Craniofacial phenotyping with fetal MRI: a feasibility study of 3D visualisation, segmentation, surface-rendered and physical models.

This study explores the potential of 3D Slice-to-Volume Registration (SVR) motion-corrected fetal MRI for craniofacial assessment, traditionally used only for fetal brain analysis. In addition, we present the first description of an automated pipeline based on 3D Attention UNet trained for 3D fetal MRI craniofacial segmentation, followed by surface refinement. Results of 3D printing of selected models are also presented.Qualitative analysis of multiplanar volumes, based on the SVR output and surface segmentations outputs, were assessed with computer and printed models, using standardised protocols that we developed for evaluating image quality and visibility of diagnostic craniofacial features. A test set of 25, postnatally confirmed, Trisomy 21 fetal cases (24-36 weeks gestational age), revealed that 3D reconstructed T2 SVR images provided 66-100% visibility of relevant craniofacial and head structures in the SVR output, and 20-100% and 60-90% anatomical visibility was seen for the baseline and refined 3D computer surface model outputs respectively. Furthermore, 12 of 25 cases, 48%, of refined surface models demonstrated good or excellent overall quality with a further 9 cases, 36%, demonstrating moderate quality to include facial, scalp and external ears. Additional 3D printing of 12 physical real-size models (20-36 weeks gestational age) revealed good/excellent overall quality in all cases and distinguishable features between healthy control cases and cases with confirmed anomalies, with only minor manual adjustments required before 3D printing.Despite varying image quality and data heterogeneity, 3D T2w SVR reconstructions and models provided sufficient resolution for the subjective characterisation of subtle craniofacial features. We also contributed a publicly accessible online 3D T2w MRI atlas of the fetal head, validated for accurate representation of normal fetal anatomy.Future research will focus on quantitative analysis, optimizing the pipeline, and exploring diagnostic, counselling, and educational applications in fetal craniofacial assessment.

3D T2w fetal body MRI: automated organ volumetry, growth charts and population-averaged atlas.

Structural fetal body MRI provides true 3D information required for volumetry of fetal organs. However, current clinical and research practice primarily relies on manual slice-wise segmentation of raw T2-weighted stacks, which is time consuming, subject to inter- and intra-observer bias and affected by motion-corruption. Furthermore, there are no existing standard guidelines defining a universal approach to parcellation of fetal organs. This work produces the first parcellation protocol of the fetal body organs for motion-corrected 3D fetal body MRI. It includes 10 organ ROIs relevant to fetal quantitative volumetry studies. We also introduce the first population-averaged T2w MRI atlas of the fetal body. The protocol was used as a basis for training of a neural network for automated organ segmentation. It showed robust performance for different gestational ages. This solution minimises the need for manual editing and significantly reduces time. The general feasibility of the proposed pipeline was also assessed by analysis of organ growth charts created from automated parcellations of 91 normal control 3T MRI datasets that showed expected increase in volumetry during 22-38 weeks gestational age range. In addition, the results of comparison between 60 normal and 12 fetal growth restriction datasets revealed significant differences in organ volumes.

Incidental findings on brain MR imaging of asymptomatic term neonates in the Developing Human Connectome Project.

BACKGROUND: Interpretation of incidental findings on term neonatal MRI brain imaging can be challenging as there is a paucity of published normative data on asymptomatic term neonates. Reporting radiologists and clinicians need to be familiar with these incidental findings to avoid over-investigation and misinterpretation particularly in relation to neurodevelopmental outcome. This study aimed to determine the prevalence of incidental findings in a large group of asymptomatic term neonates participating in the Developing Human Connectome Project (dHCP) who were invited for neurodevelopmental assessment at 18 months. METHODS: We retrospectively reviewed MRI brain scans performed on 500 term neonates enrolled in the dHCP study between 2015 and 2019 with normal clinical examination. We reviewed the results of the Bayley Scales of Infant and Toddler Development (Bayley III) applied to participants who attended for neurodevelopmental follow-up at 18 months. Scores considered "delayed" if <70 on language, cognitive or motor scales. FINDINGS: Incidental findings were observed in 47% of term infants. Acute cerebral infarcts were incidentally noted in five neonates (1%). More common incidental findings included punctate white matter lesions (PWMLs) (12%) and caudothalamic subependymal cysts (10%). The most frequent incidental finding was intracranial haemorrhage (25%), particularly subdural haemorrhage (SDH). SDH and PWMLs were more common in infants delivered with ventouse-assistance versus other delivery methods.Neurodevelopmental results were available on 386/500 (77%). 14 infants had a language score < 70 (2 SD below the mean). Of the 386 infants with neurodevelopmental follow up at 18 months, group differences in motor and language scores between infants with and without incidental findings were not significant (p = 0·17 and p = 0·97 respectively). Group differences in cognitive scores at 18 months between infants with (median (interquartile range) -100 (95-105)) and without (100 (95-110)) incidental findings were of small effect size to suggest clinical significance (Cliff's d = 0·15; p<0·05). INTERPRETATION: Incidental findings are relatively common on brain MRI in asymptomatic term neonates, majority are clinically insignificant with normal neurodevelopment at 18 months. FUNDING: This work was supported by the European Research Council under the European Union's Seventh Framework Programme (FP7/20072013/ERC grant agreement no. [319456] dHCP project), by core funding from the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z] and by the National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London and/or the NIHR Clinical Research Facility. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.