APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network

Deep learning has been successfully demonstrated in MRI reconstruction of accelerated acquisitions. However, its dependence on representative training data limits the application across different contrasts, anatomies, or image sizes. To address this limitation, we propose an unsupervised, auto-calibrated k-space completion method, based on a uniquely designed neural network that reconstructs the full k-space from an undersampled k-space, exploiting the redundancy among the multiple channels in the receive coil in a parallel imaging acquisition. To achieve this, contrary to common convolutional network approaches, the proposed network has a decreasing number of feature maps of constant size. In contrast to conventional parallel imaging methods such as GRAPPA that estimate the prediction kernel from the fully sampled autocalibration signals in a linear way, our method is able to learn nonlinear relations between sampled and unsampled positions in k-space. The proposed method was compared to the start-of-the-art ESPIRiT and RAKI methods in terms of noise amplification and visual image quality in both phantom and in-vivo experiments. The experiments indicate that APIR-Net provides a promising alternative to the conventional parallel imaging methods, and results in improved image quality especially for low SNR acquisitions.Comment: To appear in the proceedings of MICCAI 2019 Workshop Machine Learning for Medical Image Reconstructio

Improved navigator-gated motion compensation in cardiac MR using additional constraint of magnitude of motion-corrupted data

Background. In conventional prospective respiratory navigator (NAV) acquisitions, 40-60% of the acquired data are discarded resulting in low efficiency and long scan times [1,2].Compressed-sensing Motion Compensation (CosMo) has a shorter fixed scan time by acquiring the full inner k-space and estimating the NAV-rejected outer k-space lines [3]. Respiratory motion will mainly manifest itself as phase variation in the acquired k-space data. We sought to determine if the addition of the magnitude of the rejected k-space lines as a constraint in image reconstruction will improve the performance of CosMo. Methods. To investigate the variability of the magnitude of kspace lines at different respiratory phases, free-breathing, ECG-triggered, targeted right coronary images with multiple averages were acquired from 10 healthy adult subjects. Magnitude variability was investigated quantitatively by calculating the cross-correlation between accepted and rejected k-space lines. CosMo was implemented retrospectively on one acquisition from each subject. The inner k-space (31 ky by 7 kz lines) was filled with lines acquired within the 5mm gating window from all acquisitions. The outer kspace was then filled only with lines from the first average acquired within the 5 mm gating window, resulting in an undersampled k-space with a fully sampled center. For reliable image reconstruction with CosMo, 10-20% of the inner k-space must be fully-sampled. The missing outer k-space lines were then estimated using LOST with an additional magnitude constraint within each estimation iteration or in the final iteration for each coil [4]. The results were compared with prospective NAVgating with a gating window of 5 mm and CosMo reconstruction without the magnitude constraint. Results. Figure 1 shows the cross-correlation between the accepted and worst rejected k-space lines for each position. The correlation is close to 1 at the center of kspace where the majority of image information is contained, indicating low variability in magnitude information at different respiratory phases. Figure 2 shows right coronary images acquired using a) fully-sampled, 5-mm gated data, b) the original CosMo, and CosMo with the additional magnitude constraint c) inside each iteration and d) in the final iteration. The relative signal-to-noise in the left ventricle blood pool is: $30.71 \pm 6.5; 40.32 \pm 14.2; 53.9 \pm 26.8; 56.8 \pm 25.9$ for each reconstruction, respectively. Significant differences (p<0.05) are present for all measurements except between the original CosMo and the CosMo image with the magnitude constraint in each iteration (p=0.09). Conclusions. The addition of the magnitude of rejected lines, readily available in all navigator-gated scans, as a constraint in CosMo results in improved image quality as measured by relative SNR. Funding. NIH R01EB008743-01A2

Clarifying misconceptions of extinction risk assessment with the IUCN Red List

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The identification of species at risk of extinction is a central goal of conservation. As the use of data compiled for IUCN Red List assessments expands, a number of misconceptions regarding the purpose, application and use of the IUCN Red List categories and criteria have arisen. We outline five such classes of misconception; the most consequential drive proposals for adapted versions of the criteria, rendering assessments among species incomparable. A key challenge for the future will be to recognize the point where understanding has developed so markedly that it is time for the next generation of the Red List criteria. We do not believe we are there yet but, recognizing the need for scrutiny and continued development of Red Listing, conclude by suggesting areas where additional research could be valuable in improving the understanding of extinction risk among species

