Normative volume measurements of the fetal intra-cranial compartments using 3D volume in utero MR imaging

Examining Craniofacial and Velopharyngeal Structures in Premature Infants: A Window Into the Womb

BACKGROUND

Very little is known about how the velopharynx and levator veli palatini muscle develop in utero. The purpose of this study was to describe craniofacial, velopharyngeal, and levator veli palatini dimensions in a group of infants born prematurely and imaged before 40 weeks gestation.

METHODS

A retrospective, descriptive study design was utilized to examine the MRI scans of 6 infants less than 40 weeks' gestation. Imaging was initially completed for medically necessity and pulled from patients' charts retrospectively for the purpose of this study. Craniofacial, velopharyngeal, and levator veli palatini dimensions were analyzed.

RESULTS

All linear measures were consistently shorter across all variable categories. While effective VP ratio was less favorable for speech in infants under 40 weeks' gestation, angle measures such as LVP angle of origin, NSB angle, SNA angle, and SNB angle were relatively unchanged.

CONCLUSIONS

Linear craniofacial, VP, and LVP variables tend to be smaller in infants under 40 weeks' gestation than those reported within the first 6 months of life while angulation is relatively similar. Future research in this area may be relevant to better diagnosis of craniofacial conditions in utero.

Fetal Brain Growth in the Early Second Trimester

BACKGROUND AND PURPOSE

Recent advances in fetal MR imaging technology have enabled acquisition of diagnostic images in the early second trimester. Interpretation of these examinations is limited by a lack of familiarity with the developmental changes that occur during these early stages of growth. This study aimed to characterize normal fetal brain growth between the 12th and 20th weeks of gestational age.

MATERIALS AND METHODS

This study was conducted as an observational retrospective analysis. Data were obtained from a tertiary care center's PACS database. All fetuses included had late fetal MR imaging (>20 weeks) or postnatal MR imaging, which confirmed normality. Each MR image was manually segmented, with ROIs placed to calculate the volume of the supratentorial parenchyma, brainstem, cerebellum, ventricular CSF, and extra-axial CSF. A linear regression analysis was used to evaluate gestational age as a predictor of the volume of each structure.

RESULTS

Thirty-one subjects with a mean gestational age of 17.23 weeks (range, 12-19 weeks) were studied. There was a positive, significant association between gestational age and intracranial, supratentorial parenchyma; brainstem cerebellum; intraventricular CSF; and extra-axial CSF volumes (P < .001). Growth was fastest in the supratentorial parenchyma and extra-axial CSF. Fetal sex was not associated with the volume in any of the ROIs.

CONCLUSIONS

This study demonstrates distinct trajectories for the major compartments of the fetal brain in the early second trimester. The fastest growth rates were observed in the supratentorial brain and extra-axial CSF.

Fetal head-down posture may explain the rapid brain evolution in humans and other primates: An interpretative review

Evolutionary cerebrovascular consequences of upside-down postural verticality of the anthropoid fetus have been largely overlooked in the literature. This working hypothesis-based report provides a literature interpretation from an aspect that the rapid evolution of the human brain has been promoted by fetal head-down position due to maternal upright and semi-upright posture. Habitual vertical torso posture is a feature not only of humans, but also of monkeys and non-human apes that spend considerable time in a sitting position. Consequently, the head-down position of the fetus may have caused physiological craniovascular hypertension that stimulated expansion of the intracranial vessels and acted as an epigenetic physiological stress, which enhanced neurogenesis and eventually, along with other selective pressures, led to the progressive growth of the anthropoid brain and its organization. This article collaterally opens a new insight into the conundrum of high cephalopelvic proportions (i.e., the tight fit between the pelvic birth canal and fetal head) in phylogenetically distant lineages of monkeys, lesser apes, and humans. Low cephalopelvic proportions in non-human great apes could be accounted for by their energetically efficient horizontal nest-sleeping and consequently by their larger body mass compared to monkeys and lesser apes that sleep upright. One can further hypothesize that brain size varies in anthropoids according to the degree of exposure of the fetus to postural verticality. The supporting evidence for this postulation includes a finding that in fossil hominins cerebral blood flow rate increased faster than brain volume. This testable hypothesis opens a perspective for research on fetal postural cerebral hemodynamics.

