Senka Pantic

Gray level co-occurrence matrix texture analysis of germinal center light zone lymphocyte nuclei: physiology viewpoint with focus on apoptosis.

In our study we investigated the relationship between conventional morphometric indicators of nuclear size and shape (area and circularity) and the parameters of gray level co-occurrence matrix texture analysis (entropy, homogeneity, and angular second moment) in cells committed to apoptosis. A total of 432 lymphocyte nuclei images from the spleen germinal center light zones (cells in early stages of apoptosis) were obtained from eight healthy male guinea pigs previously immunized with sheep red blood cells (antigen). For each nucleus, area, circularity, entropy, homogeneity, and angular second moment were determined. All measured parameters of gray level co-occurrence matrix (GLCM) were significantly correlated with morphometric indicators of nuclear size and shape. The strongest correlation was observed between GLCM homogeneity and nuclear area (p < 0.0001, r(s) = 0.61). Angular second moment values were also highly significantly correlated with nuclear area (r(s)= 0.39, p < 0.0001). These results indicate that the GLCM method may be a powerful tool in evaluation of ultrastructural nuclear changes during early stages of the apoptotic process.

Complexity reduction of chromatin architecture in macula densa cells during mouse postnatal development.

To determine whether complexity of chromatin structure in kidney macula densa cells (MDC) decreases during postnatal development in mice.

Aging increases nuclear chromatin entropy of erythroid precursor cells in mice spleen hematopoietic tissue.

Despite recent advances in hematopoietic tissue research, effects of aging on hematopoietic erythroid precursor (EP) cells are unclear. In this article we present results suggesting that chromatin textural entropy of EP cells in mouse spleen increases with age, while chromatin homogeneity decreases. The experiment was conducted on a total of 32 male Swiss white mice. Spleen tissue was acquired from four age groups: 10 days, 1 month, 4 months, and 7 months old mice. A total of 640 randomly selected, nonoverlapping EP cell nuclei (20 per animal) were analyzed using the gray level co-occurrence matrix method. There was statistically highly significant difference between the age groups, both in chromatin entropy (ANOVA, F = 12.99, p < 0.0001) and in homogeneity (ANOVA, F = 7.05, p < 0.001). When the individual groups were compared (ANOVA post hoc test), statistical difference was detected in all group pairs, except between the animals 4 months and 7 months old, either in chromatin entropy or homogeneity. The detected increase of chromatin disorder in mouse juvenile period/early adulthood suggests that cell intrinsic factors such as epigenetic dysregulation and DNA damage accumulation may have an important role in EP cell aging.

Application of fractal and grey level co-occurrence matrix analysis in evaluation of brain corpus callosum and cingulum architecture.

This aim of this study was to assess the discriminatory value of fractal and grey level co-occurrence matrix (GLCM) analysis methods in standard microscopy analysis of two histologically similar brain white mass regions that have different nerve fiber orientation. A total of 160 digital micrographs of thionine-stained rat brain white mass were acquired using a Pro-MicroScan DEM-200 instrument. Eighty micrographs from the anterior corpus callosum and eighty from the anterior cingulum areas of the brain were analyzed. The micrographs were evaluated using the National Institutes of Health ImageJ software and its plugins. For each micrograph, seven parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, GLCM variance, fractal dimension, and lacunarity. Using the Receiver operating characteristic analysis, the highest discriminatory value was determined for inverse difference moment (IDM) (area under the receiver operating characteristic (ROC) curve equaled 0.925, and for the criterion IDM≤0.610 the sensitivity and specificity were 82.5 and 87.5%, respectively). Most of the other parameters also showed good sensitivity and specificity. The results indicate that GLCM and fractal analysis methods, when applied together in brain histology analysis, are highly capable of discriminating white mass structures that have different axonal orientation.

Discriminatory ability of fractal and grey level co-occurrence matrix methods in structural analysis of hippocampus layers

Fractal and grey level co-occurrence matrix (GLCM) analysis represent two mathematical computer-assisted algorithms that are today thought to be able to accurately detect and quantify changes in tissue architecture during various physiological and pathological processes. However, despite their numerous applications in histology and pathology, their sensitivity, specificity and validity regarding evaluation of brain tissue remain unclear. In this article we present the results indicating that certain parameters of fractal and GLCM analysis have high discriminatory ability in distinguishing two morphologically similar regions of rat hippocampus: stratum lacunosum-moleculare and stratum radiatum. Fractal and GLCM algorithms were performed on a total of 240 thionine-stained hippocampus micrographs of 12 male Wistar albino rats. 120 digital micrographs represented stratum lacunosum-moleculare, and another 120 stratum radiatum. For each image, 7 parameters were calculated: fractal dimension, lacunarity, GLCM angular second moment, GLCM contrast, inverse difference moment, GLCM correlation, and GLCM variance. GLCM variance (VAR) resulted in the largest area under the Receiver operating characteristic (ROC) curve of 0.96, demonstrating an outstanding discriminatory power in analysis of stratum lacunosum-moleculare (average VAR equaled 478.1 ± 179.8) and stratum radiatum (average VAR of 145.9 ± 59.2, p < 0.0001). For the criterion VAR ≤ 227.5, sensitivity and specificity were 90% and 86.7%, respectively. GLCM correlation as a parameter also produced large area under the ROC curve of 0.95. Our results are in accordance with the findings of our previous study regarding brain white mass fractal and textural analysis. GLCM algorithm as an image analysis method has potentially high applicability in structural analysis of brain tissue cytoarcitecture.