Converting Endangered Species Categories to Probabilities of Extinction for Phylogenetic Conservation Prioritization

Categories of imperilment like the global IUCN Red List have been transformed to probabilities of extinction and used to rank species by the amount of imperiled evolutionary history they represent (e.g. by the Edge of Existence programme). We investigate the stability of such lists when ranks are converted to probabilities of extinction under different scenarios.Using a simple example and computer simulation, we show that preserving the categories when converting such list designations to probabilities of extinction does not guarantee the stability of the resulting lists.Care must be taken when choosing a suitable transformation, especially if conservation dollars are allocated to species in a ranked fashion. We advocate routine sensitivity analyses

Cardiac phase-resolved late gadolinium enhancement imaging

Late gadolinium enhancement (LGE) with cardiac magnetic resonance (CMR) imaging is the clinical reference for assessment of myocardial scar and focal fibrosis. However, current LGE techniques are confined to imaging of a single cardiac phase, which hampers assessment of scar motility and does not allow cross-comparison between multiple phases. In this work, we investigate a three step approach to obtain cardiac phase-resolved LGE images: (1) Acquisition of cardiac phase-resolved imaging data with varying T(1) weighting. (2) Generation of semi-quantitative T(*)(1) maps for each cardiac phase. (3) Synthetization of LGE contrast to obtain functional LGE images. The proposed method is evaluated in phantom imaging, six healthy subjects at 3T and 20 patients at 1.5T. Phantom imaging at 3T demonstrates consistent contrast throughout the cardiac cycle with a coefficient of variation of 2.55 ± 0.42%. In-vivo results show reliable LGE contrast with thorough suppression of the myocardial tissue is healthy subjects. The contrast between blood and myocardium showed moderate variation throughout the cardiac cycle in healthy subjects (coefficient of variation 18.2 ± 3.51%). Images were acquired at 40–60 ms and 80 ms temporal resolution, at 3T and 1.5, respectively. Functional LGE images acquired in patients with myocardial scar visualized scar tissue throughout the cardiac cycle, albeit at noticeably lower imaging resolution and noise resilience than the reference technique. The proposed technique bears the promise of integrating the advantages of phase-resolved CMR with LGE imaging, but further improvements in the acquisition quality are warranted for clinical use

Simulated Effects of Recruitment Variability, Exploitation, and Reduced Habitat Area on the Muskellunge Population in Shoepack Lake, Voyageurs National Park, Minnesota

The genetically unique population of muskellunge Esox masquinongy inhabiting Shoepack Lake in Voyageurs National Park, Minnesota, is potentially at risk for loss of genetic variability and long-term viability. Shoepack Lake has been subject to dramatic surface area changes from the construction of an outlet dam by beavers Castor canadensis and its subsequent failure. We simulated the long-term dynamics of this population in response to recruitment variation, increased exploitation, and reduced habitat area. We then estimated the effective population size of the simulated population and evaluated potential threats to long-term viability, based on which we recommend management actions to help preserve the long-term viability of the population. Simulations based on the population size and habitat area at the beginning of a companion study resulted in an effective population size that was generally above the threshold level for risk of loss of genetic variability, except when fishing mortality was increased. Simulations based on the reduced habitat area after the beaver dam failure and our assumption of a proportional reduction in population size resulted in an effective population size that was generally below the threshold level for risk of loss of genetic variability. Our results identified two potential threats to the long-term viability of the Shoepack Lake muskellunge population, reduction in habitat area and exploitation. Increased exploitation can be prevented through traditional fishery management approaches such as the adoption of no-kill, barbless hook, and limited entry regulations. Maintenance of the greatest possible habitat area and prevention of future habitat area reductions will require maintenance of the outlet dam built by beavers. Our study should enhance the long-term viability of the Shoepack Lake muskellunge population and illustrates a useful approach for other unique populations

An efficient protocol for the global sensitivity analysis of stochastic ecological models

