Prevalence of obstructive coronary artery disease and prognosis in patients with stable symptoms and a zero-coronary calcium score

© The Author 2017. Published by Oxford University Press on behalf of the European Society of Cardiology.Aims: CT calcium scoring (CTCS) and CT cardiac angiography (CTCA) are widely used in patients with stable chest pain to exclude significant coronary artery disease (CAD). We aimed to resolve uncertainty about the prevalence of obstructive coronary artery disease and long-term outcomes in patients with a zero-calcium score (ZCS). Methods and results: Consecutive patients with stable cardiac symptoms referred for CTCS or CTCS and CTCA from chest pain clinics to a tertiary cardiothoracic centre were prospectively enrolled. In those with a ZCS, the prevalence of obstructive CAD on CTCA was determined. A follow-up for all-cause mortality was obtained from the NHS tracer service. A total of 3914 patients underwent CTCS of whom 2730 (69.7%) also had a CTCA. Half of the patients were men (50.3%) with a mean age of 56.9 years. Among patients who had both procedures, a ZCS was present in 52.2%, with a negative predictive value of 99.5% for excluding ≥70% stenosis on CTCA. During a mean follow-up of 5.2 years, the annual event rate was 0.3% for those with ZCS compared with 1.2% for CS ≥1. The presence of non-calcified atheroma on CTCA in patients with ZCS did not affect the prognostic value (P = 0.98). Conclusion: In patients with stable symptoms and a ZCS, obstructive CAD is rare, and prognosis over the long-term is excellent, regardless of whether non-calcified atheroma is identified. A ZCS could reliably be used as a 'gatekeeper' in this patient cohort, obviating the need for further more expensive tests.Peer reviewedFinal Published versio

Multiscale, multimodal analysis of tumor heterogeneity in IDH1 mutant vs wild-type diffuse gliomas.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations

Implementation of GIS-Based Applications in Water Governance

__Abstract__ Geographical Information Systems (GIS) are computer programs that are able to bring large amounts of data of both the physical and the social system together in one comprehensive overview shown digitally. GIS occurred very rapidly on the Dutch policy agenda. In this paper we analyze how the fast introduction process of GIS-based instruments in water management and more specifically in river flood management can be explained. By applying a range of classical models on agenda-setting, we show the important contribution of GIS to the water and flood issue in current spatial planning and policy development in the Netherland

Multi-factor service design: identification and consideration of multiple factors of the service in its design process

Service design is a multidisciplinary area that helps innovate services by bringing new ideas to customers through a design-thinking approach. Services are affected by multiple factors, which should be considered in designing services. In this paper, we propose the multi-factor service design (MFSD) method, which helps consider the multi-factor nature of service in the service design process. The MFSD method has been developed through and used in five service design studies with industry and government. The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question (in short, value creation factors), (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors. We provide real stories and examples from the five service design studies to illustrate the MFSD method and demonstrate its utility. This study will contribute to the design of modern complex services that are affected by varied factors

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types