Nuclear entropy, angular second moment, variance and texture correlation of thymus cortical and medullar lymphocytes: Grey level co-occurrence matrix analysis

Grey level co-occurrence matrix analysis (GLCM) is a well-known mathematical method for quantification of cell and tissue textural properties, such as homogeneity, complexity and level of disorder. Recently, it was demonstrated that this method is capable of evaluating fine structural changes in nuclear structure that otherwise are undetectable during standard microscopy analysis. In this article, we present the results indicating that entropy, angular second moment, variance, and texture correlation of lymphocyte nuclear structure determined by GLCM method are different in thymus cortex when compared to medulla. A total of 300 thymus lymphocyte nuclei from 10 one-month-old mice were analyzed: 150 nuclei from cortex and 150 nuclei from medullar regions of thymus. Nuclear GLCM analysis was carried out using National Institutes of Health ImageJ software. For each nucleus, entropy, angular second moment, variance and texture correlation were determined. Cortical lymphocytes had significantly higher chromatin angular second moment (p < 0.001) and texture correlation (p < 0.05) compared to medullar lymphocytes. Nuclear GLCM entropy and variance of cortical lymphocytes were on the other hand significantly lower than in medullar lymphocytes (p < 0.001). These results suggest that GLCM as a method might have a certain potential in detecting discrete changes in nuclear structure associated with lymphocyte migration and maturation in thymus.

Age-related reduction of structural complexity in spleen hematopoietic tissue architecture in mice.

The effects of aging on structural complexity in hematopoietic tissue are unknown. In this work, in a mouse experimental model, we report the age-related reduction of spleen hematopoietic tissue (SHT) complexity. Spleen tissue was obtained from the total of 64 male Swiss albino mice divided into 8 age groups: newborns (0 days old), 10 days, 20 days, 30 days, 120 days, 210 days, 300 and 390 days old. SHT was stained using conventional hematoxylin/eosin, and DNA-binding toluidine blue dyes. Fractal dimension as an indicator of cellular complexity, and lacunarity as indicator of tissue heterogeneity were determined based on the binarized SHT micrographs. Results indicate that fractal dimension of mice spleen hematopoietic tissue decreases with age, while lacunarity increases. These changes/trends have been detected in SHT stained both with toluidine blue and conventional hematoxylin/eosin. Fractal dimension was negatively correlated with lacunarity. The detected reduction in complexity suggests that age-related structural changes are present in mouse SHT both in general tissue architecture and progenitor cell DNA.

Germinal Center Texture Entropy as Possible Indicator of Humoral Immune Response: Immunophysiology Viewpoint

PurposeIn this article, we present the results indicating that spleen germinal center (GC) texture entropy determined by gray-level co-occurrence matrix (GLCM) method is related to humoral immune response.ProceduresSpleen tissue was obtained from eight outbred male short-haired guinea pigs previously immunized by sheep red blood cells (SRBC). A total of 312 images from 39 germinal centers (156 GC light zone images and 156 GC dark zone images) were acquired and analyzed by GLCM method. Angular second moment, contrast, correlation, entropy, and inverse difference moment were calculated for each image. Humoral immune response to SRBC was measured using T cell-dependent antibody response (TDAR) assay.ResultsStatistically highly significant negative correlation was detected between light zone entropy and the number of TDAR plaque-forming cells (rs = −0.86, p < 0.01). The entropy decreased as the plaque-forming cells increased and vice versa. A statistically significant negative correlation was also detected between dark zone entropy values and the number of plaque-forming cells (rs = −0.69, p < 0.05).ConclusionsGerminal center texture entropy may be a powerful indicator of humoral immune response. This study is one of the first to point out the potential scientific value of GLCM image texture analysis in lymphoid tissue cytoarchitecture evaluation. Lymphoid tissue texture analysis could become an important and affordable addition to the conventional immunophysiology techniques.

Effects of Ghrelin on the Structural Complexity of Exocrine Pancreas Tissue Architecture

Recent studies have shown that ghrelin increases pancreatic exocrine secretion. However, the potential effects of ghrelin on the morphology of exocrine pancreas (EP) remain unknown. In this work, using fractal analysis, we demonstrate that centrally administered ghrelin increases structural complexity and tissue disorder in rat EP. The study was carried out on a total of 40 male Wistar rats divided into four groups (n = 10): ghrelin-treated animals (average age, 1.5 months), ghrelin-treated animals (8.5 months), and controls (1.5 and 8.5 months). The pancreas tissue sections were stained with hematoxylin/eosin and visualized by light microscopy. For each animal, the average values of tissue fractal dimension, lacunarity, as well as parameters of co-occurrence matrix texture, were determined using tissue digital micrographs. The results indicate that ghrelin administration increases EP fractal dimension and textural entropy, and decreases lacunarity, regardless of the age. To our knowledge, this is the first study to investigate the effects of ghrelin on the morphological properties of pancreatic tissue, and also the first to apply fractal and textural analysis methods in quantification of EP tissue architecture.

Screen viewing, body mass index, cigarette smoking and sleep duration in Belgrade University student population: results of an observational, cross-sectional study

BACKGROUND Subjects that spend more time working on computers or watching television could have a higher body mass index. AIM To assess the relationship between time spent in front of a screen and studying, body mass index (BMI), smoking, and sleep duration among university students. MATERIAL AND METHODS A cross-sectional study of 734 randomly selected students aged 21 ± 2 years (450 females) that responded an anonymous, structured questionnaire about time spent watching television or in front of a computer, time spent studying, number of daily hours of sleep, smoking habits and number of daily meals. Body mass index was also calculated for all subjects RESULTS Among males, the number of daily sleep hours, time spent working with computers and number of daily meals were significantly higher and time spent studying was significantly lower than females. Nonsmokers ate a significantly higher number of meals and spent less time watching television. No association was observed between time spent in front of a screen and number of sleep hours of body mass index. CONCLUSIONS Men and smokers spend more time working in computers. There is no association between body mass index and time spent in front of screens.