Functional assessment of brain development in fetuses that subsequently deliver very preterm: An MRI pilot study

OBJECTIVES

To evaluate changes occurring in the fetal brain prior to very preterm delivery using MRI T2* relaxometry, an indirect assessment of tissue perfusion.

METHOD

Fetuses that subsequently delivered spontaneously <32 weeks gestation and a control cohort were identified from pre-existing datasets. Participants had undergone a 3T MRI assessment including T2* relaxometry of the fetal brain using a 2D multi-slice gradient echo single shot echo planar imaging sequence. T2* maps were generated, supratentorial brain tissue was manually segmented and mean T2* values were generated. Groups were compared using quadratic regression.

RESULTS

Twenty five fetuses that subsequently delivered <32 weeks and 67 that delivered at term were included. Mean gestation at MRI was 24.5 weeks (SD 3.3) and 25.4 weeks (SD 3.1) and gestation at delivery 25.5 weeks (SD 3.4) and 39.7 weeks (SD 1.2) in the preterm and term cohorts respectively. Brain mean T2* values were significantly lower in fetuses that subsequently delivered before 32 weeks gestation (p < 0.001).

CONCLUSION

Alterations in brain maturation appear to occur prior to preterm delivery. Further work is required to explore these associations, but these findings suggest a potential window for therapeutic neuroprotective agents in fetuses at high risk of preterm delivery in the future.

Fast fetal head compounding from multi-view 3D ultrasound

The diagnostic value of ultrasound images may be limited by the presence of artefacts, notably acoustic shadows, lack of contrast and localised signal dropout. Some of these artefacts are dependent on probe orientation and scan technique, with each image giving a distinct, partial view of the imaged anatomy. In this work, we propose a novel method to fuse the partially imaged fetal head anatomy, acquired from numerous views, into a single coherent 3D volume of the full anatomy. Firstly, a stream of freehand 3D US images is acquired using a single probe, capturing as many different views of the head as possible. The imaged anatomy at each time-point is then independently aligned to a canonical pose using a recurrent spatial transformer network, making our approach robust to fast fetal and probe motion. Secondly, images are fused by averaging only the most consistent and salient features from all images, producing a more detailed compounding, while minimising artefacts. We evaluated our method quantitatively and qualitatively, using image quality metrics and expert ratings, yielding state of the art performance in terms of image quality and robustness to misalignments. Being online, fast and fully automated, our method shows promise for clinical use and deployment as a real-time tool in the fetal screening clinic, where it may enable unparallelled insight into the shape and structure of the face, skull and brain.

Automated 3D reconstruction of the fetal thorax in the standard atlas space from motion-corrupted MRI stacks for 21-36 weeks GA range

Slice-to-volume registration (SVR) methods allow reconstruction of high-resolution 3D images from multiple motion-corrupted stacks. SVR-based pipelines have been increasingly used for motion correction for T2-weighted structural fetal MRI since they allow more informed and detailed diagnosis of brain and body anomalies including congenital heart defects (Lloyd et al., 2019). Recently, fully automated rigid SVR reconstruction of the fetal brain in the atlas space was achieved in Salehi et al. (2019) that used convolutional neural networks (CNNs) for segmentation and pose estimation. However, these CNN-based methods have not yet been applied to the fetal trunk region. Meanwhile, the existing rigid and deformable SVR (DSVR) solutions (Uus et al., 2020) for the fetal trunk region are limited by the requirement of manual input as well the narrow capture range of the classical gradient descent based registration methods that cannot resolve severe fetal motion frequently occurring at the early gestational age (GA). Furthermore, in our experience, the conventional 2D slice-wise CNN-based brain masking solutions are reportedly prone to errors that require manual corrections when applied on a wide range of acquisition protocols or abnormal cases in clinical setting. In this work, we propose a fully automated pipeline for reconstruction of the fetal thorax region for 21-36 weeks GA range T2-weighted MRI datasets. It includes 3D CNN-based intra-uterine localisation of the fetal trunk and landmark-guided pose estimation steps that allow automated DSVR reconstruction in the standard radiological space irrespective of the fetal trunk position or the regional stack coverage. The additional step for generation of the common template space and rejection of outliers provides the means for automated exclusion of stacks affected by low image quality or extreme motion. The pipeline was quantitatively evaluated on a series of experiments including fetal MRI datasets and simulated rotation motion. Furthermore, we performed a qualitative assessment of the image reconstruction quality in terms of the definition of vascular structures on 100 early (median 23.14 weeks) and late (median 31.79 weeks) GA group MRI datasets covering 21 to 36 weeks GA range.

