MLC tracking for lung SABR reduces planning target volumes and dose to organs at risk.

PURPOSE: Assess the dosimetric impact of multi-leaf collimator (MLC) tracking and mid-ventilation (midV) planning compared with the internal target volume (ITV)-based planning approach for lung Stereotactic Ablative Body Radiotherapy (SABR). METHOD: Ten lung SABR patients originally treated with an ITV-based plan were re-planned according to MLC tracking and midV planning schemes. All plans were delivered on a linac to a motion phantom in a simulated treatment with real lung motions. Delivered dose was reconstructed in patient planning scans. ITV-based, tracking and midV regimes were compared at the planning and delivered stages based on PTV volume and dose metrics for the GTV and OAR. RESULTS: MLC tracking and midV schemes yielded favourable outcomes compared with ITV-based plans. Average reduction in PTV volume was (MLC tracking/MidV) 33.9%/22%. GTV dose coverage performed better with MLC tracking than the other regimes. Reduction in dose to OAR were for the lung (mean lung dose, 0.8Gy/0.2Gy), oesophagus (D3cc, 1.9Gy/1.4Gy), great vessels (D10cc, 3.2Gy/1.3Gy), trachea (D4cc, 1.1Gy/0.9Gy), heart (D1cc, 2.0Gy/0.5Gy) and spinal cord (D0.03cc, 0.5Gy/-0.1Gy). CONCLUSION: MLC tracking showed reduction in PTV volume, superior GTV dose coverage and organ dose sparing than MidV and ITV-based strategies

An augmented correlation framework for the estimation of tumour translational and rotational motion during external beam radiotherapy treatments using intermittent monoscopic x-ray imaging and an external respiratory signal

© 2018 Institute of Physics and Engineering in Medicine. Increasing evidence shows that intrafraction tumour motion monitoring must include both six degrees of freedom (6DoF): 3D translations and 3D rotations. Existing real-time algorithms for 6DoF target motion estimation require continuous intrafraction fluoroscopic imaging at high frequency, thereby exposing patients to additional high imaging dose. This paper presents the first method capable of 6DoF motion monitoring using intermittent 2D kV imaging and a continuous external respiratory signal. Our approach is to optimise a state-augmented linear correlation model between an external signal and internal 6DoF motion. In standard treatments, the model can be built using information obtained during pre-treatment cone beam CT (CBCT). Real-time 6DoF tumor motion can then be estimated using just the external signal. Intermittent intrafraction kV images are used to update the model parameters, accounting for changes in correlation and baseline shifts. The method was evaluated in silico using data from 6 lung SABR patients, with the internal tumour motion recorded with electromagnetic beacons and the external signal from a bellows belt. Projection images from CBCT (10 Hz) and intermittent kV images were simulated by projecting the 3D Calypso beacon positions onto an imager. IMRT and VMAT treatments were simulated with increasing imaging update intervals: 0.1 s, 1 s, 3 s, 10 s and 30 s. For all the tested clinical scenarios, translational motion estimates with our method had sub-mm accuracy (mean) and precision (standard deviation) while rotational motion estimates were accurate to < and precise to . Motion estimation errors increased as the imaging update interval increased. With the largest imaging update interval (30 s), the errors were mm, mm and mm for translation in the left-right, superior-inferior and anterior-posterior directions, respectively, and , and for rotation around the aforementioned axes for both VMAT and IMRT treatments. In conclusion, we developed and evaluated a novel method for highly accurate real-time 6DoF motion monitoring on a standard linear accelerator without requiring continuous kV imaging. The proposed method achieved sub-mm and sub-degree accuracy on a lung cancer patient dataset

Quantifying the accuracy and precision of a novel real-time 6 degree-of-freedom kilovoltage intrafraction monitoring (KIM) target tracking system.

Target rotation can considerably impact the delivered radiotherapy dose depending on the tumour shape. More accurate tumour pose during radiotherapy treatment can be acquired through tracking in 6 degrees-of-freedom (6 DoF) rather than in translation only. A novel real-time 6 DoF kilovoltage intrafraction monitoring (KIM) target tracking system has recently been developed. In this study, we experimentally evaluated the accuracy and precision of the 6 DoF KIM implementation. Real-time 6 DoF KIM motion measurements were compared against the ground truth motion retrospectively derived from kV/MV triangulation for a range of lung and prostate tumour motion trajectories as well as for various static poses using a phantom. The accuracy and precision of 6 DoF KIM were calculated as the mean and standard deviation of the differences between KIM and kV/MV triangulation for each DoF, respectively. We found that KIM is able to provide 6 DoF motion with sub-degree and sub-millimetre accuracy and precision for a range of realistic tumour motion

Technical Note: In silico and experimental evaluation of two leaf-fitting algorithms for MLC tracking based on exposure error and plan complexity.

PURPOSE: Multileaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and pelvic motion during radiotherapy. The purpose of this work was to characterize the performance of two MLC leaf-fitting algorithms, direct optimization and piecewise optimization, for real-time motion compensation with different plan complexity and tumor trajectories. METHODS: To test the algorithms, both in silico and phantom experiments were performed. The phantom experiments were performed on a Trilogy Varian linac and a HexaMotion programmable motion platform. High and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC leaf-fitting algorithms, the plans were run with their corresponding patient trajectories. To compare algorithms, the average exposure errors, i.e., the difference in shape between ideal and fitted MLC leaves by the algorithm, plan complexity and system latency of each experiment were calculated. RESULTS: Comparison of exposure errors for the in silico and phantom experiments showed minor differences between the two algorithms. The average exposure errors for in silico experiments with low/high plan complexity were 0.66/0.88 cm2 for direct optimization and 0.66/0.88 cm2 for piecewise optimization, respectively. The average exposure errors for the phantom experiments with low/high plan complexity were 0.73/1.02 cm2 for direct and 0.73/1.02 cm2 for piecewise optimization, respectively. The measured latency for the direct optimization was 226 ± 10 ms and for the piecewise algorithm was 228 ± 10 ms. In silico and phantom exposure errors quantified for each treatment plan demonstrated that the exposure errors from the high plan complexity (0.96 cm2 mean, 2.88 cm2 95% percentile) were all significantly different from the low plan complexity (0.70 cm2 mean, 2.18 cm2 95% percentile) (P < 0.001, two-tailed, Mann-Whitney statistical test). CONCLUSIONS: The comparison between the two leaf-fitting algorithms demonstrated no significant differences in exposure errors, neither in silico nor with phantom experiments. This study revealed that plan complexity impacts the overall exposure errors significantly more than the difference between the algorithms

Aluminum-, Calcium- And Titanium-Rich Oxide Stardust In Ordinary Chondrite Meteorites

We report isotopic data for a total of 96 presolar oxide grains found in residues of several unequilibrated ordinary chondrite meteorites. Identified grain types include Al2O3, MgAl2O4, hibonite (CaAl12O19) and Ti oxide. This work greatly increases the presolar hibonite database, and is the first report of presolar Ti oxide. O-isotopic compositions of the grains span previously observed ranges and indicate an origin in red giant and asymptotic giant branch (AGB) stars of low mass (<2.5 MSun) for most grains. Cool bottom processing in the parent AGB stars is required to explain isotopic compositions of many grains. Potassium-41 enrichments in hibonite grains are attributable to in situ decay of now-extinct 41Ca. Inferred initial 41Ca/40Ca ratios are in good agreement with model predictions for low-mass AGB star envelopes, provided that ionization suppresses 41Ca decay. Stable Mg and Ca isotopic ratios of most of the hibonite grains reflect primarily the initial compositions of the parent stars and are generally consistent with expectations for Galactic chemical evolution, but require some local interstellar chemical inhomogeneity. Very high 17O/16O or 25Mg/24Mg ratios suggest an origin for some grains in binary star systems where mass transfer from an evolved companion has altered the parent star compositions. A supernova origin for the hitherto enigmatic 18O-rich Group 4 grains is strongly supported by multi-element isotopic data for two grains. The Group 4 data are consistent with an origin in a single supernova in which variable amounts of material from the deep 16O-rich interior mixed with a unique end-member mixture of the outer layers. The Ti oxide grains primarily formed in low-mass AGB stars. They are smaller and rarer than presolar Al2O3, reflecting the lower abundance of Ti than Al in AGB envelopes.Comment: Accepted for publication in ApJ; 47 pages, 13 figure

Quantitative analysis of powder mixtures by raman spectrometry : the influence of particle size and its correction

Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness

MLC tracking for lung SABR is feasible, efficient and delivers high-precision target dose and lower normal tissue dose.

Background and purposeThe purpose of this work is to present the clinical experience from the first-in-human trial of real-time tumor targeting via MLC tracking for stereotactic ablative body radiotherapy (SABR) of lung lesions.Methods and materialsSeventeen patients with stage 1 non-small cell lung cancer (NSCLC) or lung metastases were included in a study of electromagnetic transponder-guided MLC tracking for SABR (NCT02514512). Patients had electromagnetic transponders inserted near the tumor. An MLC tracking SABR plan was generated with planning target volume (PTV) expanded 5 mm from the end-exhale gross tumor volume (GTV). A clinically approved comparator plan was generated with PTV expanded 5 mm from a 4DCT-derived internal target volume (ITV). Treatment was delivered using a standard linear accelerator to continuously adapt the MLC based on transponder motion. Treated volumes and reconstructed delivered dose were compared between MLC tracking and comparator ITV-based treatment.ResultsAll seventeen patients were successfully treated with MLC tracking (70 successful fractions). MLC tracking treatment delivery time averaged 8 minutes. The time from the start of CBCT to the end of treatment averaged 22 minutes. The MLC tracking PTV for 16/17 patients was smaller than the ITV-based PTV (range -1.6% to 44% reduction, or -0.6 to 18 cc). Reductions in mean lung dose (27 cGy) and V20Gy (50 cc) were statistically significant (p ConclusionThe first treatments with lung MLC tracking have been successfully performed in seventeen SABR patients. MLC tracking for lung SABR is feasible, efficient and delivers high-precision target dose and lower normal tissue dose

