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

Authors

Hongjie Ke
Bhim M Adhikari
Yezhi Pan
David B Keator
Daniel Amen
Si Gao
Yizhou Ma
Paul M Thompson
Neda Jahanshad
Jessica A Turner
Theo G M van Erp
Mohammed R Milad
Jair C Soares
Vince D Calhoun
Juergen Dukart
L Elliot Hong
Tianzhou Ma
Peter Kochunov

Language

English

Publication Date

8-23-2025

Journal

Brain Sciences

DOI

10.3390/brainsci15090908

PMID

41008269

PMCID

PMC12467352

PubMedCentral® Posted Date

8-23-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Background: Regional cerebral blood flow (rCBF) is a putative biomarker for neuropsychiatric disorders, including major depressive disorder (MDD).

Methods: Here, we show that rCBF can be predicted from resting-state functional MRI (rsfMRI) at the voxel level while correcting for partial volume averaging (PVA) artifacts. Cortical patterns of MDD-related CBF differences decoded from rsfMRI using a PVA-corrected approach showed excellent agreement with CBF measured using single-photon emission computed tomography (SPECT) and arterial spin labeling (ASL). A support vector machine algorithm was trained to decode cortical voxel-wise CBF from temporal and power-spectral features of voxel-level rsfMRI time series while accounting for PVA. Three datasets, Amish Connectome Project (N = 300; 179 M/121 F, both rsfMRI and ASL data), UK Biobank (N = 8396; 3097 M/5319 F, rsfMRI data), and Amen Clinics Inc. datasets (N = 372: N = 183 M/189 F, SPECT data), were used.

Results: PVA-corrected CBF values predicted from rsfMRI showed significant correlation with the whole-brain (r = 0.54, p = 2 × 10-5) and 31 out of 34 regional (r = 0.33 to 0.59, p < 1.1 × 10-3) rCBF measures from 3D ASL. PVA-corrected rCBF values showed significant regional deficits in the UKBB MDD group (Cohen's d = -0.30 to -0.56, p < 10-28), with the strongest effect sizes observed in the frontal and cingulate areas. The regional deficit pattern of MDD-related hypoperfusion showed excellent agreement with CBF deficits observed in the SPECT data (r = 0.74, p = 4.9 × 10-7). Consistent with previous findings, this new method suggests that perfusion signals can be predicted using voxel-wise rsfMRI signals.

Conclusions: CBF values computed from widely available rsfMRI can be used to study the impact of neuropsychiatric disorders such as MDD on cerebral neurophysiology.

Keywords

cerebral blood flow, partial volume correction, prediction, support vector machine, rsfMRI

Published Open-Access

yes

Recommended Citation

Ke, Hongjie; Adhikari, Bhim M; Pan, Yezhi; et al., "Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI" (2025). Faculty, Staff and Student Publications. 6555.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/6555