
New research links noninvasive brain blood flow and oxygenation markers to hallmark Alzheimer's disease changes, suggesting early risk detection potential.
Key Details
- 1Study conducted at the Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC.
- 2Researchers used transcranial Doppler ultrasound and near-infrared spectroscopy to measure brain blood flow and oxygenation.
- 3Findings associated higher vascular function indicators with lower amyloid plaques and larger hippocampal volume.
- 4Amyloid PET imaging was also used to correlate vascular markers with known AD pathology.
- 5Techniques are less costly and more tolerable for large-scale or difficult-to-image populations than MRI or PET.
- 6Longitudinal studies are underway to assess if changes in these markers can predict cognitive decline.
Why It Matters

Source
EurekAlert
Related News

NIH-Backed AI Model Predicts Cancer Survival Using Single-Cell Data
Researchers have developed scSurvival, a machine learning tool that uses single-cell tumor data to accurately predict cancer patient survival and identify high-risk cell populations.

Deep Learning Pathomics Platform Improves Immunotherapy Prediction in Lung Cancer
A deep learning pathomics platform accurately predicts immunotherapy response in metastatic NSCLC using routine pathology slides.

AI Pathology Model Outperforms PD-L1 in Predicting NSCLC Immunotherapy Response
MD Anderson's Path-IO machine learning platform accurately predicts immunotherapy responses in metastatic non-small cell lung cancer, surpassing current biomarker standards.