Cytoarchitectureal changes in hippocampal subregions of the NZB/W F1 mouse model of lupus.

Over 50% of clinical patients affected by the systemic lupus erythematosus disease display impaired neurological cognitive functions and psychiatric disorders, a form called neuropsychiatric systemic lupus erythematosus. Hippocampus is one of the brain structures most sensitive to the cognitive deficits and psychiatric disorders related to neuropsychiatric lupus. The purpose of this study was to compare, layer by layer, neuron morphology in lupus mice model NZB/W F1 versus Wild Type mice. By a morphometric of cells identified on Nissl-stained sections, we evaluated structural alterations between NZB/W F1 and Wild Type mice in seven hippocampal subregions: Molecular dentate gyrus, Granular dentate gyrus, Polymorph dentate gyrus, Oriens layer, Pyramidal layer, Radiatum layer and Lacunosum molecular layer. By principal component analysis we distinguished healthy Wild Type from NZB/W F1 mice. In NZB/W F1 mice hippocampal cytoarchitecture, the neuronal cells resulted larger in size and more regular than those of Wild Type. In NZB/W F1, neurons were usually denser than in WT. The Pyramidal layer neurons were much denser in Wild Type than in NZB/W F1. Application of principal component analysis, allowed to distinguish NZB/W F1 lupus mice from healthy, showing as NZBW subjects presented a scattered distribution and intrasubject variability. Our results show a hypertrophy of the NZB/W F1 hippocampal neurons associated with an increase in perikaryal size within the CA1, CA2, CA3 region and the DG. These results help advance our understanding on hippocampal organization and structure in the NZB/W F1 lupus model, suggesting the hypothesis that the different subregions could be differentially affected in neuropsychiatric systemic lupus erythematosus disease. Leveraging an in-depth analysis of the morphology of neural cells in the hippocampal subregions and applying dimensionality reduction using PCA, we propose an efficient methodology to distinguish pathological NZBW mice from WT mice."

Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains.

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies.

An Ultrasonographic Multiparametric Carotid Plaque Risk Index Associated with Cerebrovascular Symptomatology: A Study Comparing Color Doppler Imaging and Contrast-Enhanced Ultrasonography.

BACKGROUND AND PURPOSE: Various ultrasonographic features of carortid plaques have been associated with the occurence of stroke, highlighting the need for multi-parametric assessment of plaque's vulnerability. Our aim was to compare ultrasonographic multiparametric indices using color Doppler imaging and contrast-enhanced sonography between symptomatic and asymptomatic carotid plaques. MATERIALS AND METHODS: This was a cross-sectional observational study recruiting 54 patients (72.2% male; median age, 61 years) undergoing sonography and contrast-enhanced sonography. Patients were included if a moderately or severely stenotic internal carotid artery plaque was detected, with the plaque being considered symptomatic if it was ipsilateral to a stroke occuring within the last 6 months. A vulnerability index, previously described by Kanber et al, combined the degree of stenosis, gray-scale median, and a quantitative measure of surface irregularities (surface irregularity index) derived from color Doppler imaging and contrast-enhanced ultrasonography, resulting in 2 vulnerability indices, depending on the surface irregularity index used. Mann-Whitney U and t tests were used to compare variables between groups, and receiver operating characteristic curves were used to compare diagnostic accuracy. RESULTS: Sixty-two plaques were analyzed (50% symptomatic), with a mean degree of stenosis of 68.9%. Symptomatic plaques had a significantly higher degree of stenosis (mean, 74.7% versus 63.1%; P < .001), a lower gray-scale median (13 versus 38; P = .001), and a higher Kanber vulnerability index based both on color Doppler imaging (median, 61.4 versus 16.5; P < .001) and contrast-enhanced ultrasonography (median, 88.6 versus 25.2; P < .001). The area under the curve for the detection of symptomatic plaques was 0.772 for the degree of stenosis alone, 0.783 for the vulnerability index-color Doppler imaging, and 0.802 for the vulnerability index-contrast-enhanced ultrasonography, though no statistical significance was achieved. CONCLUSIONS: Symptomatic plaques had a higher degree of stenosis, lower gray-scale median values, and higher values of the Kanber vulnerability index using both color Doppler imaging and contrast-enhanced ultrasonography for plaque surface delineation.

Detection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease.

