Inter-scan variability of coronary artery calcium scoring assessed on 64-multidetector computed tomography vs. dual-source computed tomography: a head-to-head comparison

Aims Coronary artery calcium (CAC) scoring has emerged as a tool for risk stratification and potentially for monitoring response to risk factor modification. Therefore, repeat measurements should provide robust results and low inter-scanner variability for allowing meaningful comparison. The purpose of this study was to investigate inter-scanner variability of CAC for Agatston, volume, and mass scores by head-to-head comparison using two different cardiac computed tomography scanners: 64-detector multislice CT (MSCT) and 64-slice dual-source CT (DSCT). Methods and results Thirty patients underwent CAC measurements on both 64-MSCT (GE LightSpeed XT scanner: 120 kV, 70 mAs, 2.5 mm slices) and 64-DSCT (Siemens Somatom Definition: 120 kV, 80 mAs, 3 mm slices) within <100 days (0-97). Retrospective intra-scan comparison revealed an excellent correlation. The excellent intra-scan (inter-observer) agreement was documented by narrow limits of agreement and a correlation coefficient of variation (COV) of r ≥ 0.99 (P < 0.001) for all CAC scores with a low COV for both scanners (64-MSCT/64-DSCT), i.e. Agatston (2.0/2.1%), mass (3.0/2.0%), and volume (4.7/3.9%). Inter-scanner comparison revealed larger Bland-Altman (BA) limits of agreement, despite high correlation (r ≥ 0.97) for all scores, with COV at 15.1, 21.6, and 44.9% for Agatston, mass, and volume scores. The largest BA limits were observed for volume scores (−1552.8 to 574.2), which was massively improved (−241.0 to 300.4, COV 11.5%) after reanalysing the 64-DSCT scans (Siemens) with GE software/workstation (while Siemens software/workstation does not allow cross-vendor analysis). Phantom measurements confirmed overestimation of volume scores by ‘syngo Ca-Scoring' (Siemens) software which should therefore be reviewed (vendor has been notified). Conclusion Intra- and inter-scan agreement of CAC measurement in a given data set is excellent. Inter-scanner variability is reasonable, particularly for Agatston units in the clinically most relevant range <1000. The use of different software solutions has a greater influence particularly on volume scores than the use of different scanner type

ERP System Effects - A Comparison of Theory and Practice

Background: Information Technology (IT) is becoming increasingly important for companies and enormous amounts of money is spent on implementing Enterprise Resource Planning Systems (ERP), i.e. a software which integrates all functions and processes within a company. Therefore, the need to evaluate these investments is also increasing. Previous research has primarily focused on evaluating IT and ERP investments in financial terms. Therefore, there is a need for studies dealing with nonfinancialissues. Research Question: To what extent do ERP Systems in practice achieve the effects that are most frequently related to such systems in theory? Objective: The objective of the study is to explore the congruence between theory and practice concerning effects of an ERP System implementation. Delimitations: We have chosen only to examine companies who are using SAP R/3. Furthermore, we have only examined the effects of R/3 in the Swedish activities of the companies, even though most of them operate worldwide. The number of companies included in the study is also delimited to seven companies, due to the limited scope of a master thesis. Methodology: Literature dealing with ERP effects have been summarized and six categories of effects and 25 aspects have been identified. Moreover, respondents at seven companies that have implemented at least six of twelve SAP R/3 modules and have experienced effects of this ERP investment have been interviewed regarding these effects stated in theory. Finally, theory and practice have been compared. Results and Conclusions: All of the identified categories from the ERP literature exist within the responding companies, but only to a certain extent. Within each category, the importance of each aspect also varies. Some aspects are not planned at all and some are planned in almost all of the seven companies. Furthermore, some companies experienced bonus effects that they were not expecting. Suggestions for Further Research: We suggest a case study of one or two companies or broaden the study, investigating a large number of companies, so that statistical generalization can be made

Joint data analysis in nutritional epidemiology: identification of observational studies and minimal requirements

Background: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. Objective: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well asminimal requirements for joint data analysis. Methods: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Results: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Conclusions: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, t he minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition

Inter-scan variability of coronary artery calcium scoring assessed on 64-multidetector computed tomography vs. dual-source computed tomography: a head-to-head comparison

Intra- and inter-scan agreement of CAC measurement in a given data set is excellent. Inter-scanner variability is reasonable, particularly for Agatston units in the clinically most relevant range <1000. The use of different software solutions has a greater influence particularly on volume scores than the use of different scanner types

Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements

Background: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. Objective: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. Methods: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Results: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Conclusions: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition.status: publishe