Magnetic resonance imaging of brain anomalies in fetal alcohol syndrome

Ethanol-induced apoptotic neurodegeneration and fetal alcohol syndrome

The deleterious effects of ethanol on the developing human brain are poorly understood. Here it is reported that ethanol, acting by a dual mechanism [blockade of N-methyl-D-aspartate (NMDA) glutamate receptors and excessive activation of GABA(A) receptors], triggers widespread apoptotic neurodegeneration in the developing rat forebrain. Vulnerability coincides with the period of synaptogenesis, which in humans extends from the sixth month of gestation to several years after birth. During this period, transient ethanol exposure can delete millions of neurons from the developing brain. This can explain the reduced brain mass and neurobehavioral disturbances associated with human fetal alcohol syndrome.

Defining the phenotype of schizophrenia: cognitive dysmetria and its neural mechanisms

All research on schizophrenia depends on selecting the correct phenotype to define the sample to be studied. Definition of the phenotype is complicated by the fact that there are no objective markers for the disorder. Further, the symptoms are diverse, leading some to propose that the disorder is heterogeneous and not a single disorder or syndrome. This article explores an alternative possibility. It proposes that schizophrenia may be a single disorder linked by a common pathophysiology (a neurodevelopmental mechanism), which leads to a misconnection syndrome of neural circuitry. Evidence for disruption in a specific circuit is explored: the cortical-thalamic-cerebellar-cortical circuit (CCTCC). It is suggested that a disruption in this circuit leads to an impairment in synchrony, or the smooth coordination of mental processes. When synchrony is impaired, the patient suffers from a cognitive dysmetria, and the impairment in this basic cognitive process defines the phenotype of schizophrenia and produces its diversity of symptoms.

An MRI study of cerebellar vermis morphology in patients with schizophrenia: evidence in support of the cognitive dysmetria concept

BACKGROUND

Cumulative evidence suggests the cerebellum is involved in cognition and may be important in the pathoetiology of schizophrenia. Functional imaging studies have identified a possible neural circuit that includes the cerebellum and may be abnormal in patients with schizophrenia, manifesting as a fundamental cognitive deficit conceptualized as cognitive dysmetria. To explore the role of the cerebellum in cognitive dysfunction and schizophrenia, this study was designed to evaluate the morphology of the cerebellar vermis, its relationship to other cortical areas, and to cognitive function in patients with schizophrenia.

METHODS

Male patients with schizophrenia (n = 65) were matched by age and gender to 65 healthy male controls. Volume measures of the 4 cerebral lobes and total cerebellum were obtained using automated methods. The area of the cerebellar vermis (divided into three lobes) was traced on a midsaggital MRI slice.

RESULTS

Patients had smaller frontal and temporal lobes. There were no group differences in total cerebellar volume. Patients had a smaller vermis area, accounted for by a smaller anterior lobe. The anterior vermis area was positively correlated with total cerebellar volume, temporal lobe volume, and FSIQ in patients, but not controls.

CONCLUSIONS

These findings support the theory that regions of the cerebellum may be involved in a neural circuit that is structurally and functionally abnormal in patients with schizophrenia, leading to cognitive dysmetria.

Measurement of brain structures with artificial neural networks: two- and three-dimensional applications

PURPOSE

To evaluate the ability of an artificial neural network (ANN) to identify brain structures. This ANN was applied to postprocessed magnetic resonance (MR) images to segment various brain structures in both two- and three-dimensional applications.

MATERIALS AND METHODS

An ANN was designed that learned from experience to define the corpus callosum, whole brain, caudate, and putamen. Manual segmentation was used as a training set for the ANN. The ANN was trained on two-thirds of the manually segmented images and was tested on the remaining one-third. The reliability of the ANN was compared against manual segmentations by two technicians.

RESULTS

The ANN was able to identify the brain structures as readily and as well as did the two technicians. Reliability of the ANN compared with the technicians was 0.96 for the corpus callosum, 0.95 for the whole brain, 0.86 (right) and 0.93 (left) for the caudate, and 0.71 (right) and 0.88 (left) for the putamen.

CONCLUSION

The ANN was able to identify the structures used in this study as well as did the two technicians. The ANN could do this much more rapidly and without rater drift. Several other cortical and subcortical structures could also be readily identified with this method.

Ethanol inhibits L1-mediated neurite outgrowth in postnatal rat cerebellar granule cells

The neuropathology of the effects of ethanol on the developing central nervous system are similar to those of patients with mutations in L1, a neural cell adhesion molecule. This observation suggests that inhibition of L1 plays a role in the pathogenesis of alcohol-related neurodevelopmental disorders. Here we examine the effects of ethanol on L1 homophilic binding and on L1-mediated neurite outgrowth. Ethanol had no effect on cell adhesion or aggregation in a myeloma cell line expressing full-length human L1. In contrast, the rate of L1-mediated neurite outgrowth of rat postnatal day 6 cerebellar granule cells grown on a substratum of NgCAM, the chick homologue of L1, was inhibited by 48.6% in the presence of ethanol with a half-maximal concentration of 4.7 mM. The same effect was found with soluble L1-Fc, thus showing that the inhibitory effect is not dependent on cell adhesion. In contrast, neither laminin nor N-cadherin-mediated neurite outgrowth was inhibited by physiologic concentrations of ethanol. We conclude that one mechanism of ethanol's toxicity to the developing central nervous system may be the inhibition of L1-mediated neurite outgrowth.

