Nehal A. Parikh

Postnatal dexamethasone therapy and cerebral tissue volumes in extremely low birth weight infants.

OBJECTIVE. Our goal was to relate postnatal dexamethasone therapy in extremely low birth weight infants (birth weight of ≤1000 g) to their total and regional brain volumes, as measured by volumetric MRI performed at term-equivalent age. METHODS. Among 53 extremely low birth weight infants discharged between June 1 and December 31, 2003, 41 had high-quality MRI studies; 30 of those infants had not received postnatal steroid treatment and 11 had received dexamethasone, all after postnatal age of 28 days, for a mean duration of 6.8 days and a mean cumulative dose of 2.8 mg/kg. Anatomic brain MRI scans obtained at 39.5 weeks (mean) postmenstrual age were segmented by using semiautomated and manual, pretested, scoring algorithms to generate three-dimensional cerebral component volumes. Volumes were adjusted according to postmenstrual age at MRI. RESULTS. After controlling for postmenstrual age at MRI, we observed a 10.2% smaller total cerebral tissue volume in the dexamethasone-treated group, compared with the untreated group. Cortical tissue volume was 8.7% smaller in the treated infants, compared with untreated infants. Regional volume analysis revealed a 20.6% smaller cerebellum and a 19.9% reduction in subcortical gray matter in the dexamethasone-treated infants, compared with untreated infants. In a series of regression analyses, the reductions in total cerebral tissue, subcortical gray matter, and cerebellar volumes associated with dexamethasone administration remained significant after controlling not only for postmenstrual age but also for bronchopulmonary dysplasia and birth weight. CONCLUSIONS. We identified smaller total and regional cerebral tissue volumes in extremely low birth weight infants treated with relatively conservative regimens of dexamethasone. These volume deficits may be the structural antecedents of neuromotor and cognitive abnormalities reported after postnatal dexamethasone treatment.

Prediction of Death for Extremely Premature Infants in a Population-Based Cohort

OBJECTIVE: Although gestational age (GA) is often used as the primary basis for counseling and decision-making for extremely premature infants, a study of tertiary care centers showed that additional factors could improve prediction of outcomes. Our objective was to determine how such a model could improve predictions for a population-based cohort. METHODS: From 2005 to 2008, data were collected prospectively for the California Perinatal Quality Care Collaborative, which encompasses 90% of NICUs in California. For infants born at GAs of 22 to 25 weeks, we assessed the ability of the Eunice Kennedy Shriver National Institute of Child Health and Human Development 5-factor model to predict survival rates, compared with a model using GA alone. RESULTS: In the study cohort of 4527 infants, 3647 received intensive care. Survival rates were 53% for the whole cohort and 66% for infants who received intensive care. In multivariate analyses of data for infants who received intensive care, prenatal steroid exposure, female sex, singleton birth, and higher birth weight (per 100-g increment) were each associated with a reduction in the risk of death before discharge similar to that for a 1-week increase in GA. The multivariate model increased the ability to group infants in the highest and lowest risk categories (mortality rates of >80% and <20%, respectively). CONCLUSIONS: In a population-based cohort, the addition of prenatal steroid exposure, sex, singleton or multiple birth, and birth weight to GA allowed for improved prediction of rates of survival to discharge for extremely premature infants.

The Developmental Trajectory of Brain-Scalp Distance from Birth through Childhood: Implications for Functional Neuroimaging

Measurements of human brain function in children are of increasing interest in cognitive neuroscience. Many techniques for brain mapping used in children, including functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS), use probes placed on or near the scalp. The distance between the scalp and the brain is a key variable for these techniques because optical, electrical and magnetic signals are attenuated by distance. However, little is known about how scalp-brain distance differs between different cortical regions in children or how it changes with development. We investigated scalp-brain distance in 71 children, from newborn to age 12 years, using structural T1-weighted MRI scans of the whole head. Three-dimensional reconstructions were created from the scalp surface to allow for accurate calculation of brain-scalp distance. Nine brain landmarks in different cortical regions were manually selected in each subject based on the published fNIRS literature. Significant effects were found for age, cortical region and hemisphere. Brain-scalp distances were lowest in young children, and increased with age to up to double the newborn distance. There were also dramatic differences between brain regions, with up to 50% differences between landmarks. In frontal and temporal regions, scalp-brain distances were significantly greater in the right hemisphere than in the left hemisphere. The largest contributors to developmental changes in brain-scalp distance were increases in the corticospinal fluid (CSF) and inner table of the cranium. These results have important implications for functional imaging studies of children: age and brain-region related differences in fNIRS signals could be due to the confounding factor of brain-scalp distance and not true differences in brain activity.

