Uniform acquisition modelling across PET imaging systems: Unified scatter modelling

© 2016 IEEE. PET imaging is an important tool commonly used for studying disease by research consortia which implement multi-centre studies to improve the statistical power of findings. The UK government launched the Dementias Platform UK to facilitate one of the world's largest dementia population study involving national centres equipped with state-of-the-art PET/MR scanners from two major vendors. However, the difference in PET detector technology between the two scanners involved makes the standardisation of data acquisition and image reconstruction necessary. We propose a new approach to PET acquisition system modelling across different PET systems and technologies, focusing in particular on unified scatter estimation across TOF (time-of-flight) and non-TOF PET systems. The proposed scatter modelling is fully 3D and voxel based, as opposed to the popular line-of-response driven methods. This means that for each emitting voxel an independent 3D scatter estimate is found, inherently preserving the necessary information for TOF calculations as well as accounting for the large axial field of view. With adequate sampling of the input images, the non-TOF scatter estimate is identical to the summed TOF estimates across TOF bins, without an additional computational cost used for the TOF estimation. The model is implemented using the latest NVIDA GPU CUDA platform, allowing finer sampling of image space which is more essential for accurate TOF modelling. The high accuracy of the proposed scatter model is validated using Monte Carlo simulations. The model is deployed in our stand-alone image reconstruction pipeline for the Biograph mMR scanner, demonstrating accurate 3D scatter estimates resulting in uniform reconstruction for a high statistics phantom scan

Fast Quasi-Newton Algorithms for Penalized Reconstruction in Emission Tomography and Further Improvements via Preconditioning

OAPA This paper reports on the feasibility of using a quasi-Newton optimization algorithm, limited-memory Broyden- Fletcher-Goldfarb-Shanno with boundary constraints (L-BFGSB), for penalized image reconstruction problems in emission tomography (ET). For further acceleration, an additional preconditioning technique based on a diagonal approximation of the Hessian was introduced. The convergence rate of L-BFGSB and the proposed preconditioned algorithm (L-BFGS-B-PC) was evaluated with simulated data with various factors, such as the noise level, penalty type, penalty strength and background level. Data of three 18F-FDG patient acquisitions were also reconstructed. Results showed that the proposed L-BFGS-B-PC outperforms L-BFGS-B in convergence rate for all simulated conditions and the patient data. Based on these results, L-BFGSB- PC shows promise for clinical application

Joint reconstruction of PET-MRI by exploiting structural similarity

Recent advances in technology have enabled the combination of positron emission tomography (PET) with magnetic resonance imaging (MRI). These PET-MRI scanners simultaneously acquire functional PET and anatomical or functional MRI data. As function and anatomy are not independent of one another the images to be reconstructed are likely to have shared structures. We aim to exploit this inherent structural similarity by reconstructing from both modalities in a joint reconstruction framework. The structural similarity between two modalities can be modelled in two different ways: edges are more likely to be at similar positions and/or to have similar orientations. We analyse the diffusion process generated by minimizing priors that encapsulate these different models. It turns out that the class of parallel level set priors always corresponds to anisotropic diffusion which is sometimes forward and sometimes backward diffusion. We perform numerical experiments where we jointly reconstruct from blurred Radon data with Poisson noise (PET) and under-sampled Fourier data with Gaussian noise (MRI). Our results show that both modalities benefit from each other in areas of shared edge information. The joint reconstructions have less artefacts and sharper edges compared to separate reconstructions and the ℓ2-error can be reduced in all of the considered cases of under-sampling

Association of anorexia nervosa with risk of cancer. A systematic review and meta-analysis