Automatic biometry of fetal brain MRIs using deep and machine learning techniques

Linear biometric measurements on magnetic resonance images are important for the assessment of fetal brain development, which is expert knowledge dependent and laborious. This study aims to construct a segmentation-based method for automatic two-dimensional biometric measurements of fetal brain on magnetic resonance images that provides a fast and accurate measurement of fetal brain. A total of 268 volumes (5360 images) magnetic resonance images of normal fetuses were included. The automatic method involves two steps. First, the fetal brain was segmented into four parts with a deep segmentation network: cerebrum, cerebellum, and left and right lateral ventricles. Second, the measurement plane was determined, and the corresponding biometric parameters were calculated according to clinical guidelines, including cerebral biparietal diameter (CBPD), transverse cerebellar diameter (TCD), left and right atrial diameter (LAD/RAD). Pearson correlation coefficient and Bland-Altman plots were used to assess the correlation and agreement between computer-predicted values and manual measurements. Mean differences were used to evaluate the errors quantitatively. Analysis of fetal cerebral growth based on the automatic measurements was also displayed. The experiment results show that correlation coefficients for CBPD, TCD, LAD and RAD were as follows: 0.977, 0.990, 0.817, 0.719, mean differences were - 2.405 mm, - 0.008 mm, - 0.33 mm, - 0.213 mm, respectively. The correlation between the errors and gestational age was not statistically significant (p values were 0.2595, 0.0510, 0.1995, and 0.0609, respectively). The proposed automatic method for linear measurements on fetal brain MRI achieves excellent performance, which is expected to be applied in clinical practice and be helpful for prenatal diagnosis and clinical work efficiency improvement.

Validation of an automatic software in assessing fetal brain volume from three dimensional ultrasonographic volumes: Comparison with manual analysis

OBJECTIVE

This study was aimed to test the agreement between a manual and an automatic technique in measuring fetal brain volume (FBV) from three-dimensional (3D) fetal head datasets.

METHODS

FBV were acquired independently by two operators from low risk singleton pregnancies at a gestational age between 19 and 34 weeks. FBV measurements were obtained using an automatic software (Smart ICV™) and manually by Virtual Organ Computer-aided AnaLysis (VOCAL™). Intraclass correlation coefficient (ICC) were calculated to assess reliability, while bias and agreement were evaluate by examining Bland-Altman plots. The time spent in measuring volumes was calculated and values obtained compared.

RESULTS

Sixty-three volumes were considered for the study. In all the included volumes successful volume analysis were obtained with both techniques. Smart ICV™ showed a high intra-observer (0.996; 95% CI 0.994-0.998) and inter-observer (ICC 0.995; 95% CI 0.991-0.997). An excellent degree of reliability was found when the two techniques were compared (ICC 0.995; 95% CI 0.987-0.998). The time required to perform FBV was significantly lower for Smart ICV™ than VOCAL™ (8.2 ± 4.5 vs. 121.3 ± 19.0 s; p < 0.0001).

CONCLUSIONS

The measurement of FBV is feasible with both manual and automatic techniques. Smart ICV™ showed an excellent intra- and inter-observer reliability associated with a valuable agreement with volume measurements obtained manually with VOCAL™. Volumes may be measured significantly faster with smart ICV™ than manually and this automatic software has the potential to become the preferred methods for the assessment of FBV.

Fetal brain tissue annotation and segmentation challenge results

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, gray matter, white matter, ventricles, cerebellum, brainstem, deep gray matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.

Sex differences in fetal intracranial volumes assessed by in utero MR imaging

BACKGROUND

The primary aim of the study is to test the null hypothesis that there are no statistically significant differences in intracranial volumes between male and female fetuses. Furthermore, we have studied the symmetry of the cerebral hemispheres in the cohort of low-risk fetuses.

METHODS

200 normal fetuses between 18 and 37 gestational weeks (gw) were included in the cohort and all had in utero MR, consisting of routine and 3D-volume imaging. The surfaces of the cerebral ventricles, brain and internal table of the skull were outlined manually and volume measurements were obtained of ventricles (VV), brain parenchyma (BPV), extraaxial CSF spaces (EAV) and the total intracranial volume (TICV). The changes in those values were studied over the gestational range, along with potential gender differences and asymmetries of the cerebral hemispheres.

