Neurodevelopmental Correlates of Fetal Motor Behavior Assessed Using Cine MR Imaging

Computation of Fetal Kicking in Various Fetal Health Examinations: A Systematic Review

Fetal movement has always been considered an essential indicator to evaluate the health of the unborn fetus. Many factors affect fetal movement. The frequency of fetal kicking is an important measurement of whether fetal development is progressing and healthy. Various instruments and methods of detecting fetal movement have been used and each method has its advantages and disadvantages. Although limited by the fetal environment in utero, the finite element method and musculoskeletal model can be used to calculate fetal lower limb movement. This review aims to summarize the current detection techniques for fetal movement, especially in the lower limbs. These will be outlined by describing the different measurements of fetal movement, and the related biomechanical analyses of fetal lower limb skeletogenesis and the associated muscular development to better evaluate and calculate the movements of the fetus in the womb.

Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging

Fetal magnetic resonance imaging (MRI) is challenged by uncontrollable, large, and irregular fetal movements. It is, therefore, performed through visual monitoring of fetal motion and repeated acquisitions to ensure diagnostic-quality images are acquired. Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level of stacks-of-slices is inefficient. The current process is highly operator-dependent, increases scanner usage and cost, and significantly increases the length of fetal MRI scans which makes them hard to tolerate for pregnant women. To help build automatic MRI motion tracking and navigation systems to overcome the limitations of the current process and improve fetal imaging, we have developed a new real-time image-based motion tracking method based on deep learning that learns to predict fetal motion directly from acquired images. Our method is based on a recurrent neural network, composed of spatial and temporal encoder-decoders, that infers motion parameters from anatomical features extracted from sequences of acquired slices. We compared our trained network on held-out test sets (including data with different characteristics, e.g. different fetuses scanned at different ages, and motion trajectories recorded from volunteer subjects) with networks designed for estimation as well as methods adopted to make predictions. The results show that our method outperformed alternative techniques, and achieved real-time performance with average errors of 3.5 and 8 degrees for the estimation and prediction tasks, respectively. Our real-time deep predictive motion tracking technique can be used to assess fetal movements, to guide slice acquisitions, and to build navigation systems for fetal MRI.

Sonographic Detection of Seizure-Like Activity in Fetuses with Congenital Infection: Report of Three Cases and Review of the Literature

Fetal seizure is a very rare prenatal finding and associated with an almost invariably poor outcome, the most common causes being hypoxic-ischemic encephalopathy, congenital anomalies of either the central nervous system (CNS) or musculoskeletal system, and metabolic disorders. The prenatal detection of seizure-like activity in fetuses with congenital infection has not been previously reported. In this report, we describe 3 cases of seizures in fetuses with congenital infection including Zika virus (n = 2) and toxoplasmosis (n = 1). All 3 fetuses had associated CNS abnormalities and the perinatal outcome was uniformly poor. This report suggests that for fetuses with proven congenital infections an extended and targeted sonographic examination may be helpful in -detecting associated fetal seizures that may even worsen the neonatal outcome.

Neuroimaging perspectives on fetal motor behavior

We are entering a new era of understanding human development with the ability to perform studies at the earliest time points possible. There is a substantial body of evidence to support the concept that early motor behaviour originates from supraspinal motor centres, reflects neurological integrity, and that altered patterns of behaviour precede clinical manifestation of disease. Cine Magnetic Resonance Imaging (cineMRI) has established its value as a novel method to visualise motor behaviour in the human fetus, building on the wealth of knowledge gleaned from ultrasound based studies. This paper presents a state of the art review incorporating findings from human and preclinical models, the insights from which, we propose, can proceed a reconceptualisation of fetal motor behaviour using advanced imaging techniques. Foremost is the need to better understand the role of the intrauterine environment, and its inherent unique set of stimuli that activate sensorimotor pathways and shape early brain development. Finally, an improved model of early motor development, combined with multimodal imaging, will provide a novel source of in utero biomarkers predictive of neurodevelopmental disorders.