Children and Megadisasters: Lessons Learned in the New Millennium

Hurricane Katrina is America’s most recent encounter with a megadisaster. But what made it a megadisaster instead of just another category 3 hurricane of the type that seasonally exists in the Gulf of Mexico? Katrina was not the largest or strongest hurricane to strike the United States mainland in the recent past, but its effects were devastating and wide reaching beyond our wildest nightmares, far beyond those of Hurricane Andrew (1992), a category 5 hurricane that scoured much of Florida and the Gulf Coast. Hurricane Katrina’s track directly targeted gaping vulnerabilities in infrastructure and society, and set in motion a series of events that culminated in the deaths of nearly 2000 people, resulted in hundreds of missing individuals, and caused a potential economic impact of up to $150 billion. The disruption of people’s lives was immeasurable, as was the impact on the long-term physical and mental health of the victims, which continues today. Katrina also led to a substantial decline in the confidence that the public has in its government to provide essential services during a disaster. Children are among the most susceptible members of a community when catastrophes such as these strike because of their dependent nature as well as their physiologic and psychological vulnerability. Children affected by Katrina were no exception. Persistent critical gaps exist in the ability to prepare for and respond to the needs of the youngest victims. These were clearly exposed as children endured an at times ineffectual disaster response followed by a stressful recovery that is still ongoing. An analysis of the issues that faced children during this event and some others from the recent past may help society reduce the impact of such disasters on children in the future. This article focuses on a few of the major shortfalls in the care of children that have become especially apparent in the last few years: Facilitating evacuation; Providing shelter; Caring for those with special medical needs; Addressing mental health needs

MRI estimates of brain iron concentration in normal aging: Comparison of field-dependent (FDRI) and phase (SWI) methods

Different brain structures accumulate iron at different rates throughout the adult life span. Typically, striatal and brain stem structures are higher in iron concentrations in older than younger adults, whereas cortical white matter and thalamus have lower concentrations in the elderly than young adults. Brain iron can be measured in vivo with MRI by estimating the relaxivity increase across magnetic field strengths, which yields the Field-Dependent Relaxation Rate Increase (FDRI) metric. The influence of local iron deposition on susceptibility, manifests as MR phase effects, forms the basis for another approach for iron measurement, Susceptibility-Weighted Imaging (SWI), for which imaging at only one field strength is sufficient. Here, we compared the ability of these two methods to detect and quantify brain iron in 11 young (5 men, 6 women; 21 to 29 years) and 12 elderly (6 men, 6 women; 64 to 86 years) healthy adults. FDRI was acquired at 1.5 T and 3.0 T, and SWI was acquired at 1.5 T. The results showed that both methods detected high globus pallidus iron concentration regardless of age and significantly greater iron in putamen with advancing age. The SWI measures were more sensitive when the phase signal intensities themselves were used to define regions of interest, whereas FDRI measures were robust to the method of region of interest selection. Further, FDRI measures were more highly correlated than SWI iron estimates with published postmortem values and were more sensitive than SWI to iron concentration differences across basal ganglia structures. Whereas FDRI requires more imaging time than SWI, two field strengths, and across-study image registration for iron concentration calculation, FDRI appears more specific to age-dependent accumulation of non-heme brain iron than SWI, which is affected by heme iron and non-iron source effects on phase.National Institutes of Health (U.S.) (Grant AG017919)National Institutes of Health (U.S.) (Grant AA005965)National Institutes of Health (U.S.) (Grant AA017168

Quantitative Susceptibility Mapping by Inversion of a Perturbation Field Model: Correlation With Brain Iron in Normal Aging