RESULTS

BPV and VV increased steadily from 18 to 37 gestational weeks, and as a result TICV also increased steadily over that period. TICV and BPV increased at a statistically significantly greater rate in male relative to female fetuses after 24gw. The greater VV in male fetuses was apparent earlier, but the rate of increase was similar for male and female fetuses. There was no difference between the genders in the left and right hemispherical volumes, and they remained symmetrical over the age range measured.

CONCLUSIONS

We have described the growth of the major intracranial compartments in fetuses between 18 and 37gw. We have shown a number of statistically different features between male and female fetuses, but we have not detected any asymmetry in volumes of the fetal cerebral hemispheres.

Three-dimensional ultrasound virtual organ computer-aided analysis to monitor fetal intracranial volume development characteristics: A multi-center study in a Chinese population

OBJECTIVES

This study aimed to evaluate the feasibility of monitoring fetal intracranial volume using three-dimensional ultrasound virtual organ computer-aided analysis (VOCAL) technology and to analyze normal fetal brain growth.

METHODS

This multi-center prospective cross-sectional study included 821 pregnant women (18-40 gestational weeks) divided into 23 groups according to gestational week. We used transabdominal three-dimensional ultrasound VOCAL to monitor fetal intracranial volume; explore the correlation between intracranial volume and gestational age, biparietal diameter (BPD), and head circumference (HC); and analyze the proportion of brain weight to body weight.

RESULTS

The intracranial volume of normal fetuses conformed to the normal distribution, gradually increased with gestational age, and was highly correlated with gestational age (r = 0.977), BPD (r = 0.975), and HC (r = 0.953; p < 0.001). The median percentage of brain weight (BW) to estimated fetal weight (EFW) was between 13% and 21%, and the BW/EFW ratio showed a significant downward trend in the third trimester. The VOCAL technology monitored the fetal intracranial volume with good repeatability.

CONCLUSIONS

VOCAL technology is feasible for monitoring the fetal intracranial volume, and the intracranial volume increases more than 10-times in the second and third trimesters.

Development of Gestational Age-Based Fetal Brain and Intracranial Volume Reference Norms Using Deep Learning

BACKGROUND AND PURPOSE

Fetal brain MR imaging interpretations are subjective and require subspecialty expertise. We aimed to develop a deep learning algorithm for automatically measuring intracranial and brain volumes of fetal brain MRIs across gestational ages.

MATERIALS AND METHODS

This retrospective study included 246 patients with singleton pregnancies at 19-38 weeks gestation. A 3D U-Net was trained to segment the intracranial contents of 2D fetal brain MRIs in the axial, coronal, and sagittal planes. An additional 3D U-Net was trained to segment the brain from the output of the first model. Models were tested on MRIs of 10 patients (28 planes) via Dice coefficients and volume comparison with manual reference segmentations. Trained U-Nets were applied to 200 additional MRIs to develop normative reference intracranial and brain volumes across gestational ages and then to 9 pathologic fetal brains.

RESULTS

Fetal intracranial and brain compartments were automatically segmented in a mean of 6.8 (SD, 1.2) seconds with median Dices score of 0.95 and 0.90, respectively (interquartile ranges, 0.91-0.96/0.89-0.91) on the test set. Correlation with manual volume measurements was high (Pearson r = 0.996, P < .001). Normative samples of intracranial and brain volumes across gestational ages were developed. Eight of 9 pathologic fetal intracranial volumes were automatically predicted to be >2 SDs from this age-specific reference mean. There were no effects of fetal sex, maternal diabetes, or maternal age on intracranial or brain volumes across gestational ages.

CONCLUSIONS

Deep learning techniques can quickly and accurately quantify intracranial and brain volumes on clinical fetal brain MRIs and identify abnormal volumes on the basis of a normative reference standard.

Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders

Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.

Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics

To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative analysis of the human fetal brain is essential. This analysis requires the use of automatic multi-tissue fetal brain segmentation techniques. This paper proposes an end-to-end automatic yet effective method for a multi-tissue fetal brain segmentation model called IRMMNET. It includes a inception residual encoder block (EB) and a dense spatial attention (DSAM) block, which facilitate the extraction of multi-scale fetal-brain-tissue-relevant information from multi-view MRI images, enhance the feature reuse, and substantially reduce the number of parameters of the segmentation model. Additionally, we propose three methods for predicting gestational age (GA)-GA prediction by using a 3D autoencoder, GA prediction using radiomics features, and GA prediction using the IRMMNET segmentation model's encoder. Our experiments were performed on a dataset of 80 pathological and non-pathological magnetic resonance fetal brain volume reconstructions across a range of gestational ages (20 to 33 weeks) that were manually segmented into seven different tissue categories. The results showed that the proposed fetal brain segmentation model achieved a Dice score of 0.791±0.18, outperforming the state-of-the-art methods. The radiomics-based GA prediction methods achieved the best results (RMSE: 1.42). We also demonstrated the generalization capabilities of the proposed methods for tasks such as head and neck tumor segmentation and the prediction of patients' survival days.