Outcome Trajectories in Extremely Preterm Infants

OBJECTIVE: Methods are required to predict prognosis with changes in clinical course. Death or neurodevelopmental impairment in extremely premature neonates can be predicted at birth/admission to the ICU by considering gender, antenatal steroids, multiple birth, birth weight, and gestational age. Predictions may be improved by using additional information available later during the clinical course. Our objective was to develop serial predictions of outcome by using prognostic factors available over the course of NICU hospitalization. METHODS: Data on infants with birth weight ≤1.0 kg admitted to 18 large academic tertiary NICUs during 1998–2005 were used to develop multivariable regression models following stepwise variable selection. Models were developed by using all survivors at specific times during hospitalization (in delivery room [n = 8713], 7-day [n = 6996], 28-day [n = 6241], and 36-week postmenstrual age [n = 5118]) to predict death or death/neurodevelopmental impairment at 18 to 22 months. RESULTS: Prediction of death or neurodevelopmental impairment in extremely premature infants is improved by using information available later during the clinical course. The importance of birth weight declines, whereas the importance of respiratory illness severity increases with advancing postnatal age. The c-statistic in validation models ranged from 0.74 to 0.80 with misclassification rates ranging from 0.28 to 0.30. CONCLUSIONS: Dynamic models of the changing probability of individual outcome can improve outcome predictions in preterm infants. Various current and future scenarios can be modeled by input of different clinical possibilities to develop individual “outcome trajectories” and evaluate impact of possible morbidities on outcome.

Perinatal Factors and Regional Brain Volume Abnormalities at Term in a Cohort of Extremely Low Birth Weight Infants

Our objective was to investigate diverse clinical antecedents of total and regional brain volume abnormalities and white matter hyperintensity volume on term MRI in extremely low birth weight (birth weight ≤1000 g) survivors. A consecutive cohort of extremely low birth weight infants who survived to 38 weeks postmenstrual age (n = 122) and a control group of 16 healthy term newborns underwent brain MRI at term-equivalent age. Brain volumes were measured using semi-automated and manual segmentation methods. Using multivariable linear regression, clinical antecedents were correlated with volumes of total brain tissue, white matter hyperintensities, and regional tissues/structures, adjusted for age at MRI, total cranial volume, and total tissue volume. Regional brain volumes were markedly reduced in extremely low birth weight infants as compared to term newborns (relative difference range: −11.0%, −35.9%). Significant adverse clinical associations for total brain tissue volume included: small for gestational age, seizures, caffeine therapy/apnea of prematurity, duration of parenteral nutrition, pulmonary hemorrhage, and white matter injury (p<0.01 for each; relative difference range: −1.4% to −15.0%). Surgery for retinopathy of prematurity and surgery for necrotizing enterocolitis or spontaneous intestinal perforation were significantly associated with increasing volume of white matter hyperintensities. Regional brain volumes are sensitive to multiple perinatal factors and neonatal morbidities or interventions. Brain growth measurements in extremely low birth weight infants can advance our understanding of perinatal brain injury and development.

Comprehensive brain MRI segmentation in high risk preterm newborns.

Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes.

Perinatal Clinical Antecedents of White Matter Microstructural Abnormalities on Diffusion Tensor Imaging in Extremely Preterm Infants

Objective To identify perinatal clinical antecedents of white matter microstructural abnormalities in extremely preterm infants. Methods A prospective cohort of extremely preterm infants (N = 86) and healthy term controls (N = 16) underwent diffusion tensor imaging (DTI) at term equivalent age. Region of interest-based measures of white matter microstructure - fractional anisotropy and mean diffusivity - were quantified in seven vulnerable cerebral regions and group differences assessed. In the preterm cohort, multivariable linear regression analyses were conducted to identify independent clinical factors associated with microstructural abnormalities. Results Preterm infants had a mean (standard deviation) gestational age of 26.1 (1.7) weeks and birth weight of 824 (182) grams. Compared to term controls, the preterm cohort exhibited widespread microstructural abnormalities in 9 of 14 regional measures. Chorioamnionitis, necrotizing enterocolitis, white matter injury on cranial ultrasound, and increasing duration of mechanical ventilation were adversely correlated with regional microstructure. Conversely, antenatal steroids, female sex, longer duration of caffeine therapy, and greater duration of human milk use were independent favorable factors. White matter injury on cranial ultrasound was associated with a five weeks or greater delayed maturation of the corpus callosum; every additional 10 days of human milk use were associated with a three weeks or greater advanced maturation of the corpus callosum. Conclusions Diffusion tensor imaging is sensitive in detecting the widespread cerebral delayed maturation and/or damage increasingly observed in extremely preterm infants. In our cohort, it also aided identification of several previously known or suspected perinatal clinical antecedents of brain injury, aberrant development, and neurodevelopmental impairments.

