In nuclear medicine, estimating the number of radioactive decays that occur in a source organ per unit administered activity of a radiopharmaceutical (i.e., the time-integrated activity coefficient [TIAC]) is an essential task within the internal dosimetry workflow. TIAC estimation is commonly derived by least-squares fitting of various exponential models to organ time-activity data (radiopharmaceutical biodistribution). Rarely, however, are methods used to objectively determine the model that best characterizes the data. Additionally, the uncertainty associated with the resultant TIAC is generally not evaluated. As part of the MIRDsoft initiative, MIRDfit has been developed to offer a biodistribution fitting software solution that provides the following essential features and advantages for internal dose assessment: nuclear medicine-appropriate fit functions; objective metrics for guiding best-fit selection; TIAC uncertainty calculation; quality control and data archiving; integration with MIRDcalc software for dose calculation; and a user-friendly Excel-based interface. For demonstration and comparative validation of MIRDfit's performance, TIACs were derived from serial imaging studies involving F-FDG and Lu-DOTATATE using MIRDfit. These TIACs were then compared with TIAC estimates obtained using other software. In most cases, the TIACs agreed within approximately 10% between MIRDfit and the other software. MIRDfit has been endorsed by the MIRD Committee of the Society of Nuclear Medicine and Molecular Imaging and has been integrated into the MIRDsoft suite of free dosimetry software; it is available for download at no user cost (https://mirdsoft.org/).
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http://dx.doi.org/10.2967/jnumed.124.268011 | DOI Listing |
J Air Waste Manag Assoc
January 2025
Department of Civil and Environmental Engineering, University of California, Berkeley, Berkeley, California, USA.
In this review paper, we provide a comprehensive overview of approaches for collecting time-activity pattern (TAP) data from individuals, a crucial component in understanding human behavior and its implications across various fields such as urban planning, environmental science, and, particularly, public health in relation to air pollution exposures.Furthermore, our paper introduces and critically evaluates several emerging methods for TAP data collection. These novel approaches, including but not limited to Google Location History, iPhone Significant Locations, and crowdsourced smartphone location data, offer unprecedented granularity in tracking human activities.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Management, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China.
Background: Depression is one of the most common mental health problems in older adults. Community social capital and depressive symptoms in older adults have been discussed in previous studies but remain limited. This study aims to explore the association between community social capital and depressive symptoms among older adults relocated for poverty alleviation in China.
View Article and Find Full Text PDFMol Imaging Biol
January 2025
Molecular Imaging Chemistry Laboratory, Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0QQ, UK.
Purpose: Positron Emission Tomography (PET) scans with radioligands targeting tau neurofibrillary tangles (NFT) have accelerated our understanding of the role of misfolded tau in neurodegeneration. While intended for human research, applying these radioligands to small animals establishes a vital translational link. Transgenic animal models of dementia, such as the tau rat SHR24, play a crucial role in enhancing our understanding of these disorders.
View Article and Find Full Text PDFJ Expo Sci Environ Epidemiol
January 2025
Environmental Research Group, School of Public Health, Imperial College London, London, UK.
Background: Accurate estimates of personal exposure to ambient air pollution are difficult to obtain and epidemiological studies generally rely on residence-based estimates, averaged spatially and temporally, derived from monitoring networks or models. Few epidemiological studies have compared the associated health effects of personal exposure and residence-based estimates.
Objective: To evaluate the association between exposure to air pollution and cognitive function using exposure estimates taking mobility and location into account.
Sci Total Environ
January 2025
Center for Environmental Measurement and Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Epidemiologic studies of ambient fine particulate matter (PM) and ozone (O) often use outdoor concentrations from central-site monitors or air quality model estimates as exposure surrogates, which can result in exposure errors. We previously developed an exposure model called TracMyAir, which is an iPhone application that determines seven tiers of individual-level exposure metrics for ambient PM and O using outdoor concentrations, home building characteristics, weather, time-activities. The exposure metrics with increasing information needs and complexity include: outdoor concentration (C, Tier 1), building infiltration factor (F, Tier 2), indoor concentration (C, Tier 3), time spent in microenvironments (ME) (T, Tier 4), personal exposure factor (F, Tier 5), exposure (E, Tier 6), and inhaled dose (D, Tier 7).
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