Evidence map›Paper›PMID 39180686›Full record

ArticleMagma (New York, N.Y.)2024

Improving the lesion appearance on FLAIR images synthetized from quantitative MRI: a fast, hybrid approach.

Fei Xu, Stefano Mandija, Jordi P D Kleinloog, Hongyan Liu, Oscar van der Heide, Anja G van der Kolk, Jan Willem Dankbaar, Cornelis A T van den Berg, Alessandro Sbrizzi

Abstract read
In one paragraph

Article in Magma (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

9 authors.

Fei XuComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands. f.xu@umcutrecht.nl.ORCID http://orcid.org/0000-0001-8505-9981
Stefano MandijaComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Jordi P D KleinloogComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Hongyan LiuComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Oscar van der HeideComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Anja G van der KolkDepartment of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
Jan Willem DankbaarDepartment of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Cornelis A T van den BergComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.
Alessandro SbrizziComputational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek 17986
6 · The paper itself

Abstract

objectiveThe image quality of synthetized FLAIR (fluid attenuated inversion recovery) images is generally inferior to its conventional counterpart, especially regarding the lesion contrast mismatch. This work aimed to improve the lesion appearance through a hybrid methodology. MATERIALS AND

methodsWe combined a full brain 5-min MR-STAT acquisition followed by FLAIR synthetization step with an ultra-under sampled conventional FLAIR sequence and performed the retrospective and prospective analysis of the proposed method on the patient datasets and a healthy volunteer.

resultsAll performance metrics of the proposed hybrid FLAIR images on patient datasets were significantly higher than those of the physics-based FLAIR images (p < 0.005), and comparable to those of conventional FLAIR images. The small difference between prospective and retrospective analysis on a healthy volunteer demonstrated the validity of the retrospective analysis of the hybrid method as presented for the patient datasets. DISCUSSION: The proposed hybrid FLAIR achieved an improved lesion appearance in the clinical cases with neurological diseases compared to the physics-based FLAIR images, Future prospective work on patient data will address the validation of the method from a diagnostic perspective by radiological inspection of the new images over a larger patient cohort.

Indexed as

BrainMagnetic Resonance ImagingAdultAgedAlgorithmsFemaleHealthy VolunteersHumansImage EnhancementImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedMaleMiddle AgedProspective StudiesReproducibility of ResultsRetrospective StudiesBrain MRIFLAIRQuantitative MRISynthetic MRI

Identifiers

PMID39180686
PMCPMC11582199

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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.