Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study

Automated Craniofacial Biometry with 3D T2w Fetal MRI

Objectives

Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated landmark propagation pipeline using 3D motion-corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements.

Methods

A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers.

Results

Automated labels were produced for all 132 subjects with a 0.03% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research.

Conclusion

This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.

Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imaging

Objective

To assess the accuracy of corpus callosum (CC) biometry, including sub-segments, using 3D super-resolution fetal brain MRI (SR) compared to 2D or 3D ultrasound (US) and clinical low-resolution T2-weighted MRI (T2WS).

Method

Fetal brain biometry was conducted by two observers on 57 subjects [21-35 weeks of gestational age (GA)], including 11 cases of partial CC agenesis. Measures were performed by a junior observer (obs1) on US, T2WS and SR and by a senior neuroradiologist (obs2) on T2WS and SR. CC biometric regression with GA was established. Statistical analysis assessed agreement within and between modalities and observers.

Results

This study shows robust SR to US concordance across gestation, surpassing T2WS. In obs1, SR aligns with US, except for genu and CC length (CCL), enhancing splenium visibility. In obs2, SR closely corresponds to US, differing in rostrum and CCL. The anterior CC (rostrum and genu) exhibits higher variability. SR's regression aligns better with literature (US) for CCL, splenium and body than T2WS. SR is the method with the least missing values.

Conclusion

SR yields CC biometry akin to US (excluding anterior CC). Thanks to superior 3D visualization and better through plane spatial resolution, SR allows to perform CC biometry more frequently than T2WS.

FetusMapV2: Enhanced fetal pose estimation in 3D ultrasound

Fetal pose estimation in 3D ultrasound (US) involves identifying a set of associated fetal anatomical landmarks. Its primary objective is to provide comprehensive information about the fetus through landmark connections, thus benefiting various critical applications, such as biometric measurements, plane localization, and fetal movement monitoring. However, accurately estimating the 3D fetal pose in US volume has several challenges, including poor image quality, limited GPU memory for tackling high dimensional data, symmetrical or ambiguous anatomical structures, and considerable variations in fetal poses. In this study, we propose a novel 3D fetal pose estimation framework (called FetusMapV2) to overcome the above challenges. Our contribution is three-fold. First, we propose a heuristic scheme that explores the complementary network structure-unconstrained and activation-unreserved GPU memory management approaches, which can enlarge the input image resolution for better results under limited GPU memory. Second, we design a novel Pair Loss to mitigate confusion caused by symmetrical and similar anatomical structures. It separates the hidden classification task from the landmark localization task and thus progressively eases model learning. Last, we propose a shape priors-based self-supervised learning by selecting the relatively stable landmarks to refine the pose online. Extensive experiments and diverse applications on a large-scale fetal US dataset including 1000 volumes with 22 landmarks per volume demonstrate that our method outperforms other strong competitors.

Effect of magnet strength on fetal brain biometry - a single-center retrospective MRI-based cohort study

PURPOSE

Abnormal fetal brain measurements might affect clinical management and parental counseling. The effect of between-field-strength differences was not evaluated in quantitative fetal brain imaging until now. Our study aimed to compare fetal brain biometry measurements in 3.0 T with 1.5 T scanners.

METHODS

A retrospective cohort of 1150 low-risk fetuses scanned between 2012 and 2021, with apparently normal brain anatomy, were retrospectively evaluated for biometric measurements. The cohort included 1.5 T (442 fetuses) and 3.0 T scans (708 fetuses) of populations with comparable characteristics in the same tertiary medical center. Manually measured biometry included bi-parietal, fronto-occipital and trans-cerebellar diameters, length of the corpus-callosum, vermis height, and width. Measurements were then converted to centiles based on previously reported biometric reference charts. The 1.5 T centiles were compared with the 3.0 T centiles.

RESULTS

No significant differences between centiles of bi-parietal diameter, trans-cerebellar diameter, or length of the corpus callosum between 1.5 T and 3.0 T scanners were found. Small absolute differences were found in the vermis height, with higher centiles in the 3.0 T, compared to the 1.5 T scanner (54.6th-centile, vs. 39.0th-centile, p < 0.001); less significant differences were found in vermis width centiles (46.9th-centile vs. 37.5th-centile, p = 0.03). Fronto-occipital diameter was higher in 1.5 T than in the 3.0 T scanner (66.0th-centile vs. 61.8th-centile, p = 0.02).

CONCLUSIONS

The increasing use of 3.0 T MRI for fetal imaging poses a potential bias when using 1.5 T-based charts. We elucidate those biometric measurements are comparable, with relatively small between-field-strength differences, when using manual biometric measurements. Small inter-magnet differences can be related to higher spatial resolution with 3 T scanners and may be substantial when evaluating small brain structures, such as the vermis.

Onset of Chiari type 1 malformation: insights from a small series of intrauterine MR imaging cases

PURPOSE

Morphometric studies on idiopathic Chiari malformation type 1 (CM1) pathogenesis have been mainly based on post-natal neuroimaging. Prenatal clues related to CM1 development are lacking. We present pre- and post-natal imaging time course in idiopathic CM1 and assess fetal skull and brain biometry to establish if clues about CM1 development are present at fetal age.

METHODS

Multicenter databases were screened to retrieve intrauterine magnetic resonance (iuMR) of children presenting CM1 features at post-natal scan. Syndromes interfering with skull-brain growth were excluded. Twenty-two morphometric parameters were measured at fetal (average 24.4 weeks; range 21 to 32) and post-natal (average 15.4 months; range 1 to 45) age; matched controls were included.

RESULTS

Among 7000 iuMR cases, post-natal scans were available for 925, with postnatal CM1 features reported in seven. None of the fetuses presented CM1 features. Tonsillar descent was clear at a later post-natal scan in all seven cases. Six fetal parameters resulted to be statistically different between CM1 and controls: basal angle (p = 0.006), clivo-supraoccipital angle (p = 0.044), clivus' length (p = 0.043), posterior cranial fossa (PCF) width (p = 0.009), PCF height (p = 0.045), and PCFw/BPDb (p = 0.013). Postnatally, only the clivus' length was significant between CM1 cases and controls.

CONCLUSION

Pre- and post-natal CM1 cases did not share striking common features, making qualitative prenatal assessment not predictive; however, our preliminary results support the view that some of the pathogenetic basis of CM1 may be embedded to some extent already in intrauterine life.

Retrospective motion correction in foetal MRI for clinical applications: existing methods, applications and integration into clinical practice

Foetal MRI is a complementary imaging method to antenatal ultrasound. It provides advanced information for detection and characterisation of foetal brain and body anomalies. Even though modern single shot sequences allow fast acquisition of 2D slices with high in-plane image quality, foetal MRI is intrinsically corrupted by motion. Foetal motion leads to loss of structural continuity and corrupted 3D volumetric information in stacks of slices. Furthermore, the arbitrary and constantly changing position of the foetus requires dynamic readjustment of acquisition planes during scanning.

Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester

Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.

A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN)

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.

Developmental Brain Asymmetry. The Good and the Bad Sides

Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.