Predicting neurodevelopmental outcomes in fetuses with isolated mild ventriculomegaly

BACKGROUND

Fetal ventriculomegaly is the the most common intracranial abnormality detected antenatally. When ventriculomegaly is mild and the only, isolated, abnormality detected (isolated mild ventriculomegaly (IMVM)) the prognosis is generally considered to be good. We aim to determine if there are features on in utero MRI (iuMRI) that can identify fetuses with IMVM who have lower risks of abnormal neurodevelopment outcome.

METHODS

We studied cases recruited into the MRI to enhance the diagnosis of fetal developmental brain abnormalities in utero (MERIDIAN) study, specifically those with: confirmed IMVM, 3D volume imaging of the fetal brain and neurodevelopmental outcomes at 3 years. We explored the influence of sex of the fetus, laterality of the ventriculomegaly and intracranial compartmental volumes in relation to neurodevelopmental outcome.

FINDINGS

Forty-two fetuses met the criteria (33 male and 9 female). There was no obvious correlation between fetal sex and the risk of poor neurodevelopmental outcome. Unilateral IMVM was present in 23 fetuses and bilateral IMVM in 19 fetuses. All fetuses with unilateral IMVM had normal neurodevelopmental outcomes, while only 12/19 with bilateral IMVM had normal neurodevelopmental outcomes. There was no obvious correlation between measure of intracranial volumes and risk of abnormal developmental outcomes.

INTERPRETATION

The most important finding is the very high chance of a good neurodevelopmental outcome observed in fetuses with unilateral IMVM, which is a potentially important finding for antenatal counselling. There does not appear to be a link between the volume of the ventricular system or brain volume and the risk of poor neurodevelopmental outcome.

A Case of Prenatally Diagnosed Congenital Adrenal Hyperplasia With Brain Morphometric Differences

We report a case of a fetus with a prenatal diagnosis of classical congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency. Although CAH is typically assessed postnatally, this fetal case had multiple prenatal clinical assessments made feasible by an interdisciplinary CAH center. The approach facilitated the development and delivery of comprehensive and earlier care for the fetus, and the family living with this complex, congenital condition, with perinatology, endocrinology, genetic counseling, psychology, and urology involvement. As well, the addition of fetal MRI to standard ultrasound revealed significant deficits in the biparietal diameter, occipitofrontal diameter, and total intracranial volume of the fetal CAH brain. These early anomalies in the brain suggest that neurological comorbidities observed in older children and adults with CAH should be studied as early as prenatally, with the addition of fetal MRI to ultrasound potentially being useful for identifying and understanding prenatal anomalies in CAH.

Quantification of Intracranial Structures Volume in Fetuses Using 3-D Volumetric MRI: Normal Values at 19 to 37 Weeks' Gestation

Objective

The purpose of this study is to establish a reference of intracranial structure volumes in normal fetuses ranging from 19 to 37 weeks' gestation (mean 27 weeks).

Materials and Methods

A retrospective analysis of 188 MRI examinations (1.5 T) of fetuses with a normal brain appearance (19–37 gestational weeks) from January 2018 to December 2021 was included in this study. Three dimensional (3-D) volumetric parameters from slice-to-volume reconstructed (SVR) images, such as total brain volume (TBV), cortical gray matter volume (GMV), subcortical brain tissue volume (SBV), intracranial cavity volume (ICV), lateral ventricles volume (VV), cerebellum volume (CBV), brainstem volume (BM), and extra-cerebrospinal fluid volume (e-CSFV), were quantified by manual segmentation from two experts. The mean, SD, minimum, maximum, median, and 25th and 75th quartiles for intracranial structures volume were calculated per gestational week. A linear regression analysis was used to determine the gestational weekly age-related change adjusted for sex. A t-test was used to compare the mean TBV and ICV values to previously reported values at each gestational week. The formulas to calculate intracranial structures volume derived from our data were created using a regression model. In addition, we compared the predicted mean TBV values derived by our formula with the expected mean TBV predicted by the previously reported Jarvis' formula at each time point. For intracranial volumes, the intraclass correlation coefficient (ICC) was calculated to convey association within and between observers.

