Cross-Modality Comparison of Fetal Brain Phenotypes: Insights From Short-Interval Second-Trimester MRI and Ultrasound Imaging.
Authors
Affiliations (7)
Affiliations (7)
- Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science, University of Oxford, Oxford, UK.
- Research Department of Imaging Physics and Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
- Fetal Medicine Department, GSTT, London, UK.
- School of Health and Psychological Sciences, City, University of London, London, UK.
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.
- Harvard Medical School, Charlestown, Massachusetts, USA.
Abstract
Advances in fetal three-dimensional (3D) ultrasound (US) and magnetic resonance imaging (MRI) have revolutionized the study of fetal brain development, enabling detailed analysis of brain structures and growth. Despite their complementary capabilities, these modalities capture fundamentally different physical signals, potentially leading to systematic differences in image-derived phenotypes (IDPs). Here, we evaluate the agreement of IDPs between US and MRI by comparing the volumes of eight brain structures from 90 subjects derived using deep-learning algorithms from majority same-day imaging (days between scans: mean = 1.2, mode = 0 and max = 4). Excellent agreement (intra-class correlation coefficient, <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics><mrow><mi>ICC</mi> <mo>></mo> <mn>0.75</mn></mrow> <annotation>$$ ICC>0.75 $$</annotation></semantics> </math> ) was observed for the cerebellum, cavum septum pellucidum, thalamus, white matter and deep grey matter volumes, with significant correlations <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics> <mrow> <mfenced><mrow><mi>p</mi> <mo><</mo> <mn>0.001</mn></mrow> </mfenced> </mrow> <annotation>$$ \left(p<0.001\right) $$</annotation></semantics> </math> for most structures, except the ventricular system. Bland-Altman analysis revealed some systematic biases: intracranial and cortical plate volumes were larger on US than MRI, by an average of <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics><mrow><mn>35</mn> <mspace></mspace> <msup><mi>cm</mi> <mn>3</mn></msup> </mrow> <annotation>$$ 35\ {\mathrm{cm}}^3 $$</annotation></semantics> </math> and <math xmlns="http://www.w3.org/1998/Math/MathML"> <semantics><mrow><mn>4.1</mn> <mspace></mspace> <msup><mi>cm</mi> <mn>3</mn></msup> </mrow> <annotation>$$ 4.1\ {\mathrm{cm}}^3 $$</annotation></semantics> </math> , respectively. Finally, we found the labels of the brainstem and ventricular system were not comparable between the modalities. These findings highlight the necessity of structure-specific adjustments when interpreting fetal brain IPDs across modalities and underscore the complementary roles of US and MRI in advancing fetal neuroimaging.