There is increasing evidence that iron deposition occurs in specific regions of the brain in normal aging and neurodegenerative disorders such as Parkinson's, Huntington's, and Alzheimer's disease. Iron deposition changes the magnetic susceptibility of tissue, which alters the MR signal phase, and allows estimation of susceptibility differences using quantitative susceptibility mapping (QSM). We present a method for quantifying susceptibility by inversion of a perturbation model, or “QSIP.” The perturbation model relates phase to susceptibility using a kernel calculated in the spatial domain, in contrast to previous Fourier-based techniques. A tissue/air susceptibility atlas is used to estimate B[subscript 0] inhomogeneity. QSIP estimates in young and elderly subjects are compared to postmortem iron estimates, maps of the Field-Dependent Relaxation Rate Increase, and the L1-QSM method. Results for both groups showed excellent agreement with published postmortem data and in vivo FDRI: statistically significant Spearman correlations ranging from Rho=0.905 to Rho=1.00 were obtained. QSIP also showed improvement over FDRI and L1-QSM: reduced variance in susceptibility estimates and statistically significant group differences were detected in striatal and brainstem nuclei, consistent with age-dependent iron accumulation in these regions.National Institutes of Health (U.S.) (Grant P41EB015902)National Institutes of Health (U.S.) (Grant P41RR013218)National Institutes of Health (U.S.) (Grant P41EB015898)National Institutes of Health (U.S.) (Grant P41RR019703)National Institutes of Health (U.S.) (Grant T32EB0011680-06)National Institutes of Health (U.S.) (Grant K05AA017168)National Institutes of Health (U.S.) (Grant R01AA012388

MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping

Quantifying tissue iron concentration in vivo is instrumental for understanding the role of iron in physiology and in neurological diseases associated with abnormal iron distribution. Herein, we use recently-developed Quantitative Susceptibility Mapping (QSM) methodology to estimate the tissue magnetic susceptibility based on MRI signal phase. To investigate the effect of different regularization choices, we implement and compare ℓ[subscript 1] and ℓ[subscript 2] norm regularized QSM algorithms. These regularized approaches solve for the underlying magnetic susceptibility distribution, a sensitive measure of the tissue iron concentration, that gives rise to the observed signal phase. Regularized QSM methodology also involves a pre-processing step that removes, by dipole fitting, unwanted background phase effects due to bulk susceptibility variations between air and tissue and requires data acquisition only at a single field strength. For validation, performances of the two QSM methods were measured against published estimates of regional brain iron from postmortem and in vivo data. The in vivo comparison was based on data previously acquired using Field-Dependent Relaxation Rate Increase (FDRI), an estimate of MRI relaxivity enhancement due to increased main magnetic field strength, requiring data acquired at two different field strengths. The QSM analysis was based on susceptibility-weighted images acquired at 1.5 T, whereas FDRI analysis used Multi-Shot Echo-Planar Spin Echo images collected at 1.5 T and 3.0 T. Both datasets were collected in the same healthy young and elderly adults. The in vivo estimates of regional iron concentration comported well with published postmortem measurements; both QSM approaches yielded the same rank ordering of iron concentration by brain structure, with the lowest in white matter and the highest in globus pallidus. Further validation was provided by comparison of the in vivo measurements, ℓ[subscript 1]-regularized QSM versus FDRI and ℓ[subscript 2]-regularized QSM versus FDRI, which again yielded perfect rank ordering of iron by brain structure. The final means of validation was to assess how well each in vivo method detected known age-related differences in regional iron concentrations measured in the same young and elderly healthy adults. Both QSM methods and FDRI were consistent in identifying higher iron concentrations in striatal and brain stem ROIs (i.e., caudate nucleus, putamen, globus pallidus, red nucleus, and substantia nigra) in the older than in the young group. The two QSM methods appeared more sensitive in detecting age differences in brain stem structures as they revealed differences of much higher statistical significance between the young and elderly groups than did FDRI. However, QSM values are influenced by factors such as the myelin content, whereas FDRI is a more specific indicator of iron content. Hence, FDRI demonstrated higher specificity to iron yet yielded noisier data despite longer scan times and lower spatial resolution than QSM. The robustness, practicality, and demonstrated ability of predicting the change in iron deposition in adult aging suggest that regularized QSM algorithms using single-field-strength data are possible alternatives to tissue iron estimation requiring two field strengths.National Institutes of Health (U.S.) (Grant NIH R01 EB007942)National Institutes of Health (U.S.) (Grant AG019717)National Institutes of Health (U.S.) (Grant AA005965)National Institutes of Health (U.S.) (Grant AA017168)National Institutes of Health (U.S.) (Grant EB008381)National Science Foundation (U.S.) (Grant 0643836)Siemens CorporationSiemens-MIT AllianceMIT-Center for Integration of Medicine and Innovative Technology (Medical Engineering Fellowship

Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet

In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature denoising, feature selection, training a StackNet, and predicting fluid intelligence. The extracted feature is the distribution of different brain tissues in different brain parcellation regions. The proposed StackNet consists of three layers and 11 models. Each layer uses the predictions from all previous layers including the input layer. The proposed StackNet is tested on a public benchmark Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge 2019 and achieves a mean squared error of 82.42 on the combined training and validation set with 10-fold cross-validation. In addition, the proposed StackNet also achieves a mean squared error of 94.25 on the testing data. The source code is available on GitHub.Comment: 8 pages, 2 figures, 3 tables, Accepted by MICCAI ABCD-NP Challenge 2019; Added ND

ABCD Neurocognitive Prediction Challenge 2019: Predicting individual fluid intelligence scores from structural MRI using probabilistic segmentation and kernel ridge regression

We applied several regression and deep learning methods to predict fluid intelligence scores from T1-weighted MRI scans as part of the ABCD Neurocognitive Prediction Challenge (ABCD-NP-Challenge) 2019. We used voxel intensities and probabilistic tissue-type labels derived from these as features to train the models. The best predictive performance (lowest mean-squared error) came from Kernel Ridge Regression (KRR; $\lambda=10$), which produced a mean-squared error of 69.7204 on the validation set and 92.1298 on the test set. This placed our group in the fifth position on the validation leader board and first place on the final (test) leader board.Comment: Winning entry in the ABCD Neurocognitive Prediction Challenge at MICCAI 2019. 7 pages plus references, 3 figures, 1 tabl

Cognitive control in belief-laden reasoning during conclusion processing: An ERP study

Belief bias is the tendency to accept conclusions that are compatible with existing beliefs more frequently than those that contradict beliefs. It is one of the most replicated behavioral findings in the reasoning literature. Recently, neuroimaging studies using functional magnetic resonance imaging (fMRI) and event-related potentials (ERPs) have provided a new perspective and have demonstrated neural correlates of belief bias that have been viewed as supportive of dual-process theories of belief bias. However, fMRI studies have tended to focus on conclusion processing, while ERPs studies have been concerned with the processing of premises. In the present research, the electrophysiological correlates of cognitive control were studied among 12 subjects using high-density ERPs. The analysis was focused on the conclusion presentation phase and was limited to normatively sanctioned responses to valid–believable and valid–unbelievable problems. Results showed that when participants gave normatively sanctioned responses to problems where belief and logic conflicted, a more positive ERP deflection was elicited than for normatively sanctioned responses to nonconflict problems. This was observed from −400 to −200 ms prior to the correct response being given. The positive component is argued to be analogous to the late positive component (LPC) involved in cognitive control processes. This is consistent with the inhibition of empirically anomalous information when conclusions are unbelievable. These data are important in elucidating the neural correlates of belief bias by providing evidence for electrophysiological correlates of conflict resolution during conclusion processing. Moreover, they are supportive of dual-process theories of belief bias that propose conflict detection and resolution processes as central to the explanation of belief bias

Association between a longer duration of illness, age and lower frontal lobe grey matter volume in schizophrenia

