Evidence map›Paper›PMID 30903339›Full record

ArticleEuropean radiology2019

Automated quantitative evaluation of brain MRI may be more accurate for discriminating preterm born adults.

Alina Jurcoane, Marcel Daamen, Vera C Keil, Lukas Scheef, Josef G Bäuml, Chun Meng, Afra M Wohlschläger, Christian Sorg, Barbara Busch, Nicole Baumann and 6 more

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Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Alina JurcoaneFunctional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany. alinajw@outlook.de.ORCID http://orcid.org/0000-0001-5571-9635
Marcel DaamenFunctional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany.
Vera C KeilSection of Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53105, Bonn, Germany.
Lukas ScheefFunctional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany.
Josef G BäumlDepartment of Neuroradiology, Klinikum rechts der Isar, Munich, Germany.
Chun MengDepartment of Neuroradiology, Klinikum rechts der Isar, Munich, Germany.
Afra M WohlschlägerDepartment of Neuroradiology, Klinikum rechts der Isar, Munich, Germany.
Christian SorgDepartment of Neuroradiology, Klinikum rechts der Isar, Munich, Germany.
Barbara BuschDepartment of Neonatology, University Hospital Bonn, Bonn, Germany.
Nicole BaumannDepartment of Psychology, University of Warwick, Coventry, UK.
Dieter WolkeDepartment of Psychology, University of Warwick, Coventry, UK.
Peter BartmannDepartment of Neonatology, University Hospital Bonn, Bonn, Germany.
Henning BoeckerFunctional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany.
Guido LüchtersCenter for Development Research, University of Bonn, Bonn, Germany.
Milka MarinovaSection of Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53105, Bonn, Germany.
Elke HattingenSection of Neuroradiology, Department of Radiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53105, Bonn, Germany.

Funding

Bundesministerium f?r Bildung und Forschung 01ER0801Bundesministerium f?r Bildung und Forschung 01ER0803Bundesministerium f?r Bildung und Forschung 01EV0710Fakult?t f?r Medizin, Technische Universit?t M?nchen KKF 8765162
6 · The paper itself

Abstract

objectiveTo investigate the structural brain abnormalities and their diagnostic accuracy through qualitative and quantitative analysis in term born and very preterm birth or with very low birth weight (VP/VLBW) adults.

methodsWe analyzed 3-T MRIs acquired in 2011-2013 from 67 adults (27 term born controls, mean age 26.4 years, 8 females; 40 VP/VLBWs, mean age 26.6 years, 16 females). We compared automatic segmentations of the white matter, deep gray matter and cortical gray matter, manual corpus callosum measurements and visual ratings of the ventricles and white matter with t tests, logistic regression, and receiver operator characteristic (ROC) curves.

resultsAutomatic segmentation correctly classified 84% of cases; visual ratings correctly classified 63%. Quantitative volumetry based on automatic segmentation revealed higher ventricular volume, lower posterior corpus callosum, and deep gray matter volumes in VP/VLBW subjects compared to controls (p < 0.01). Visual rating and manual measurement revealed a thinner corpus callosum in VP/VLBW adults (p = 0.04) and deformed lateral ventricles (p = 0.03) and tendency towards more "dirty" white matter (p = 0.06). Automatic/manual measures combined with visual ratings correctly classified 87% of cases. Stepwise logistic regression identified three independent features that correctly classify 81% of cases: ventricular volume, deep gray matter volume, and white matter aspect.

conclusionEnlarged and deformed lateral ventricles, thinner corpus callosum, and "dirty" white matter are prevalent in preterm born adults. Their visual evaluation has low diagnostic accuracy. Automatic volume quantification is more accurate but time consuming. It may be useful to ask for prematurity before initiating further diagnostics in subjects with these alterations. KEY POINTS: • Our study confirms prior reports showing that structural brain abnormalities related to preterm birth persist into adulthood. • In the clinical practice, if large and deformed lateral ventricles, small and thin corpus callosum, and "dirty" white matter are visible on MRI, ask for prematurity before considering other diagnoses. • Although prevalent, visual findings have low accuracy; adding automatic segmentation of lateral ventricles and deep gray matter nuclei improves the diagnostic accuracy.

Indexed as

Infant, Very Low Birth WeightPremature BirthAdultBrainBrain DiseasesCross-Sectional StudiesFemaleHumansMagnetic Resonance ImagingMaleProspective StudiesReproducibility of ResultsAdultsLow birth weightMagnetic resonance imagingPreterm birth

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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.