$ ) between two adjacent control points ( G = | Δ table angle / Δ gantry angle | $G = | \Delta {{\mathrm{table\ angle}}/\Delta {\mathrm{gantry\ angle}}} |$ ) and maximum absolute change of G ( Δ G m a x ${{\Delta}}{G}_{max}$ ). Four DTRT plans are created with different maximum G&∆G: G m a x ${G}_{max}$ & Δ G m a x ${{\Delta}}{G}_{max}$  = 0.5&0.125 (DTRT-1), 1&0.125 (DTRT-2), 3&0.125 (DTRT-3) and 3&1|(DTRT-4), including 3-4 dynamic trajectories, for three clinically motivated cases in the head and neck and brain region (A, B, and C). A reference VMAT plan for each case is created. For all plans, plan quality is assessed and compared. Dosimetric plan quality is evaluated by target coverage, conformity, and OAR sparing. Dosimetric robustness is evaluated against systematic and random patient-setup uncertainties between ± 3 mm $ \pm 3\ {\mathrm{mm}}$ in the lateral, longitudinal, and vertical directions, and machine uncertainties between ± 4 ∘ $ \pm 4^\circ \ $ in the dynamically rotating machine components (gantry, table, collimator rotation). Delivery time is recorded. Deliverability and delivery accuracy on a TrueBeam are assessed by logfile analysis for all plans and additionally verified by film measurements for one case. All dose calculations are Monte Carlo based. RESULTS: The extension of the DTRT planning process with user-defined G m a x & Δ G m a x ${G}_{max}\& {{\Delta}}{G}_{max}$ to investigate the impact of the GT rotation gradient on plan quality is successfully demonstrated. With increasing G m a x & Δ G m a x ${G}_{max}\& {{\Delta}}{G}_{max}$ , slight (case C, D m e a n , p a r o t i d l . ${D}_{mean,\ parotid\ l.}$ : up to|-1|Gy) and substantial (case A, D 0.03 c m 3 , o p t i c n e r v e r . ${D}_{0.03c{m}^3,\ optic\ nerve\ r.}$ : up to -9.3 Gy, case|B, D m e a n , b r a i n $\ {D}_{mean,\ brain}$ : up to -4.7|Gy) improvements in OAR sparing are observed compared to VMAT, while maintaining similar target coverage. All plans are delivered on the TrueBeam. Expected and actual machine position values recorded in the logfiles deviated by <0.2° for gantry, table and collimator rotation. The film measurements agreed by >96% (2%|global/2 mm Gamma passing rate) with the dose calculation. With increasing G m a x & Δ G m a x ${G}_{max}\& {{\Delta}}{G}_{max}$ , delivery time is prolonged by <2 min/trajectory (DTRT-4) compared to VMAT and DTRT-1. The DTRT plans for case A and B and the VMAT plan for case C plan reveal the best dosimetric robustness for the considered uncertainties. CONCLUSION: The impact of the GT rotation gradient on DTRT plan quality is comprehensively investigated for three cases in the head and neck and brain region. Increasing freedom in this gradient improves dosimetric plan quality at the cost of increased delivery time for the investigated cases. No clear dependency of GT rotation gradient on dosimetric robustness is observed.

Technical note: Feasibility of gating for dynamic trajectory radiotherapy - Mechanical accuracy and dosimetric performance.

BACKGROUND: Dynamic trajectory radiotherapy (DTRT) extends state-of-the-art volumetric modulated arc therapy (VMAT) by dynamic table and collimator rotations during beam-on. The effects of intrafraction motion during DTRT delivery are unknown, especially regarding the possible interplay between patient and machine motion with additional dynamic axes. PURPOSE: To experimentally assess the technical feasibility and quantify the mechanical and dosimetric accuracy of respiratory gating during DTRT delivery. METHODS: A DTRT and VMAT plan are created for a clinically motivated lung cancer case and delivered to a dosimetric motion phantom (MP) placed on the table of a TrueBeam system using Developer Mode. The MP reproduces four different 3D motion traces. Gating is triggered using an external marker block, placed on the MP. Mechanical accuracy and delivery time of the VMAT and DTRT deliveries with and without gating are extracted from the logfiles. Dosimetric performance is assessed by means of gamma evaluation (3% global/2 mm, 10% threshold). RESULTS: The DTRT and VMAT plans are successfully delivered with and without gating for all motion traces. Mechanical accuracy is similar for all experiments with deviations <0.14° (gantry angle), <0.15° (table angle), <0.09° (collimator angle) and <0.08 mm (MLC leaf positions). For DTRT (VMAT), delivery times are 1.6-2.3 (1.6- 2.5) times longer with than without gating for all motion traces except one, where DTRT (VMAT) delivery is 5.0 (3.6) times longer due to a substantial uncorrected baseline drift affecting only DTRT delivery. Gamma passing rates with (without) gating for DTRT/VMAT were ≥96.7%/98.5% (≤88.3%/84.8%). For one VMAT arc without gating it was 99.6%. CONCLUSION: Gating is successfully applied during DTRT delivery on a TrueBeam system for the first time. Mechanical accuracy is similar for VMAT and DTRT deliveries with and without gating. Gating substantially improved dosimetric performance for DTRT and VMAT.

