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| 001 | 1052300 | ||
| 005 | 20260122203309.0 | ||
| 024 | 7 | _ | |a 10.3390/brainsci15090908 |2 doi |
| 024 | 7 | _ | |a 10.34734/FZJ-2026-00915 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2026-00915 |
| 082 | _ | _ | |a 570 |
| 100 | 1 | _ | |a Ke, Hongjie |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI |
| 260 | _ | _ | |a Basel |c 2025 |b MDPI AG |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1769095049_32683 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a 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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| 700 | 1 | _ | |a Adhikari, Bhim M. |0 0009-0008-1047-4206 |b 1 |
| 700 | 1 | _ | |a Pan, Yezhi |b 2 |
| 700 | 1 | _ | |a Keator, David B. |b 3 |
| 700 | 1 | _ | |a Amen, Daniel |b 4 |
| 700 | 1 | _ | |a Gao, Si |0 0000-0002-4473-1142 |b 5 |
| 700 | 1 | _ | |a Ma, Yizhou |b 6 |
| 700 | 1 | _ | |a Thompson, Paul M. |0 0000-0002-4720-8867 |b 7 |
| 700 | 1 | _ | |a Jahanshad, Neda |b 8 |
| 700 | 1 | _ | |a Turner, Jessica A. |b 9 |
| 700 | 1 | _ | |a van Erp, Theo G. M. |b 10 |
| 700 | 1 | _ | |a Milad, Mohammed R. |b 11 |
| 700 | 1 | _ | |a Soares, Jair C. |b 12 |
| 700 | 1 | _ | |a Calhoun, Vince D. |b 13 |
| 700 | 1 | _ | |a Dukart, Juergen |0 P:(DE-Juel1)177727 |b 14 |
| 700 | 1 | _ | |a Hong, L. Elliot |0 P:(DE-HGF)0 |b 15 |
| 700 | 1 | _ | |a Ma, Tianzhou |0 0000-0003-3605-0811 |b 16 |
| 700 | 1 | _ | |a Kochunov, Peter |0 P:(DE-HGF)0 |b 17 |
| 773 | _ | _ | |a 10.3390/brainsci15090908 |g Vol. 15, no. 9, p. 908 - |0 PERI:(DE-600)2651993-8 |n 9 |p 908 - |t Brain Sciences |v 15 |y 2025 |x 2076-3425 |
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