Improving tissue classification in MRI: a three-dimensional multispectral discriminant analysis method with automated training class selection

PURPOSE

To improve the reliability, accuracy, and computational efficiency of tissue classification with multispectral sequences [T1, T2, and proton density (PD)], we developed an automated method for identifying training classes to be used in a discriminant function analysis. We compared it with a supervised operator-dependent method, evaluating its reliability and validity. We also developed a fuzzy (continuous) classification to correct for partial voluming.

METHOD

Images were obtained on a 1.5 T GE Signa MR scanner using three pulse sequences that were co-registered. Training classes for the discriminant analysis were obtained in two ways. The operator-dependent method involved defining circular ROIs containing 5-15 voxels that represented "pure" samples of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), using a total of 150-300 voxels for each tissue type. The automated method involved selecting a large number of samples of brain tissue with sufficiently low variance and randomly placed throughout the brain ("plugs"), partitioning these samples into GM, WM, and CSF, and minimizing the amount of variance within each partition of samples to optimize its "purity." The purity of the plug was estimated by calculating the variance of 8 voxels in all modalities (T1, T2, and PD). We also compared "sharp" (discrete) measurements (which classified tissue only as GM, WM, or CSF) and "fuzzy" (continuous) measurements (which corrected for partial voluming by weighting the classification based on the mixture of tissue types in each voxel).

RESULTS

Reliability was compared for the operator-dependent and automated methods as well as for the fuzzy versus sharp classification. The automated sharp classifications consistently had the highest interrater and intrarater reliability. Validity was assessed in three ways: reproducibility of measurements when the same individuals were scanned on multiple occasions, sensitivity of the method to detecting changes associated with aging, and agreement between the automated segmentation values and those produced through expert manual segmentation. The sharp automated classification emerged as slightly superior to the other three methods according to each of these validators. Its reproducibility index (intraclass r) was 0.97, 0.98, and 0.98 for total CSF, total GM, and total WM, respectively. Its correlations with age were 0.54, -0.61, and -0.53, respectively. Its percent agreement with the expert manually segmented tissue for the three tissue types was 93, 90, and 94%, respectively.

CONCLUSION

Automated identification of training classes for discriminant analysis was clearly superior to a method that required operator intervention. A sharp (discrete) classification into three tissue types was also slightly superior to one that used "fuzzy" classification to produce continuous measurements to correct for partial voluming. This multispectral automated discriminant analysis method produces a computationally efficient, reliable, and valid method for classifying brain tissue into GM, WM, and CSF. It corrects some of the problems with reliability and computational inefficiency previously observed for operator-dependent approaches to segmentation.

A review of the neuroanatomical findings in children with fetal alcohol syndrome or prenatal exposure to alcohol

Human and animal studies have clearly demonstrated that alcohol is both a physical and behavioral teratogen and that heavy prenatal alcohol exposure can lead to a distinct pattern of birth defects termed the fetal alcohol syndrome. Underlying the behavioral and cognitive anomalies seen in fetal alcohol syndrome are alterations in brain structure and/or function. This paper reviews the literature examining brain anomalies attributable to prenatal alcohol exposure, beginning with a survey of autopsy studies and leading up to current findings using magnetic resonance imaging and positron emission tomography studies. Autopsy reports clearly illustrate the wide and devastating influence alcohol has on the developing brain, although for the most part no specific pattern of brain malformation has been identified. More recent magnetic resonance imaging studies, particularly when combined with quantitative analysis, have indicated that specific brain areas--such as the basal ganglia, the corpus callosum, and parts of the cerebellum--might be especially susceptible to alcohol's teratogenic effects. Further studies using functional brain imaging techniques may provide even more information about the unique effects prenatal alcohol exposure has on the developing brain. Discovering specific areas of the brain that are affected by alcohol may allow clinicians and researchers to look for patterns of vulnerable regions in the brain, thereby helping in the future detection of children who are prenatally exposed to alcohol.

Alcohol, astroglia, and brain development

Glial cells constitute one of the most common cell types in the brain. They play critical roles in central nervous system (CNS) development. Recent evidence demonstrates that glial cells are profoundly affected by prenatal alcohol exposure, suggesting that alterations in these cells may participate in CNS abnormalities associated with ethanol-induced teratogenesis. In vivo studies show that prenatal exposure to alcohol hampers myelinogenesis and is associated with neuroglial heterotopias and abnormal astrogliogenesis. Studies using primary cultures of rat cortical astrocytes show that ethanol affects DNA, RNA, and protein synthesis, decreases the number of mitotic cells, alters the content and distribution of several cytoskeletal proteins including the astroglial marker, glial fibrillary acidic protein (GFAP), and the levels of plasma-membrane glycoproteins, reduces the capacity of astrocytes to secrete growth factors, and induces oxidative stress. Furthermore, ethanol exposure during early embryogenesis alters the normal development of radial glia cells (the main astrocytic precursors), delays the onset of GFAP expression, and decreases mRNA GFAP levels in fetal and postnatal brains and in radial glia and astrocytes in primary culture. Recent evidence suggests that ethanol interferes with the transcription process of GFAP, thus leading to a reduction in GFAP-gene expression during astrogliogenesis. However, brief exposure of rats to high levels of ethanol during the neonatal period (the period of astrocyte differentiation) causes a transient gliosis, with an increase in GFAP and its mRNA levels. These findings indicate that astroglial cells are an important target of ethanol toxicity during central nervous system (CNS) development.