Thilo Sothmann

A dosimetric comparison of real-time adaptive and non-adaptive radiotherapy: A multi-institutional study encompassing robotic, gimbaled, multileaf collimator and couch tracking.

Purpose A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presence of patient-measured tumor motion. Methods and materials Ten institutions with robotic(2), gimbaled(2), MLC(4) or couch tracking(2) used common materials including CT and structure sets, motion traces and planning protocols to create a lung and a prostate plan. For each motion trace, the plan was delivered twice to a moving dosimeter; with and without real-time adaptation. Each measurement was compared to a static measurement and the percentage of failed points for γ-tests recorded. Results For all lung traces all measurement sets show improved dose accuracy with a mean 2%/2 mm γ-fail rate of 1.6% with adaptation and 15.2% without adaptation (p < 0.001). For all prostate the mean 2%/2 mm γ-fail rate was 1.4% with adaptation and 17.3% without adaptation (p < 0.001). The difference between the four systems was small with an average 2%/2 mm γ-fail rate of <3% for all systems with adaptation for lung and prostate. Conclusions The investigated systems all accounted for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive delivery methods.

Real time tracking in liver SBRT: comparison of CyberKnife and Vero by planning structure-based γ-evaluation and dose-area-histograms.

The purpose of this study was to evaluate and compare two clinical tracking systems for radiosurgery with regard to their dosimetric and geometrical accuracy in liver SBRT: the robot-based CyberKnife and the gimbal-based Vero. Both systems perform real-time tumour tracking by correlating internal tumour and external surrogate motion. CyberKnife treatment plans were delivered to a high resolution 2D detector array mounted on a 4D motion platform, with the platform simulating (a) tumour motion trajectories extracted from the corresponding CyberKnife predictor log files and (b) the tumour motion trajectories with superimposed baseline-drift. Static reference and tracked dose measurements were compared and dosimetric as well as geometrical uncertainties analyzed by a planning structure-based evaluation. For (a), γ-passing rates inside the CTV (γ-criteria of 1% / 1u2009mm) ranged from 95% to 100% (CyberKnife) and 98% to 100% (Vero). However, dosimetric accuracy decreases in the presence of the baseline-drift. γ-passing rates for (b) ranged from 26% to 92% and 94% to 99%, respectively; i.e. the effect was more pronounced for CyberKnife. In contrast, the Vero system led to maximum dose deviations in the OAR betweenu2009u2009+1.5 Gy to +6.0 Gy (CyberKnife: +0.5 Gy to +3.5 Gy). Potential dose shifts were interpreted as motion-induced geometrical tracking errors. Maximum observed shift ranges wereu2009u2009-1.0u2009mm tou2009u2009+0.7u2009mm (lateral) /-0.6u2009mm to +0.1u2009mm (superior-inferior) for CyberKnife andu2009u2009-0.8u2009mm to +0.2u2009mm /-0.8u2009mm to +0.4u2009mm for Vero. These values illustrate that CyberKnife and Vero provide high precision tracking of regular breathing patterns. Even for the modified motion trajectory, the obtained dose distributions appear to be clinical acceptable with regard to literature QA γ-criteria of 3% / 3u2009mm.

4D dose simulation in volumetric arc therapy: Accuracy and affecting parameters

Radiotherapy of lung and liver lesions has changed from normofractioned 3D-CRT to stereotactic treatment in a single or few fractions, often employing volumetric arc therapy (VMAT)-based techniques. Potential unintended interference of respiratory target motion and dynamically changing beam parameters during VMAT dose delivery motivates establishing 4D quality assurance (4D QA) procedures to assess appropriateness of generated VMAT treatment plans when taking into account patient-specific motion characteristics. Current approaches are motion phantom-based 4D QA and image-based 4D VMAT dose simulation. Whereas phantom-based 4D QA is usually restricted to a small number of measurements, the computational approaches allow simulating many motion scenarios. However, 4D VMAT dose simulation depends on various input parameters, influencing estimated doses along with mitigating simulation reliability. Thus, aiming at routine use of simulation-based 4D VMAT QA, the impact of such parameters as well as the overall accuracy of the 4D VMAT dose simulation has to be studied in detail–which is the topic of the present work. In detail, we introduce the principles of 4D VMAT dose simulation, identify influencing parameters and assess their impact on 4D dose simulation accuracy by comparison of simulated motion-affected dose distributions to corresponding dosimetric motion phantom measurements. Exploiting an ITV-based treatment planning approach, VMAT treatment plans were generated for a motion phantom and different motion scenarios (sinusoidal motion of different period/direction; regular/irregular motion). 4D VMAT dose simulation results and dose measurements were compared by local 3% / 3 mm γ-evaluation, with the measured dose distributions serving as ground truth. Overall γ-passing rates of simulations and dynamic measurements ranged from 97% to 100% (mean across all motion scenarios: 98% ± 1%); corresponding values for comparison of different day repeat measurements were between 98% and 100%. Parameters of major influence on 4D VMAT dose simulation accuracy were the degree of temporal discretization of the dose delivery process (the higher, the better) and correct alignment of the assumed breathing phases at the beginning of the dose measurements and simulations. Given the high γ-passing rates between simulated motion-affected doses and dynamic measurements, we consider the simulations to provide a reliable basis for assessment of VMAT motion effects that–in the sense of 4D QA of VMAT treatment plans–allows to verify target coverage in hypofractioned VMAT-based radiotherapy of moving targets. Remaining differences between measurements and simulations motivate, however, further detailed studies.