Pilot Randomized Trial of Hydrocortisone in Ventilator-Dependent Extremely Preterm Infants: Effects on Regional Brain Volumes

OBJECTIVE To test the hypothesis that high-risk ventilator-dependent extremely low birth weight (birth weight ≤1000 g) infants treated with 7 days of hydrocortisone will have larger total brain tissue volumes than placebo treated infants. STUDY DESIGN A predetermined sample size of 64 extremely low birth weight infants, between 10-21 days old and ventilator-dependent with a respiratory index score ≥2, were randomized to systemic hydrocortisone (17 mg/kg cumulative dose) or saline placebo. Primary outcome was total brain tissue volume. Volumetric magnetic resonance imaging was performed at 38 weeks postmenstrual age; brain tissue regions were segmented and quantified automatically with a high degree of accuracy and 9 structures were segmented manually. All analyses of regional brain volumes were adjusted by postmenstrual age at magnetic resonance imaging scan. RESULTS The study groups were similar at baseline and 8 infants died in each arm. Unadjusted total brain tissue volume (mean ± SD) in the hydrocortisone (N = 23) and placebo treated infants (N = 21) was 272 ± 40.3 cm(3) and 277.8 ± 59.1 cm(3), respectively (adjusted mean difference: 6.35 cm(3) (95% CI: (-20.8, 32.5); P = .64). Three of the 31 hydrocortisone treated infants and 5 of the 33 placebo treated infants survived without severe bronchopulmonary dysplasia (relative risk 0.62, 95% CI: 0.13, 2.66; P = .49). No significant differences were noted in prespecified secondary outcomes of regional structural volumes or days on respiratory support. No adverse effects of hydrocortisone were observed. CONCLUSIONS Low dose hydrocortisone in high-risk ventilator-dependent infants after a week of age had no discernible effect on regional brain volumes or pulmonary outcomes prior to neonatal intensive care unit discharge.

Changes in the PQRST Intervals and Heart Rate Variability Associated with Rewarming in Two Newborns Undergoing Hypothermia Therapy

Background: Little is known about the effects of hypothermia therapy and subsequent rewarming on the PQRST intervals and heart rate variability (HRV) in term newborns with hypoxic-ischemic encephalopathy (HIE). Objectives: This study describes the changes in the PQRST intervals and HRV during rewarming to normal core body temperature of 2 newborns with HIE after hypothermia therapy. Methods: Within 6 h after birth, 2 newborns with HIE were cooled to a core body temperature of 33.5°C for 72 h using a cooling blanket, followed by gradual rewarming (0.5°C per hour) until the body temperature reached 36.5°C. Custom instrumentation recorded the electrocardiogram from the leads used for clinical monitoring of vital signs. Generalized linear mixed models were calculated to estimate temperature-related changes in PQRST intervals and HRV. Results: For every 1°C increase in body temperature, the heart rate increased by 9.2 bpm (95% CI 6.8–11.6), the QTc interval decreased by 21.6 ms (95% CI 17.3–25.9), and low and high frequency HRV decreased by 0.480 dB (95% CI 0.052–0.907) and 0.938 dB (95% CI 0.460–1.416), respectively. Conclusions: Hypothermia-induced changes in the electrocardiogram should be monitored carefully in future studies.

Automated detection of white matter signal abnormality using T2 relaxometry: application to brain segmentation on term MRI in very preterm infants.

Hyperintense white matter signal abnormalities, also called diffuse excessive high signal intensity (DEHSI), are observed in up to 80% of very preterm infants on T2-weighted MRI scans at term-equivalent age. DEHSI may represent a developmental stage or diffuse microstructural white matter abnormalities. Automated quantitative assessment of DEHSI severity may help resolve this debate and improve neonatal brain tissue segmentation. For T2-weighted sequence without fluid attenuation, the signal intensity distribution of DEHSI greatly overlaps with that of cerebrospinal fluid (CSF) making its detection difficult. Furthermore, signal intensities of T2-weighted images are susceptible to magnetic field inhomogeneity. Increased signal intensities caused by field inhomogeneity may be confused with DEHSI. To overcome these challenges, we propose an algorithm to detect DEHSI using T2 relaxometry, whose reflection of the rapid changes in free water content provides improved distinction between CSF and DEHSI over that of conventional T2-weighted imaging. Moreover, the parametric transverse relaxation time T2 is invulnerable to magnetic field inhomogeneity. We conducted computer simulations to select an optimal detection parameter and to validate the proposed method. We also demonstrated that brain tissue segmentation is further enhanced by incorporating DEHSI detection for both simulated preterm infant brain images and in vivo in very preterm infants imaged at term-equivalent age.