A population-based morphometric MRI study in patients with first-episode psychotic bipolar disorder: comparison with geographically matched healthy controls and major depressive disorder subjects

Objectives: Many morphometric magnetic resonance imaging (MRI) studies that have investigated the presence of gray matter (GM) volume abnormalities associated with the diagnosis of bipolar disorder (BD) have reported conflicting findings. None of these studies has compared patients with recent-onset psychotic BD with asymptomatic controls selected from exactly the same environment using epidemiological methods, or has directly contrasted BD patients against subjects with first-onset psychotic major depressive disorder (MDD). We examined structural brain differences between (i) BD (type I) subjects and MDD subjects with psychotic features in their first contact with the healthcare system in Brazil, and (ii) these two mood disorder groups relative to a sample of geographically matched asymptomatic controls. Methods: A total of 26 BD subjects, 20 subjects with MDD, and 94 healthy controls were examined using either of two identical MRI scanners and acquisition protocols. Diagnoses were based on DSM-IV criteria and confirmed one year after brain scanning. Image processing was conducted using voxel-based morphometry. Results: The BD group showed increased volume of the right dorsal anterior cingulate cortex relative to controls, while the MDD subjects exhibited bilateral foci GM deficits in the dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons). Direct comparison between BD and MDD patients showed a focus of GM reduction in the right-sided dorsolateral prefrontal cortex (p < 0.05, corrected for multiple comparisons) and a trend (p < 0.10, corrected) toward left-sided GM deficits in the dorsolateral prefrontal cortex of MDD patients. When analyses were repeated with scanner site as a confounding covariate the finding of increased right anterior cingulate volumes in BD patients relative to controls remained statistically significant (p = 0.01, corrected for multiple comparisons). Conclusions: These findings reinforce the view that there are important pathophysiological distinctions between BD and MDD, and indicate that subtle dorsal anterior cingulate abnormalities may be relevant to the pathophysiology of BD.

Does the degree of smoking effect the severity of tardive dyskinesia? A longitudinal clinical trial

Background. - Tardive dyskinesia (TD) is a movement disorder observed after chronic neuroleptic treatment. Smoking is presumed to increase the prevalence of TD. The question of a cause-effect-relationship between smoking and TD, however, remains to be answered. Purpose of this study was to examine the correlation between the degree of smoking and the severity of TD with respect to differences caused by medication. Method. - We examined 60 patients suffering from schizophrenia and TD, We compared a clozapine-treated group With a group treated with typical neuroleptics. Movement disorders were assessed using the Abnormal-Involuntary-Movement-Scale and the technical device digital image processing, providing rater independent information on perioral movements. Results. - We found a strong correlation (.80 < r < .90, always p < .0001) between the degree of smoking and severity of TD. Repeated measurements revealed a positive correlation between changes in cigarette consumption and changes of the severity of TD (p < .0001). Analyses of covariance indicated a significant group-effect with a lower severity of TD in the clozapine-group compared to the typical-neuroleptics-group (p = .010). Interaction-analyses indicated a higher impact of smoking oil the severity of TD in the typical-neuroleptics-group compared to the clozapine-group (p = .033). Conclusion. - Concerning a possible cause-effect-relationship between smoking and TD, smoking is more of a general health hazard than neuroleptic exposure in terms of TD. (C) 2008 Elsevier Masson SAS. All rights reserved.

Radon-domain detection of the nipple and the pectoral muscle in mammograms

In this paper, methods are presented for automatic detection of the nipple and the pectoral muscle edge in mammograms via image processing in the Radon domain. Radon-domain information was used for the detection of straight-line candidates with high gradient. The longest straight-line candidate was used to identify the pectoral muscle edge. The nipple was detected as the convergence point of breast tissue components, indicated by the largest response in the Radon domain. Percentages of false-positive (FP) and false-negative (FN) areas were determined by comparing the areas of the pectoral muscle regions delimited manually by a radiologist and by the proposed method applied to 540 mediolateral-oblique (MLO) mammographic images. The average FP and FN were 8.99% and 9.13%, respectively. In the detection of the nipple, an average error of 7.4 mm was obtained with reference to the nipple as identified by a radiologist on 1,080 mammographic images (540 MLO and 540 craniocaudal views).