Impact of random outliers in auto-segmented targets on radiotherapy treatment plans for glioblastoma.

AIMS: To save time and have more consistent contours, fully automatic segmentation of targets and organs at risk (OAR) is a valuable asset in radiotherapy. Though current deep learning (DL) based models are on par with manual contouring, they are not perfect and typical errors, as false positives, occur frequently and unpredictably. While it is possible to solve this for OARs, it is far from straightforward for target structures. In order to tackle this problem, in this study, we analyzed the occurrence and the possible dose effects of automated delineation outliers. METHODS: First, a set of controlled experiments on synthetically generated outliers on the CT of a glioblastoma (GBM) patient was performed. We analyzed the dosimetric impact on outliers with different location, shape, absolute size and relative size to the main target, resulting in 61 simulated scenarios. Second, multiple segmentation models where trained on a U-Net network based on 80 training sets consisting of GBM cases with annotated gross tumor volume (GTV) and edema structures. On 20 test cases, 5 different trained models and a majority voting method were used to predict the GTV and edema. The amount of outliers on the predictions were determined, as well as their size and distance from the actual target. RESULTS: We found that plans containing outliers result in an increased dose to healthy brain tissue. The extent of the dose effect is dependent on the relative size, location and the distance to the main targets and involved OARs. Generally, the larger the absolute outlier volume and the distance to the target the higher the potential dose effect. For 120 predicted GTV and edema structures, we found 1887 outliers. After construction of the planning treatment volume (PTV), 137 outliers remained with a mean distance to the target of 38.5 ± 5.0 mm and a mean size of 1010.8 ± 95.6 mm3. We also found that majority voting of DL results is capable to reduce outliers. CONCLUSIONS: This study shows that there is a severe risk of false positive outliers in current DL predictions of target structures. Additionally, these errors will have an evident detrimental impact on the dose and therefore could affect treatment outcome.

VoiceS: voice quality after transoral CO2 laser surgery versus single vocal cord irradiation for unilateral stage 0 and I glottic larynx cancer-a randomized phase III trial.

BACKGROUND: Surgery and radiotherapy are well-established standards of care for unilateral stage 0 and I early-stage glottic cancer (ESGC). Based on comparative studies and meta-analyses, functional and oncological outcomes after both treatment modalities are similar. Historically, radiotherapy (RT) has been performed by irradiation of the whole larynx. However, only the involved vocal cord is being treated with recently introduced hypofractionated concepts that result in 8 to 10-fold smaller target volumes. Retrospective data argues for an improvement in voice quality with non-inferior local control. Based on these findings, single vocal cord irradiation (SVCI) has been implemented as a routine approach in some institutions for ESGC in recent years. However, prospective data directly comparing SVCI with surgery is lacking. The aim of VoiceS is to fill this gap. METHODS: In this prospective randomized multi-center open-label phase III study with a superiority design, 34 patients with histopathologically confirmed, untreated, unilateral stage 0-I ESGC (unilateral cTis or cT1a) will be randomized to SVCI or transoral CO2-laser microsurgical cordectomy (TLM). Average difference in voice quality, measured by using the voice handicap index (VHI) will be modeled over four time points (6, 12, 18, and 24 months). Primary endpoint of this study will be the patient-reported subjective voice quality between 6 to 24 months after randomization. Secondary endpoints will include perceptual impression of the voice via roughness - breathiness - hoarseness (RBH) assessment at the above-mentioned time points. Additionally, quantitative characteristics of voice, loco-regional tumor control at 2 and 5 years, and treatment toxicity at 2 and 5 years based on CTCAE v.5.0 will be reported. DISCUSSION: To our knowledge, VoiceS is the first randomized phase III trial comparing SVCI with TLM. Results of this study may lead to improved decision-making in the treatment of ESGC. TRIAL REGISTRATION: ClinicalTrials.gov NCT04057209. Registered on 15 August 2019. Cantonal Ethics Committee KEK-BE 2019-01506.