Results

The intracranial volume data are shown in graphs and tabular summaries. The male fetuses had significantly larger VV compared with female fetuses (p = 0.01). Measured mean ICV values at 19 weeks are significantly different from those published in the literature (p &lt; 0.05). Means were compared with the expected TBV generated by the previously reported formula, showing statistically differences at 22, 26, 29, and 30 weeks' gestational age (GA) (all p &lt; 0.05). A comparison between our data-derived formula and the previously reported formula for TBV showed very similar values at every GA. The predicted TBV means derived from the previously reported formula were all within the 95% confidence interval (CI) of the predicted means of this study. Intra- and inter-observer agreement was high, with an intraclass correlation coefficient larger than 0.98.

Conclusion

We have shown that the intracranial structural volume of the fetal brain can be reliably quantified using 3-D volumetric MRI with a high degree of reproducibility and reinforces the existing data with more robust data in the earlier second and third stages of pregnancy.

Normal Growth, Sexual Dimorphism, and Lateral Asymmetries at Fetal Brain MRI

Background Tools in image reconstruction, motion correction, and segmentation have enabled the accurate volumetric characterization of fetal brain growth at MRI. Purpose To evaluate the volumetric growth of intracranial structures in healthy fetuses, accounting for gestational age (GA), sex, and laterality with use of a spatiotemporal MRI atlas of fetal brain development. Materials and Methods T2-weighted 3.0-T half-Fourier acquired single-shot turbo spin-echo sequence MRI was performed in healthy fetuses from prospectively recruited pregnant volunteers from March 2013 to May 2019. A previously validated section-to-volume reconstruction algorithm was used to generate intensity-normalized superresolution three-dimensional volumes that were registered to a fetal brain MRI atlas with 28 anatomic regions of interest. Atlas-based segmentation was performed and manually refined. Labels included the bilateral hippocampus, amygdala, caudate nucleus, lentiform nucleus, thalamus, lateral ventricle, cerebellum, cortical plate, hemispheric white matter, internal capsule, ganglionic eminence, ventricular zone, corpus callosum, brainstem, hippocampal commissure, and extra-axial cerebrospinal fluid. For fetuses younger than 31 weeks of GA, the subplate and intermediate zones were delineated. A linear regression analysis was used to determine weekly age-related change adjusted for sex and laterality. Results The final analytic sample consisted of 122 MRI scans in 98 fetuses (mean GA, 29 weeks ± 5 [range, 20-38 weeks]). All structures had significant volume growth with increasing GA (P < .001). Weekly age-related change for individual structures in the brain parenchyma ranged from 2.0% (95% CI: 0.9, 3.1; P < .001) in the hippocampal commissure to 19.4% (95% CI: 18.7, 20.1; P < .001) in the cerebellum. The largest sex-related differences were 22.1% higher volume in male fetuses for the lateral ventricles (95% CI: 10.9, 34.4; P < .001). There was rightward volumetric asymmetry of 15.6% for the hippocampus (95% CI: 14.2, 17.2; P < .001) and leftward volumetric asymmetry of 8.1% for the lateral ventricles (95% CI: 3.7, 12.2; P < .001). Conclusion With use of a spatiotemporal MRI atlas, volumetric growth of the fetal brain showed complex trajectories dependent on structure, gestational age, sex, and laterality. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Rollins in this issue.

Clinical Applications of Fetal MRI in the Brain

Fetal magnetic resonance imaging (MRI) has become a widely used tool in clinical practice, providing increased accuracy in prenatal diagnoses of congenital abnormalities of the brain, allowing for more accurate prenatal counseling, optimization of perinatal management, and in some cases fetal intervention. In this article, a brief description of how fetal ultrasound (US) and fetal MRI are used in clinical practice will be followed by an overview of the most common reasons for referral for fetal MRI of the brain, including ventriculomegaly, absence of the cavum septi pellucidi (CSP) and posterior fossa anomalies.

