No abstract

In 76 normal volunteers studied by positron emission tomography, with [18F]fluorodeoxyglucose, CMRglu was significantly lower in the elderly as compared with young subjects and significantly higher in females relative to males. However, in 58 of these subjects who also had magnetic resonance imaging scans, age and gender were found to be unrelated to CMRglu, when the effects of brain volume and brain atrophy on CMRglu were partialed out using covariate analyses. Individually, brain volume was found to have a significant effect on CMRglu, explaining approximately 17% of the variability in CMRglu measures and brain atrophy explaining approximately 8% of the variance in CMRglu. Together these two measures accounted for approximately 21% of the variance. Cerebrovascular risk factors in normal subjects were not found to affect mean CMRglu or the variability of CMRglu measures. In this study almost 80% of the variance in CMRglu could not be explained by any of the factors that had been considered. This implies a lack of sensitivity of absolute values of global CMRglu to the mild effects of brain dysfunction. Although some of the unexplained variance is probably methodological in origin, physiological factors that are difficult to quantify, such as the state of arousal, are likely to be contributory as well.

Quetiapine is suggested to be effective treatment of youths with psychotic disorders and to have a favorable side-effect profile.

Back-propagation neural networks were used to classify PET scans as either normal or abnormal, with abnormal subjects defined as subjects who had previously been clinically diagnosed with memory disorders. Numerous neural network experiments were performed in order to achieve optimization with respect to number of hidden unJts and training duration. Optimizations and performance evaluations were based on ROC analysis, in which the area under the ROC curve was the figure of merit The neural network's performance was better than that of dlscrlminant analysis, and comparable to the expen's performance. despite the low resolution image data, which consisted of one value per brain lobe, provided to the network. INTRODUCI10NQuantitatJve approaches to the analysis and/or classification of Positron Emission Tomography (PE1) scans usually involve a reglon-of·interest (ROI) analysis, in which regional metabolic function in the brain is evaluated [I). Pattern recognition stUdies are then performed on these data.Various pattern recognltion technJques, including the back-propagation neural network (2), have been applied to the classification of normal and abnormal PET scans based on ROI data. Neural networks appear to perform better than standard statistical methods like dlscrlminant analysis (3).In the literature describing various recent applications of neural networks, there appears to be relatJvely little standardization In neural-network training. Networks are often trained to satisfy panicular "convergence criteria", which essentially specify how well the hypersurfaces defined by the network are able to separate the different classes comprising the trainJng set A more imponant consIderation in most drcumstances, however, is the abillty of a network to generalize and Identify previOUSly-unseen patterns, an issue which involves the number of traIning patterns, the dimensionality of these patterns, the architecture of the network (e.g., the number of hidden unJts) and number of trainJng Iterations. Complex networks trained on high-dlmenslonaJ patterns for an excessive number of iterations may tend to "memorize" their training sets, and learn criteria that are not generally applicable to populations of given pattern classes. Evaluation of a network's abillty to generalize is accomplished by cross-validation studies, that is, testing trained networks on new and independent data sets. The question then arises: what is the most appropriate figure of merit for performance evaluation?The ROC (Relative-Operating-Characteristic) method of analysis has recently come to be recognized as an Objective and comprehensive way to evaluate diagnostic systems, since It measures a diagnostic system's performance independent of dedsion biases and prior probabillties (4). The ROC curve represents a system's performance at several different settings of the particular dedsion criteria. The area under the curve is the "only performance measure available that is unin1Juenced by dedsion biases and prior probabillties. and it places the per...

grou p s were also significantly activated. The RMT did not allow a better discrimination of AD patients from nor mal controls on the basis of regional metabolic deficits. Regions in the AD grou p that were individually classified as hypo metabolic during rest also exhibited metabolic ac tivation. The apparent viability of hypometabolic regions in AD patients challenges current hypotheses regarding the cause of abnormal metabolism in AD.

Positron emission tomographic (PET) scans using [¹⁸F]-fluorodeoxyglucose and magnetic resonance imaging (MRI) scans were quantitatively analyzed for metabolic and structural abnormalities in normal subjects and patients classified as having Alzheimer’s disease (AD), mixed dementia and multi-infarct dementia (MID) according to Hachinski ischemic scores. MRI-detected abnormalities in the periventricular white matter and in subcortical locations increased in incidence with age in normals and increased markedly in AD and especially in MID. Upper limits for the severity of these white matter lesions could be defined only for normal young and elderly subjects, but not for AD, mixed or MID patients. PET scan abnormalities occurred in about 90% of demented patients and in 54% of elderly and 34% of young normals. There was no characteristic pattern of abnormality that distinguished MID from AD patients. It is concluded that PET and MRI studies in demented patients are useful ancillary tests especially in evaluating the mild, questionably demented subject and for assessing the functional impact of structural disease.

Positron-emission tomography (PET) was used to study regional cerebral metabolic activity during oral reading in right-handed adult males with, and without a childhood and family history of developmental dyslexia. Significant group differences in normalized regional metabolic values were revealed in prefrontal cortex and in the lingual (inferior) region of the occipital lobe. Lingual values were bilaterally higher for dyslexic than normal readers. In contrast to the asymmetry observed in prefrontal and lingual regions in nondyslexic subjects during reading, the dyslexic pattern was more symmetric. These results demonstrate that individuals who suffered from familial developmental dyslexia as children, activate different brain regions during reading as adults, as compared to individuals without such childhood history.

The effect of behavioral activation on cerebral and cerebellar glucose metabolism was studied in normal subjects when performing either a verbal memory task or a tactile somatosensory task. Each subject was also studied in a resting state control condition, either 1 h earlier or later than the activation task. Compared to the resting state, both tasks produced asymmetrical metabolic activation, which was opposite in direction within the cerebral and cerebellar hemispheres. In both tasks, the difference of activation of CMRglc in the right and left hemispheres in the cerebellum was negatively correlated with that in the sensory-motor region. This apparently coupled metabolic activation of one cerebellum and areas within the opposite cerebral hemisphere represents the inverse of the crossed cerebellar diaschisis phenomenon commonly observed when a vascular lesion affects one cerebral hemisphere and hypometabolism occurs in the opposite cerebellum. Because these correlations were selective and concordant with known anatomical connections, and were found in two different tasks, they suggest strong functional connections between these specific brain regions.