Stochastic simulation models requiring many input parameters are widely used to inform the management of ecological systems. The interpretation of complex models is aided by global sensitivity analysis, using simulations for distinct parameter sets sampled from multidimensional space. Ecologists typically analyze such output using an “emulator”; that is, a statistical model used to approximate the relationship between parameter inputs and simulation outputs and to derive sensitivity measures. However, it is typical for ad hoc decisions to be made regarding: (1) trading off the number of parameter samples against the number of simulation iterations run per sample, (2) determining whether parameter sampling is sufficient, and (3) selecting an appropriate emulator. To evaluate these choices, we coupled different sensitivity-analysis designs and emulators for a stochastic, 20-parameter model that simulated the re-introduction of a threatened species subject to predation and disease, and then validated the emulators against new output generated from the simulation model. Our results lead to the following sensitivity analysis-protocol for stochastic ecological models. (1) Run a single simulation iteration per parameter sample generated, even if the focal response is a probabilistic outcome, while sampling extensively across the parameter space. In contrast to designs that invested in many model iterations (tens to thousands) per parameter sample, this approach allowed emulators to capture the input-output relationship of the simulation model more accurately and also to produce sensitivity measures that were robust to variation inherent in the parameter-sampling stage. (2) Confirm that parameter sampling is sufficient, by emulating subsamples of the sensitivity-analysis output. As the subsample size is increased, the cross-validatory performance of the emulator and sensitivity measures derived from it should exhibit asymptotic behavior. This approach can also be used to compare candidate emulators and select an appropriate interaction depth. (3) If required, conduct further simulations for additional parameter samples, and then report sensitivity measures and illustrate key response curves using the selected emulator. This protocol will generate robust sensitivity measures and facilitate the interpretation of complex ecological models, while minimizing simulation effort.Thomas A. A. Prowse, Corey J. A. Bradshaw, Steven Delean, Phillip Cassey, Robert C. Lacy, Konstans Wells, Matthew E. Aiello-Lammens, H. R. Akçakaya, and Barry W. Broo

Adenomatous polyposis coli-mediated control of β-catenin is essential for both chondrogenic and osteogenic differentiation of skeletal precursors

Background: During skeletogenesis, protein levels of β-catenin in the canonical Wnt signaling pathway determine lineage commitment of skeletal precursor cells to osteoblasts and chondrocytes. Adenomatous polyposis coli (Apc) is a key controller of β-catenin turnover by down-regulating intracellular levels of β-catenin. Results: To investigate whether Apc is involved in lineage commitment of skeletal precursor cells, we generated conditional knockout mice lacking functional Apc in Col2a1-expressing cells. In contrast to other models in which an oncogenic variant of β-catenin was used, our approach resulted in the accumulation of wild type β-catenin protein due to functional loss of Apc. Conditional homozygous Apc mutant mice died perinatally showing greatly impaired skeletogenesis. All endochondral bones were misshaped and lacked structural integrity. Lack of functional Apc resulted in a pleiotropic skeletal cell phenotype. The majority of the precursor cells lacking Apc failed to differentiate into chondrocytes or osteoblasts. However, skeletal precursor cells in the proximal ribs were able to escape the noxious effect of functional loss of Apc resulting in formation of highly active osteoblasts. Inactivation of Apc in chondrocytes was associated with dedifferentiation of these cells. Conclusion: Our data indicate that a tight Apc-mediated control of β-catenin levels is essential for differentiation of skeletal precursors as well as for the maintenance of a chondrocytic phenotype in a spatio-temporal regulated manner

Bridging the research-implementation gap in IUCN Red List assessments

The International Union for Conservation of Nature (IUCN) Red List of Threatened Species is central in biodiversity conservation, but insufficient resources hamper its long-term growth, updating, and consistency. Models or automated calculations can alleviate those challenges by providing standardised estimates required for assessments, or prioritising species for (re-)assessments. However, while numerous scientific papers have proposed such methods, few have been integrated into assessment practice, highlighting a critical research-implementation gap. We believe this gap can be bridged by fostering communication and collaboration between academic researchers and Red List practitioners, and by developing and maintaining user-friendly platforms to automate application of the methods. We propose that developing methods better encompassing Red List criteria, systems, and drivers is the next priority to support the Red List.Peer reviewe

Developing population models with data from marked individuals

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, densitydependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources -notably, mark-recapture studies -remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark-recapture dataset. Unlike standard mark-recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from markrecapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern