Наукові праці. 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 Фрактальні розмірності кори та білої речовини як міра атрофічних змін головного мозку при нормальному старінні(Дніпровський держ. мед. університитет, 2023-11) Мар'єнко, Наталія Іванівна; Степаненко, Олександр ЮрійовичItem Фрактальний аналіз у нейроморфології: особливості підбору способів попередньої обробки зображень(КНМУ, 2023-06) Мар'єнко, Наталія Іванівна; Степаненко, Олександр ЮрійовичItem Фрактальний аналіз магнітно-резонансних зображень головного мозку: діагностична цінність (огляд літератури)(ДУ «Інститут неврології, психіатрії та наркології Національної Академії Медичних Наук України», 2023) Мар'єнко, Наталія ІванівнаФрактальний аналіз є відносно новим методом математичного аналізу зображень, що дає змогу кількісно охарактеризувати ступінь складності просторової конфігурації досліджуваних об’єктів. У клінічних нейронауках фрактальний аналіз найчастіше використовують для морфометричного досліджування великих півкуль головного мозку та мозочка. Можна проводити аналіз кори і білої речовини, їхніх зовнішніх поверхонь, а також тканини мозку цілком. Значення фрактальної розмірності (величини, що визначають за допомогою фрактального аналізу) залежать від індивідуальних анатомічних особливостей і можуть змінюватися у процесі онтоґенезу. Зміни фрактальної розмірності виявлені в процесі розвитку головного мозку та при його порушеннях, при нормальному старінні та нейродегенеративних захворюваннях, гострих ураженнях тканини головного мозку (травматичному ушкодженні головного мозку і гострих порушеннях мозкового кровообігу) та при деяких психічних розладах. Перевагами використання фрактального аналізу у клінічній практиці є можливість визначення наявних морфологічних змін структур головного мозку, а також можливість кількісного й об’єктивного оцінювання ступеня вираженості виявлених змін.Item Фрактальний аналіз клітинних кластерів як спосіб кількісного дослідження цитоархітектоніки зернистого шару кори мозочка(Полтавський Держ. Мед. Ун-ту, 2023-04) Мар'єнко, Наталія Іванівна; Степаненко, Олександр ЮрійовичItem Вікові зміни великих півкуль головного мозку у чоловіків та жінок: фрактальний аналіз силуетних магнітно-резонансних зображень(видавництво ХНМУ, 2023-02) Мар'єнко, Наталія ІванівнаItem Відеолекції з гістології, цитології та ембріології як складова система дистанційного навчання та самостійної роботи студентів(КНМУ, 2023-06) Мар'єнко, Наталія Іванівна; Степаненко, Олександр ЮрійовичСтуденти, чиї доповіді визнано найкращими, мають можливість виступити на засіданнях студентського наукового гуртка кафедри, а також на науковій конференції студентів та молодих вчених, яка щорічно проводиться в університеті. Така робота сприяє інтелектуальному розвитку студента, знайомить його з особливостям роботи з науковою літературою як на паперових так і електронних носіях (робота з електронними базами та бібліотеками, такими як https://pubmed. ncbi. nlm. nih. gov/, https:// library. gov. ua/, https://lib. zsmu. edu. ua/), закладає основи як індивідуальної так і групової або колективної праці, основи статистичного та метааналізу, готує до публічних доповідей і роботи з аудиторією. Треба зазначити, що такий вид праці дуже позитивно сприймається студентами. Багато з них активно включається у роботу і, крім запланованих тем, студенти іноді пропонують власні теми для досліджень. Висновки. Участь в науково-дослідній роботі має ґрунтовну мету розвитку клінічного мислення студента та його компетентностей, закладає основи статистичного та метааналізу. Як результат, здобувач освіти отримує навички індивідуальної та командної роботи, а також досвід публічних виступів і роботи з аудиторією.Item Spatial and structural complexity of cerebral hemispheres in male and female brain: fractal and quantitative analyses of MRI brain scans(2023) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrObjectives: The aim of the present study was to compare the features of the structural complexity of the cerebral hemispheres in men and women using fractal analysis of outlined and skeletonized images, as well as quantitative analysis of digital skeletons of the cerebral hemispheres. Material and Methods: Magnetic resonance imaging brain scans of 100 individuals aged 18-86 years (44 males and 56 females) were investigated. Five sections of each brain were selected for morphometric study (4 coronal and 1 axial sections). The sections were preprocessed, and outlined and skeletonized images were obtained. Fractal analysis was conducted using the two-dimensional box counting method, and fractal dimensions of outlined and skeletonized images were determined. Additionally, quantitative analysis of skeletonized images was performed, determining the following parameters: branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points, average branch length, and maximum branch length. Results: We observed that both variants of fractal dimension in males and females did not show significant differences, although most quantitative parameters in males were larger than those in females. Conclusions: The spatial and structural complexity of the cerebral hemispheres, as characterized by fractal dimensions, is almost indistinguishable between males and females. However, in some individual brain sections, the male brain may exhibit a slightly higher number of end-point voxels, corresponding to the gyri of the cerebral hemispheres. The obtained data can be used in clinical practice for diagnostic purposes (e.g., for detecting malformations) and for theoretical studies in neuroanatomy.Item 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 silhouette Magnetic Resonance brain images as a measure of age-associated changes in cerebral hemispheres(2023) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrAim: The aim of the present study was to characterize age-associated changes in the spatial configuration of cerebral hemispheres (including changes in spatial complexity and space-filling capacity) using fractal analysis of silhouette magnetic resonance brain images. Material and Methods: Magnetic resonance brain images of 100 (44 male, 56 female) participants aged between 18-86 years were studied. Five magnetic resonance images were selected from the magnetic resonance imaging dataset of each brain, including four tomographic sections in the coronal plane and one in the axial plane. Fractal dimension values of the cerebral hemispheres silhouettes were measured using the two-dimensional box-counting algorithm. Morphometric parameters based on Euclidean geometry (perimeter, area, and their derivative values) were determined as well. Results: The average fractal dimension value of the five studied tomographic sections was 1.878±0.0009, the average value of four coronal sections was 1.868±0.0010. It was shown that fractal dimension values of cerebral silhouettes for all studied tomographic sections and four coronal sections significantly decrease with age (r=-0.512, p<0.001 and r=-0.491, p<0.001, respectively). The difference in the character of age-related changes in males and females was not statistically significant. Based on the age and the fractal dimension values of the studied sample, the confidence intervals of the fractal dimension values of cerebral hemispheres silhouettes were determined, which can be used as norm criteria in clinical neuroimaging. Conclusion: The fractal analysis and obtained data can be used in neuroimaging for assessing the degree of age-related cerebral atrophy and for differentiating between normal aging and neurodegenerative diseases.Item Atrophic age-related changes in cerebral hemispheres: Euclidean geometry based morphometry of MRI brain scans(2023) Мар'єнко, Наталія Іванівна; Maryenko, Nataliia; Степаненко, Олександр Юрійович; Stepanenko, OleksandrThe aim of the present study was to conduct a comprehensive morphometric analysis of two-dimensional MRI brain images and determine the simple morphometric parameters of the cerebral hemispheres that best characterize quantitatively brain atrophic changes in normal aging. This study analyzed MRI brain scans from 100 apparently healthy individuals (44 males and 56 females) aged 18 to 86 years (mean age 41.72±1.58 years). For each brain investigation, five tomographic sections were selected, including four coronal and one axial. The perimeter, area values, and their derivative indices were determined. The study has shown that the parameter most sensitive to aging changes was the ratio of two area values: the area corresponding specifically to cerebral tissue and the area that captures the cerebral tissue and the sulcal content. The results of the present study can be used in clinical practice for the quantitative assessment of age-related atrophic changes in cerebral hemispheres.Item Shape of cerebral hemispheres: structural and spatial complexity. Quantitative analysis of skeletonized MR images(2022) Maryenko, Nataliia; Stepanenko, OleksandrFor quantitative characterization of the complexity of the spatial configuration of anatomical structures, including cerebral hemispheres, fractal analysis is the most often used method, in addition to which, other methods of image analysis are quite promising, including quantitative analysis of skeletonized images. The purpose of the study was to determine the features of the structural and spatial complexity of the cerebral hemispheres shape using quantitative analysis of skeletonized magnetic resonance images of the cerebral hemispheres. Magnetic