{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Ke H"],"funding":["NIBIB NIH HHS","NIDA NIH HHS","NIEHS NIH HHS","NIMH NIH HHS","NINDS NIH HHS","NIH HHS"],"pagination":["908"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12467352"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(9)"],"pubmed_abstract":["<b>Background:</b> Regional cerebral blood flow (rCBF) is a putative biomarker for neuropsychiatric disorders, including major depressive disorder (MDD). <b>Methods:</b> 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 (<i>N</i> = 300; 179 M/121 F, both rsfMRI and ASL data), UK Biobank (<i>N</i> = 8396; 3097 M/5319 F, rsfMRI data), and Amen Clinics Inc. datasets (<i>N</i> = 372: <i>N</i> = 183 M/189 F, SPECT data), were used. <b>Results:</b> PVA-corrected CBF values predicted from rsfMRI showed significant correlation with the whole-brain (<i>r</i> = 0.54, <i>p</i> = 2 × 10<sup>-5</sup>) and 31 out of 34 regional (<i>r</i> = 0.33 to 0.59, <i>p</i> < 1.1 × 10<sup>-3</sup>) rCBF measures from 3D ASL. PVA-corrected rCBF values showed significant regional deficits in the UKBB MDD group (Cohen's <i>d</i> = -0.30 to -0.56, <i>p</i> < 10<sup>-28</sup>), 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 (<i>r</i> = 0.74, <i>p</i> = 4.9 × 10<sup>-7</sup>). Consistent with previous findings, this new method suggests that perfusion signals can be predicted using voxel-wise rsfMRI signals. <b>Conclusions:</b> CBF values computed from widely available rsfMRI can be used to study the impact of neuropsychiatric disorders such as MDD on cerebral neurophysiology."],"journal":["Brain sciences"],"pubmed_title":["Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI."],"pmcid":["PMC12467352"],"funding_grant_id":["U01 MH108148","R01 MH117601","S10 OD023696","R01 MH133812","R01 ES033961","RF1 NS114628","R01 MH116948","RF1NS114628, R01MH112180, R01MH133812, R01MH116948","R01 MH112180","R01 EB015611","K01 DA059603"],"pubmed_authors":["Ke H","Pan Y","Amen D","Jahanshad N","Soares JC","Ma Y","Milad MR","Keator DB","Ma T","Kochunov P","Turner JA","Hong LE","Dukart J","Calhoun VD","Adhikari BM","Thompson PM","van Erp TGM","Gao S"],"additional_accession":[]},"is_claimable":false,"name":"Predicting Regional Cerebral Blood Flow Using Voxel-Wise Resting-State Functional MRI.","description":"<b>Background:</b> Regional cerebral blood flow (rCBF) is a putative biomarker for neuropsychiatric disorders, including major depressive disorder (MDD). <b>Methods:</b> 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 (<i>N</i> = 300; 179 M/121 F, both rsfMRI and ASL data), UK Biobank (<i>N</i> = 8396; 3097 M/5319 F, rsfMRI data), and Amen Clinics Inc. datasets (<i>N</i> = 372: <i>N</i> = 183 M/189 F, SPECT data), were used. <b>Results:</b> PVA-corrected CBF values predicted from rsfMRI showed significant correlation with the whole-brain (<i>r</i> = 0.54, <i>p</i> = 2 × 10<sup>-5</sup>) and 31 out of 34 regional (<i>r</i> = 0.33 to 0.59, <i>p</i> < 1.1 × 10<sup>-3</sup>) rCBF measures from 3D ASL. PVA-corrected rCBF values showed significant regional deficits in the UKBB MDD group (Cohen's <i>d</i> = -0.30 to -0.56, <i>p</i> < 10<sup>-28</sup>), 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 (<i>r</i> = 0.74, <i>p</i> = 4.9 × 10<sup>-7</sup>). Consistent with previous findings, this new method suggests that perfusion signals can be predicted using voxel-wise rsfMRI signals. <b>Conclusions:</b> CBF values computed from widely available rsfMRI can be used to study the impact of neuropsychiatric disorders such as MDD on cerebral neurophysiology.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-05-02T03:13:37.945Z","creation":"2026-05-02T03:07:57.84Z"},"accession":"S-EPMC12467352","cross_references":{"pubmed":["41008269"],"doi":["10.3390/brainsci15090908"]}}