Palpebral fissure changes after monobloc frontofacial advancement in faciocraniosynostosis

There is virtually no literature on the effect of correction of syndromal faciocraniosynostosis with monobloc advancement on the palpebral fissure shape. Using image processing software, we measured the effect of monobloc advancement on the position of the upper and lower eyelids as well as the palpebral fissure slant in a series of 18 patients with syndromal faciocraniosynostosis who had undergone surgery for correction of orbital and midface hypoplasia. For both eyed of each patient, 3 variables were measured on the pre- and postoperative photographs: the linear distances between the upper and lower eyelid margins, the pupil center and the angle between the inner and outer canthi. The globe protrusion was also measured on axial computed tomography scans before and after surgery. The results indicate that the exorbitism reduction induced by monobloc advancement is accompanied by a diminution of the distance between both eyelids and the pupil center. However, the downward slant of the palpebral fissure is increased after surgery. The data suggest that the lower and upper eyelid retraction seen preoperatively in the majority of patients with faciocraniosynostosis tend to be corrected when the frontofacial region is advanced by the monobloc. On the other hand, the surgery tends to lower the outer canthus, increasing the negative slant of the fissure. The postoperative changes induced by the frontofacial monobloc advancement need to be taken into account when the surgery is going to be performed.

Using a cartographic modeling language to manipulate spectral satellite imagery

Land related information about the Earth's surface is commonIJ found in two forms: (1) map infornlation and (2) satellite image da ta. Satellite imagery provides a good visual picture of what is on the ground but complex image processing is required to interpret features in an image scene. Increasingly, methods are being sought to integrate the knowledge embodied in mop information into the interpretation task, or, alternatively, to bypass interpretation and perform biophysical modeling directly on derived data sources. A cartographic modeling language, as a generic map analysis package, is suggested as a means to integrate geographical knowledge and imagery in a process-oriented view of the Earth. Specialized cartographic models may be developed by users, which incorporate mapping information in performing land classification. In addition, a cartographic modeling language may be enhanced with operators suited to processing remotely sensed imagery. We demonstrate the usefulness of a cartographic modeling language for pre-processing satellite imagery, and define two nerv cartographic operators that evaluate image neighborhoods as post-processing operations to interpret thematic map values. The language and operators are demonstrated with an example image classification task.

Theory and applications of fuzzy Volterra integral equations

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formalism to fuzzy integral equations and shows that the resulting solution sets and attainability sets are fuzzy and far better descriptions of uncertain models involving integral equations. The investigation is restricted to Volterra type equations with mildly restrictive conditions, but the methods are capable of extensive generalization to other types and more general assumptions. The results are illustrated by integral equations relating to control models with fuzzy uncertainties.

High resolution 3-D imaging via multi-pass SAR

Spaceborne/airborne synthetic aperture radar (SAR) systems provide high resolution two-dimensional terrain imagery. The paper proposes a technique for combining multiple SAR images, acquired on flight paths slightly separated in the elevation direction, to generate high resolution three-dimensional imagery. The technique could be viewed as an extension to interferometric SAR (InSAR) in that it generates topographic imagery with an additional dimension of resolution. The 3-D multi-pass SAR imaging system is typically characterised by a relatively short ambiguity length in the elevation direction. To minimise the associated ambiguities we exploit the relative phase information within the set of images to track the terrain landscape. The SAR images are then coherently combined, via a nonuniform DFT, over a narrow (in elevation) volume centred on the 'dominant' terrain ground plane. The paper includes a detailed description of the technique, background theory, including achievable resolution, and the results of an experimental study.

