Evidence map›Paper›PMID 37546181›Full record

ArticleBrain multiphysics2023

A multiphysics model to predict periventricular white matter hyperintensity growth during healthy brain aging.

Andreia Caçoilo, Berkin Dortdivanlioglu, Henry Rusinek, Johannes Weickenmeier

Open access · goldAbstract read
In one paragraph

Article in Brain multiphysics, 2023. 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
1.4field-weighted citation impact, top 19% of its field
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, 6 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Andreia CaçoiloDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.
Berkin DortdivanliogluCivil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, United States of America.
Henry RusinekDepartment of Radiology, New York University Grossman School of Medicine, New York, NY 10016, United States of America.
Johannes WeickenmeierDepartment of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ 07030, United States of America.
Stevens Institute of Technology · USNew York University · USThe University of Texas at Austin · US

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Mary Sherman Mittelman · 2020 to 2026
$28.4M
Advanced Software for MRI, PET, SPECT and CT Image AnalysisU24EB028980 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI RUSINEK, HENRY · 2019 to 2021
$1.2M
Personalized predictions of biomarker progression in Alzheimer's diseaseR21AG067442 · NIA · THE TRUSTEES OF THE STEVENS INSTITUTE OF TECHNOLOGY · PI WEICKENMEIER, JOHANNES · 2020 to 2020
$424k
NIA NIH HHS P30 AG066512NIA NIH HHS R21 AG067442NIBIB NIH HHS U24 EB028980
6 · The paper itself

Abstract

Periventricular white matter hyperintensities (WMH) are a common finding in medical images of the aging brain and are associated with white matter damage resulting from cerebral small vessel disease, white matter inflammation, and a degeneration of the lateral ventricular wall. Despite extensive work, the etiology of periventricular WMHs remains unclear. We pose that there is a strong coupling between age-related ventricular expansion and the degeneration of the ventricular wall which leads to a dysregulated fluid exchange across this brain-fluid barrier. Here, we present a multiphysics model that couples cerebral atrophy-driven ventricular wall loading with periventricular WMH formation and progression. We use patient data to create eight 2D finite element models and demonstrate the predictive capabilities of our damage model. Our simulations show that we accurately capture the spatiotemporal features of periventricular WMH growth. For one, we observe that damage appears first in both the anterior and posterior horns and then spreads into deeper white matter tissue. For the other, we note that it takes up to 12 years before periventricular WMHs first appear and derive an average annualized periventricular WMH damage growth rate of 15.2 ± 12.7 mm

Indexed as

Finite element modelingMultiphysics damage modelPeriventricular white matter hyperintensitiesVentricular wall loading

Identifiers

PMID37546181
PMCPMC10399513
OpenAlexW4378470583

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.