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Related Concept Videos

Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

Blood Studies for Cardiovascular System I: Cardiac Biomarkers

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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
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Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers01:19

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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
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Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Jiaxin Yue1, Jianwei Zhang2, Yonggang Shi2

  • 1Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

A new computational framework effectively removes meningeal artifacts from tau PET scans, improving the accuracy of Alzheimer's disease diagnosis. This enhances the reliability of tau PET quantification on cortical regions for better disease interpretation.

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Area of Science:

  • Neuroimaging
  • Molecular Imaging
  • Computational Neuroscience

Background:

  • Second-generation tau PET tracers like PI-2620 and MK-6240 exhibit off-target meningeal binding, complicating cortical uptake interpretation.
  • These artifacts lead to falsely elevated uptake values, hindering accurate tau PET quantification.

Purpose of the Study:

  • To introduce a novel computational framework for removing meningeal off-target binding artifacts in tau PET scans.
  • To enhance the reliability and diagnostic power of tau PET quantification on cortical regions.

Main Methods:

  • Developed a voxel-wise deconvolution method to reduce spill-in from meningeal regions.
  • Implemented a surface-based method to detect and remove residual meningeal artifacts on cortical surfaces.
  • Applied Laplacian smoothing for spatial consistency and noise reduction in reconstructed surface data.

Main Results:

  • The framework effectively removed meningeal artifacts while preserving cortical tau pathology.
  • Processed tau PET data showed improved longitudinal consistency and expected tau deposition patterns.
  • Enhanced association between temporal meta-ROI SUVRs and diagnostic groups (CN/MCI/AD) and Aβ status.

Conclusions:

  • The proposed framework successfully eliminates meningeal artifacts from tau PET data.
  • This preprocessing enhances the diagnostic reliability and interpretation of cortical tau pathology.