Кафедра гістології, цитології та ембріології
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Item Fractal analysis of the cerebral cortex and white matter for quantitative assessment of age-related brain atrophy in men and women(Sivas Cumhuriyet University, 2023-10) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrItem Fractal analysis of brain Magnetic Resonance images: a quantitative assessment of brain aging in men and women(Ordu University, 2023-07) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrItem Quantitative characterization of age-related atrophic changes in cerebral hemispheres: A novel “contour smoothing” fractal analysis method(Elsevier, 2023) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrBackground: Quantitatively assessing age-related atrophic changes in cerebral hemispheres remains a crucial challenge, particularly in distinguishing between normal and pathological brain atrophy caused by neurodegenerative diseases. In this study, we introduced a new fractal analysis algorithm, referred to as the “contour smoothing” method, to quantitatively characterize age-related atrophic changes in cerebral hemispheres. Materials and methods: MRI scans from 100 healthy individuals (44 males, 56 females), aged 18–86 (mean age 41.72 ± 1.58), were analyzed. We used two fractal analysis methods: the novel “contour smoothing” method (with stages: 1–6, 1–5, 2–6, 1–4, 2–5) and the classical “box-counting” method to assess cerebral cortex pial surface contours. Results: Fractal dimensions obtained using the “box-counting” method showed weak or statistically insignificant correlations with age. Conversely, fractal dimensions derived from the “contour smoothing” method exhibited significant age-related correlations. The “contour smoothing” method with 1–4 stages proved more suitable for quantifying atrophic changes. The average fractal dimension for 1–4 coronal sections was 1.402 ± 0.005 (minimum 1.266, maximum 1.490), and for all five tomographic sections, it was 1.415 ± 0.004 (minimum 1.278, maximum 1.514). These fractal dimensions exhibited the strongest correlations with age: r = 0.709 (p <0.001) and r = 0.669 (p < 0.001), respectively. Conclusion: The “contour smoothing” fractal analysis method introduced in this study can effectively examine cerebral hemispheres to detect and quantify age-related atrophic changes associated with normal or pathological aging. This method holds promise for clinical application in diagnosing neurodegenerative disorders, such as Alzheimer’s disease.Item Fractal dimension of skeletonized MR images as a measure of cerebral hemispheres spatial complexity(2022) Maryenko, Nataliia; Stepanenko, OleksandrIn recent decades, fractal analysis has been increasingly used in various scientific fields, including neuroscience; this method of mathematical analysis allows you to quantify the space filling degree of the studied object and the degree of its spatial configuration complexity. The aim of the study was to determine the values of the fractal dimension of the cerebral hemispheres using fractal analysis of skeletonized magnetic resonance brain images. The present study used magnetic resonance brain images of 100 relatively healthy individuals (who had no structural changes in the brain) of both sexes (56 women, 44 men) aged 18-86 years (mean age 41.72±1.58 years). 5 tomographic sections of each brain were studied. The 1st coronal tomographic section was located at the level of the most anterior points of the temporal lobes, the 2nd - at the level of the mammillary bodies, the 3rd - at the level of the quadrigeminal plate, the 4th - at the level of the splenium of corpus callosum. The axial tomographic section was located at the level of the thalamus. Fractal analysis of skeletonized images was performed using box counting method. The obtained data were processed using generally accepted statistical methods. The average, minimum and maximum values of the fractal dimension of different tomographic sections were the following: 1st coronal section - 1.207±0.003 (1.147÷1.277), 2nd coronal section - 1.162±0.003 (1.077÷1.243), 3rd coronal section - 1.156±0.003 (1.094÷1.224), 4th coronal section - 1.158±0.003 (1.109÷1.218), axial section - 1.138±0.002 (1.079÷1.194). The average value of the fractal dimension of the five tomographic sections was 1.164±0.002 (1.126÷1.209), and the average value of the fractal dimension of the four coronal sections was 1.171±0.002 (1.122÷1.219). Fractal analysis of skeletonized images of the cerebral hemispheres allows to quantify the features of the topology and complexity of the spatial configuration of the cerebral hemispheres. The value of the fractal dimension can be influenced by the anatomical features of the studied areas of the brain, individual anatomical features, as well as atrophic and other pathological changes that lead to changes in the shape of the cerebral