Analysis of the influence of imaging-related uncertainties on cerebral aneurysm deformation quantification using a no-deformation physical flow phantom

Cardiac-cycle related pulsatile aneurysm motion and deformation is assumed to provide valuable information for assessing cerebral aneurysm rupture risk. Accordingly, numerous studies addressed quantification of cerebral aneurysm wall motion and deformation. Most of them utilized in vivo imaging data, but image-based aneurysm deformation quantification is subject to pronounced uncertainties: unknown ground-truth deformation; image resolution in the order of the expected deformation; direct interplay between contrast agent inflow and image intensity. To analyze the impact of the uncertainties on deformation quantification, a multi-imaging modality ground-truth phantom study is performed. A physical flow phantom was designed that allowed simulating pulsatile flow through a variety of modeled cerebral vascular structures. The phantom was imaged using different modalities [MRI, CT, 3D-RA] and mimicking physiologically realistic flow conditions. Resulting image data was analyzed by an established registration-based approach for automated wall motion quantification. The data reveals severe dependency between contrast media inflow-related image intensity changes and the extent of estimated wall deformation. The study illustrates that imaging-related uncertainties affect the accuracy of cerebral aneurysm deformation quantification, suggesting that in vivo imaging studies have to be accompanied by ground-truth phantom experiments to foster data interpretation and to prove plausibility of the applied image analysis algorithms.

Influence of deformable image registration on 4D dose simulation for extracranial SBRT: A multi-registration framework study

BACKGROUND AND PURPOSEnTo evaluate the influence of deformable image registration approaches on correspondence model-based 4D dose simulation in extracranial SBRT by means of open source deformable image registration (DIR) frameworks.nnnMATERIAL AND METHODSnEstablished DIR algorithms of six different open source DIR frameworks were considered and registration accuracy evaluated using freely available 4D image data. Furthermore, correspondence models (regression-based correlation of external breathing signal measurements and internal structure motion field) were built and model accuracy evaluated. Finally, the DIR algorithms were applied for motion field estimation in radiotherapy planning 4D CT data of five lung and five liver lesion patients, correspondence model formation, and model-based 4D dose simulation. Deviations between the original, statically planned and the 4D-simulated VMAT dose distributions were analyzed and correlated to DIR accuracy differences.nnnRESULTSnRegistration errors varied among the DIR approaches, with lower DIR accuracy translating into lower correspondence modeling accuracy. Yet, for lung metastases, indices of 4D-simulated dose distributions widely agreed, irrespective of DIR accuracy differences. In contrast, liver metastases 4D dose simulation results strongly vary for the different DIR approaches.nnnCONCLUSIONSnEspecially in treatment areas with low image contrast (e.g. the liver), DIR-based 4D dose simulation results strongly depend on the applied DIR algorithm, drawing resulting dose simulations and indices questionable.

Correspondence model-based 4D VMAT dose simulation for analysis of local metastasis recurrence after extracranial SBRT