This is the final version. Available from the publisher via the DOI in this record.IMPORTANCE Anorexia nervosa is recognized as an important cause of morbidity in young people. However, the risk of cancer in people with anorexia nervosa remains uncertain. OBJECTIVE To evaluate the association of anorexia nervosa with the risk of developing or dying of cancer. DATA SOURCES MEDLINE, Scopus, Embase, and Web of Science from database inception to January 9, 2019. STUDY SELECTION Published observational studies in humans examining the risk of cancer in people with anorexia nervosa compared with the general population or those without anorexia nervosa. Studies needed to report incidence or mortality rate ratios (RRs). DATA EXTRACTION AND SYNTHESIS Screening, data extraction, and methodological quality assessment were performed by at least 2 researchers independently. A random-effects model was used to synthesize individual studies. Heterogeneity (I 2 ) was assessed and 95% prediction intervals (PIs) were calculated. MAIN OUTCOMES AND MEASURES All cancer incidence and cancer mortality associated with anorexia nervosa. Secondary outcomes were site-specific cancer incidence and mortality. RESULTS Seven cohort studies published in 10 articles (42 602 participants with anorexia nervosa) were included. Anorexia nervosa was not associated with risk of developing any cancer (4 studies in women; RR, 0.97; 95% CI, 0.89-1.06; P = .53; I 2 , 0%; 95% PI, 0.80-1.18; moderate confidence). Anorexia nervosa was associated with decreased breast cancer incidence (5 studies in women; RR, 0.60; 95% CI, 0.50-0.80; P < .001; I 2 , 0%; 95% PI, 0.44-0.83; high confidence). Conversely, anorexia nervosa was associated with increased risk of developing lung cancer (3 studies in women; RR, 1.50; 95% CI, 1.06-2.12; P = .001; I 2 , 0%; 95% PI, 0.19-16.46; low confidence) and esophageal cancer (2 studies in women; RR, 6.10; 95% CI, 2.30-16.18; P < .001; I 2 , 0%; low confidence). CONCLUSIONS AND RELEVANCE Among people with anorexia nervosa, risk of developing cancer did not differ compared with the general population, but a significantly reduced risk of breast cancer was observed. Understanding the mechanisms underlying these associations could have important preventive potentialGeneralitat ValencianaCarlos III Health Institut

Improving the use of research evidence in guideline development: 11. Incorporating considerations of cost-effectiveness, affordability and resource implications

BACKGROUND: The World Health Organization (WHO), like many other organisations around the world, has recognised the need to use more rigorous processes to ensure that health care recommendations are informed by the best available research evidence. This is the 11(th )of a series of 16 reviews that have been prepared as background for advice from the WHO Advisory Committee on Health Research to WHO on how to achieve this. OBJECTIVES: We reviewed the literature on incorporating considerations of cost-effectiveness, affordability and resource implications in guidelines and recommendations. METHODS: We searched PubMed and three databases of methodological studies for existing systematic reviews and relevant methodological research. We did not conduct systematic reviews ourselves. Our conclusions are based on the available evidence, consideration of what WHO and other organisations are doing and logical arguments. KEY QUESTIONS AND ANSWERS: When is it important to incorporate cost-effectiveness, resource implications and affordability considerations in WHO guidelines (which topics)? • For cost-effectiveness: The need for cost/effectiveness information should be dictated by the specific question, of which several may be addressed in a single guideline. It is proposed that the indications for undertaking a cost-effectiveness analysis (CEA) could be a starting point for determining which recommendation(s) in the guideline would benefit from such analysis. • For resource implications/affordability: The resource implications of each individual recommendation need to be considered when implementation issues are being discussed. How can cost-effectiveness, resource implications and affordability be explicitly taken into account in WHO guidelines? • For cost-effectiveness: ∘ If data are available, the ideal time to consider cost-effectiveness is during the evidence gathering and synthesizing stage. However, because of the inconsistent availability of CEAs and the procedural difficulty associated with adjusting results from different CEAs to make them comparable, it is also possible for cost-effectiveness to be considered during the stage of developing recommendations. ∘ Depending on the quantity and quality and relevance of the data available, such data can be considered in a qualitative way or in a quantitative way, ranging from a listing of the costs to a modelling exercise. At the very least, a qualitative approach like a commentary outlining the economic issues that need to be considered is necessary. If a quantitative approach is to be used, the full model should be transparent and comprehensive. • For resource implications/affordability: ∘ Resource implications, including health system changes, for each recommendation in a WHO guideline should be explored. At the minimum, a qualitative description that can serve as a gross indicator of the amount of resources needed, relative to current practice, should be provided. How does one provide guidance in contextualizing guideline recommendations at the country level based on considerations of cost-effectiveness, resource implications and affordability? • All models should be made available and ideally are designed to allow for analysts to make changes in key parameters and reapply results in their own country. • In the global guidelines, scenarios and extensive sensitivity/uncertainty analysis can be applied. Resource implications for WHO • From the above, it is clear that guidelines development groups will need a health economist. There is need to ensure that this is included in the budget for guidelines and that there is in-house support for this as well

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Altered synapse stability in the early stages of tauopathy

Synapse loss is a key feature of dementia, but it is unclear whether synaptic dysfunction precedes degenerative phases of the disease. Here, we show that even before any decrease in synapse density, there is abnormal turnover of cortical axonal boutons and dendritic spines in a mouse model of tauopathy-associated dementia. Strikingly, tauopathy drives a mismatch in synapse turnover; postsynaptic spines turn over more rapidly, whereas presynaptic boutons are stabilized. This imbalance between pre- and post-synaptic stability coincides with reduced synaptically driven neuronal activity in pre-degenerative stages of the disease

NiftyPET: A high-throughput software platform for high quantitative accuracy and precision PET imaging and analysis

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coeffi- cient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxel-level image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data