Evidence map›Paper›PMID 34109320›Full record

ArticleBrain multiphysics2021

An inverse modelling study on the local volume changes during early morphoelastic growth of the fetal human brain.

Z Wang, B Martin, J Weickenmeier, K Garikipati

Abstract read
In one paragraph

Article in Brain multiphysics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Brain aging mechanisms with mechanical manifestations.Mechanisms of ageing and development · 2021
    Review
  6. Article
  7. 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

4 authors.

Z WangMechanical Engineering, University of Michigan, United States.
B MartinComputer Science and Engineering, University of Michigan, United States.
J WeickenmeierMechanical Engineering, Stevens Institute of Technology, United States.
K GarikipatiMechanical Engineering, Mathematics and Michigan Institute for Computational Discovery & Engineering, University of Michigan, United States.

Funding

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 R21 AG067442
6 · The paper itself

Abstract

We take a data-driven approach to deducing the local volume changes accompanying early development of the fetal human brain. Our approach uses fetal brain atlas MRI data for the geometric changes in representative cases. Using a nonlinear continuum mechanics model of morphoelastic growth, we invert the deformation obtained from MRI registration to arrive at a field for the growth deformation gradient tensor. Our field inversion uses a combination of direct and adjoint methods for computing gradients of the objective function while constraining the optimization by the physics of morphoelastic growth. We thus infer a growth deformation gradient field that obeys the laws of morphoelastic growth. The errors between the MRI data and the forward displacement solution driven by the inverted growth deformation gradient field are found to be smaller than the reference displacement by well over an order of magnitude, and can be driven even lower. The results thus reproduce the three-dimensional growth during the early development of the fetal brain with controllable error. Our findings confirm that early growth is dominated by in plane cortical expansion rather than thickness increase.

Identifiers

PMID34109320
PMCPMC8186493

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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.