Evidence map›Paper›PMID 35583667›Full record

ArticleNeuroradiology2022

Assessment of 2D conventional and synthetic MRI in multiple sclerosis.

Francesc Xavier Aymerich, Cristina Auger, Julio Alonso, Andrea Barros, Margareta A Clarke, Juan Mora, Georgina Arrambide, Juan Francisco Corral, Ana Andrino, Jaume Sastre-Garriga and 1 more

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Article in Neuroradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Francesc Xavier AymerichSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain. xavier.aymerich.idi@gencat.cat.ORCID http://orcid.org/0000-0002-6129-9208
Cristina AugerSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Julio AlonsoSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Andrea BarrosSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Margareta A ClarkeSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Juan MoraSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Georgina ArrambideServei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain.
Juan Francisco CorralSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Ana AndrinoSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.
Jaume Sastre-GarrigaServei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya, (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain.
Alex RoviraSection of Neuroradiology, Department of Radiology (Institut de Diagnòstic per la Imatge), Vall d'Hebron Hospital Universitari, Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Pg Vall d'Hebron 119-129, 08035, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo qualitatively and quantitatively compare synthetic and conventional MRI sequences acquired on a 1.5-T system for patients with multiple sclerosis (MS).

methodsProspective study that involved twenty-seven consecutive relapsing-remitting MS patients scanned on a 1.5-T MRI scanner. The MRI protocol included 2D transverse conventional spin-echo sequences: proton density-weighted (PD), T2-weighted, T2-FLAIR, and T1-weighted. Synthetic images were generated using 2D transverse QRAPMASTER and SyMRI software with the same voxel size, repetition, echo, and inversion times as the conventional sequences. Four raters performed a crosstab qualitative analysis that involved evaluating global image quality, contrast, flow artefacts, and confidence in lesion assessment introducing the concepts of predominance, agreement, and disagreement. A quantitative analysis was also performed and included evaluating the number of lesions (periventricular, juxtacortical, brainstem, and cerebellum) and the contrast-to-noise ratio between regions (CSF, white matter, grey matter, lesions).

resultsThe global image quality assessment showed predominance for better scores for conventional sequences over synthetic sequences, whereas contrast, confidence in lesion assessment, and flow artefacts showed predominance for agreement between sequences. There was predominance for disagreement between all pairs of raters in most of the evaluated qualitative parameters. Synthetic PD and T2-FLAIR images showed higher contrast-to-noise ratios than the corresponding conventional images for most comparison between regions. There were no significant differences in the number of lesions detected for most of the study regions between conventional and synthetic images.

conclusionSynthetic MRI can be potentially used as an alternative to conventional brain MRI sequences in the assessment of MS.

Indexed as

Multiple SclerosisArtifactsBrainHumansMagnetic Resonance ImagingProspective StudiesBrainMagnetic resonance imagingMultiple sclerosisSynthetic MRI

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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.