Reference ranges for fetal brain structures using magnetic resonance imaging: systematic review

OBJECTIVE

To evaluate the methodology of studies reporting reference ranges for fetal brain structures on magnetic resonance imaging (MRI).

METHODS

MEDLINE, EMBASE, CINAHL and the Web of Science databases were searched electronically up to 31 December 2020 to identify studies investigating biometry and growth of the fetal brain and reporting reference ranges for brain structures using MRI. The primary aim was to evaluate the methodology of these studies. A list of 26 quality criteria divided into three domains, including 'study design', 'statistical and reporting methods' and 'specific aspects relevant to MRI', was developed and applied to evaluate the methodological appropriateness of each of the included studies. The overall quality score of a study, ranging between 0 and 26, was defined as the sum of scores awarded for each quality criterion and expressed as a percentage (the lower the percentage, the higher the risk of bias).

RESULTS

Fifteen studies were included in this systematic review. The overall mean quality score of the studies evaluated was 48.7%. When focusing on each domain, the mean quality score was 42.0% for 'study design', 59.4% for 'statistical and reporting methods' and 33.3% for 'specific aspects relevant to MRI'. For the 'study design' domain, sample size calculation and consecutive enrolment of women were the items found to be at the highest risk of bias. For the 'statistical and reporting methods' domain, the presence of regression equations for mean and SD for each measurement, the number of measurements taken for each variable and the presence of postnatal assessment information were the items found to be at the highest risk of bias. For the 'specific aspects relevant to MRI' domain, whole fetal brain assessment was not performed in any of the included studies and was therefore considered to be the item at the highest risk of bias.

CONCLUSIONS

Most of the previously published studies reporting fetal brain reference ranges on MRI are highly heterogeneous and have low-to-moderate quality in terms of methodology, which is similar to the findings reported for ultrasound studies. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Reference biometry of foetal brain by prenatal MRI and the distribution of measurements in foetuses with ventricular septal defect

OBJECTIVE

To provide the reference biometric measurements of the normal foetal brain by prenatal MRI and describe the distribution of measurements in the foetuses with ventricular septal defect (VSD).

METHODS

This retrospective study analysed the biometric measurements of 218 foetuses between 18 - 37 gestational weeks with normal MRI findings from July 2014 to August 2019, as well as 18 foetuses with VSD. The measurements included fronto-occipital diameter (FOD), biparietal diameter (BPD), and transverse cerebellar diameter (TCD). All the prenatal MRI examinations have been taken on the same 1.5 T MR unit with a standard protocol of the foetal brain. All the linear measurements of the foetal brain were obtained on the T2-weighted imaging. The distribution of measurements in 18 foetuses with VSD was plotted on centile curves.

RESULTS

The reference data were presented in mean, standard deviation, 95% predicted confidence intervals, and the 3rd, 10th, 25th, 50th, 75th, 90th, 97th centiles at each gestational age. The value of TCD in 56% (10/18 cases) foetuses with VSD was lower than the 3rd centile, and the rate for FOD and BPD was 33% (6/18 cases) and 22% (4/18 cases) separately. On the curves, most VSD cases with measurements lower than the 3rd centile were in relatively early gestational stage (≤28 weeks).

CONCLUSIONS

We have presented reference linear biometry of the foetal brain by prenatal MRI from 18 to 37 gestational weeks, which could help us to interpret and monitor the brain development for foetuses with VSD and other congenital heart diseases.Key messages:We have presented reference linear biometry of the foetal brain by prenatal MRI from 18 to 37 gestational weeks in multiple statistical methods: mean and standard deviation; 95% predicted confidence intervals and the 3rd, 10th, 25th, 50th, 75th, 90th, 97th centiles.Our data showed that the involvement of the brain in VSD may be not globally, but regionally, and the cerebellum may be more possible to be involved.We speculated that the earlier the VSD diagnosed the worse the brain involved, which might suggest a poor outcome and necessary follow-up.

