To 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.
We 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.
Automatic 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.
Enlarged 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.
• 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.
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Area under the curve
Fluid attenuated inversion recovery
Picture archiving and communication system
Receiver operator characteristic
- T1- or T2-w:
T1- or T2-weighted
Very preterm birth or very low birth weight
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We thank all current and former Bavarian Longitudinal Study Group members who contributed to study organization, recruitment, data collection, management, and analyses, including (in alphabetical order) Stephan Czeschka, Claudia Grünzinger, Julia Jaekel, Christian Koch, Diana Kurze, Sonja Perk, Andrea Schreier, Antje Strasser, Julia Trummer, and Eva van Rossum. Most importantly, we thank all the study participants for their efforts to take part in this study.
This study has received funding from the German Federal Ministry of Education and Science (BMBF 01ER0801 to PB and DW, BMBF 01EV0710 to AMW, BMBF 01ER0803 to CS) and the Kommission für Klinische Forschung, Technische Universität München (KKF 8765162 to CS).
The scientific guarantor of this publication is Dr. Alina Jurcoane.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
One of the authors, GL, has significant statistical expertise.
Written informed consent was obtained from all subjects in this study.
The Ethics Committee at the University Hospital Bonn approved the study.
Study subjects or cohorts overlap
Some study subjects or cohorts have been previously reported in several articles (https://www.ncbi.nlm.nih.gov/pubmed/?term=bartmann+wolke+mri). These were on topics of functional MRI, diffusion tensor imaging or behavioral measures; the current article is the only publication with neuroradiological focus.
• cross-sectional study
• performed at one institution
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Milka Marinova and Elke Hattingen share authorship.
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Jurcoane, A., Daamen, M., Keil, V.C. et al. Automated quantitative evaluation of brain MRI may be more accurate for discriminating preterm born adults. Eur Radiol 29, 3533–3542 (2019). https://doi.org/10.1007/s00330-019-06099-7
- Preterm birth
- Low birth weight
- Magnetic resonance imaging