publications

2022

1. Impact of COVID-19 Related Maternal Stress on Fetal Brain Development: A Multimodal MRI Study

   Vidya Rajagopalan, William T. Reynolds, Jeremy Zepeda, and 5 more authors

   Journal of Clinical Medicine 2022, Vol. 11, Page 6635 Nov 2022

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   Background: Disruptions in perinatal care and support due to the COVID-19 pandemic was an unprecedented but significant stressor among pregnant women. Various neurostructural differences have been re-ported among fetuses and infants born during the pandemic compared to pre-pandemic counterparts. The relationship between maternal stress due to pandemic related disruptions and fetal brain is yet unexamined. Increased maternal perception of pandemic related stress positively correlated with normalized fetal brainstem volume (suggesting accelerated brainstem maturation). In contrast, increased maternal perception of pandemic related stress correlated with reduced global fetal brain temporal functional variance (suggesting reduced functional connectivity). Conclusions: We report alterations in fetal brainstem structure and global functional fetal brain activity associated with increased maternal stress due to pandemic related disruptions, suggesting altered fetal programming. Long term follow-up studies are required to better understand the sequalae of these early multi-modal brain disruptions among infants born during the COVID-19 pandemic.

2. Clinical factors associated with microstructural connectome related brain dysmaturation in term neonates with congenital heart disease

   Jodie K. Votava-Smith, Jenna Gaesser, Anna Lonyai Harbison, and 16 more authors

   Frontiers in Neuroscience Nov 2022

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   Objective: Term congenital heart disease (CHD) neonates display abnormalities of brain structure and maturation, which are possibly related to underlying patient factors and perioperative insults. Our primary goal was to delineate associations between clinical factors and postnatal brain microstructure in term CHD neonates using diffusion tensor imaging (DTI) magnetic resonance (MR) acquisition combined with complementary data-driven connectome and seed-based tractography quantitative analysis. Our secondary goal was to delineate associations between mild dysplastic structural abnormalities and connectome and seed-base tractography as our primary goal. A total of 133 term neonates with complex CHD were prospectively enrolled and 110 had analyzable DTI. Multiple patient-specific factors including d-transposition of the great arteries physiology and severity of impairment of fetal cerebral substrate delivery were predictive of preoperative reduced cost (p<0.0073), reduced global/nodal efficiency (p <0.03). Multiple postoperative factors (extracorporeal membrane oxygenation [ECMO], seizures, cardiopulmonary resuscitation) were predictive of postoperative reduced cost, reduced global/nodal efficiency (p < 0.05). All three subcortical structures of the BDS (including olfactory bulb/sulcus, cerebellum, and hippocampus) predicted distinct patterns of altered nodal efficiency (p<0.05). Conclusion: Patient-specific and postoperative clinical factors were most predictive of diffuse postnatal microstructural dysmaturation in term CHD neonates. In contrast, subcortical components of a structurally based- brain dysplasia score, predicted more regional based postnatal microstructural differences. Collectively, these findings suggest that brain DTI connectome may facilitate deciphering the mechanistic relative contribution of clinical and genetic risk factors related to poor neurodevelopmental outcomes in CHD.

3. Reduced Cerebellar Volume in Term Infants with Complex Congenital Heart Disease: Correlation with Postnatal Growth Measurements

   Rafael Ceschin, Alexandria Zahner, William Reynolds, and 2 more authors

   Diagnostics 2022, Vol. 12, Page 1644 Jul 2022

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   Aberrant cerebellar development and the associated neurocognitive deficits has been postulated in infants with congenital heart disease (CHD). Our objective is to investigate the effect of postnatal head and somatic growth on cerebellar development in neonates with CHD. We compared term-born neonates with a history of CHD with a cohort of preterm-born neonates, two cohorts at similar risk for neurodevelopment impairment, in order to determine if they are similarly affected in the early developmental period. Study Design: 51 preterms-born healthy neonates, 62 term-born CHD neonates, and 54 term-born healthy neonates underwent a brain MRI with volumetric imaging. Cerebellar volumes were extracted through an automated segmentation pipeline that was developed in-house. Volumes were correlated with clinical growth parameters at both the birth and time of MRI. Results: The CHD cohort showed significantly lower cerebellar volumes when compared with both the control (p < 0.015) and preterm (p < 0.004) groups. Change in weight from birth to time of MRI showed a moderately strong correlation with cerebellar volume at time of MRI (r = 0.437, p < 0.002) in the preterms, but not in the CHD neonates (r = 0.205, p < 0.116). Changes in birth length and head circumference showed no significant correlation with cerebellar volume at time of MRI in either cohort. Conclusions: Cerebellar development in premature-born infants is associated with change in birth weight in the early post-natal period. This association is not observed in term-born neonates with CHD, suggesting differential mechanisms of aberrant cerebellar development in these perinatal at-risk populations.

4. Associations Between Maternal Risk Factors and Intrinsic Placental and Fetal Brain Functional Properties in Congenital Heart Disease

   Vidya Rajagopalan, Vanessa Schmithorst, Alex El-Ali, and 8 more authors

   medRxiv Sep 2022

   Abs

   Background The relationship between maternal risk factors (MRFs) (particularly pre-gravid obesity, diabetes, and hypertension) and congenital heart disease (CHD) to placental and fetal brain outcomes is poorly understood. Here, we tested the hypothesis that MRF and CHD would be associated with reduced intrinsic placental and fetal brain function using a novel non-invasive technique.MRF and CHD reduced functional characteristic of placenta and brain in fetuses. MRF modification and management during pregnancy may have the potential to not only provide additional risk stratification but may also improve neurodevelopmental outcomes.