The purpose of this study is to introduce a novel approach to incorporate patient-specific breathing variability information into 4D dose simulation of volumetric arc therapy (VMAT)-based stereotactic body radiotherapy (SBRT) of extracranial metastases. Feasibility of the approach is illustrated by application to treatment planning and motion data of lung and liver metastasis patients. The novel 4D dose simulation approach makes use of a regression-based correspondence model that allows representing patient motion variability by breathing signal-steered interpolation and extrapolation of deformable image registration motion fields. To predict the internal patient motion during treatment with only external breathing signal measurements being available, the patients internal motion information and external breathing signals acquired during 4D CT imaging were correlated. Combining the correspondence model, patient-specific breathing signal measurements during treatment and time-resolved information about dose delivery, reconstruction of a motion variability-affected dose becomes possible. As a proof of concept, the proposed approach is illustrated by a retrospective 4D simulation of VMAT-based SBRT treatment of ten patients with 15 treated lung and liver metastases and known clinical endpoints for the individual metastases (local metastasis recurrence yes/no). Resulting 4D-simulated dose distributions were compared to motion-affected dose distributions estimated by standard 4D CT-only dose accumulation and the originally (i.e. statically) planned dose distributions by means of GTV [Formula: see text] indices (dose to 98% of the GTV volume). A potential linkage of metastasis-specific endpoints to differences between GTV [Formula: see text] indices of planned and 4D-simulated dose distributions was analyzed.

Low Rank and Sparse Matrix Decomposition as Stroke Segmentation Prior: Useful or Not? A Random Forest-Based Evaluation Study.

Manual ischemic stroke lesion segmentation in MR image data is a time-consuming task subject to inter-rater variability. Reliable automated lesion segmentation is of high interest for clinical trials and research in ischemic stroke. However, recent segmentation challenges (e.g. ISLES 2015) illustrate that current state-of-the-art approaches still lack accuracy and ischemic stroke segmentation remains a complicated problem. Within this context, low rank-&-sparse matrix decomposition (also known as robust PCA, RPCA) and RPCA-based non-linear subject-toatlas registration could provide valuable segmentation prior information. The aim of this study is to evaluate the suitability of RPCA and RPCAbased registration for ischemic stroke segmentation in follow-up FLAIR MR data sets. Building on a top-ranked segmentation approach of ISLES 2015, the performance of RPCA sparse component image information as random forest (RF) feature is evaluated. A comprehensive feature-byfeature comparison of the segmentation performance with and without RPCA sparse component information as RF feature illustrate the potential of low rank-&-sparse decomposition to improve stroke segmentation.

TH‐AB‐303‐01: Benchmarking Real‐Time Adaptive Radiotherapy Systems: A Multi‐ Platform Multi‐Institutional Study

Purpose: The era of real-time adaptive radiotherapy is here: patients are being treated by CyberKnife (since 2004), Vero (2011) and MLC tracking (2013) technology, with couch tracking planned to be clinical in 2015. We have developed a common set of tools for benchmarking real-time adaptive radiotherapy systems and to test the hypothesis that, across delivery systems and institutions, real-time adaptive radiotherapy improves the dosimetric accuracy over non-adaptive radiotherapy in the presence of realistic tumor motion. Methods: Ten institutions with CyberKnife, Vero, MLC or couch tracking technology were involved in the study. Common materials were anonymized lung and prostate CT and structure sets, patient-measured motion traces (four lung, four prostate) and SBRT planning protocols (lung: RTOG1021, prostate: RTOG0938). The institutions delivered lung and prostate plans to a moving dosimeter programmed with tumor motion. For each trace the plan was delivered twice; with and without motion adaptation, each measurement was compared to the static dosimeter dose and the percentage of failed points for γ-tests recorded. Results: Eleven measurement sets were obtained for this study; two CyberKnife, two Vero, five MLC and two couch tracking sets. For all lung traces all sets show improved dose accuracy from a mean 2%/2mm γ-failrate of 1.6% with adaptation and 14.7% with no motion correction(p<0.001). For all prostate traces the mean 2%/2mm γ-failrate was 1.6% with adaptation and 17.4% with no motion correction (p<0.001). The difference between the four adaptive systems was small with an average 2%/2mm γ-failrate of <3% for all systems with adaptation for lung and prostate. Conclusion: A common set of tools has been developed for benchmarking real-time adaptive radiotherapy systems and a multi-platform multi-institutional study performed. The results show the systems all account for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive methods.

Under-reported dosimetry errors due to interplay effects during VMAT dose delivery in extreme hypofractionated stereotactic radiotherapy

