Background

Neonatal neurocritical care is a growing and rapidly evolving medical subspecialty, with increasing numbers of dedicated multidisciplinary clinical, educational, and research programs established at academic institutions. The growth of these programs has provided trainees in neurology, neonatology, and pediatrics with increased exposure to the field, sparking interest in dedicated fellowship training in fetal-neonatal neurology.

Objectives

To meet this rising demand, increasing numbers of training programs are being established to provide trainees with the requisite knowledge and skills to independently deliver care for infants with neurological injury or impairment from the fetal care center and neonatal intensive care unit to the outpatient clinic. This article provides an initial framework for standardization of training across these programs.

Results

Recommendations include goals and objectives for training in the field; core areas where clinical competency must be demonstrated; training activities and neuroimaging and neurodiagnostic modalities which require proficiency; and programmatic requirements necessary to support a comprehensive and well-rounded training program.

Conclusions

With consistent implementation, the proposed model has the potential to establish recognized standards of professional excellence for training in the field, provide a pathway toward Accreditation Council for Graduate Medical Education certification for program graduates, and lead to continued improvements in medical and neurological care provided to patients in the neonatal intensive care unit.

Neuroimaging is widely used to aid in the diagnosis and clinical management of neonates with neonatal encephalopathy (NE). Yet, despite widespread use clinically, there are few published guidelines on neuroimaging for neonates with NE. This review outlines the primary patterns of brain injury associated with hypoxic-ischemic injury in neonates with NE and their frequency, associated neuropathological features, and risk factors. In addition, it provides an overview of neuroimaging methods, including the most widely used scoring systems used to characterize brain injury in these neonates and their utility as predictive biomarkers. Last, recommendations for neuroimaging in neonates with NE are presented.

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

Motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down the precentral gyrus from foot to face representations^1,2, despite evidence for concentric functional zones³ and maps of complex actions⁴. Here, using precision functional magnetic resonance imaging (fMRI) methods, we find that the classic homunculus is interrupted by regions with distinct connectivity, structure and function, alternating with effector-specific (foot, hand and mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, as well as to the cingulo-opercular network (CON), critical for action⁵ and physiological control⁶, arousal⁷, errors⁸ and pain⁹. This interdigitation of action control-linked and motor effector regions was verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant and child) precision fMRI suggested cross-species homologues and developmental precursors of the inter-effector system. A battery of motor and action fMRI tasks documented concentric effector somatotopies, separated by the CON-linked inter-effector regions. The inter-effectors lacked movement specificity and co-activated during action planning (coordination of hands and feet) and axial body movement (such as of the abdomen or eyebrows). These results, together with previous studies demonstrating stimulation-evoked complex actions⁴ and connectivity to internal organs¹⁰ such as the adrenal medulla, suggest that M1 is punctuated by a system for whole-body action planning, the somato-cognitive action network (SCAN). In M1, two parallel systems intertwine, forming an integrate-isolate pattern: effector-specific regions (foot, hand and mouth) for isolating fine motor control and the SCAN for integrating goals, physiology and body movement.