Evidence map›Paper›PMID 40800994›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Longitudinal reproducibility of brain and spinal cord quantitative MRI biomarkers.

Mathieu Boudreau, Agah Karakuzu, Arnaud Boré, Basile Pinsard, Kiril Zelenkovski, Eva Alonso-Ortiz, Julie Boyle, Lune Bellec, Julien Cohen-Adad

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. 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. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Automatic segmentation of the spinal cord nerve rootlets.Imaging neuroscience (Cambridge, Mass.) · 2024
    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

9 authors.

Mathieu BoudreauNeuroPoly, Polytechnique Montreal, Montreal, QC, Canada.
Agah KarakuzuNeuroPoly, Polytechnique Montreal, Montreal, QC, Canada.
Arnaud BoréCentre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, Canada.
Basile PinsardCentre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, Canada.
Kiril ZelenkovskiFaculty of Computer Science and Engineering (FINKI), Skopje, Macedonia.
Eva Alonso-OrtizNeuroPoly, Polytechnique Montreal, Montreal, QC, Canada.
Julie BoyleCentre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, Canada.
Lune BellecCentre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montreal, QC, Canada.
Julien Cohen-AdadNeuroPoly, Polytechnique Montreal, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative MRI (qMRI) promises better specificity, accuracy, repeatability, and reproducibility relative to its clinically-used qualitative MRI counterpart. Longitudinal reproducibility is particularly important in qMRI. The goal is to reliably quantify tissue properties that may be assessed in longitudinal clinical studies throughout disease progression or during treatment. In this work, we present the initial data release of the quantitative MRI portion of the Courtois project on neural modelling (CNeuroMod), where the brain and cervical spinal cord of six participants were scanned at regular intervals over the course of several years. This first release includes 3 years of data collection and up to 10 sessions per participant using quantitative MRI imaging protocols (T

Indexed as

biomarkerbrainlongitudinalquantitative MRIreproducibilityspinal cord

Identifiers

PMID40800994
PMCPMC12319937

What OpenQuestion holds

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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.