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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.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
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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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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Farzaneh Rahmani1, Joseph E Ippolito2, Jingxia Liu3

  • 1Mallinckrodt Institute of Radiology, St. Louis, MO, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

Higher head fat increases Alzheimer's disease (AD) risk, while temporalis muscle volume may be protective in males. Head composition metrics can predict dementia conversion and brain atrophy.

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Area of Science:

  • Neurology
  • Radiology
  • Gerontology

Background:

  • Visceral and neck adiposity, along with sarcopenia, are linked to increased Alzheimer's disease (AD) risk.
  • Computed tomography (CT) scan-derived adipose and fat quantification can help estimate AD pretest probability.
  • Investigating head CT composition metrics offers insights into AD risk.

Purpose of the Study:

  • To examine the relationship between head CT composition metrics and the risk of developing Alzheimer's disease (AD).
  • To determine if head and neck composition can predict conversion from normal cognition to early dementia.
  • To explore correlations between head composition metrics and brain atrophy in individuals at risk for AD.

Main Methods:

  • Participants with normal cognition and negative amyloid PET scans were followed for dementia conversion.
  • CT scans were analyzed for composition metrics using the Data Analysis Facilitation Suite (DAFS).
  • Brain MRI volumetric analyses were performed using FreeSurfer; survival and correlation analyses were conducted.

Main Results:

  • Higher inter-intramuscular adipose tissue in the head was associated with a 3-fold increased risk of dementia conversion.
  • Increased temporalis muscle volume in males, but not females, showed a protective effect against dementia conversion.
  • Temporalis muscle volume directly correlated with precuneus and entorhinal cortex volumes, even after adjusting for intracranial volume.

Conclusions:

  • Head and neck composition metrics derived from CT scans can predict future dementia risk.
  • These metrics correlate with brain atrophy, suggesting potential for automated CT-based screening for AD.
  • Sex-specific differences in the relationship between muscle volume and dementia risk were observed.