A hybrid column generation and simulated annealing algorithm for direct aperture optimization.

The purpose of this work was to develop a hybrid column generation (CG) and simulated annealing (SA) algorithm for direct aperture optimization (H-DAO) and to show its effectiveness in generating high quality treatment plans for intensity modulated radiation therapy (IMRT) and mixed photon-electron beam radiotherapy (MBRT). The H-DAO overcomes limitations of the CG-DAO with two features improving aperture selection (branch-feature) and enabling aperture shape changes during optimization (SA feature). The H-DAO algorithm iteratively adds apertures to the plan. At each iteration, a branch is created for each field provided. First, each branch determines the most promising aperture of its assigned field and adds it to a copy of the current apertures. Afterwards, the apertures of each branch undergo an MU-weight optimization followed by an SA-based simultaneous shape and MU-weight optimization and a second MU-weight optimization. The next H-DAO iteration continues the branch with the lowest objective function value. IMRT and MBRT treatment plans for an academic, a brain and a head and neck case generated using the CG DAO and H DAO were compared. For every investigated case and both IMRT and MBRT, the H-DAO leads to a faster convergence of the objective function value with number of apertures compared to the CG-DAO. In particular, the H DAO needs on average half the apertures to reach the same objective function value as the CG DAO for a specifically selected number of apertures. The average aperture areas are 27% smaller for H-DAO than for CG-DAO leading to a slightly larger discrepancy between optimized and final dose. However, a dosimetric benefit remains. The H-DAO was successfully developed and applied to IMRT and MBRT. The faster convergence with number of apertures of the H-DAO compared to the CG-DAO allows to select a better compromise between plan quality and number of apertures

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

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 ( ) between two adjacent control points ( ) and maximum absolute change of G ( ). Four DTRT plans are created with different maximum G&∆G: &  = 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 in the lateral, longitudinal, and vertical directions, and machine uncertainties between 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 to investigate the impact of the GT rotation gradient on plan quality is successfully demonstrated. With increasing , slight (case C, : up to‍-1‍Gy) and substantial (case A, : up to -9.3 Gy, case‍B, : up to -4.7‍Gy) 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 96% (2%‍global/2 mm Gamma passing rate) with the dose calculation. With increasing , 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

Real-time reconstruction and visualisation towards dynamic feedback control during time-resolved tomography experiments at TOMCAT

Tomographic X-ray microscopy beamlines at synchrotron light sources worldwide have pushed the achievable time-resolution for dynamic 3-dimensional structural investigations down to a fraction of a second, allowing the study of quickly evolving systems. The large data rates involved impose heavy demands on computational resources, making it difficult to readily process and interrogate the resulting volumes. The data acquisition is thus performed essentially blindly. Such a sequential process makes it hard to notice problems with the measurement protocol or sample conditions, potentially rendering the acquired data unusable, and it keeps the user from optimizing the experimental parameters of the imaging task at hand. We present an efficient approach to address this issue based on the real-time reconstruction, visualisation and on-the-fly an

Deep learning based classification of dynamic processes in time-resolved X-ray tomographic microscopy

Time-resolved X-ray tomographic microscopy is an invaluable technique to investigate dynamic processes in 3D for extended time periods. Because of the limited signal-to-noise ratio caused by the short exposure times and sparse angular sampling frequency, obtaining quantitative information through post-processing remains challenging and requires intensive manual labor. This severely limits the accessible experimental parameter space and so, prevents fully exploiting the capabilities of the dedicated time-resolved X-ray tomographic stations. Though automatic approaches, often exploiting iterative reconstruction methods, are currently being developed, the required computational costs typically remain high. Here, we propose a highly efficient reconstruction and classification pipeline (SIRT-FBP-MS-D-DIFF) that combines an algebraic filter approximation and machine learning to significantly reduce the computational time. The dynamic features are reconstructed by standard filtered back-projection with an algebraic filter to approximate iterative reconstruction quality in a computationally efficient manner. The raw reconstructions are post-processed with a trained convolutional neural network to extract the dynamic features from the low signal-to-noise ratio reconstructions in a fully automatic manner. The capabilities of the proposed pipeline are demonstrated on three different dynamic fuel cell datasets, one exploited for training and two for testing without network retraining. The proposed approach enables automatic processing of several hundreds of datasets in a single day on a single GPU node readily available at most institutions, so extending the possibilities in future dynamic X-ray tomographic investigations

In Vivo Time- Resolved Microtomography Reveals the Mechanics of the Blowfly Flight Motor

