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Blood Studies for Cardiovascular System I: Cardiac Biomarkers01:20

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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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Related Experiment Video

Updated: Jan 7, 2026

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

Bénédicte Maréchal1,2,3, Tommaso Di Noto1,2,3, Thanchanok Jomsak4

  • 1Swiss Innovation Hub, Siemens Healthineers International AG, Lausanne, Switzerland.

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

Hippocampal atrophy on MRI correlates strongly with hypometabolism on PET scans for Alzheimer's Disease (AD) diagnosis. Hippocampal volume shows good discrimination ability, potentially serving as a screening tool where PET is unavailable.

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence
  • Alzheimer's Disease Research

Background:

  • Hippocampal atrophy and hypometabolism are key neuroimaging biomarkers for early Alzheimer's Disease (AD) diagnosis.
  • Artificial intelligence (AI) enables quantitative automated volumetric analysis of brain MRI for objective brain atrophy assessment.
  • This study compares hippocampal volume from MRI with 18F-FDG PET hypometabolism for early AD diagnosis.

Purpose of the Study:

  • To compare hippocampal volume derived from MRI with 18F-FDG PET hypometabolism.
  • To assess the utility of these biomarkers in the early diagnosis of Alzheimer's Disease.
  • To evaluate the diagnostic discrimination ability of hippocampal volumetry versus hypometabolism.

Main Methods:

  • Twenty-two AD patients and twenty-six controls underwent structural MRI and 18F-FDG PET scans on a 3T MR-PET system.
  • A deep-learning tool (MorphoBox) quantified normalized brain volumes from MRI; p-mod software calculated SUVR from PET.
  • Pearson correlations and ROC analyses were performed to compare imaging modalities and assess discrimination.

Main Results:

  • Significant differences in SUVR were observed between AD and control groups in multiple brain regions, including the hippocampus (p < 0.001).
  • Strong correlations (ρ=0.60-0.73) were found between SUVR and normalized brain volumes, especially in the hippocampus, frontal, parietal, and temporal lobes.
  • Hippocampal relative volume showed good discrimination ability with an AUC of 0.79.

Conclusions:

  • A strong correlation exists between hippocampal volumetry (MRI) and hypometabolism (FDG PET) in Alzheimer's Disease.
  • AI-driven hippocampal volumetry may serve as a valuable screening tool, particularly when PET access is limited.
  • Hippocampal volumetry demonstrated superior discrimination power in this study, warranting further investigation with larger cohorts.