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Magnetic Resonance Imaging

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Updated: Jan 16, 2026

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy

Published on: May 27, 2020

Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI.

Hongjie Ke¹, Bhim M Adhikari², Yezhi Pan³

¹Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA.

|September 27, 2025

Summary

This summary is machine-generated.

Regional cerebral blood flow (rCBF) can be accurately predicted from resting-state functional MRI (rsfMRI) data, offering a new way to study major depressive disorder (MDD). This method corrects for artifacts and shows strong agreement with established imaging techniques.

Keywords:

cerebral blood flow partial volume correction prediction rsfMRI support vector machine

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Area of Science:

Neuroimaging
Neuroscience
Biomarkers

Background:

Regional cerebral blood flow (rCBF) is a potential biomarker for neuropsychiatric disorders like major depressive disorder (MDD).
Current methods for measuring rCBF can be resource-intensive.

Purpose of the Study:

To develop and validate a method for predicting rCBF from resting-state functional MRI (rsfMRI).
To assess the utility of rsfMRI-derived rCBF in identifying MDD-related cerebral changes.

Main Methods:

rsfMRI data were analyzed using a support vector machine algorithm to predict voxel-wise rCBF, correcting for partial volume averaging (PVA) artifacts.
The method was validated using three independent datasets (Amish Connectome Project, UK Biobank, Amen Clinics Inc.) with ASL and SPECT data.

Main Results:

PVA-corrected rCBF predicted from rsfMRI showed significant correlations with ASL-measured rCBF.
Significant regional cerebral blood flow deficits were identified in the MDD group within the UK Biobank dataset.
The pattern of MDD-related hypoperfusion from rsfMRI showed high agreement with SPECT findings.

Conclusions:

Cerebral blood flow (CBF) can be reliably computed from widely available rsfMRI data.
This rsfMRI-based approach provides a scalable method for investigating cerebral neurophysiology in neuropsychiatric disorders like MDD.