Evidence map›Paper›PMID 29352390›Full record

ArticleNeuroinformatics2018

A Spatial Registration Toolbox for Structural MR Imaging of the Aging Brain.

Marco Ganzetti, Quanying Liu, Dante Mantini, Alzheimer’s Disease Neuroimaging Initiative

Open access · greenAbstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Neuroinformatics, 2018. 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
0.9field-weighted citation impact, top 26% 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, 13 citations in OpenAlex.

  1. Article
  2. aXonica: A support package for MRI based Neuroimaging.Biotechnology notes (Amsterdam, Netherlands) · 2024
    Article
  3. Article
  4. Review
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 2 institutions in 3 countries.

Marco GanzettiLaboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium. marco.ganzetti@kuleuven.be.
Quanying LiuLaboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.
Dante MantiniLaboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.
Alzheimer’s Disease Neuroimaging Initiative
ETH Zurich · CHKU Leuven · BE

Funding

FWO 665501
6 · The paper itself

Abstract

During aging the brain undergoes a series of structural changes, in size, shape as well as tissue composition. In particular, cortical atrophy and ventricular enlargement are often present in the brain of elderly individuals. This poses serious challenges in the spatial registration of structural MR images. In this study, we addressed this open issue by proposing an enhanced framework for MR registration and segmentation. Our solution was compared with other approaches based on the tools available in SPM12, a widely used software package. Performance of the different methods was assessed on 229 T1-weighted images collected in healthy individuals, with age ranging between 55 and 90 years old. Our method showed a consistent improvement as compared to other solutions, especially for subjects with enlarged lateral ventricles. It also provided a superior inter-subject alignment in cortical regions, with the most marked improvement in the frontal lobe. We conclude that our method is a valid alternative to standard approaches based on SPM12, and is particularly suitable for the processing of structural MR images of brains with cortical atrophy and ventricular enlargement. The method is integrated in our software toolbox MRTool, which is freely available to the scientific community.

Indexed as

Databases, FactualSoftwareAgedAged, 80 and overAgingBrainFemaleHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedAgingLarge ventriclesMagnetic resonance imagingMRToolNormalizationSegmentationSpatial registration

Identifiers

PMID29352390
OpenAlexW2785722547

What OpenQuestion holds

Textmetadata
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.