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 PURPOSE: To 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. MATERIAL AND METHODS: Established 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. RESULTS: Registration 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. CONCLUSIONS: Especially 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.

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

BACKGROUND AND PURPOSE: Radiotherapy 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. METHODS: For 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. RESULTS: Our 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. CONCLUSION: This 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.

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.

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%/2mm γ-fail rate of 1.6% with adaptation and 15.2% without adaptation (p<0.001). For all prostate the mean 2%/2mm 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%/2mm 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.