Harmonization of Multi-Center Diffusion Tensor Tractography in Neonates with Congenital Heart Disease: Optimizing Post-Processing and Application of ComBat.

Advanced brain imaging of neonatal macrostructure and microstructure, which has prognosticating importance, is more frequently being incorporated into multi-center trials of neonatal neuroprotection. Multicenter neuroimaging studies, designed to overcome small sample sized clinical cohorts, are essential but lead to increased technical variability. Few harmonization techniques have been developed for neonatal brain microstructural (diffusion tensor) analysis. The work presented here aims to remedy two common problems that exist with the current state of the art approaches: 1) variance in scanner and protocol in data collection can limit the researcher's ability to harmonize data acquired under different conditions or using different clinical populations. 2) The general lack of objective guidelines for dealing with anatomically abnormal anatomy and pathology. Often, subjects are excluded due to subjective criteria, or due to pathology that could be informative to the final analysis, leading to the loss of reproducibility and statistical power. This proves to be a barrier in the analysis of large multi-center studies and is a particularly salient problem given the relative scarcity of neonatal imaging data. We provide an objective, data-driven, and semi-automated neonatal processing pipeline designed to harmonize compartmentalized variant data acquired under different parameters. This is done by first implementing a search space reduction step of extracting the along-tract diffusivity values along each tract of interest, rather than performing whole-brain harmonization. This is followed by a data-driven outlier detection step, with the purpose of removing unwanted noise and outliers from the final harmonization. We then use an empirical Bayes harmonization algorithm performed at the along-tract level, with the output being a lower dimensional space but still spatially informative. After applying our pipeline to this large multi-site dataset of neonates and infants with congenital heart disease (n= 398 subjects recruited across 4 centers, with a total of n=763 MRI pre-operative/post-operative time points), we show that infants with single ventricle cardiac physiology demonstrate greater white matter microstructural alterations compared to infants with bi-ventricular heart disease, supporting what has previously been shown in literature. Our method is an open-source pipeline for delineating white matter tracts in subject space but provides the necessary modular components for performing atlas space analysis. As such, we validate and introduce Diffusion Imaging of Neonates by Group Organization (DINGO), a high-level, semi-automated framework that can facilitate harmonization of subject-space tractography generated from diffusion tensor imaging acquired across varying scanners, institutions, and clinical populations. Datasets acquired using varying protocols or cohorts are compartmentalized into subsets, where a cohort-specific template is generated, allowing for the propagation of the tractography mask set with higher spatial specificity. Taken together, this pipeline can reduce multi-scanner technical variability which can confound important biological variability in relation to neonatal brain microstructure.

Brain Dysplasia Associated with Ciliary Dysfunction in Infants with Congenital Heart Disease.

OBJECTIVE: To test for associations between abnormal respiratory ciliary motion (CM) and brain abnormalities in infants with congenital heart disease (CHD) STUDY DESIGN: We recruited 35 infants with CHD preoperatively and performed nasal tissue biopsy to assess respiratory CM by videomicroscopy. Cranial ultrasound scan and brain magnetic resonance imaging were obtained pre- and/or postoperatively and systematically reviewed for brain abnormalities. Segmentation was used to quantitate cerebrospinal fluid and regional brain volumes. Perinatal and perioperative clinical variables were collected. RESULTS: A total of 10 (28.5%) patients with CHD had abnormal CM. Abnormal CM was not associated with brain injury but was correlated with increased extraaxial cerebrospinal fluid volume (P < .001), delayed brain maturation (P < .05), and a spectrum of subtle dysplasia including the hippocampus (P < .0078) and olfactory bulb (P < .034). Abnormal CM was associated with higher composite dysplasia score (P < .001), and both were correlated with elevated preoperative serum lactate (P < .001). CONCLUSIONS: Abnormal respiratory CM in infants with CHD is associated with a spectrum of brain dysplasia. These findings suggest that ciliary defects may play a role in brain dysplasia in patients with CHD and have the potential to prognosticate neurodevelopmental risks.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex.

OBJECTIVE: Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth. METHODS: Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri). RESULTS: Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups. CONCLUSION: Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.

Alterations of resting state networks and structural connectivity in relation to the prefrontal and anterior cingulate cortices in late prematurity.

Late preterm birth is increasingly recognized as a risk factor for cognitive and social deficits. The prefrontal cortex is particularly vulnerable to injury in late prematurity because of its protracted development and extensive cortical connections. Our study examined children born late preterm without access to advanced postnatal care to assess structural and functional connectivity related to the prefrontal cortex. Thirty-eight preadolescents [19 born late preterm (34-36 /7 weeks gestational age) and 19 at term] were recruited from a developing community in Brazil. Participants underwent neuropsychological testing. Individuals underwent three-dimensional T1-weighted, diffusion-weighted, and resting state functional MRI. Probabilistic tractography and functional connectivity analyses were carried out using unilateral seeds combining the medial prefrontal cortex and the anterior cingulate cortex. Late preterm children showed increased functional connectivity within regions of the default mode, salience, and central-executive networks from both right and left frontal cortex seeds. Decreased functional connectivity was observed within the right parahippocampal region from left frontal seeding. Probabilistic tractography showed a pattern of decreased streamlines in frontal white matter pathways and the corpus callosum, but also increased streamlines in the left orbitofrontal white matter and the right frontal white matter when seeded from the right. Late preterm children and term control children scored similarly on neuropsychological testing. Prefrontal cortical connectivity is altered in late prematurity, with hyperconnectivity observed in key resting state networks in the absence of neuropsychological deficits. Abnormal structural connectivity indicated by probabilistic tractography suggests subtle changes in white matter development, implying disruption of normal maturation during the late gestational period.