hemispheres. The values of the fractal dimension of skeletonized brain images tend to decrease with age. Coronal tomographic sections are the most representative for characterizing age-related atrophic changes. Fractal analysis of skeletonized images of the cerebral hemispheres can be used to diagnose diseases of the nervous system, and the results of the present study can be used as norm criteria.Item Fractal analysis of anatomical structures linear contours: modified Caliper method vs Box counting method(2022) Maryenko, Nataliia; Stepanenko, OleksandrFractal analysis estimates the metric dimension and complexity of the spatial configuration of different anatomical structures. This allows the use of this mathematical method for morphometry in morphology and clinical medicine. Two methods of fractal analysis are most often used for fractal analysis of linear fractal objects: the Box counting method (Grid method) and the Caliper method (Richardson's method, Perimeter stepping method, Ruler method, Divider dimension, Compass dimension, Yard stick method). The aim of the research is a comparative analysis of two methods of fractal analysis - Box counting method and author's modification of Caliper method for fractal analysis of linear contours of anatomical structures. A fractal analysis of three linear fractals was performed: an artificial fractal - a Koch snowflake and two natural fractals - the outer contours of the pial surface of the human cerebellar vermis cortex and the cortex of the cerebral hemispheres. Fractal analysis was performed using the Box counting method and the author's modification of the Caliper method. The values of the fractal dimension of the artificial linear fractal (Koch snowflakes) obtained by the Caliper method coincide with the true value of the fractal dimension of this fractal, but the values of the fractal dimension obtained by the Box counting method do not match the true value of the fractal dimension. Therefore, fractal analysis of linear fractals using the Caliper method allows you to get more accurate results than the Box counting method. The values of the fractal dimension of artificial and natural fractals, calculated using the Box counting method, decrease with increasing image size and resolution; when using the Caliper method, fractal dimension values do not depend on these image parameters. The values of the fractal dimension of linear fractals, calculated using the Box counting method, increase with increasing width of the linear contour; the values calculated using the Caliper method do not depend on the contour line width. Thus, for the fractal analysis of linear fractals, preference should be given to the Caliper method and its modifications.Item Comparative analysis of fractal dimensions of human cerebellum: impact of image preprocessing and fractal analysis methods(2022) Maryenko, Nataliia; Stepanenko, OleksandrThe aim: To compare the values of the fractal dimensions of human cerebellum obtained using different algorithms of image preprocessing and different methods of fractal analysis. Materials and methods: The study involved 120 people without structural changes in the brain (age 18-86 years, 55 men and 65 women). T1- and T2-weighted MR brain images were studied. Fractal analysis was performed using box counting and pixel dilatation methods. Fractal dimensions of cerebellar tissue as a whole, cerebellar cortex and its individual layers, cerebellar white matter were measured and compared to each other and to fractal dimension of cerebellar white matter determined in cadaveric cerebella. Results: It was no significant difference between fractal dimension values of cerebellar tissue as a whole measured on T1 and T2 weighted magnetic resonance images of cerebellum, and fractal dimension values measured on the same images using different methods of fractal analysis – pixel dilatation and box counting. T2 weighted images are preferable for fractal analysis of different components of cerebellar tissue. Segmentation according to pixel luminance is the preferable image preprocessing method for fractal analysis of cerebellar cortex as a whole, individual cortical layers and cerebellar tissue as a whole; skeletonizing of cerebellar magnetic resonance images is the preferable method of the image preprocessing for fractal analysis of cerebellar white matter. Conclusions: The algorithm of image preprocessing, magnetic resonance imaging sequence and method of fractal analysis should be chosen according to aim of quantitative study of cerebellar magnetic resonance images and features of the studied structure of cerebellum.Item Fractal analysis of images in medicine and morphology: basic principles and methodologies(ДДМУ, 2021) Maryenko, Nataliia; Stepanenko, OleksandrItem Fractal dimension of external linear contour of human cerebellum (magnetic resonance imaging study)(2021) Maryenko, Nataliia; Stepanenko, OleksandrFractal