Fetal MRI for dummies: what the fetal medicine specialist should know about acquisitions and sequences

Fetal MRI is an increasingly used tool in the field of prenatal diagnosis. While US remains the first line screening tool, as an adjuvant imaging tool, MRI has been proven to increase diagnostic accuracy and change patient counseling. Further, there are instances when US may not be sufficient for diagnosis. As a multidisciplinary field, it is important that every person involved in the referral, diagnosis, counseling and treatment of the patients is familiar with the basic principles, indications and findings of fetal MRI. The purpose of the current paper is to equip radiologists and non-radiologists with basic MRI principles and essential topics in patient preparation and provide illustrative examples of when fetal MRI may be used. This aims to aid the referring clinician in better selecting and improve patient counseling prior to arrival in the radiology department and, ultimately, patient care.

Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects

Fetal imaging is a burgeoning topic. New advancements in both magnetic resonance imaging and (3D) ultrasound currently allow doctors to diagnose fetal structural abnormalities such as those involved in twin-to-twin transfusion syndrome, gestational diabetes mellitus, pulmonary sequestration and hypoplasia, congenital heart disease, diaphragmatic hernia, ventriculomegaly, etc. Considering the continued breakthroughs in utero image analysis and (3D) reconstruction models, it is now possible to gain more insight into the ongoing development of the fetus. Best prenatal diagnosis performances rely on the conscious preparation of the clinicians in terms of fetal anatomy knowledge. Therefore, fetal imaging will likely span and increase its prevalence in the forthcoming years. This review covers state-of-the-art segmentation and classification methodologies for the whole fetus and, more specifically, the fetal brain, lungs, liver, heart and placenta in magnetic resonance imaging and (3D) ultrasound for the first time. Potential applications of the aforementioned methods into clinical settings are also inspected. Finally, improvements in existing approaches as well as most promising avenues to new areas of research are briefly outlined.

3D R 2 * mapping of the placenta during early gestation using free-breathing multiecho stack-of-radial MRI at 3T

BACKGROUND

Multiecho gradient-echo Cartesian MRI characterizes placental oxygenation by quantifying R 2 * . Previous research was performed at 1.5T using breath-held 2D imaging during later gestational age (GA).

PURPOSE

To evaluate the accuracy and repeatability of a free-breathing (FB) 3D multiecho gradient-echo stack-of-radial technique (radial) for placental R 2 * mapping at 3T and report placental R 2 * during early GA.

STUDY TYPE

Prospective.

POPULATION

Thirty subjects with normal pregnancies and three subjects with ischemic placental disease (IPD) were scanned twice: between 14-18 and 19-23 weeks GA.

FIELD STRENGTH

3T.

SEQUENCE

FB radial.

ASSESSMENT

Linear correlation (concordance coefficient, ρ_c ) and Bland-Altman analyses (mean difference, MD) were performed to evaluate radial R 2 * mapping accuracy compared to Cartesian in a phantom. Radial R 2 * mapping repeatability was characterized using the coefficient of repeatability (CR) between back-to-back scans. The mean and spatial coefficient of variation (CV) of R 2 * was determined for all subjects, and separately for anterior and posterior placentas, at each GA range.

STATISTICAL TESTS

ρ_c was tested for significance. Differences in mean R 2 * and CV were tested using Wilcoxon Signed-Rank and Rank-Sum tests. P < 0.05 was considered significant. Z-scores for the IPD subjects were determined.

RESULTS

FB radial demonstrated accurate (ρ_c ≥0.996; P < 0.001; |MD|<0.2s^-1 ) and repeatable (CR<4s^-1 ) R 2 * mapping in a phantom, and repeatable (CR≤4.6s^-1 ) R 2 * mapping in normal subjects. At 3T, placental R 2 * mean ± standard deviation was 12.9s^-1  ± 2.7s^-1 for 14-18 and 13.2s^-1  ± 1.9s^-1 for 19-23 weeks GA. The CV was significantly greater (P = 0.043) at 14-18 (0.63 ± 0.12) than 19-23 (0.58 ± 0.13) weeks GA. At 19-23 weeks, the CV was significantly lower (P < 0.001) for anterior (0.49 ± 0.08) than posterior (0.67 ± 0.11) placentas. One IPD subject had a lower mean R 2 * than normal subjects at both GA ranges (Z<-2).

DATA CONCLUSION

FB radial provides accurate and repeatable 3D R 2 * mapping for the entire placenta at 3T during early GA.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:291-303.