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Molecular imaging, near-infrared theranostics may help improve Alzheimer's detection, treatment
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September 17, 2025
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Study compares visual read algorithms for tau PET imaging
(The Journal of Nuclear Medicine/Society of Nuclear Medicine and Molecular Imaging)
Study compares visual read algorithms for tau PET imaging
A study in The Journal of Nuclear Medicine compared two visual read algorithms for tau PET imaging in Alzheimer's disease. The BioFINDER visual read protocol and the established visual read method for flortaucipir were assessed using data for 1,654 participants. The BioFINDER protocol was more accurate in detecting tau in the entorhinal cortex, while both algorithms performed similarly in identifying abnormalities in plasma phospho-tau 217.
Full Story: Journal of Nuclear Medicine (9/16)
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Clinical News & Research
 
Researchers describe PET image reconstruction method
Researchers provided details in a nuclear medicine journal about how they developed a fast PET image reconstruction method to improve the speed and quality of PET scans. Their algorithm, which won the 2024 PET Rapid Image Reconstruction Challenge, used a stochastic variance reduced gradient approach and a harmonic mean preconditioner.
Full Story: Frontiers in Nuclear Medicine (9/16)
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Molecular imaging, near-infrared theranostics may help improve Alzheimer's detection, treatment
Molecular imaging and near-infrared theranostic agents have the potential to improve early detection and treatment of Alzheimer's disease, according to a report in Bioorganic Chemistry. The review covers advances in biomarker research and theranostic technologies that could enhance diagnostic accuracy and treatment efficacy for Alzheimer's disease.
Full Story: ScienceDirect (9/11)
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News from the Field
 
Survey finds 55% of health care workers plan to change jobs
A survey by Strategic Education found 55% of US health care workers plan to change roles within a year, either within their current organizations or externally. The survey found 49% of respondents cited inadequate compensation and benefits as a reason, while 48% cited burnout and 48% cited a lack of career advancement opportunities. The survey also found 80% of workers felt health care professionals were taken for granted.
Full Story: Becker's Hospital Review (9/15)
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Rising uninsured rate will strain US health care system
Recent policy changes are expected to leave 14 million more Americans without health insurance over the next decade. The new tax and spending law also limits support programs for providing care to uninsured patients. Sara Rosenbaum, founding chair of the Department of Health Policy and Management at George Washington University's School of Public Health, says the health care system may collapse in communities with limited resources.
Full Story: KFF Health News (9/17)
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Health Policy
 
House lawmakers unveil stopgap funding bill
Republicans in the House have unveiled legislation to extend government funding through Nov. 21, excluding provisions addressing health care costs that had been sought by Democrats. The legislation could get a vote in the House by Friday, Senate Majority Leader John Thune has suggested that he would prefer that the upper chamber also consider the bill this week.
Full Story: The Associated Press (9/16), The Wall Street Journal (9/16)
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CMS accepting applications for $50B rural health program
The CMS has opened the application window for the $50 billion Rural Health Transformation Program, aimed at improving rural health care infrastructure and access. States have until Nov. 5 to apply for the funding, which will be distributed over five years beginning in fiscal 2026. The CMS will prioritize projects featuring new technologies, strategic partnerships and financial stability, with a focus on improving access, outcomes and workforce recruitment.
Full Story: Healthcare Innovation (9/15)
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Advancing Health Care
 
Deep learning classifies lung nodules
An in-house deep learning AI algorithm developed using data from the National Lung Screening Trial predicted lung nodule malignancy as well as the Pan-Canadian Early Detection of Lung Cancer model, with a 40% lower false-positive rate, researchers reported. The AI model performed better than the PanCan model with indeterminate nodules and with malignant nodules that were size-matched with benign nodules. "Deep-learning algorithms can assist radiologists in deciding whether follow-up imaging is needed, but prospective validation is required to determine the clinical applicability of these tools and to guide their implementation in practice," said lead author Noa Antonissen.
Full Story: AuntMinnie (free registration) (9/16)
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