Single-Input Multi-Output U-Net for Automated 2D Foetal Brain Segmentation of MR Images

In this work, we develop the Single-Input Multi-Output U-Net (SIMOU-Net), a hybrid network for foetal brain segmentation inspired by the original U-Net fused with the holistically nested edge detection (HED) network. The SIMOU-Net is similar to the original U-Net but it has a deeper architecture and takes account of the features extracted from each side output. It acts similar to an ensemble neural network, however, instead of averaging the outputs from several independently trained models, which is computationally expensive, our approach combines outputs from a single network to reduce the variance of predications and generalization errors. Experimental results using 200 normal foetal brains consisting of over 11,500 2D images produced Dice and Jaccard coefficients of 94.2 ± 5.9% and 88.7 ± 6.9%, respectively. We further tested the proposed network on 54 abnormal cases (over 3500 images) and achieved Dice and Jaccard coefficients of 91.2 ± 6.8% and 85.7 ± 6.6%, respectively.

An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset

It is critical to quantitatively analyse the developing human fetal brain in order to fully understand neurodevelopment in both normal fetuses and those with congenital disorders. To facilitate this analysis, automatic multi-tissue fetal brain segmentation algorithms are needed, which in turn requires open datasets of segmented fetal brains. Here we introduce a publicly available dataset of 50 manually segmented pathological and non-pathological fetal magnetic resonance brain volume reconstructions across a range of gestational ages (20 to 33 weeks) into 7 different tissue categories (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, deep grey matter, brainstem/spinal cord). In addition, we quantitatively evaluate the accuracy of several automatic multi-tissue segmentation algorithms of the developing human fetal brain. Four research groups participated, submitting a total of 10 algorithms, demonstrating the benefits the dataset for the development of automatic algorithms.

Ontogenetic and in silico models of spatial-packing in the hypermuscular mouse skull

Networks linking single genes to multiple phenotypic outcomes can be founded on local anatomical interactions as well as on systemic factors like biochemical products. Here we explore the effects of such interactions by investigating the competing spatial demands of brain and masticatory muscle growth within the hypermuscular myostatin-deficient mouse model and in computational simulations. Mice that lacked both copies of the myostatin gene (-/-) and display gross hypermuscularity, and control mice that had both copies of the myostatin gene (+/+) were sampled at 1, 7, 14 and 28 postnatal days. A total of 48 mice were imaged with standard as well as contrast-enhanced microCT. Size metrics and landmark configurations were collected from the image data and were analysed alongside in silico models of tissue expansion. Findings revealed that: masseter muscle volume was smaller in -/- mice at day 1 but became, and remained thereafter, larger by 7 days; -/- endocranial volumes begin and remained smaller; -/- enlargement of the masticatory muscles was associated with caudolateral displacement of the calvarium, lateral displacement of the zygomatic arches, and slight dorsal deflection of the face and basicranium. Simulations revealed basicranial retroflexion (flattening) and dorsal deflection of the face associated with muscle expansion and abrogative covariations of basicranial flexion and ventral facial deflection associated with endocranial expansion. Our findings support the spatial-packing theory and highlight the importance of understanding the harmony of competing spatial demands that can shape and maintain mammalian skull architecture during ontogeny.

Normative linear and volumetric biometric measurements of fetal brain development in magnetic resonance imaging

PURPOSE

To provide normative two-dimensional and three-dimensional measurements of brain development in normal fetuses during the second and third trimester by a new semi-automated method.

METHODS

In this retrospective study, we included 98 normal fetuses at our institution between 21 and 38 weeks of gestation. Two-dimensional measurements of the brain were including biparietal diameter, occipitofrontal diameter, head circumference, transverse cerebellar diameter, and atrial diameter. Volumetric parameters were obtained by using ITK-SNAP software, including left and right cerebral hemispheres, lateral ventricle, the cerebellum, and extracerebral cerebrospinal fluid.

RESULTS

All linear and volume measurements were positively correlated with gestational age except for cerebrospinal fluid. Each anatomical region of the fetal brain showed a different relative growth rate. There was some volume asymmetry between the left and right lateral ventricles, and the left side was larger. The inter-observer and intra-observer agreement was excellent for all measures.

CONCLUSION

We established the 5th, 50th, and 95th percentile values of fetal brain volume measurements in magnetic resonance, and this may be helpful to understand the damage of fetal brain development.

Association of gestational age with MRI-based biometrics of brain development in fetuses

Background

Reported date of last menstrual period and ultrasonography measurements are the most commonly used methods for determining gestational age in antenatal life. However, the mother cannot always determine the last menstrual period with certainty, and ultrasonography measurements are accurate only in the first trimester. We aimed to assess the ability of various biometric measurements on magnetic resonance imaging (MRI) in determining the accurate gestational age of an individual fetus in the second half of gestation.

