Pharmacokinetic modelling on dynamic positron emission tomography (PET) data is a quantitative technique. However, the long acquisition time is prohibitive for routine clinical use. Instead, the semi-quantitative standardised uptake value ratio (SUVR) from a shorter static acquisition is used, despite its sensitivity to blood flow confounding longitudinal analysis. A method has been proposed to reduce the dynamic acquisition time for quantification by incorporating cerebral blood flow (CBF) information from arterial spin labelling (ASL) magnetic resonance imaging (MRI) into the pharmacokinetic modelling. In this work, we optimise and validate this framework for a study of ageing and preclinical Alzheimer's disease. This methodology adapts the simplified reference tissue model (SRTM) for a reduced acquisition time (RT-SRTM) and is applied to [F]-florbetapir PET data for amyloid-β quantification. Evaluation shows that the optimised RT-SRTM can achieve amyloid burden estimation from a 30-min PET/MR acquisition which is comparable with the gold standard SRTM applied to 60 min of PET data. Conversely, SUVR showed a significantly higher error and bias, and a statistically significant correlation with tracer delivery due to the influence of blood flow. The optimised RT-SRTM produced amyloid burden estimates which were uncorrelated with tracer delivery indicating its suitability for longitudinal studies.
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http://dx.doi.org/10.1177/0271678X18797343 | DOI Listing |
Sci Rep
January 2025
Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Subject-specific parameters in lumped hemodynamic models of the cardiovascular system can be estimated using data from experimental measurements, but the parameter estimation may be hampered by the variability in the input data. In this study, we investigate the influence of inter-sequence, intra-observer, and inter-observer variability in input parameters on estimation of subject-specific model parameters using a previously developed approach for model-based analysis of data from 4D Flow MRI acquisitions and cuff pressure measurements. The investigated parameters describe left ventricular time-varying elastance and aortic compliance.
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January 2025
Department of Radiology, University of Groningen, University Medical Center of Groningen, Groningen, The Netherlands.
Objective: To evaluate the repeatability of AI-based automatic measurement of vertebral and cardiovascular markers on low-dose chest CT.
Methods: We included participants of the population-based Imaging in Lifelines (ImaLife) study with low-dose chest CT at baseline and 3-4 month follow-up. An AI system (AI-Rad Companion chest CT prototype) performed automatic segmentation and quantification of vertebral height and density, aortic diameters, heart volume (cardiac chambers plus pericardial fat), and coronary artery calcium volume (CACV).
Int Emerg Nurs
January 2025
University of Health Sciences, Gulhane Faculty of Nursing, Department of Pediatric Nursing, Ankara, Turkey. Electronic address:
Background: The aim of this study was to investigate the factors leading to more than one time visit to the pediatric emergency department within 72 h, parental wishes and experiences with emergency nurses from the parents' perspective.
Material And Methods: A cross-sectional study was conducted between April 15, 2023 and April 14, 2024 with 596 parents of children aged between 0 and 18 years who had return visits to the pediatric emergency department of a gynaecology and pediatrics hospital in the Western Black Sea Region of Türkiye within 72 h after the first visit. Following the acquisition of written informed consent from the parents, the data were collected using the Descriptive Characteristics of Children and Experiences of Parents Information Form.
Environ Microbiol
January 2025
Frontiers Science Center for Deep Ocean Multispheres and Earth System, and College of Marine Life Sciences, Ocean University of China, Qingdao, China.
Deep-sea sediments contain a large number of Thaumarchaeota that are phylogenetically distinct from their pelagic counterparts. However, their ecology and evolutionary adaptations are not well understood. Metagenomic analyses were conducted on samples from various depths of a 750-cm sediment core collected from the Mariana Trench Challenger Deep.
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