Evidence map›Paper›PMID 42202031›Full record

ArticleScience advances2026

MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI.

Juan Diego Toscano, Yisen Guo, Zhibo Wang, Mohammad Vaezi, Yuki Mori, George Em Karniadakis, Kimberly A S Boster, Douglas H Kelley

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Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Juan Diego ToscanoDivision of Applied Mathematics, Brown University, Providence, RI 02912, USA.ORCID 0009-0007-6515-3306
Yisen GuoDepartment of Mechanical Engineering, University of Rochester, Rochester, NY 14627, USA.ORCID 0009-0003-7387-5908
Zhibo WangSchool of Engineering, Brown University, Providence, RI 02912, USA.ORCID 0000-0002-8691-6583
Mohammad VaeziDepartment of Mechanical Engineering, University of Rochester, Rochester, NY 14627, USA.ORCID 0009-0006-4580-424X
Yuki MoriCenter for Translational Neuromedicine, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0003-4208-0005
George Em KarniadakisDivision of Applied Mathematics, Brown University, Providence, RI 02912, USA.ORCID 0000-0002-9713-7120
Kimberly A S BosterDepartment of Mechanical Engineering, University of Rochester, Rochester, NY 14627, USA.ORCID 0000-0001-5178-128X
Douglas H KelleyDepartment of Mechanical Engineering, University of Rochester, Rochester, NY 14627, USA.ORCID 0000-0001-9658-2954

Funding

Viral Tool Development Core: Visualization and manipulation of brain fluid dynamics by recombinant viral vectorsU19NS128613 · NINDS · UNIVERSITY OF ROCHESTER · PI Hajime Hirase · 2022 to 2026
$13.6M
CRCNS: Waste-clearance flows in the brain measured using physics-informed neural networkR01AT012312 · NCCIH · UNIVERSITY OF ROCHESTER · PI Douglas H Kelley · 2022 to 2026
$1.6M
NCCIH NIH HHS R01 AT012312NINDS NIH HHS U19 NS128613
6 · The paper itself

Abstract

The circulation of cerebrospinal and interstitial fluid plays a vital role in clearing metabolic waste from the brain, and its disruption has been linked to neurological disorders. However, directly measuring brain-wide fluid transport, especially in the deep brain, has remained elusive. Here, we introduce magnetic resonance artificial intelligence velocimetry (MR-AIV), a framework featuring a specialized physics-informed architecture and optimization method that reconstructs three-dimensional fluid velocity fields from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MR-AIV unveils brain-wide velocity maps while providing estimates of tissue permeability and pressure fields, quantities inaccessible to other methods. Applied to the brain, MR-AIV reveals a functional landscape of interstitial and perivascular flow, quantitatively distinguishing slow diffusion-driven transport [∼0.1 micrometers per second (μm/s)] from rapid advective flow (∼3 μm/s). This approach enables new investigations into brain clearance mechanisms and fluid dynamics in health and disease, with broad potential applications to other porous medium systems, from geophysics to tissue mechanics.

Indexed as

BrainMagnetic Resonance ImagingRheologyAnimalsHumansHydrodynamics

Identifiers

PMID42202031
PMCPMC13215179

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Registered trials

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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.