Dipteran flies are amongst the smallest and most agile of flying animals. Their wings are driven indirectly by large power muscles, which cause cyclical deformations of the thorax that are amplified through the intricate wing hinge. Asymmetric flight manoeuvres are controlled by 13 pairs of steering muscles acting directly on the wing articulations. Collectively the steering muscles account for <3% of total flight muscle mass, raising the question of how they can modulate the vastly greater output of the power muscles during manoeuvres. Here we present the results of a synchrotron-based study performing micrometre-resolution, time-resolved microtomography on the 145 Hz wingbeat of blowflies. These data represent the first four-dimensional visualizations of an organism's internal movements on sub-millisecond and micrometre scales. This technique allows us to visualize and measure the three-dimensional movements of five of the largest steering muscles, and to place these in the context of the deforming thoracic mechanism that the muscles actuate. Our visualizations show that the steering muscles operate through a diverse range of nonlinear mechanisms, revealing several unexpected features that could not have been identified using any other technique. The tendons of some steering muscles buckle on every wingbeat to accommodate high amplitude movements of the wing hinge. Other steering muscles absorb kinetic energy from an oscillating control linkage, which rotates at low wingbeat amplitude but translates at high wingbeat amplitude. Kinetic energy is distributed differently in these two modes of oscillation, which may play a role in asymmetric power management during flight control. Structural flexibility is known to be important to the aerodynamic efficiency of insect wings, and to the function of their indirect power muscles. We show that it is integral also to the operation of the steering muscles, and so to the functional flexibility of the insect flight motor

Dissecting abdominal aortic aneurysm in Ang II-infused mice: suprarenal branch ruptures and apparent luminal dilatation.

AIMS In this work, we provide novel insight into the morphology of dissecting abdominal aortic aneurysms in angiotensin II-infused mice. We demonstrate why they exhibit a large variation in shape and, unlike their human counterparts, are located suprarenally rather than infrarenally. METHODS AND RESULTS We combined synchrotron-based, ultra-high resolution ex vivo imaging (phase contrast X-Ray tomographic microscopy) with in vivo imaging (high-frequency ultrasound and contrast-enhanced micro-CT) and image-guided histology. In all mice, we observed a tear in the tunica media of the abdominal aorta near the ostium of the celiac artery. Independently we found that, unlike the gradual luminal expansion typical for human aneurysms, the outer diameter increase of angiotensin II-induced dissecting aneurysms in mice was related to one or several intramural haematomas. These were caused by ruptures of the tunica media near the ostium of small suprarenal side branches, which had never been detected by the established small animal imaging techniques. The tear near the celiac artery led to apparent luminal dilatation, while the intramural haematoma led to a dissection of the tunica adventitia on the left suprarenal side of the aorta. The number of ruptured branches was higher in those aneurysms that extended into the thoracic aorta, which explained the observed variability in aneurysm shape. CONCLUSION Our results are the first to describe apparent luminal dilatation, suprarenal branch ruptures, and intramural haematoma formation in dissecting abdominal aortic aneurysms in mice. Moreover, we validate and demonstrate the vast potential of phase contrast X-ray tomographic microscopy in cardiovascular small animal applications

Evidence confirms an anthropic origin of Amazonian Dark Earths.

Arising from: Silva et al. Nature Communications https://doi.org/10.1038/s41467-020-20184-2 (2021

A Swiss cheese error detection method for real-time EPID-based quality assurance and error prevention.

PURPOSE To develop a robust and efficient process that detects relevant dose errors (dose errors of ≥5%) in external beam radiation therapy and directly indicates the origin of the error. The process is illustrated in the context of electronic portal imaging device (EPID)-based angle-resolved volumetric modulated arc therapy (VMAT) quality assurance (QA), particularly as would be implemented in a real-time monitoring program. METHODS A Swiss cheese error detection (SCED) method was created as a paradigm for a cine EPID-based during-treatment QA. For VMAT, the method compares a treatment-plan-based reference set of EPID images with images acquired over each 2° gantry angle interval. The process utilizes a sequence of independent consecutively executed error detection tests: an aperture check that verifies infield radiation delivery and ensures no out-of-field radiation; output normalization checks at two different stages; global image alignment check to examine if rotation, scaling and translation are within tolerances; pixel intensity check containing the standard gamma evaluation (3%, 3 mm) and pixel intensity deviation checks including and excluding high dose gradient regions. Tolerances for each check were determined. To test the SCED method, 12 different types of errors were selected to modify the original plan. A series of angle-resolved predicted EPID images was artificially generated for each test case, resulting in a sequence of pre-calculated frames for each modified treatment plan. The SCED method was applied multiple times for each test case to assess the ability to detect introduced plan variations. To compare the performance of the SCED process with that of a standard gamma analysis, both error detection methods were applied to the generated test cases with realistic noise variations. RESULTS Averaged over ten test runs, 95.1% of all plan variations that resulted in relevant patient dose errors were detected within 2° and 100% within 14° (<4% of patient dose delivery). Including cases that led to slightly modified but clinically equivalent plans, 89.1% were detected by the SCED method within 2°. Based on the type of check that detected the error, determination of error sources was achieved. With noise ranging from no random noise to four times the established noise value, the averaged relevant dose error detection rate of the SCED method was between 94.0% and 95.8% and that of gamma between 82.8% and 89.8%. CONCLUSIONS An EPID-frame-based error detection process for VMAT deliveries was successfully designed and tested via simulations. The SCED method was inspected for robustness with realistic noise variations, demonstrating that it has the potential to detect a large majority of relevant dose errors. Compared to a typical (3%, 3 mm) gamma analysis, the SCED method produced a higher detection rate for all introduced dose errors, identified errors in an earlier stage, displayed a higher robustness to noise variations and indicated the error source. This article is protected by copyright. All rights reserved