Mapping glider habitat in dry eucalypt forests for Montreal Process indicator 1.1: Fragmentation of forest types

Accurate habitat mapping is critical to landscape ecological studies such as required for developing and testing Montreal Process indicator 1.1e, fragmentation of forest types. This task poses a major challenge to remote sensing, especially in mixedspecies, variable-age forests such as dry eucalypt forests of subtropical eastern Australia. In this paper, we apply an innovative approach that uses a small section of one-metre resolution airborne data to calibrate a moderate spatial resolution model (30 m resolution; scale 1:50 000) based on Landsat Thematic Mapper data to estimate canopy structural properties in St Marys State Forest, near Maryborough, south-eastern Queensland. The approach applies an image-processing model that assumes each image pixel is significantly larger than individual tree crowns and gaps to estimate crown-cover percentage, stem density and mean crown diameter. These parameters were classified into three discrete habitat classes to match the ecology of four exudivorous arboreal species (yellowbellied glider Petaurus australis, sugar glider P. breviceps, squirrel glider P. norfolcensis , and feathertail glider Acrobates pygmaeus), and one folivorous arboreal marsupial, the greater glider Petauroides volans. These species were targeted due to the known ecological preference for old trees with hollows, and differences in their home range requirements. The overall mapping accuracy, visually assessed against transects (n = 93) interpreted from a digital orthophoto and validated in the field, was 79% (KHAT statistic = 0.72). The KHAT statistic serves as an indicator of the extent that the percentage correct values of the error matrix are due to ‘true’ agreement verses ‘chance’ agreement. This means that we are able to reliably report on the effect of habitat loss on target species, especially those with a large home range size (e.g. yellow-bellied glider). However, the classified habitat map failed to accurately capture the spatial patterning (e.g. patch size and shape) of stands with a trace or sub-dominance of senescent trees. This outcome makes the reporting of the effects of habitat fragmentation more problematic, especially for species with a small home range size (e.g. feathertail glider). With further model refinement and validation, however, this moderateresolution approach offers an important, cost eff e c t i v e advancement in mapping the age of dry eucalypt forests in the region.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

Automated regional myocardial displacement for facilitating the interpretation of dobutamine echocardiography

Quantification of stress echocardiography may overcome the training requirements and subjective nature of visual wall motion score (WMS) assessment, but quantitative approaches may be difficult to apply and require significant time for image processing. The integral of long-axis myocardial velocity is displacement, which may be represented as a color map over the left ventricular myocardium. This study was designed to explore the feasibility and accuracy of measuring long-axis myocardial displacement, derived from tissue Doppler, for the detection of coronary artery disease (CAD) during dobutamine stress echocardiography (DBE). One hundred thirty patients underwent standard DBE, including 30 patients at low risk of CAD, 30 patients with normal coronary angiography (both groups studied to define normal ranges of displacement), and 70 patients who underwent coronary angiography in whom the accuracy of normal ranges was tested. Regional myocardial displacement was obtained by analysis of color tissue Doppler apical images acquired at peak stress. Displacement was compared with WMS, and with the presence of CAD by angiography. The analysis time was 3.2 +/- 1.5 minutes per patient. Segmental displacement was correlated with wall motion (normal 7.4 +/- 3.2 mm, ischemia 5.8 +/- 4.2 mm, viability 4.6 +/- 3.0 mm, scar 4.5 +/- 3.5 mm, p <0.001). Reversal of normal base-apex displacement was an insensitive (19%) but specific (90%) marker of CAD. The sum of displacements within each vascular territory had a sensitivity and specificity of 89% and 79%, respectively, for prediction of significant CAD, compared with 86% and 78%, respectively, for WMS (p = NS). The displacements in the basal segments had a sensitivity and specificity of 83% and 78%, respectively (p = NS). Regional myocardial displacement during DBE is feasible and offers a fast and accurate method for the diagnosis of CAD. (C),2002 by Excerpta Medica, Inc.

Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces

Combinatorial optimization problems share an interesting property with spin glass systems in that their state spaces can exhibit ultrametric structure. We use sampling methods to analyse the error surfaces of feedforward multi-layer perceptron neural networks learning encoder problems. The third order statistics of these points of attraction are examined and found to be arranged in a highly ultrametric way. This is a unique result for a finite, continuous parameter space. The implications of this result are discussed.