Evidence map›Paper›PMID 29193244›Full record

ArticleMagnetic resonance in medicine2018

An efficient sequence for fetal brain imaging at 3T with enhanced T

Giulio Ferrazzi, Anthony N Price, Rui Pedro A G Teixeira, Lucilio Cordero-Grande, Jana Hutter, Ana Gomes, Francesco Padormo, Emer Hughes, Torben Schneider, Mary Rutherford and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 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
–field-weighted citation impact, top 84% 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, 5 citations in OpenAlex.

  1. ISUOG Practice Guidelines (updated): performance of fetal magnetic resonance imaging.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2023
    Article
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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

12 authors at 2 institutions in 2 countries.

Giulio FerrazziCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Anthony N PriceCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Rui Pedro A G TeixeiraCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.ORCID 0000-0001-6508-9315
Lucilio Cordero-GrandeCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Jana HutterCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Ana GomesCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Francesco PadormoCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Emer HughesCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Torben SchneiderPhilips Healthcare, Guildford, Surrey, UK.
Mary RutherfordCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Maria Kuklisova MurgasovaCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
Joseph V HajnalCentre for the Developing Brain, Department of Perinatal Imaging and Health, Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.ORCID 0000-0002-2690-5495
King's College London · GBPhilips (United Kingdom) · GB

Funding

Department of HealthEuropean Research Council 319456Medical Research Council MC_U120088465Wellcome TrustWellcome Trust WT 203148/Z/16/Z
6 · The paper itself

Abstract

purposeUltrafast single-shot T

methodsA 2D gradient echo sequence with an adiabatic inversion was optimized to be robust to fetal motion and maternal breathing optimizing grey/white matter contrast at the same time. This was combined with slice to volume registration and super resolution methods to produce volumetric reconstructions. The sequence was tested on 22 fetuses.

resultsOptimized grey/white matter contrast and robustness to fetal motion and maternal breathing were achieved. Signal from cerebrospinal fluid (CSF) and amniotic fluid was nulled and 0.75 mm isotropic anatomical reconstructions of the fetal brain were obtained using slice-to-volume registration and super resolution techniques. Total acquisition time for a single stack was 56 s, all acquired during free breathing. Enhanced sensitivity to normal anatomy and pathology with respect to established methods is demonstrated. A direct comparison with a 3D spoiled gradient echo sequence and a controlled motion experiment run on an adult volunteer are also shown.

conclusionThis paper describes a robust framework to perform T

Indexed as

AdultAlgorithmsArtifactsBrainContrast MediaFemaleGray MatterHealthy VolunteersHumansImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMotionNeuroimagingPregnancyContrast Mediafetal MRIhemorrhagemotion tolerance and efficiencyslice-to-volume reconstructionT1 contrast

Identifiers

PMID29193244
PMCPMC5900721
OpenAlexW2770224131

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.