Texture Image Analysis in Differentiating Malignant from Benign Adrenal Cortical Tumors in Children and Adults

Objective: To investigate the possible role of chromatin texture parameters, nuclear morphology, DNA ploidy and clinical functional status in discriminating benign from malignant adrenocortical tumors (ACT). Patients and Methods: Forty-eight cases of clinically benign (n=40) and clinically malignant (n=8) ACT with a minimum of 5-years` follow-up were evaluated for chromatin texture parameters (run length, standard deviation, configurable run length, valley, slope, peak and other 21 Markovian features that describe the distribution of the chromatin in the nucleus), nuclear morphology (nuclear area, nuclear perimeter, nuclear maximum and minumum diameter, nuclear shape), and DNA ploidy. Nuclear parameters were evaluated in Feulgen-stained 5 mu m paraffin-sections analyzed using a CAS 200 image analyzer. Results: Since ACTs present different biological features in children and adults, patients were divided into two groups: children (<= 15 years) and adults (>15 years). In the group of children DNA ploidy presented a marginal significance (p=0.05) in discriminating ACTs. None of the parameters discriminated between malignant and benign ACT in the adult group. Conclusion: ACTs are uncommon and definitive predictive criteria for malignancy remain uncertain, particularly in children. Our data point to DNA content evaluated by image analysis as a new candidate tool for this challenging task. Texture image analysis did not help to differentiate malignant from benign adrenal cortical tumors in children and adults.

Centrilobular Fibrosis: An Underrecognized Pattern in Systemic Sclerosis

Background: The impressive association of lung involvement and gastroesophageal reflux in scleroderma raises the possibility of a cause-effect relationship. Objectives: To determine clinical, radiological and histopathological features of systemic sclerosis (SSc) patients according the presence or absence of centrilobular fibrosis (CLF). Methods: Twenty-eight SSc patients with lung involvement were submitted to open lung biopsy and the specimens classified for the presence of CLF (bronchocentric distribution of the lesions and intraluminal matter according to the classification of idiopathic interstitial pneumonia). HRCT, pulmonary function tests and esophageal analysis were also performed. Subsequently, cyclophosphamide was introduced for the nonspecific interstitial pneumonia subgroup and antireflux treatment was intensified for isolated CLF patients. Results: Isolated CLF was found in 21% of the biopsies and also found associated to nonspecific interstitial pneumonia in 84% of these patients. The other 3 cases had usual interstitial pneumonia, pulmonary hypertension and respiratory bronchiolitis-associated interstitial lung disease. The histopathological analysis revealed that all 6 patients with isolated CLF had the bronchocentric distribution and intraluminal basophilic content, with foreign bodies detected in one third of them. The central distribution of lung involvement on HRCT was found in 67% of these patients with a consistent patchy distribution (100%). Ground glass (67%) and consolidation (33%) were the predominant patterns found. The constant clinical finding in all isolated CLF cases was dyspnea, esophageal abnormalities and a moderate lung impairment (FVC: 63.83 +/- 16.31%; DLCO: 61.66 +/- 18.84%). Lung function parameters in isolated CLF patients remained stable after 1 year of exclusively intensive antireflux treatment (FVC, p = 0.23; DLCO, p = 0.59). Conclusions: The novel description of CLF pattern in SSc lung disease with peculiar histological, tomographic and clinical features will certainly contribute to a more appropriate therapeutic approach. Copyright (C) 2008 S. Karger AG, Basel

The effect of spatial definition on the allocation of clients to screening clinics

We compared four strategies for inviting 91,456 women aged 50-69 years to one of six clinics for mammography screening and 40,142 men aged 60-79 years to one of 10 clinics for abdominal aortic aneurysm (AAA) screening. The strategies were invitation to the clinic nearest to the client and invitation to the clinic nearest to the client's area of residence defined by census small area, postcode and local government area. For each strategy we calculated the expected demand at each clinic and the travel distances for clients. We found that when women were allocated to mammography clinics on the basis of the local government area instead of their individual address, expected demand at one clinic increased by 60%, and 19% of clients were invited to attend a more remote clinic, entailing 99,000 km of additional travel. Similar results were obtained for men allocated to AAA clinics by their postcode of residence instead of their individual address: 55% difference in expected demand, 13% to a more remote clinic and 60,000 km of extra travel. Allocation on the basis of small areas did not show such great differences, except for travel distance, which was about 5% higher for each clinic type. We recommend that allocation of clients to screening clinics be made according to residential address, that assessment of the location of clinics be based on distances between residences and nearest clinic, but that planning new locations for clinics be aided with spatial analysis tools using small area demographic and social data. (C) 1997 Elsevier Science Ltd.