Methods

We used MRI to scan a total of 637 fetuses ranging in age from 22 to 40 gestational weeks. We evaluated 9 standard fetal 2D biometric parameters, and regression models were fitted to assess normal fetal brain development. A stepwise linear regression model was constructed to predict gestational age, and measurement accuracy was determined in a held-out, unseen test sample (n = 49).

Results

A second-order polynomial regression model was found to be the best descriptor of biometric measures including brain bi-parietal diameter, head circumference, and fronto-occipital diameter in relation to normal fetal growth. Normal fetuses showed divergent growth patterns for the cerebrum and cerebellum, where the cerebrum undergoes rapid growth in the second trimester, while the cerebellum undergoes rapid growth in the third trimester. Moreover, a linear model based on biometrics of brain bi-parietal diameter, length of the corpus callosum, vermis area, transverse cerebellar diameter, and cerebellar area accurately predicted gestational age in the second and third trimesters (cross-validation R² = 0.822, p < 0.001).

Conclusions

These results support the use of MRI biometry charts to improve MRI evaluation of fetal growth and suggest that MRI biometry measurements offer a potential estimation model of fetal gestational age in the second half of gestation, which is vital to any assessment of pregnancy, fetal development, and neonatal care.

Normal appearances and dimensions of the foetal cavum septi pellucidi and vergae on in utero MR imaging

Purpose

The aim of this study is to provide normative data about the appearances and dimensions of the cavum septi pellucidi and vergae (CSPV) on in utero MR (iuMR) imaging in second and third trimester foetuses.

Methods

Two hundred normal foetuses (from a low-risk pregnancy, with normal ante-natal USS findings and no intracranial abnormality of iuMR) had iuMR imaging between 18 and 37 gestational weeks (gw). The anatomical features on those studies were compared with published atlases of post-mortem foetal brains. The length, width and volume of the CSPV were measured in all foetuses.

Results

The anatomy of the CSPV and its relationship with the corpus callosum and the fornices on iuMR imaging was comparable with post-mortem data at all gestational ages studied. The length of the CSPV increased throughout pregnancy, whereas the width and volume of CSPV reached a maximum between 29 and 31 gw and then showed a reduction later in pregnancy.

Conclusion

The iuMR imaging features of the CSPV and its close anatomical relations closely correspond to post-mortem data. The CSPV was patent in all cases but we have shown that closure commences in the midpart of the third trimester and advances in a posterior to anterior direction.

Electronic supplementary material

The online version of this article (10.1007/s00234-020-02364-5) contains supplementary material, which is available to authorized users.

An integrated in utero MR method for assessing structural brain abnormalities and measuring intracranial volumes in fetuses with congenital heart disease: results of a prospective case-control feasibility study

Purpose

To refine methods that assess structural brain abnormalities and calculate intracranial volumes in fetuses with congenital heart diseases (CHD) using in utero MR (iuMR) imaging. Our secondary objective was to assess the prevalence of brain abnormalities in this high-risk cohort and compare the brain volumes with normative values.

Methods

We performed iuMR on 16 pregnant women carrying a fetus with CHD and gestational age ≥ 28-week gestation and no brain abnormality on ultrasonography. All cases had fetal echocardiography by a pediatric cardiologist. Structural brain abnormalities on iuMR were recorded. Intracranial volumes were made from 3D FIESTA acquisitions following manual segmentation and the use of 3D Slicer software and were compared with normal fetuses. Z scores were calculated, and regression analyses were performed to look for differences between the normal and CHD fetuses.

Results

Successful 2D and 3D volume imaging was obtained in all 16 cases within a 30-min scan. Despite normal ultrasonography, 5/16 fetuses (31%) had structural brain abnormalities detected by iuMR (3 with ventriculomegaly, 2 with vermian hypoplasia). Brain volume, extra-axial volume, and total intracranial volume were statistically significantly reduced, while ventricular volumes were increased in the CHD cohort.

Conclusion

We have shown that it is possible to perform detailed 2D and 3D studies using iuMR that allow thorough investigation of all intracranial compartments in fetuses with CHD in a clinically appropriate scan time. Those fetuses have a high risk of structural brain abnormalities and smaller brain volumes even when brain ultrasonography is normal.