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Related Concept Videos

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.
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
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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 14, 2026

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

Marc D Rudolph1, Melissa M Rundle1, Kathryn H Alphin1

  • 1Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|January 13, 2026
PubMed
Summary
This summary is machine-generated.

New segmentation software (SynthSeg) improved brain atrophy classification compared to older FreeSurfer methods. SynthSeg is robust to image quality, potentially reducing costs and manual segmentation needs in dementia research.

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Area of Science:

  • Neuroimaging
  • Medical Image Analysis
  • Computational Neuroscience

Background:

  • Image artifacts and poor segmentation can bias brain atrophy estimates in clinical populations.
  • This impacts the quantification of age- and disease-related changes, increasing costs due to discarded scans.

Purpose of the Study:

  • To compare FreeSurfer (v7.2) recon-all and FreeSurfer (v7.4) recon-all-clinical (SynthSeg) pipelines for brain structure segmentation.
  • To evaluate the impact of these pipelines on atrophy classification in a cohort with varying cognitive statuses.

Main Methods:

  • Structural T1-MRI scans from 624 participants (cognitively normal, MCI, dementia) were processed.
  • Cortical thickness, gray/white matter volume, and hippocampal volume were quantified.
  • Tau-PET imaging was performed, and global/regional tau deposition was measured.

Main Results:

  • SynthSeg produced comparable volumetric estimates but showed better agreement for hippocampal volume compared to FreeSurfer v7.2.
  • Cortical thickness estimates differed significantly, leading to discordant atrophy classification (36% for meta-temporal thickness).
  • Tau-PET quantification remained unaffected by the segmentation pipeline.

Conclusions:

  • SynthSeg segmentations are robust to image quality and improve atrophy classification accuracy, especially for cortical thickness.
  • Deep learning-based methods like SynthSeg offer faster processing and may reduce the need for manual segmentation or discarding low-quality scans.