Evidence map›Paper›PMID 42108754›Full record

ArticleMagnetic resonance in medicine2026

Ultrafast fMRI Detects Age-Related Changes in Harmonics of Cardiac Pulsations in the Brain at 7 T.

Charles Marchini, Dema Abdelkarim, Yuhui Chai, Monica Fabiani, Gabriele Gratton, Bradley P Sutton

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Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Charles MarchiniBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.ORCID https://orcid.org/0009-0009-1191-6659
Dema AbdelkarimBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Yuhui ChaiBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Monica FabianiBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Gabriele GrattonBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Bradley P SuttonBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.ORCID https://orcid.org/0000-0002-8443-0408

Funding

Optical measures of cerebral arterial function as predictors of brain and cognitive agingR01AG059878 · NIA · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI FABIANI, MONICA, GRATTON, GABRIELE · 2018 to 2022
$3.5M
Role of arterial stiffness in the decline of cognitive control in agingRF1AG062666 · NIA · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI FABIANI, MONICA, GRATTON, GABRIELE · 2019 to 2019
$3.0M
Beckman Institute Biomedical Imaging CenterNIA NIH HHS R01 AG059878NIA NIH HHS R01AG059878NIA NIH HHS RF1AG062666
6 · The paper itself

Abstract

purposeAging impacts pulsatility of blood vessels in the brain, reflecting vascular health. Resolving characteristics of cardiac pulsatility requires faster acquisitions than traditional fMRI. An ultrafast fMRI method was developed and applied to sample several harmonics of cardiac pulsations at 7 T.

methodsLeveraging partial separability, an ultrafast fMRI method (TR = 65 ms) was applied at 7 T with full brain coverage at 2 mm isotropic resolution and concurrent pulse plethysmographic (PPG) recordings in 28 healthy adults, 22 of whom had acceptable PPG and MRI data. The reliability of the pulsation was assessed for each voxel through even/odd splitting of heartbeats. The PPG was used to retrospectively temporally align signals across heartbeats, and analysis was performed on amplitudes of harmonic frequencies to explore age- and sex-related differences. Reliable measures of four harmonics of the heartbeat were characterized along with the ratios of the harmonics to the primary harmonic.

resultsHigh reliability of the pulsation was found near major arteries, tested by Spearman correlation between the first harmonic and a vessel atlas (p < 0.0001). Consistent with previous literature, older adults exhibited higher harmonic amplitudes with the strongest result in the second harmonic in gray matter with FDR-corrected q = 0.020. In addition, males had a higher third-to-first harmonic ratio.

conclusionUltrafast fMRI can reliably resolve several harmonics of cardiac pulsations in the brain in and around blood vessels. This may provide a way to characterize vascular health throughout the brain during aging.

Indexed as

AgingBrainHeartMagnetic Resonance ImagingAdultAgedFemaleHeart RateHumansImage Processing, Computer-AssistedMaleMiddle AgedPlethysmographyPulsatile FlowReproducibility of ResultsYoung Adult7 Teslaagingarterial stiffeningBOLD fMRIcerebrovascular pulsatilitypartial separability

Identifiers

PMID42108754
PMCPMC13327429

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.