Background and purposeRadiotherapy of extracranial metastases changed from normofractioned 3D CRT to extreme hypofractionated stereotactic treatment using VMAT beam techniques. Random interaction between tumour motion and dynamically changing beam parameters might result in underdosage of the CTV even for an appropriately dimensioned ITV (interplay effect). This study presents a clinical scenario of extreme hypofractionated stereotactic treatment and analyses the impact of interplay effects on CTV dose coverage.MethodsFor a thoracic/abdominal phantom with an integrated high-resolution detector array placed on a 4D motion platform, dual-arc treatment plans with homogenous target coverage were created using a common VMAT technique and delivered in a single fraction. CTV underdosage through interplay effects was investigated by comparing dose measurements with and without tumour motion during plan delivery.ResultsOur study agrees with previous works that pointed out insignificant interplay effects on target coverage for very regular tumour motion patterns like simple sinusoidal motion. However, we identified and illustrated scenarios that are likely to result in a clinically relevant CTV underdosage. For tumour motion with abnormal variability, target coverage quantified by the CTV area receiving more than 98% of the prescribed dose decreased to 78% compared to 100% at static dose measurement.ConclusionThis study is further proof of considerable influence of interplay effects on VMAT dose delivery in stereotactic radiotherapy. For selected conditions of an exemplary scenario, interplay effects and related motion-induced target underdosage primarily occurred in tumour motion pattern with increased motion variability and VMAT plan delivery using complex MLC dose modulation.ZusammenfassungHintergrund und ZielsetzungDie Strahlentherapie extrakranieller Metastasen hat sich von einer normofraktionierten 3D-CRT zu einer extrem hypofraktionierten stereotaktischen Behandlung unter Verwendung einer VMAT-Bestrahlungstechnik entwickelt. Zufällige Interaktion zwischen Tumorbewegung und dynamisch veränderlicher VMAT-Bestrahlungsparameter kann zu einer Unterdosierung des klinischen Zielvolumens – auch für ein ausreichend dimensioniertes ITV – führen (Interplay-Effekt). Diese Studie untersucht ein klinisches Szenario einer extrem hypofraktionierten stereotaktischen Behandlung und analysiert die Auswirkungen von Interplay-Effekten auf die Zielvolumenabdeckung.MethodenFür ein thorakales/abdominelles Messphantom mit einem integrierten hochauflösenden Detektorarray auf einer 4D-Bewegungsplattform wurden Bestrahlungspläne für eine Fraktion und eine homogene Zielvolumenabdeckung mittels einer weitverbreiteten VMAT-Bestrahlungstechnik erstellt. Unterdosierung des CTV durch Interplay-Effekte wurde mittels Vergleich von Dosismessungen mit und ohne artifizieller/realer Tumorbewegung während der Bestrahlung untersucht.ErgebnisseUnsere Analyse stimmt mit früheren Arbeiten überein, die auf geringe Interplay-Effekte im Zielvolumen bei sehr regelmäßigen Bewegungsmustern, wie einfache sinusoidale Bewegung, hingewiesen haben. Allerdings haben wir Szenarien identifiziert und untersucht, die zu klinisch relevanten CTV-Unterdosierungen führen können. Für reale Tumorbewegungsmuster mit intrafraktioneller Variabilität verringerte sich die Zielabdeckung – quantifiziert durch den CTV-Bereich, der mehr als 98% der verschriebenen Dosis erhält – auf 78% im Vergleich zu 100% der statischen Dosismessung.SchlussfolgerungDiese Studie ist ein weiterer Nachweis für beträchtliche Interplay-Effekte bei VMAT-Bestrahlungen in einer stereotaktischen Strahlentherapie. Für ausgewählte Bedingungen eines typischen Szenarios traten Interplay-Effekte und eine damit verbundene bewegungsinduzierte Zielvolumenunterdosierung überwiegend bei realen Tumorbewegungsmustern mit erhöhter Bewegungsvariabilität sowie bei VMAT-Bestrahlung mit komplexer MLC Dosismodulation auf.

Technical considerations for automated low-pitch spiral 4D CT scanning protocol selection

Respiration-correlated CT (4D CT) represents the basis of radiotherapy treatment planning for thoracic and abdominal tumor patients. A common approach is low-pitch spiral 4D CT. Similar to standard spiral 3D CT, CT projection data are continuously acquired while the patient couch is moving through the gantry. To ensure sufficient projection data coverage for 4D CT reconstruction, the so-called 4D CT data sufficiency condition (DSC) has to be fulfilled: For a fixed pitch factor and gantry rotation time, the patient breathing rate must be above a certain threshold; otherwise, artifacts impair image quality. For the current Siemens 4D CT scanner generation, three 4D CT protocols can be selected manually, associated with DSC thresholds of 6, 9 and 12 breaths per minute (BPM). Due to, e.g., a limited achievable z-range during scanning with lower BPM protocols, these options are, however, often not selected in practice. As a result, a high fraction of artifact-affected 4D CT data are reported. Aiming to optimize respective 4D CT workflows and improve image quality, this study systematically investigates the influence of parameters to be considered for automated scanning protocol selection and their interrelation (e.g. severity of artifacts due to DSC violation vs. clinically required z-scan range).