Local dispersion of the Eucalyptus leaf beetle Chrysophtharta bimaculata (Coleoptera: Chrysomelidae), and implications for forest protection

1. Chrysophtharta bimaculata is a native chrysomelid species that can cause chronic defoliation of plantation and regrowth Eucalyptus forests in Tasmania, Australia. Knowledge of the dispersion pattern of C. bimaculata was needed in order to assess the efficiency of an integrated pest management (IPM) programme currently used for its control. 2. Using data from yellow flight traps, local populations of C. bimaculata adults were monitored over a season at spatial scales relevant to commercial forestry: within a 50-ha operational management unit (a forestry 'coupe') and between coupes. In addition, oviposition was monitored over a season at a subset of the between-coupe sites. 3. Dispersion indices (Taylor's Power Law and Iwao's Mean Crowding regression method) demonstrated that C. bimaculata adults were spatially aggregated within and between coupes, although the number of egg-batches laid at the between-coupe scale was uniform. Spatial autocorrelation analysis showed that trap-catches at the within-coupe level were similar (positively autocorrelated) to a radius distance of approximately 110 m, and then dissimilar (negatively autocorrelated) at approximately 250 m. At the between-coupe scale, no repeatable spatial autocorrelation patterns were observed. 4. For any individual site, rapid changes in beetle density were observed to be associated with loosely aggregated flights of beetles into and out of that site. Peak adult catches (> the weekly mean plus standard deviation trap-catch) for a site occurred for a period of 2.0 +/- 0.22 weeks at a time (n = 37), with normally only one or two peaks per site per season. Peak oviposition events for a site occurred on average 1.4 +/- 0.11 times per season and lasted 1.5 +/- 0.12 weeks. 5. Analysis of an extensive data set (n = 417) demonstrated that adult abundance at a site was positively correlated with egg density, but negatively correlated with tree damage (caused by conspecifics) and the presence of conspecific larvae. There was no relationship between adult abundance and a visual estimate of the amount of young foliage on trees. 6. Adults of C. bimaculata are show n to occur in relatively small, mobile aggregations. This means that pest surveys must be both regular (less than 2 weeks apart) and intensive (with sampling points no more than 150 m apart) if beetle populations are to be monitored with confidence. Further refinement of the current IPM strategy must recognize the problems posed by this temporal and spatial patchiness, particularly with regard to the use of biological insecticides, such as Bacillus thuringiensis, for which only a very short operational window exists.

From EEG to BOLD: Brain mapping and estimating transfer functions in simultaneous EEG-fMRI acquisitions

Simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) aims to disentangle the description of brain processes by exploiting the advantages of each technique. Most studies in this field focus on exploring the relationships between fMRI signals and the power spectrum at some specific frequency bands (alpha, beta, etc.). On the other hand, brain mapping of EEG signals (e.g., interictal spikes in epileptic patients) usually assumes an haemodynamic response function for a parametric analysis applying the GLM, as a rough approximation. The integration of the information provided by the high spatial resolution of MR images and the high temporal resolution of EEG may be improved by referencing them by transfer functions, which allows the identification of neural driven areas without strong assumptions about haemodynamic response shapes or brain haemodynamic`s homogeneity. The difference on sampling rate is the first obstacle for a full integration of EEG and fMRI information. Moreover, a parametric specification of a function representing the commonalities of both signals is not established. In this study, we introduce a new data-driven method for estimating the transfer function from EEG signal to fMRI signal at EEG sampling rate. This approach avoids EEG subsampling to fMRI time resolution and naturally provides a test for EEG predictive power over BOLD signal fluctuations, in a well-established statistical framework. We illustrate this concept in resting state (eyes closed) and visual simultaneous fMRI-EEG experiments. The results point out that it is possible to predict the BOLD fluctuations in occipital cortex by using EEG measurements. (C) 2010 Elsevier Inc. All rights reserved.