Organ-at-risk sparing with dynamic trajectory radiotherapy for head and neck cancer: comparison with volumetric arc therapy on a publicly available library of cases.

BACKGROUND: Dynamic trajectory radiotherapy (DTRT) extends volumetric modulated arc therapy (VMAT) with dynamic table and collimator rotation during beam-on. The aim of the study is to establish DTRT path-finding strategies, demonstrate deliverability and dosimetric accuracy and compare DTRT to state-of-the-art VMAT for common head and neck (HN) cancer cases. METHODS: A publicly available library of seven HN cases was created on an anthropomorphic phantom with all relevant organs-at-risk (OARs) delineated. DTRT plans were generated with beam incidences minimizing fractional target/OAR volume overlap and compared to VMAT. Deliverability and dosimetric validation was carried out on the phantom. RESULTS: DTRT and VMAT had similar target coverage. For three locoregionally advanced oropharyngeal carcinomas and one adenoid cystic carcinoma, mean dose to the contralateral salivary glands, pharynx and oral cavity was reduced by 2.5, 1.7 and 3.1 Gy respectively on average with DTRT compared to VMAT. For a locally recurrent nasopharyngeal carcinoma, D0.03 cc to the ipsilateral optic nerve was above tolerance (54.0 Gy) for VMAT (54.8 Gy) but within tolerance for DTRT (53.3 Gy). For a laryngeal carcinoma, DTRT resulted in higher dose than VMAT to the pharynx and brachial plexus but lower dose to the upper oesophagus, thyroid gland and contralateral carotid artery. For a single vocal cord irradiation case, DTRT spared most OARs better than VMAT. All plans were delivered successfully on the phantom and dosimetric validation resulted in gamma passing rates of 93.9% and 95.8% (2%/2 mm criteria, 10% dose threshold). CONCLUSIONS: This study provides a proof of principle of DTRT for common HN cases with plans that were deliverable on a C-arm linac with high accuracy. The comparison with VMAT indicates substantial OAR sparing could be achieved.

Feasibility of postoperative spine stereotactic body radiation therapy in proximity of carbon and titanium hybrid implants using a robotic radiotherapy device.

BACKGROUND AND PURPOSE: To assess the feasibility of postoperative stereotactic body radiation therapy (SBRT) for patients with hybrid implants consisting of carbon fiber reinforced polyetheretherketone and titanium (CFP-T) using CyberKnife. MATERIALS AND METHODS: All essential steps within a radiation therapy (RT) workflow were evaluated. First, the contouring process of target volumes and organs at risk (OAR) was done for patients with CFP-T implants. Second, after RT-planning, the accuracy of the calculated dose distributions was tested in a slab phantom and an anthropomorphic phantom using film dosimetry. As a third step, the accuracy of the mandatory image guided radiation therapy (IGRT) including automatic matching was assessed using the anthropomorphic phantom. For this goal, a standard quality assurance (QA) test was modified to carry out its IGRT part in presence of CFP-T implants. RESULTS: Using CFP-T implants, target volumes could precisely delineated. There was no need for compromising the contours to overcome artifact obstacles. Differences between measured and calculated dose values were below 11% for the slab phantom, and at least 95% of the voxels were within 5% dose difference. The comparisons for the anthropomorphic phantom showed a gamma-passing rate (5%, 1 mm) of at least 97%. Additionally the test results with and without CFP-T implants were comparable. No issues concerning the IGRT were detected. The modified machine QA test resulted in a targeting error of 0.71 mm, which corresponds to the results of the unmodified standard tests. CONCLUSION: Dose calculation and delivery of postoperative spine SBRT is feasible in proximity of CFP-T implants using a CyberKnife system.

Development of a Monte Carlo based robustness calculation and evaluation tool.

BACKGROUND: Evaluating plan robustness is a key step in radiotherapy. PURPOSE: To develop a flexible Monte Carlo (MC)-based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity-modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components. METHODS: The robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user-defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intrafraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table-yaw, table-pitch, table-roll, translational positions of jaws, multileaf-collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user-specified conditions based on dose-volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on IMRT, a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT), and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry-, table-, collimator angle, MLC, and intrafraction motion. Additionally, the robustness of the IMRT, VMAT, and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available. RESULTS: The robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the planning target volume (PTV) margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of D 98 % CTV $D98{\% _{{\rm{CTV}}}}$ was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of D 2 % chiasma $D2{\% _{{\rm{chiasma}}}}$ was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma-passing rate (3% global/2 mm). CONCLUSIONS: The robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine-specific uncertainties and the combination thereof on the dose distribution are evaluated in a user-friendly GUI to quantitatively assess and compare treatment plans and their robustness.