resonance brain images of 100 conditionally healthy individuals (who did not have structural changes in the brain) of both sexes (56 women, 44 men) aged 18-86 years (average age 41.72±1.58 years) were studied, 5 tomographic sections (4 coronal sections and 1 axial section) were selected from the set of tomographic images of each brain. During preprocessing, image segmentation was performed to obtain a binary silhouette image, after which silhouette skeletonizing was carried out. Quantitative analysis of skeletonized images included determination of the following parameters: branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points, average branch length, maximum branch length. We divided quantitative parameters of skeletonized images into two groups. The first group included branches, junctions, end-point voxels, junction voxels, slab voxels, triple points, quadruple points. These parameters were related to each other and to the values of the fractal dimension by positive correlations. The second group of parameters included average branch length, maximum branch length. These parameters were positively correlated, but they had negative correlations with most of the parameters of the first group and with fractal dimension values. Quantitative parameters and fractal dimension turned out to be better parameters for characterizing the spatial and structural complexity of the cerebral hemispheres shape than traditional morphometric parameters (area, perimeter and their derivatives). It was found that the values of most of the investigated quantitative parameters decreased with age; coronal sections were the most representative for characterizing age-related changes. Quantitative assessment of the brain shape, including spatial and structural complexity, can become an informative tool for the diagnosis of some nervous diseases and the differentiation of pathological and normal age-related changes.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 dimension of cerebellum in acute cerebellar infarction (magnetic resonance imaging study)(2022) Maryenko, Nataliia; Stepanenko, OleksandrThe aim of the study was to determine the values of fractal dimension of the cerebellum in acute cerebellar infarction using the quantitative study of magnetic resonance images of brain. Materials and methods: In this study, 11 patients with acute cerebellar infarction and 120 persons without structural changes in the brain (control group) were enrolled. T2-weighted magnetic resonance images of the brain were investigated. Fractal analysis was performed using pixel dilatation method. The values of fractal dimension of the cerebellar tissue as a whole and fractal dimension of the outer contour of the cerebellar tissue were determined. The fractal dimension values were measured in the following areas: cerebellar vermis (superior and inferior cerebellar lobes), foci of cerebellar infarction and areas adjacent to the foci (superior and inferior cerebellar lobes). Results: It was established that the values of fractal dimension of cerebellar tissue as a whole and fractal dimension of the outer contour of the cerebellar tissue in the area of cerebellar ischaemic infarction foci were significantly decreased compared to the control group. There was no significant difference between fractal dimension values of the cerebellar vermis, areas adjacent to infarction foci in patients with cerebellar infarction and vermal fractal dimension values in the control group. Conclusions: Fractal analysis of cerebellar magnetic resonance images may be used as an additional quantitative method to diagnose acute cerebellar infarction and to assess ischaemic foci to detect the boundaries between damaged and undamaged cerebellar tissue.Item Навчання через дослідження: науково-дослідні реферативні конференції у практиці викладання гістології, цитології і ембріології(Степаненко О. Ю. Навчання через дослідження: науково-дослідні реферативні конференції у практиці викладання гістології, цитології і ембріології / О. Ю. Степаненко, Л. В. Кольцова // Актуальні проблеми вищої медичної освіти і науки : Всеукраїнська науково-практична конференція з міжнародною участю, Харків, 8 квітня 2021 р. / ХНМУ. – Харків, 2021. – С. 178., 2021) Степаненко, Олександр Юрійович; Кольцова, Лариса В'ячеславівнаItem Досвід викладання гістології, цитології та ембріології у дістанційному форматі(ХНМУ, 2021) Степаненко, Олександр Юрійович; Губенко, Ірина Анатоліївна; Новікова, Катерина АнатоліївнаItem Досвід дистанційного навчання на кафедрі гістології, цитології та ембріології харківського національного медичного університету(ХНМУ, 2021) Єрохіна, Вікторія Валеріївна; Степаненко, Олександр Юрійович; Дєєва, Тетяна Володимирівна; Верещакіна, Вікторія Вікторівна