White matter microstructure underlying default mode network connectivity in the human brain

Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved

Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Effects of phonophoresis with Arnica montana onto acute inflammatory process in rat skeletal muscles: An experimental study

This study aimed at verifying the effects of phonophoresis associated with Arnica montana on the acute phase of an inflammatory muscle lesion. Forty Wistar male rats (300 +/- 50 g), of which the Tibialis Anterior muscle was surgically lesioned, were divided into four groups (n = 10 each): control group received no treatment; the ultrasound group (US) was treated in pulsed mode with 1-MHz frequency, 0.5 W/cm(2) intensity (spatial and temporal average - SATA), duty cycle of 1: 2 (2 ms on, 4 ms off, 50%), time of application 3 min per session, one session per day, for 3 days; the phonophoresis or ultrasound plus arnica (US+A) group was treated with arnica with the same US parameters plus arnica gel; and the arnica group (A) was submitted to massage with arnica gel, also for 3 min, once a day, for 3 days. Treatment started 24 h after the surgical lesion. On the 4th day after lesion creation, animals were sacrificed and sections of the lesioned, inflamed muscle were removed for quantitative (mononuclear and polymorphonuclear cell count) and qualitative histological analysis. Collected data from the 4 groups were statistically analyzed and the significance level set at p < 0.05. Results show higher mononuclear cell density in all three treated groups with no significant difference between them, but values were significantly different (p < 0.0001) when compared to control group`s. As to polymorphonuclear cell density, significant differences were found between control group (p = 0.0134) and US, US+A and A groups; the arnica group presented lesser density of polymorphonuclear cells when compared (p = 0.0134) to the other groups. No significant difference was found between US and US+A groups. While the massage with arnica gel proved to be an effective anti-inflammatory on acute muscle lesion in topic use, these results point to ineffectiveness of Arnica montana phonophoresis, US having seemingly checked or minimized its anti-inflammatory effect. (C) 2008 Elsevier B. V. All rights reserved.

Spatial learning ability of rats following differing levels of exposure to alcohol during early postnatal life

Rats exposed to a relatively high dose (7.5 g/kg body weight) of alcohol on either the fifth or tenth postnatal day of age have been reported to have long-lasting deficits in spatial learning ability as tested on the Morris water maze task. The question arises concerning the level of alcohol required to achieve this effect. Wistar rats were exposed to either 2, 4 or 6 g/kg body weight of ethanol administered as a 10% solution. This ethanol was given over an 8-h period on the fifth postnatal day of age by means of an intragastric cannula. Gastrostomy controls received a 5% sucrose solution substituted isocalorically for the ethanol. Another set of pups raised by their mother were used as suckle controls. All surgical procedures were carried out under halothane vapour anaesthesia. After the artificial feeding regimes all pups were returned to lactating dams and weaned at 21 days of age. The spatial learning ability of these rats was tested in the Morris water maze when they were between 61-64 days of age. This task requires the rats to swim in a pool containing water made opaque and locate and climb onto a submerged platform. The time taken to accomplish this is known as the escape latency. Each rat was subjected to 24 trials over 3 days of the test period. Statistical analysis of the escape latency data revealed that the rats given 6 g/kg body weight of ethanol had significant deficits in their spatial learning ability compared with their control groups. However, there was no significant difference in spatial learning ability for the rats given either 2 or 4 g/kg body weight of ethanol compared with their respective gastrostomy or suckle control animals. We concluded that ethanol exposure greater than 4 g/kg over an 8-h period to 5-day-old rats is required for them to develop long-term deficits in spatial learning behaviour. (C) 1998 Elsevier Science Inc.

Wilson`s disease: two treatment modalities. Correlations to pretreatment and posttreatment brain MRI

Brain magnetic resonance imaging (MRI) studies on Wilson`s disease (WD) show lack of correlations between neurological and neuroimaging features. Long-term follow-up reports with sequential brain MRI in patients with neurological WD comparing different modalities of treatment are scarce. Eighteen patients with neurological WD underwent pretreatment and posttreatment brain MRI scans to evaluate the range of abnormalities and the evolution along these different periods. All patients underwent at least two MRI scans at different intervals, up to 11 years after the beginning of treatment. MRI findings were correlated with clinical picture, clinical severity, duration of neurological symptoms, and treatment with two different drugs. Patients were divided into two groups according to treatment: d-penicillamine (D-P), zinc (Zn), and Zn after the onset of severe intolerance to D-P. MRI scans before treatment showed, in all patients, hypersignal intensity lesions on T2- and proton-density-weighted images bilaterally and symmetrically at basal nuclei, thalamus, brain stem, cerebellum, brain cortex, and brain white matter. The most common neurological symptoms were: dysarthria, parkinsonism, dystonia, tremor, psychiatric disturbances, dysphagia, risus sardonicus, ataxia, chorea, and athetosis. From the neurological point of view, there was no difference on the evolution between the group treated exclusively with D-P and the one treated with Zn. Analysis of MRI scans with longer intervals after the beginning of treatment depicted a trend for neuroimaging worsening, without neurological correspondence, among patients treated with Zn. Neuroimaging pattern of evolution was more favorable for the group that received exclusively D-P.