Semi-classical Monte Carlo algorithm for the simulation of X-ray grating interferometry.

Traditional simulation techniques such as wave optics methods and Monte Carlo (MC) particle transport cannot model both interference and inelastic scattering phenomena within one framework. Based on the rules of quantum mechanics to calculate probabilities, we propose a new semi-classical MC algorithm for efficient and simultaneous modeling of scattering and interference processes. The similarities to MC particle transport allow the implementation as a flexible c++ object oriented extension of EGSnrc-a well-established MC toolkit. In addition to previously proposed Huygens principle based transport through optics components, new variance reduction techniques for the transport through gratings are presented as transport options to achieve the required improvement in speed and memory costs necessary for an efficient exploration (system design-dose estimations) of the medical implementation of X-ray grating interferometry (GI), an emerging imaging technique currently subject of tremendous efforts towards clinical translation. The feasibility of simulation of interference effects is confirmed in four academic cases and an experimental table-top GI setup. Comparison with conventional MC transport show that deposited energy features of EGSnrc are conserved.

Implementation and experimental validation of a robust hybrid direct aperture optimization approach for mixed-beam radiotherapy.

PURPOSE: The objectives of the work presented in this paper were to (1) implement a robust-optimization method for deliverable mixed-beam radiotherapy (MBRT) plans within a previously developed MBRT planning framework; (2) perform an experimental validation of the delivery of robust-optimized MBRT plans; and (3) compare PTV-based and robust-optimized MBRT plans in terms of target dose robustness and organs at risk (OAR) sparing for clinical head and neck and brain patient cases. METHODS: A robust-optimization method, which accounts for translational setup errors, was implemented within a previously developed treatment planning framework for MBRT. The framework uses a hybrid direct aperture optimization method combining column generation and simulated annealing. A robust plan was developed and then delivered to an anthropomorphic head phantom using the Developer Mode of a TrueBeam linac. Planar dose distributions were measured and compared to the planned dose. Robust-optimized and PTV-based plans were developed for three clinical patient cases consisting of two head and neck cases and one brain case. The plans were compared in terms of the robustness to 5 mm shifts of the target volume dose as well as in terms of OAR sparing. RESULTS: Using a gamma criterion of 3%/2 mm and a dose threshold of 10%, the agreement between film measurements and dose calculations was better than 97.7% for the total plan and better than 95.5% for the electron component of the plan. For the two head and neck patient cases, the average clinical target volume (CTV) dose homogeneity index (V95%-V107%) over all the considered setup error scenarios was on average 19% lower for the PTV-based plans and it had a larger standard deviation. The robust-optimized plans achieved, on average, a 20% reduction in the OAR doses compared to the PTV-based plans. For the brain patient case, the CTV dose homogeneity index was similar for the two plans, while the OAR doses were 22% lower, on average, for the robust-optimized plan. No clear trend in terms of electron contributions was found across the three patient cases, although robust-optimized plans tended toward higher electron beam energies. CONCLUSIONS: A framework for robust optimization of deliverable MBRT plans has been developed and validated. PTV-based MBRT were found to not be robust to setup errors, while the dose delivered by the robust-optimized plans were clinically acceptable for all considered error scenarios and had better OAR sparing. This study shows that the robust optimization is a promising alternative to conventional PTV margins for MBRT.

The predictive value of segmentation metrics on dosimetry in organs at risk of the brain.

BACKGROUND: Fully automatic medical image segmentation has been a long pursuit in radiotherapy (RT). Recent developments involving deep learning show promising results yielding consistent and time efficient contours. In order to train and validate these systems, several geometric based metrics, such as Dice Similarity Coefficient (DSC), Hausdorff, and other related metrics are currently the standard in automated medical image segmentation challenges. However, the relevance of these metrics in RT is questionable. The quality of automated segmentation results needs to reflect clinical relevant treatment outcomes, such as dosimetry and related tumor control and toxicity. In this study, we present results investigating the correlation between popular geometric segmentation metrics and dose parameters for Organs-At-Risk (OAR) in brain tumor patients, and investigate properties that might be predictive for dose changes in brain radiotherapy. METHODS: A retrospective database of glioblastoma multiforme patients was stratified for planning difficulty, from which 12 cases were selected and reference sets of OARs and radiation targets were defined. In order to assess the relation between segmentation quality -as measured by standard segmentation assessment metrics- and quality of RT plans, clinically realistic, yet alternative contours for each OAR of the selected cases were obtained through three methods: (i) Manual contours by two additional human raters. (ii) Realistic manual manipulations of reference contours. (iii) Through deep learning based segmentation results. On the reference structure set a reference plan was generated that was re-optimized for each corresponding alternative contour set. The correlation between segmentation metrics, and dosimetric changes was obtained and analyzed for each OAR, by means of the mean dose and maximum dose to 1% of the volume (Dmax 1%). Furthermore, we conducted specific experiments to investigate the dosimetric effect of alternative OAR contours with respect to the proximity to the target, size, particular shape and relative location to the target. RESULTS: We found a low correlation between the DSC, reflecting the alternative OAR contours, and dosimetric changes. The Pearson correlation coefficient between the mean OAR dose effect and the Dice was -0.11. For Dmax 1%, we found a correlation of -0.13. Similar low correlations were found for 22 other segmentation metrics. The organ based analysis showed that there is a better correlation for the larger OARs (i.e. brainstem and eyes) as for the smaller OARs (i.e. optic nerves and chiasm). Furthermore, we found that proximity to the target does not make contour variations more susceptible to the dose effect. However, the direction of the contour variation with respect to the relative location of the target seems to have a strong correlation with the dose effect. CONCLUSIONS: This study shows a low correlation between segmentation metrics and dosimetric changes for OARs in brain tumor patients. Results suggest that the current metrics for image segmentation in RT, as well as deep learning systems employing such metrics, need to be revisited towards clinically oriented metrics that better reflect how segmentation quality affects dose distribution and related tumor control and toxicity.

Assessment of Tumor Volume Dynamics and Outcome After Radiosurgery for the Treatment of Vestibular Schwannoma: A Single-Center Experience.

OBJECTIVE: To assess the factors affecting early local and audiometric outcomes in vestibular schwannoma (VS) patients treated with stereotactic radiosurgery (SRS). STUDY DESIGN: A retrospective review of medical records. SETTING: Tertiary referral center. PATIENTS: Records of all adult patients who underwent SRS between 2010 and 2016 for the treatment of VS were retrospectively reviewed. Patients treated with microsurgery or multi-fractionation schemes, and those who had neurofibromatosis type 2, were excluded. INTERVENTION: SRS, tumor volume/size measurements. MAIN OUTCOME MEASURES: The impact of tumor volume dynamics on the early local and hearing-related outcomes, together with the factors that influence them following SRS, and comparison of different tumor size measurement methods. RESULTS: From 2010 to 2016, 53 patients underwent single fraction SRS of 12 Gy. Median follow-up time was 32 months (range, 6-79). At the last follow-up, only one patient had clinical progression. Age less than or equal to 65 years (p = 0.04; odds ratio [OR]: 0.17; 95% confidence interval [CI]: 0.03-0.93) and baseline pure-tone average (PTA) level less than or equal to 30 dB (p = 0.03; OR: 0.90; 95% CI: 0.84-0.96) were associated with maintenance of serviceable hearing. On multivariate analysis, PTA remained significant (p = 0.01; OR: 0.04; 95% CI: 0.003-0.45). In patients with a loss of serviceable hearing, the mean volume increase tended to be higher than in the patients whose hearing was maintained. The linear measurement method underestimated, and the A × B × C/2 equation overestimated, the radiological progression compared with 3D-volumetric delineations. CONCLUSION: During the median observation period of almost 3 years, we reported our early outcome results. Tumor volume increase may have an impact on serviceable hearing loss after SRS. Currently there is no widely accepted method for the evaluation of post-SRS response. Linear measurement and the A × B × C/2 equation produce less reliable estimates of radiological progression compared with 3D-volumetric delineations. Accurate volume measurements with 3D delineations should be considered as part of clinical routine for assessing progression and deciding on salvage therapies.

Vestibular dose correlates with dizziness after radiosurgery for the treatment of vestibular schwannoma.

