A comprehensive approach for correcting voxel‐wise b‐value errors in diffusion MRI

Purpose In diffusion MRI, the actual b‐value played out on the scanner may deviate from the nominal value due to magnetic field imperfections. A simple image‐based correction method for this problem is presented. Methods The apparent diffusion constant (ADC) of a water phantom was measured voxel‐wise along 64 diffusion directions at b = 1000 s/mm2. The true diffusion constant of water was estimated, considering the phantom temperature. A voxel‐wise correction factor, providing an effective b‐value including any magnetic field deviations, was determined for each diffusion direction by relating the measured ADC to the true diffusion constant. To test the method, the measured b‐value map was used to calculate the corrected voxel‐wise ADC for additionally acquired diffusion data sets on the same water phantom and data sets acquired on a small water phantom at three different positions. Diffusion tensor was estimated by applying the measured b‐value map to phantom and in vivo data sets. Results The b‐value‐corrected ADC maps of the phantom showed the expected spatial uniformity as well as a marked improvement in consistency across diffusion directions. The b‐value correction for the brain data resulted in a 5.8% and 5.5% decrease in mean diffusivity and angular differences of the primary diffusion direction of 2.71° and 0.73° inside gray and white matter, respectively. Conclusion The actual b‐value deviates significantly from its nominal setting, leading to a spatially variable error in the common diffusion outcome measures. The suggested method measures and corrects these artifacts

Controlling the object phase for g factor reduction in phase-constrained parallel MRI using spatially selective RF pulses

Parallel imaging generally entails a reduction in the signal-to-noise ratio (SNR) of the final image. Phase-constrained methods aim to improve reconstruction quality by employing symmetry properties of k space. Noise amplification in phase-constrained reconstruction heavily depends on the object background phase. The purpose of this work is to present a new approach of using tailored RF pulses to optimize the object phase distribution in order to maximize the benefit of phase-constrained reconstruction, and minimize the noise amplification. Intrinsic object phase and coil sensitivity profiles are measured in a prescan. Optimal phase distribution is computed to maximize SNR in the given setup. Tailored RF pulses are designed to introduce the optimal phase map in the following accelerated acquisitions, subsequently reconstructed by phase-constrained methods. The potential of the method is demonstrated in vivo with in-plane accelerated (8x) and simultaneous multi-slice (3x) acquisitions. Mean g-factors are reduced by up to a factor of 2 compared to conventional techniques when an appropriate phase-constrained reconstruction is applied to phase-optimized acquisitions, enhancing the SNR of the final images and the visibility of small details. Combining phase-constrained reconstruction and phase optimization by tailored RF pulses can provide notable improvement in the SNR and reconstruction quality of accelerated MRI

Hematopoietic stem and progenitor cells are a distinct HIV reservoir that contributes to persistent viremia in suppressed patients

Long-lived reservoirs of persistent HIV are a major barrier to a cure. CD4+ hematopoietic stem and progenitor cells (HSPCs) have the capacity for lifelong survival, self-renewal, and the generation of daughter cells. Recent evidence shows that they are also susceptible to HIV infection in vitro and in vivo. Whether HSPCs harbor infectious virus or contribute to plasma virus (PV) is unknown. Here, we provide strong evidence that clusters of identical proviruses from HSPCs and their likely progeny often match residual PV. A higher proportion of these sequences match residual PV than proviral genomes from bone marrow and peripheral blood mononuclear cells that are observed only once. Furthermore, an analysis of near-full-length genomes isolated from HSPCs provides evidence that HSPCs harbor functional HIV proviral genomes that often match residual PV. These results support the conclusion that HIV-infected HSPCs form a distinct and functionally significant reservoir of persistent HIV in infected people

VISUAL PPINOT: A Graphical Notation for Process Performance Indicators

Process performance indicators (PPIs) allow the quantitative evaluation of business processes, providing essential information for decision making. It is common practice today that business processes and PPIs are usually modelled separately using graphical notations for the former and natural language for the latter. This approach makes PPI definitions simple to read and write, but it hinders maintenance consistency between business processes and PPIs. It also requires their manual translation into lower-level implementation languages for their operationalisation, which is a time-consuming, error-prone task because of the ambiguities inherent to natural language definitions. In this article, Visual ppinot, a graphical notation for defining PPIs together with business process models, is presented. Its underlying formal metamodel allows the automated processing of PPIs. Furthermore, it improves current state-of-the-art proposals in terms of expressiveness and in terms of providing an explicit visualisation of the link between PPIs and business processes, which avoids inconsistencies and promotes their co-evolution. The reference implementation, developed as a complete tool suite, has allowed its validation in a multiple-case study, in which five dimensions of Visual ppinot were studied: expressiveness, precision, automation, understandability, and traceability

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations:A Configurational Perspective

Big data analytics (BDA) is beneficial for organizations, yet implementing BDA to leverage profitability is fundamental challenge confronting practitioners. Although prior research has explored the impact that BDA has on business growth, there is a lack of research that explains the full complexity of BDA implementations. Examination of how and under what conditions BDA achieves organizational performance from a holistic perspective is absent from the existing literature. Extending the theoretical perspective from the traditional views (e.g. resource-based theory) to configuration theory, the authors have developed a conceptual model of BDA success that aims to investigate how BDA capabilities interact with complementary organizational resources and organizational capabilities in multiple configuration solutions leading to higher quality of care in healthcare organizations. To test this model, the authors use fuzzy-set qualitative comparative analysis to analyse multi-source data acquired from a survey and databases maintained by the Centres for Medicare & Medicaid Services. The findings suggest that BDA, when given alone, is not sufficient in achieving the outcome, but is a synergy effect in which BDA capabilities and analytical personnel's skills together with organizational resources and capabilities as supportive role can improve average excess readmission rates and patient satisfaction in healthcare organizations

Consumer-Based Leisure Constraint for Online Gaming

[[abstract]]The purpose of this study is to develop a multidimensional measure of consumer-based leisure constraint for online game play and to assess its psychometric properties. An empirical model of player constraint in online games provides the foundation to understanding and assessing how players differ from one another (such as high gamers/low gamers and high gamers/non-gamers) and how constraints on play relate to frequency of use. In the current study, an exploratory factor analysis was used to extract the common factors, and confirmatory factor analysis was used to create an empirical model of players' perception of constraint and to reveal its underlying structure. The analysis revealed six dimensions of constraint. The relationship between perception of constraint and frequency of use is also presented.[[notice]]補正完畢[[incitationindex]]SSCI[[booktype]]電子版[[booktype]]紙