118 research outputs found
Observation of Non-isotropic Auger Angular Distribution in the C(1s) Shape Resonance of CO
Angle-resolved high-resolution C(KVV) Auger spectra of CO were taken in the vicinity of the C(1s) σ* shape resonance. These spectra show clear evidence for the theoretically predicted anisotropic K-shell Auger emission in molecules. Complementary results from angle-resolved photoion spectroscopy show that the small size of the observed effect is, besides the varying intrinsic anisotropy of the Auger decay, also due to a smaller anisotropy in the primary absorption process than originally predicted but in good agreement with more recent calculations. Contrary to this, satellite Auger transitions show unexpectedly large anisotropies
Consistent and invertible deformation vector fields for a breathing anthropomorphic phantom: a post-processing framework for the XCAT phantom.
Breathing motion is challenging for radiotherapy planning and delivery. This requires advanced four-dimensional (4D) imaging and motion mitigation strategies and associated validation tools with known deformations. Numerical phantoms such as the XCAT provide reproducible and realistic data for simulation-based validation. However, the XCAT generates partially inconsistent and non-invertible deformations where tumours remain rigid and structures can move through each other. We address these limitations by post-processing the XCAT deformation vector fields (DVF) to generate a breathing phantom with realistic motion and quantifiable deformation. An open-source post-processing framework was developed that corrects and inverts the XCAT-DVFs while preserving sliding motion between organs. Those post-processed DVFs are used to warp the first XCAT-generated image to consecutive time points providing a 4D phantom with a tumour that moves consistently with the anatomy, the ability to scale lung density as well as consistent and invertible DVFs. For a regularly breathing case, the inverse consistency of the DVFs was verified and the tumour motion was compared to the original XCAT. The generated phantom and DVFs were used to validate a motion-including dose reconstruction (MIDR) method using isocenter shifts to emulate rigid motion. Differences between the reconstructed doses with and without lung density scaling were evaluated. The post-processing framework produced DVFs with a maximum [Formula: see text]-percentile inverse-consistency error of 0.02 mm. The generated phantom preserved the dominant sliding motion between the chest wall and inner organs. The tumour of the original XCAT phantom preserved its trajectory while deforming consistently with the underlying tissue. The MIDR was compared to the ground truth dose reconstruction illustrating its limitations. MIDR with and without lung density scaling resulted in small dose differences up to 1 Gy (prescription 54 Gy). The proposed open-source post-processing framework overcomes important limitations of the original XCAT phantom and makes it applicable to a wider range of validation applications within radiotherapy
Prevention and control of apple scab
Improved prevention and control of apple scab caused by Venturia inaequalis is aimed at without the use of copper containing products in the Repco-project. Substantial progress is made in selection of potential products against summer epidemics. A patent application is made for E73. New effective biocontrol agents are selected to reduce inoculum during winter. The product potassium bicarbonate has shown good efficacy and Repco contributes to the registration of this product in Europe. Earthworms tended to be stimulated to consume apple leaves treated with amino acids or beetpulp, especially when applied fresh under controlled environmental condi-tons
Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study
BACKGROUND AND PURPOSE: Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients. MATERIAL AND METHODS: Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty. RESULTS: Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance. CONCLUSION: Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance
OC-0155: Automated lung tumour delineation in cine MR images for image guided radiotherapy with an MR-Linac
Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation.
Objective.Respiratory motion of lung tumours and adjacent structures is challenging for radiotherapy. Online MR-imaging cannot currently provide real-time volumetric information of the moving patient anatomy, therefore limiting precise dose delivery, delivered dose reconstruction, and downstream adaptation methods.Approach.We tailor a respiratory motion modelling framework towards an MR-Linac workflow to estimate the time-resolved 4D motion from real-time data. We develop a multi-slice acquisition scheme which acquires thick, overlapping 2D motion-slices in different locations and orientations, interleaved with 2D surrogate-slices from a fixed location. The framework fits a motion model directly to the input data without the need for sorting or binning to account for inter- and intra-cycle variation of the breathing motion. The framework alternates between model fitting and motion-compensated super-resolution image reconstruction to recover a high-quality motion-free image and a motion model. The fitted model can then estimate the 4D motion from 2D surrogate-slices. The framework is applied to four simulated anthropomorphic datasets and evaluated against known ground truth anatomy and motion. Clinical applicability is demonstrated by applying our framework to eight datasets acquired on an MR-Linac from four lung cancer patients.Main results.The framework accurately reconstructs high-quality motion-compensated 3D images with 2 mm3isotropic voxels. For the simulated case with the largest target motion, the motion model achieved a mean deformation field error of 1.13 mm. For the patient cases residual error registrations estimate the model error to be 1.07 mm (1.64 mm), 0.91 mm (1.32 mm), and 0.88 mm (1.33 mm) in superior-inferior, anterior-posterior, and left-right directions respectively for the building (application) data.Significance.The motion modelling framework estimates the patient motion with high accuracy and accurately reconstructs the anatomy. The image acquisition scheme can be flexibly integrated into an MR-Linac workflow whilst maintaining the capability of online motion-management strategies based on cine imaging such as target tracking and/or gating
Real-time intrafraction motion monitoring in external beam radiotherapy
© 2019 Institute of Physics and Engineering in Medicine. Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT
OC-0411: Investigation of MRI-derived surrogate signals for modelling respiratory motion on an MRI-Linac
Does the Mediterranean diet predict longevity in the elderly? A Swedish perspective
Dietary pattern analysis represents a useful improvement in the investigation of diet and health relationships. Particularly, the Mediterranean diet pattern has been associated with reduced mortality risk in several studies involving both younger and elderly population groups. In this research, relationships between dietary macronutrient composition, as well as the Mediterranean diet, and total mortality were assessed in 1,037 seventy-year-old subjects (540 females) information. Diet macronutrient composition was not associated with mortality, while a refined version of the modified Mediterranean diet index showed a significant inverse association (HR = 0.93, 95% CI: 0.89; 0.98). As expected, inactive subjects, smokers and those with a higher waist circumference had a higher mortality, while a reduced risk characterized married and more educated people. Sensitivity analyses (which confirmed our results) consisted of: exclusion of one food group at a time in the Mediterranean diet index, exclusion of early deaths, censoring at fixed follow-up time, adjusting for activities of daily living and main cardiovascular risk factors including weight/waist circumference changes at follow up. In conclusion, we can reasonably state that a higher adherence to a Mediterranean diet pattern, especially by consuming wholegrain cereals, foods rich in polyunsaturated fatty acids, and a limited amount of alcohol, predicts increased longevity in the elderly
From evolutionary computation to the evolution of things
Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems
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