2020

2018

1. A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks

   Rafael Ceschin, Alexandria Zahner, William Reynolds, and 5 more authors

   NeuroImage Sep 2018

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   Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsu- pervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuroimaging datasets requires adequate sample size for training and well-defined signal intensity based structural differentiation. There is a lack of effective automated diagnostic tools for the reliable detection of brain dysmaturation in the neonatal period, related to small sample size and complex undifferenti- ated brain structures, despite both translational research and clinical importance. Volumetric information alone is insufficient for diagnosis. In this study, we developed a computational framework for the automated classification of brain dysmaturation from neonatal MRI, by combining a specific deep neural network implementation with neonatal structural brain segmentation as a method for both clinical pattern recognition and data-driven inference into the underlying structural morphology. We implemented three-dimensional convolution neural networks (3D- CNNs) to specifically classify dysplastic cerebelli, a subset of surface-based subcortical brain dysmaturation, in term infants born with congenital heart disease. We obtained a 0.985 ? 0. 0241-classification accuracy of subtle cerebellar dysplasia in CHD using 10-fold cross-validation. Furthermore, the hidden layer activations and class activation maps depicted regional vulnerability of the superior surface of the cerebellum, (composed of mostly the posterior lobe and the midline vermis), in regards to differentiating the dysplastic process from normal tissue. The posterior lobe and the midline vermis provide regional differentiation that is relevant to not only to the clinical diagnosis of cerebellar dysplasia, but also genetic mechanisms and neurodevelopmental outcome correlates. These findings not only contribute to the detection and classification of a subset of neonatal brain dysmaturation, but also provide insight to the pathogenesis of cerebellar dysplasia in CHD. In addition, this is one of the first examples of the application of deep learning to a neuroimaging dataset, in which the hidden layer activation revealed diagnostically and biologically relevant features about the clinical pathogenesis. The code developed for this project is open source, published under the BSD License, and designed to be generalizable to applications both within and beyond neonatal brain imaging. Introduction

2. Macroscopic Hyperdynamic CSF and Ciliary Motion Dysfunction Predict Executive Dysfunction in Children and Adolescents with Congenital Heart Disease [abstract]

   Vincent Kyu Lee, Rebecca Hartog, William T Reynolds, and 7 more authors

   Sep 2018

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   An important role for cilia in congenital heart disease (CHD) pathogenesis has been seen in mouse model of CHD. There is a high prevalence of motile respiratory cilia dysfunction in human CHD patients. In this study, we investigate whether abnormal respiratory cilia motion in preadolescent CHD patients may be correlated with alterations in macroscopic CSF flow dynamics and poor executive cognitive function using phase contrast imaging. We show disturbance of CSF flow dynamics is significantly correlated with neurocognitive impairment in CHD subjects.

3. Characterization of Neurodevelopmental Defects Associated with a Mouse Model of Hypoplastic Left Heart Syndrome [abstract]

   George C Gabriel, Nathan Salamacha, William T Reynolds, and 8 more authors

   Sep 2018

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   Introduction Hypoplastic left heart syndrome (HLHS), a congenital heart defect involving left-sided heart structures, is associated with poor neurodevelopmental outcome, with >30% of survivors experiencing neurodevelopmental impairment. A mouse model of HLHS showed brain abnormalities, suggesting a shared genetic etiology for brain and cardiac defects in HLHS.

2016

1. Micro-computed Tomography Provides High Accuracy Congenital Heart Disease Diagnosis in Neonatal and Fetal Mice [poster presentation]

   William T Reynolds, Andrew J Kim, Molly Schwartz, and 5 more authors

   Sep 2016

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   Micro-computed tomography (micro-CT) has been optimized using iodine contrast agents to visualize soft tissue such as fine details of the cardiovascular anatomy for congenital heart defect diagnosis. While we previously showed the efficacy of micro-CT imaging for congenital heart defects, the diagnostic capabilities of micro-CT for non-cardiac structural birth defects (SBD) has not been examined. Therefore in this study, we assessed the efficacy of which SBDs can be detected using micro-CT imaging. N-ethyl-N-nitrosourea (ENU) mutagenized mice were formalin-fixed and stained with iodine for soft tissue visualization. Micro-CT scanning was carried out using the Siemens Inveon Multimodality scanner with a custom 12-pup cradle. Mice having SBD were necropsied for confirmation, and those with lung or kidney anomalies were further analyzed by histopathology. Micro-CT scanning of 3158 samples revealed 12% of mice having at least one SBD (n=377). Kidney defects such as duplex kidney (n=53), renal agenesis (n=22), and hydronephrosis (n=53) were seen. The accuracies of which were 92.0%, 97.6%, and 86.0% respectively. Head defects including micrognathia (n=5), cleft palate (n=72), holoprosencephaly (n=29), and eye defects encompassing anophthalmia and microphthalmia (n=54) were observed with accuracies ranging from 65.0% to 100%. Lastly, abdominal abnormalities comprising of diaphragmatic hernia (n=5), megacystis (n=40), and dextrogastria (n=32) were noted. The accuracies of which were 100.0%, 99.8%, and 97.5% respectively. This study confirms micro-CT can be used to reliably detect a wide spectrum of SBD in mice. This should have considerable utility for phenotyping mice, particularly in the context of large-scale forward genetic screens and for high-throughput teratogenicity and drug toxicity testing.