BACKGROUND: Stereotactic radiosurgery (SRS) has been recognized as a first-line treatment option for small to moderate sized vestibular schwannoma (VS). Our aim is to evaluate the impact of SRS doses and other patient and disease characteristics on vestibular function in patients with VS. METHODS: Data on VS patients treated with single-fraction SRS to 12 Gy were retrospectively reviewed. No dose constraints were given to the vestibule during optimization in treatment planning. Patient and tumor characteristics, pre- and post-SRS vestibular examination results and patient-reported dizziness were assessed from patient records. RESULTS: Fifty-three patients were analyzed. Median follow-up was 32 months (range, 6-79). The median minimum, mean and maximum vestibular doses were 2.6 ± 1.6 Gy, 6.7 ± 2.8 Gy, and 11 ± 3.6 Gy, respectively. On univariate analysis, Koos grade (p = 0.04; OR: 3.45; 95% CI 1.01-11.81), tumor volume (median 6.1 cm3; range, 0.8-38; p = 0.01; OR: 4.85; 95% CI 1.43-16.49), presence of pre-SRS dizziness (p = 0.02; OR: 3.98; 95% CI 1.19-13.24) and minimum vestibular dose (p = 0.033; OR: 1.55; 95% CI 1.03-2.32) showed a significant association with patient-reported dizziness. On multivariate analysis, minimum vestibular dose remained significant (p = 0.02; OR: 1.75; 95% CI 1.05-2.89). Patients with improved caloric function had received significantly lower mean (1.5 ± 0.7 Gy, p = 0.01) and maximum doses (4 ± 1.5 Gy, p = 0.01) to the vestibule. CONCLUSIONS: Our results reveal that 5 Gy and above minimum vestibular doses significantly worsened dizziness. Additionally, mean and maximum doses received by the vestibule were significantly lower in patients who had improved caloric function. Further investigations are needed to determine dose-volume parameters and their effects on vestibular toxicity.

Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning.

BACKGROUND: Automated brain tumor segmentation methods are computational algorithms that yield tumor delineation from, in this case, multimodal magnetic resonance imaging (MRI). We present an automated segmentation method and its results for resection cavity (RC) in glioblastoma multiforme (GBM) patients using deep learning (DL) technologies. METHODS: Post-operative, T1w with and without contrast, T2w and fluid attenuated inversion recovery MRI studies of 30 GBM patients were included. Three radiation oncologists manually delineated the RC to obtain a reference segmentation. We developed a DL cavity segmentation method, which utilizes all four MRI sequences and the reference segmentation to learn to perform RC delineations. We evaluated the segmentation method in terms of Dice coefficient (DC) and estimated volume measurements. RESULTS: Median DC of the three radiation oncologist were 0.85 (interquartile range [IQR]: 0.08), 0.84 (IQR: 0.07), and 0.86 (IQR: 0.07). The results of the automatic segmentation compared to the three different raters were 0.83 (IQR: 0.14), 0.81 (IQR: 0.12), and 0.81 (IQR: 0.13) which was significantly lower compared to the DC among raters (chi-square = 11.63, p = 0.04). We did not detect a statistically significant difference of the measured RC volumes for the different raters and the automated method (Kruskal-Wallis test: chi-square = 1.46, p = 0.69). The main sources of error were due to signal inhomogeneity and similar intensity patterns between cavity and brain tissues. CONCLUSIONS: The proposed DL approach yields promising results for automated RC segmentation in this proof of concept study. Compared to human experts, the DC are still subpar.

Technological quality requirements for stereotactic radiotherapy : Expert review group consensus from the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy.

This review details and discusses the technological quality requirements to ensure the desired quality for stereotactic radiotherapy using photon external beam radiotherapy as defined by the DEGRO Working Group Radiosurgery and Stereotactic Radiotherapy and the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The covered aspects of this review are 1) imaging for target volume definition, 2) patient positioning and target volume localization, 3) motion management, 4) collimation of the irradiation and beam directions, 5) dose calculation, 6) treatment unit accuracy, and 7) dedicated quality assurance measures. For each part, an expert review for current state-of-the-art techniques and their particular technological quality requirement to reach the necessary accuracy for stereotactic radiotherapy divided into intracranial stereotactic radiosurgery in one single fraction (SRS), intracranial fractionated stereotactic radiotherapy (FSRT), and extracranial stereotactic body radiotherapy (SBRT) is presented. All recommendations and suggestions for all mentioned aspects of stereotactic radiotherapy are formulated and related uncertainties and potential sources of error discussed. Additionally, further research and development needs in terms of insufficient data and unsolved problems for stereotactic radiotherapy are identified, which will serve as a basis for the future assignments of the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The review was group peer-reviewed, and consensus was obtained through multiple working group meetings.