Evidence map›Paper›PMID 40274782›Full record

ArticleNature communications2025

MR perfusion source mapping depicts venous territories and reveals perfusion modulation during neural activation.

Ekin Karasan, Jingjia Chen, Julian Maravilla, Zhiyong Zhang, Chunlei Liu, Michael Lustig

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ekin KarasanDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA. ekin_karasan@berkeley.edu.ORCID http://orcid.org/0000-0001-5662-8145
Jingjia ChenDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.ORCID http://orcid.org/0000-0002-6023-1033
Julian MaravillaDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.
Zhiyong ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Chunlei LiuDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.ORCID http://orcid.org/0000-0001-8816-4832
Michael LustigDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, USA.

Funding

Robotically-actuated, low-noise, concurrent TMS-EEG-fMRI systemR01MH127104 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI LIU, CHUNLEI, LUSTIG, MICHAEL · 2021 to 2024
$6.5M
Multi-parametric anthropomorphic MRI Phantoms technology for reliable and reproducible structural and quantitative MRIR01EB034831 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI Ana Claudia Arias, Michael Lustig · 2023 to 2026
$2.5M
NIBIB NIH HHS R01 EB034831NIMH NIH HHS R01 MH127104U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01EB034831U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01MH127104
6 · The paper itself

Abstract

The cerebral venous system plays a crucial role in neurological and vascular conditions, yet its hemodynamics remain underexplored due to its complexity and variability across individuals. To address this, we develop a venous perfusion source mapping method using Displacement Spectrum MRI, a non-contrast technique that leverages blood water as an endogenous tracer. Our technique encodes spatial information into the magnetization of blood water spins during tagging and detects it once the tagged blood reaches the brain's surface, where the signal-to-noise ratio is 3-4 times higher. We resolve the sources of blood entering the imaging slice across short (10 ms) to long (3 s) evolution times, effectively capturing perfusion sources in reverse. This approach enables the measurement of slow venous blood flow, including potential contributions from capillary beds and surrounding tissue. We demonstrate perfusion source mapping in the superior cerebral veins, verify its sensitivity to global perfusion modulation induced by caffeine, and establish its specificity by showing repeatable local perfusion modulation during neural activation. From all blood within the imaging slice, our method localizes the portion originating from an activated region upstream.

Indexed as

BrainBrain MappingCerebral VeinsCerebrovascular CirculationMagnetic Resonance ImagingAdultCaffeineFemaleHemodynamicsHumansMalePerfusionSignal-To-Noise RatioCaffeine

Identifiers

PMID40274782
PMCPMC12022259

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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 OpenQuestion graph.