The frontal lobe has an extended maturation period and may be vulnerable to the long-term effects of schizophrenia. We tested this hypothesis by studying the relationship between duration of illness (DoI), grey matter (GM) and cerebro-spinal fluid (CSF) volume across the whole brain. Sixty-four patients with schizophrenia and 25 healthy controls underwent structural MRI scanning and neuropsychological assessment. We performed regression analyses in patients to examine the relationship between DoI and GM and CSF volumes across the whole brain, and correlations in controls between age and GM or CSF volume of the regions where GM or CSF volumes were associated with DoI in patients. Correlations were also performed between GM volume in the regions associated with DoI and neuropsychological performance. A longer DoI was associated with lower GM volume in the left dorsomedial prefrontal cortex (PFC), right middle frontal cortex, left fusiform gyrus (FG) and left cerebellum (lobule III). Additionally, age was inversely associated with GM volume in the left dorsomedial PFC in patients, and in the left FG and CSF excess near the left cerebellum in healthy controls. Greater GM volume in the left dorsomedial PFC was associated with better working memory, attention and psychomotor speed in patients. Our findings suggest that the right middle frontal cortex is particularly vulnerable to the long-term effect of schizophrenia illness whereas the dorsomedial PFC, FG and cerebellum are affected by both a long DoI and aging. The effect of illness chronicity on GM volume in the left dorsomedial PFC may be extended to brain structure–neuropsychological function relationships

Addressing the needs of children with disabilities experiencing disaster or terrorism

Purpose of review: This paper reviews the empirical literature on psychosocial factors relating to children with disabilities in the context of disaster or terrorism. Recent findings: Research indicates individuals with disabilities experience increased exposure to hazards due to existing social disparities and barriers associated with disability status. However, studies on the psychological effects of disaster/terrorism on children with preexisting disabilities are exceedingly few and empirical evidence of the effectiveness of trauma-focused therapies for this population is limited. Secondary adversities, including social stigma and health concerns, also compromise the recovery of these children post-disaster/terrorism. Schools and teachers appear to be particularly important in the recovery of children with disabilities to disaster. Disasters, terrorism, and war all contribute to the incidence of disability, as well as disproportionately affect children with preexisting disabilities. Summary: Disaster preparedness interventions and societal changes are needed to decrease the disproportionate environmental and social vulnerability of children with disabilities to disaster and terrorism

Rat strain differences in brain structure and neurochemistry in response to binge alcohol

RATIONALE: Ventricular enlargement is a robust phenotype of the chronically dependent alcoholic human brain, yet the mechanism of ventriculomegaly is unestablished. Heterogeneous stock Wistar rats administered binge EtOH (3 g/kg intragastrically every 8 h for 4 days to average blood alcohol levels (BALs) of 250 mg/dL) demonstrate profound but reversible ventricular enlargement and changes in brain metabolites (e.g., N-acetylaspartate (NAA) and choline-containing compounds (Cho)). OBJECTIVES: Here, alcohol-preferring (P) and alcohol-nonpreferring (NP) rats systematically bred from heterogeneous stock Wistar rats for differential alcohol drinking behavior were compared with Wistar rats to determine whether genetic divergence and consequent morphological and neurochemical variation affect the brain's response to binge EtOH treatment. METHODS: The three rat lines were dosed equivalently and approached similar BALs. Magnetic resonance imaging and spectroscopy evaluated the effects of binge EtOH on brain. RESULTS: As observed in Wistar rats, P and NP rats showed decreases in NAA. Neither P nor NP rats, however, responded to EtOH intoxication with ventricular expansion or increases in Cho levels as previously noted in Wistar rats. Increases in ventricular volume correlated with increases in Cho in Wistar rats. CONCLUSIONS: The latter finding suggests that ventricular volume expansion is related to adaptive changes in brain cell membranes in response to binge EtOH. That P and NP rats responded differently to EtOH argues for intrinsic differences in their brain cell membrane composition. Further, differential metabolite responses to EtOH administration by rat strain implicate selective genetic variation as underlying heterogeneous effects of chronic alcoholism in the human condition