analysis is a method of mathematical analysis, which provides quantitative assessment of the spatial configuration complexity of the anatomical structures and may be used as a morphometric method. The purpose of the study was to determine the values of the fractal dimension of the outer linear contour of human cerebellum by studying the magnetic resonance images of the brain using the authors' modification of the caliper method and compare to the values determined using the box counting method. Brain magnetic resonance images of 30 relatively healthy persons aged 18-30 years (15 men and 15 women) were used in the study. T2-weighted digital magnetic resonance images were studied. The midsagittal MR sections of the cerebellar vermis were investigated. The caliper method in the author's modification was used for fractal analysis. The average value of the fractal dimension of the linear contour of the cerebellum, determined using the caliper method, was 1.513±0.008 (1.432¸1.600). The average value of the fractal dimension of the linear contour of the cerebellum, determined using the box counting method, was 1.530±0.010 (1.427¸1.647). The average value of the fractal dimension of the cerebellar tissue as a whole, determined using the box counting method, was 1.760±0.006 (1.674¸1.837). The values of the fractal dimension of the outer linear contour of the cerebellum, determined using the caliper method and the box counting method were not statistically significantly different. Therefore, both methods can be used for fractal analysis of the linear contour of the cerebellum. Fractal analysis of the outer linear contour of the cerebellum allows to quantify the complexity of the spatial configuration of the outer surface of the cerebellum, which is difficult to estimate using traditional morphometric methods. The data obtained from this study and the methodology of the caliper method of fractal analysis in the author's modification can be used for morphometric investigations of the human cerebellum in morphological studies, as well as in assessment of cerebellar MR images for diagnostic purposes.Item Characterization of white matter branching in human cerebella: quantitative morphological assessment and fractal analysis of skeletonized MR images(2021) Maryenko, Nataliia; Stepanenko, OleksandrIntroduction: The aim of the present study was to investigate branching characteristics of the human cerebellar white matter by the means of findings obtained from the quantitative morphological assessment and fractal analysis of the skeletonized MR images of the human cerebellum. Methods: Thirty individuals with no apparent brain pathology (15 males and 15 females, ranging from 18 - 30 years of age) participated in this study. Their normal T2-weighted MR images of the cerebellar vermis (midsagittal plane) were examined. The skeletonizing procedure and subsequent quantitative morphological assessment of the acquired skeletonized MR images were performed. The following parameters were determined: the number of branches, the number of junctions, the amount of end-point voxels, junction voxels and slab voxels, the average and maximum branch lengths, the longest-shortest patch length, and the number of triple and quadruple points. Additionally, the individual branches of the obtained digital skeletons of the cerebellar white matter were examined and the following parameters were assessed: branch length variability, Euclidean distance, and branch length/Euclidean distance ratio. A fractal analysis was performed using the box counting method prior to and after the MR image skeletonizing procedure. The values of the fractal dimensions (FD) of both skeletonized and non-skeletonized MR images were calculated.Results:It was established that the cerebella, which had the maximum values of the FD, possessed a large number of small branches approximately equal in length and which were connected by numerous junctions, forming numerous endpoints. Those cerebella, which had higher values of the average branch length and greater branch length variability, showed lower values of the FD. The key characteristics of the digital skeleton that determined the values of the FD of the cerebellum and its skeletonized MR images were the number of branches and the number of junctions that had the strongest correlational relationships with the FD of the skeletonized MR images. We submitted a proposition to consider the number of branches and amount of junctions as a diagnostic criterion in the determination of normal values of the FD. Conclusions: The obtained data can be used as diagnostic criteria in assessment of the orphofunctional state of the cerebellum using magnetic resonance imaging (MRI) technique.Item Fractal analysis of the human cerebellum (magnetic resonance imaging study)(ХНМУ, 2020) Мар’єнко, Наталія Іванівна; Марьенко, Наталия Ивановна; Maryenko, Nataliia