Repurposing rapid diagnostic tests to detect falsified vaccines in supply chains

Substandard (including degraded) and falsified (SF) vaccines are a relatively neglected issue with serious global implications for public health. This has been highlighted during the rapid and widespread rollout of COVID-19 vaccines. There has been increasing interest in devices to screen for SF non-vaccine medicines including tablets and capsules to empower inspectors and standardise surveillance. However, there has been very limited published research focussed on repurposing or developing new devices for screening for SF vaccines. To our knowledge, rapid diagnostic tests (RDTs) have not been used for this purpose but have important potential for detecting falsified vaccines. We performed a proof-in-principle study to investigate their diagnostic accuracy using a diverse range of RDT-vaccine/falsified vaccine surrogate pairs. In an initial assessment, we demonstrated the utility of four RDTs in detecting seven vaccines. Subsequently, the four RDTs were evaluated by three blinded assessors with seven vaccines and four falsified vaccines surrogates. The results provide preliminary data that RDTs could be used by multiple international organisations, national medicines regulators and vaccine manufacturers/distributors to screen for falsified vaccines in supply chains, aligned with the WHO global ‘Prevent, Detect and Respond’ strategy

Emulating present and future simulations of melt rates at the base of Antarctic ice shelves with neural networks

Melt rates at the base of Antarctic ice shelves are needed to drive projections of the Antarctic ice sheet mass loss. Current basal melt parameterizations struggle to link open ocean properties to ice-shelf basal melt rates for the range of current sub-shelf cavity geometries around Antarctica. We present a proof of concept exploring the potential of simple deep learning techniques to parameterize basal melt. We train a simple feedforward neural network, or multilayer perceptron, acting on each grid cell separately, to emulate the behavior of circum-Antarctic cavity-resolving ocean simulations. We find that this kind of emulator produces reasonable basal melt rates for our training ensemble, at least as close as or closer to the reference than traditional parameterizations. On an independent ensemble of simulations that was produced with the same ocean model but with different model parameters, cavity geometries and forcing, the neural network yields similar results to traditional parameterizations on present conditions. In much warmer conditions, both traditional parameterizations and neural network struggle, but the neural network tends to produce basal melt rates closer to the reference than a majority of traditional parameterizations. While this shows that such a neural network is at least as suitable for century-scale Antarctic ice-sheet projections as traditional parameterizations, it also highlights that tuning any parameterization on present-like conditions can introduce biases and should be used with care. Nevertheless, this proof of concept is promising and provides a basis for further development of a deep learning basal melt parameterization

The Small RNA Teg41 Regulates Expression of the Alpha Phenol-Soluble Modulins and Is Required for Virulence in \u3ci\u3eStaphylococcus aureus\u3c/i\u3e

Small RNAs (sRNAs) remain an understudied class of regulatory molecules in bacteria in general and in Gram-positive bacteria in particular. In the major human pathogen Staphylococcus aureus, hundreds of sRNAs have been identified; however, only a few have been characterized in detail. In this study, we investigate the role of the sRNA Teg41 in S. aureus virulence. We demonstrate that Teg41, an sRNA divergently transcribed from the locus that encodes the cytolytic alpha phenolsoluble modulin (αPSM) peptides, plays a critical role in αPSM production. Overproduction of Teg41 leads to an increase in αPSM levels and a corresponding increase in hemolytic activity from S. aureus cells and cell-free culture supernatants. To identify regions of Teg41 important for its function, we performed an in silico RNA-RNA interaction analysis which predicted an interaction between the 3= end of Teg41 and the αPSM transcript. Deleting a 24-nucleotide region from the S. aureus genome, corresponding to the 3= end of Teg41, led to a 10-fold reduction in αPSM-dependent hemolytic activity and attenuation of virulence in a murine abscess model of infection. Restoration of hemolytic activity in the Teg41Δ3= strain was possible by expressing full-length Teg41 in trans. Restoration of hemolytic activity was also possible by expressing the 3= end of Teg41, suggesting that this region of Teg41 is necessary and sufficient for αPSMdependent hemolysis. Our results show that Teg41 is positively influencing αPSM production, demonstrating for the first time regulation of the αPSM peptides by an sRNA in S. aureus