Identification of FAM46D as a novel cancer/testis antigen using EST data and serological analysis

Cancer/testis Antigens (CTAs) are immunogenic proteins with a restricted expression pattern in normal tissues and aberrant expression in different types of tumors being considered promising candidates for immunotherapy. We used the alignment between EST sequences and the human genome sequence to identify novel CT genes. By examining the EST tissue composition of known CT clusters we defined parameters for the selection of 1184 EST clusters corresponding to putative CT genes. The expression pattern of 70 CT gene candidates was evaluated by RT-PCR in 21 normal tissues, 17 tumor cell lines and 160 primary tumors. We were able to identify 4 CT genes expressed in different types of tumors. The presence of antibodies against the protein encoded by 1 of these 4 CT genes (FAM46D) was exclusively detected in plasma samples from cancer patients. Due to its restricted expression pattern and immunogenicity FAM46D represents a novel target for cancer immunotherapy. (c) 2009 Elsevier Inc. All rights reserved.

Using frequency-doubling perimetry to detect optic neuropathy in patients with Graves` orbitopathy

to test the ability of frequency-doubling technology (FDT) perimetry to detect dysthyroid optic neuropathy (DON). Fifteen eyes of 15 patients with DON and 15 healthy control eyes were studied. Eligible eyes had a diagnosis of DON based on visual field abnormalities on standard automated perimetry and had visual acuity better than 20/30. FDT testing was performed using both the C-20-5 screening test and the C-20 full-threshold test. Normal and DON eyes were compared with regard to FDT mean sensitivity. Sensitivity ranges were 40.0%-86.7% for the screening test, and 53.3%-100.0% (total deviation) and 20.0-93.3 (pattern deviation) for the C-20 threshold test. The corresponding specificity ranges were 86.7-100.0, 33.3-93.3, and 26.7-100.0, respectively. The best sensitivity/specificity ratios were for one abnormal point depressed < 5% in the screening test (86.7%/86.7%), one point depressed < 1% in the total deviation analysis (80.0%/86.7%), and one point depressed < 2% in the pattern deviation analysis (80.0%/86.7%). DON eyes presented significantly lower than normal average sensitivity in the central, pericentral, and peripheral areas. FDT perimetry is a useful screening tool for DON in eyes with normal or only slightly reduced visual acuity.

Primary ciliary dyskinesia: evaluation using cilia beat frequency assessment via spectral analysis of digital microscopy images

Olm MA, Kogler JE Jr, Macchione M, Shoemark A, Saldiva PH, Rodrigues JC. Primary ciliary dyskinesia: evaluation using cilia beat frequency assessment via spectral analysis of digital microscopy images. J Appl Physiol 111: 295-302, 2011. First published May 5, 2011; doi:10.1152/japplphysiol.00629.2010.-Ciliary beat frequency (CBF) measurements provide valuable information for diagnosing of primary ciliary dyskinesia (PCD). We developed a system for measuring CBF, used it in association with electron microscopy to diagnose PCD, and then analyzed characteristics of PCD patients. 1 The CBF measurement system was based on power spectra measured through digital imaging. Twenty-four patients suspected of having PCD (age 1-19 yr) were selected from a group of 75 children and adolescents with pneumopathies of unknown causes. Ten healthy, nonsmoking volunteers (age >= 17 yr) served as a control group. Nasal brush samples were collected, and CBF and electron microscopy were performed. PCD was diagnosed in 12 patients: 5 had radial spoke defects, 3 showed absent central microtubule pairs with transposition, 2 had outer dynein arm defects, 1 had a shortened outer dynein arm, and 1 had a normal ultrastructure. Previous studies have reported that the most common cilia defects are in the dynein arm. As expected, the mean CBF was higher in the control group (P < 0.001) and patients with normal ultrastructure (P < 0.002), than in those diagnosed with cilia ultrastructural defects (i.e., PCD patients). An obstructive ventilatory pattern was observed in 70% of the PCD patients who underwent pulmonary function tests. All PCD patients presented bronchial wall thickening on chest computed tomography scans. The protocol and diagnostic techniques employed allowed us to diagnose PCD in 16% of patients in this study.

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.