Journal Article

FZJ-2026-00915

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI

Ke, H. (Corresponding author) ; Adhikari, B. M. ; Pan, Y. ; Keator, D. B. ; Amen, D. ; Gao, S. ; Ma, Y. ; Thompson, P. M. ; Jahanshad, N. ; Turner, J. A. ; van Erp, T. G. M. ; Milad, M. R. ; Soares, J. C. ; Calhoun, V. D. ; Dukart, J.FZJ* ; Hong, L. E. ; Ma, T. ; Kochunov, P.

2025
MDPI AG Basel

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Please use a persistent id in citations: doi:10.3390/brainsci15090908  doi:10.34734/FZJ-2026-00915

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

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Contributing Institute(s):

1. Gehirn & Verhalten (INM-7)

Research Program(s):

1. 5251 - Multilevel Brain Organization and Variability (POF4-525) (POF4-525)

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