Evidence map›Paper›PMID 42509624›Full record

ArticleMagnetic resonance in medicine2026

Phase-Sensitive Modeling Improves Fat DESPOT Multiparametric Relaxation Mapping in Fat-Water Mixtures.

Renée-Claude Bider, Cristian Ciobanu, Jorge Campos Pazmiño, Véronique Fortier, Evan McNabb, Ives R Levesque

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Renée-Claude BiderMedical Physics Unit, McGill University, Montréal, Québec, Canada.
Cristian CiobanuMedical Physics Unit, McGill University, Montréal, Québec, Canada.
Jorge Campos PazmiñoMedical Physics Unit, McGill University, Montréal, Québec, Canada.
Véronique FortierMedical Physics Unit, McGill University, Montréal, Québec, Canada.ORCID https://orcid.org/0000-0003-1859-003X
Evan McNabbMedical Physics Unit, McGill University, Montréal, Québec, Canada.
Ives R LevesqueMedical Physics Unit, McGill University, Montréal, Québec, Canada.ORCID https://orcid.org/0000-0002-0546-1733

Funding

Fonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada (NSERC)Research Institute of the McGill University Health Centre
6 · The paper itself

Abstract

purposeTo improve on a multiparametric technique-known as Fat DESPOT-to map the fat- and water-specific

methodsWe compared three-point Dixon and Graph Cut (GC) approaches to initial guesses for Fat DESPOT in experiments at 3 T in fat emulsion phantoms. Also in the phantom, we compared magnitude-based Fat DESPOT (Fat DESPOT

resultsIn phantoms, Fat DESPOT using three-point Dixon and GC returned similar parameter estimates and precision, though the former deviated from the overall trend at 50% nominal fat fraction. The complex models showed the best agreement with reference PDFF (average error 1.2% ± 1.2%) and the lowest combined standard deviation across ROIs, for PDFF,

conclusionWith more precise

Indexed as

Adipose TissueImage Processing, Computer-AssistedMagnetic Resonance ImagingAbdomenAlgorithmsBody WaterHumansImage Interpretation, Computer-AssistedLegPhantoms, ImagingReproducibility of ResultsWaterWaterfat relaxation ratefat‐water separationmultiparametric imagingrelaxation mappingwater relaxation rate

Identifiers

PMID42509624
PMCPMC13527274

What OpenQuestion holds

Textmetadata
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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.