Celiac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic computer-based method for the detection of goblet cells from confocal endoscopy images, whose density changes in case of pathological tissue. After a manual selection of a suitable region of interest, the candidate columnar and goblet cells' centers are first detected and the cellular architecture is estimated from their position using a Voronoi diagram. The region within each Voronoi cell is then analyzed and classified as goblet cell or other. The results suggest that our method is able to detect and label goblet cells immersed in a columnar epithelium in a fast, reliable and automatic way. Accepting 0.44 false positives per image, we obtain a sensitivity value of 90.3%. Furthermore, estimated and real goblet cell densities are comparable (error: 9.7 ± 16.9%, correlation: 87.2%, R(2) = 76%).

Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease.

Celiac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic method for villi detection from confocal endoscopy images, whose appearance change in case of villous atrophy. Starting from a set of manual seeds, a first rough segmentation of the villi is obtained by means of mathematical morphology operations. A merge and split procedure is then performed, to ensure that each seed originates a different region in the final segmentation. A border refinement process is finally performed, evolving the shape of each region according to local gradient intensities. Mean and median Dice coefficients for 290 villi originating from 66 images when compared to manually obtained ground truth are 80.71% and 87.96% respectively.

Estimation of prenatal aorta intima-media thickness from ultrasound examination.

Prenatal events such as intrauterine growth restriction and increased cardiovascular risk in later life have been shown to be associated with an increased intima-media thickness (aIMT) of the abdominal aorta in the fetus. In order to assess and manage atherosclerosis and cardiovascular disease risk in adults and children, in recent years the measurement of abdominal and carotid artery thickness has gained a growing appeal. Nevertheless, no computer aided method has been proposed for the analysis of prenatal vessels from ultrasound data, yet. To date, these measurements are being performed manually on ultrasound fetal images by skilled practitioners. The aim of the presented study is to introduce an automatic algorithm that identifies abdominal aorta and estimates its diameter and aIMT from routine third trimester ultrasonographic fetal data.The algorithm locates the aorta, then segments it and, by modeling the arterial wall longitudinal sections by means of a gaussian mixture, derives a set of measures of the aorta diameter (aDiam) and of the intima-media thickness (aIMT). After estimating the cardiac cycle, the mean diameter and the aIMT at the end-diastole phase are computed.Considering the aIMT value for each subject, the correlation between automatic and manual end-diastolic aIMT measurements is 0.91 in a range of values 0.44-1.10 mm, corresponding to both normal and pathological conditions. The automatic system yields a mean relative error of 19%, that is similar to the intra-observer variability (14%) and much lower that the inter-observer variability (42%).The correlation between manual and automatic measurements and the small error confirm the ability of the proposed system to reliably estimate aIMT values in prenatal ultrasound sequences, reducing measurement variability and suggesting that it can be used for an automatic assessment of aIMT.

Contrast-enhanced ultrasound findings in soft-tissue lesions: preliminary results.

OBJECTIVES: There is currently no widely available, minimally invasive first-level examination that allows physicians to identify soft-tissue lesions that are likely to be malignant. The aim of this pilot study was to explore the potential suitability of dynamic contrast-enhanced ultrasound (DCE-US) for this purpose. MATERIALS AND METHODS: 23 patients were referred to the Veneto Oncological Institute for work-up of superficial soft-tissue lesions. Fourteen lesions were examined with CEUS and enhancement kinetics was analyzed. Subsequently, all lesions were surgically removed and subjected to histological analysis. RESULTS: The 14 lesions included in the study were histologically classified as malignant (n = 7) or benign (n = 7, including 3 schwannomas). A statistically significant difference between benign and malignant lesions was found in terms of mean times to peak enhancement intensity (p = 0.03) but not mean filling times (FT). When schwannomas were analyzed as a separate group, their mean FT was found to be significantly different from that of the other benign lesions (p = 0.001) and from that of the group comprising other benign lesions as well as malignant lesions (p < 0.005). CONCLUSIONS: CEUS with analysis of contrast-enhancement kinetics is a relatively low-cost, minimally invasive imaging technique, which appears to be a potentially effective first-level method for identifying suspicious soft-tissue masses.

3-D retinal surface inference: stereo or monocular fundus camera?

Three-dimensional (3-D) imaging of the eye fundus, and in particular of the optic disc, is widely used to assess glaucoma progression over time. In the literature, 3-D images of the optic disc have been obtained from stereo and monocular fundus cameras. While stereo systems are the gold standard for optic disc examination, monocular systems are less expensive, and therefore of more practical use. This stimulated a thorough investigation of the limits and advantages of these two imaging modalities. Our conclusion is that monocular imaging is generally not suitable for 3-D estimation. This is attributed to the fact that monocular systems do not allow a change in the vantage point from which the retinal surface is observed, despite variations in the relative pose between the eye and the fundus camera. To validate this analysis we carry out several experiments on both stereo and monocular fundus cameras with standard 3-D reconstruction algorithms. Furthermore, we devise a calibration procedure to quantify experimentally the highest accuracy achievable with a stereo system.

A new computerized method for the assessment of skin lesions in localized scleroderma.

OBJECTIVE: Up to now, no validated tools are in use for the assessment of the skin lesions in localized scleroderma (LS). The aim of this study is to evaluate the performance of a new computerized skin score (CSS) method for the measurement of circumscribed lesions in LS. METHODS: The study consisted of three phases: set up of the CSS technique, measurement of target lesions of LS patients, assessment of intra- and inter-rater reliability. The CSS technique consists in delimitating the indurate lesion on an adhesive transparent film, transferring it over a cardboard and then calculating the affected area with a specifically created software. The technique was explained to a panel of 10 physicians with different expertise in LS (three paediatric rheumatologists, two dermatologists, five paediatric residents). All participants, singularly and blindly to the others, examined 10 consecutive patients twice after a time interval of at least 6 h. The intra-observer variability was evaluated by the repeatability coefficient and the inter-rater reliability by the intra-class correlation coefficient (ICC). RESULTS: The repeatability coefficients were good, ranging between 1.90 and 7.03. The mean values of skin scores were not significantly different among the examiners. The ICC for indurate area calculation were high in both the experts (0.97) and the residents (0.91-0.94). CONCLUSIONS: CSS has shown to be a reliable method to assess the skin lesions in patients with LS. It is reproducible, easy to use and, with the support of the CSS software, applicable worldwide.

Detecting false vessel recognitions in retinal fundus analysis.

Automatic tracking of blood vessels in images of retinal fundus is an important and non-invasive procedure for the diagnosis of many diseases. Tracking techniques often present a high rate of false positives. This paper presents six methods to discriminate false detections from true positives, each based on a different model of the vessel. They describe a candidate vessel in terms of its average geometric and grayscale properties considered along the full trajectory of the vessel itself. The rationale is that false vessels are caused by the small scale of the tracking algorithm necessary during the tracking phase. Once tracking has been completed, we can gather information from the full vessel trajectory and solve ambiguities that cannot be fixed during tracking. We apply Fisher linear discriminant analysis to these features to get the desired discrimination. Results on 28 images show satisfactory rejection of false positives and better results when using more complex models.

A new system for the automatic estimation of endothelial cell density in donor corneas.

AIMS: The problem of automatic estimation of endothelial cell density from microscopy images in donor corneas was addressed. METHODS: The spatial frequencies contained in digital endothelium images are extracted with a two dimension discrete Fourier transform (DFT) technique. A circular band in the DFT of the images is shown to contain the frequency information related to the cell density. An algorithm for reliably recovering this spatial frequency information and for extracting from it an estimate of endothelial cell density has been developed and implemented in a computer program. An evaluation was performed on a data set containing 100 donor corneas, by comparing automatic values with manual counts performed by three eye bank experts on two images for each cornea. RESULTS: The mean difference of automatic densities v manual ones was 14 cells/mm(2) (0.9%), with a standard deviation of 119 cells/mm(2) (5.1%) and mean absolute difference of 92 cells/mm(2) (3.9%). The ANOVA based overall inter-rater reliability was 0.935. The algorithm was also capable of identifying all non-processable images. Running times were in the order of 1-2 seconds per image. CONCLUSION: A new algorithm was developed for the fully automatic estimation of endothelial cell density. The results of a clinical evaluation on 100 corneas suggest that it is capable of reliably estimating endothelium cell density in donor corneas.

Detection of optic disc in retinal images by means of a geometrical model of vessel structure.

We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a geometrical parametric model was proposed, where two of the model parameters are the coordinates of the OD center. Using as experimental data samples of vessel centerline points and corresponding vessel directions, provided by any vessel identification procedure, model parameters were identified by means of a simulated annealing optimization technique. These estimated values provide the coordinates of the center of OD. A Matlab prototype implementing this method was developed. An evaluation of the proposed procedure was performed using the set of 81 images from the STARE project, containing images from both normal and pathological subjects. The OD position was correctly identified in 79 out of 81 images (98%), even in rather difficult pathological situations.