Sovremennye Tehnologii v Medicine最新文献

The aim of the study is to identify practical aspects of using multifractal formalism to assess the morphology of biological tissues.

Materials and methods: The objects of the study were histological images of lung tissues of Wistar rats without pathology and with detected pathological changes, obtained at 50×, 100×, 200× magnifications. Image processing was carried out using the ImageJ/Fiji universal software. The multifractal spectrum of the images, processed to obtain a linear contour, was calculated with the use of FracLac - a module for ImageJ. This module was used to determine the scaling exponent (the function of the Rényi exponent, ^τ(q)) and the singularity spectrum itself.

Results: The singularity spectra for tissues with no pathology have signs of multifractality. The image spectrum of tissue with pathology is shifted to the left relative to the spectrum characteristic of tissue without pathology. A decrease in the spectral height in the presence of pathology indicates a "simplification" of the alveolar pattern, which is presumably associated with the presence of widespread vasculitis, since it causes areas of hemorrhage to appear on the image; this leads to leveling the contour of the alveolar pattern, reducing the surface area of the alveoli and emerging areas inflamed by erythrocytes. At lower magnification, images with pathology lose signs of multifractality.

Conclusion: Correct results of assessing multifractal spectra of histological images can be achieved at 200× magnification and preprocessing to obtain linear contours. Significant differences between the morphological structure of lung tissues with and without pathology are observed when comparing the height, width, and position of the spectrum relative to the origin.

Traumas and infectious diseases of the eye play a leading role in the development of corneal blindness responsible for 1.5-2 million cases of vision loss per year. To date, the issue of reducing the incidence of fungal keratitis is acute and needs to be solved worldwide. Trauma as a risk factor for corneal fungal disease is thought to be prevalent in developing countries due to agricultural involvement, while in developed countries the onset of the disease is predisposed by medical advances such as contact vision correction and modern ophthalmic surgery. Thorough analysis of the pathogenesis gives the possibility to describe the action of fungal enzymes, biofilm formation, and the resistance mechanism, which on the one hand explains the aggressive course of the disease and difficulties in its diagnosis, and on the other hand, it encourages searching for new methods of diagnosis and treatment. The non-specific clinical picture of fungal keratitis, the variety and availability of antibiotics nowadays become an obstacle for rapid detection of this pathology. Low public awareness and late visit to an ophthalmologist are also a barrier to successful combating the increasing incidence of fungal keratitis. Belated diagnosis, increasing resistance of fungi to antibiotics, and lack of registered antifungal ophthalmic drugs justify poor treatment efficacy resulting in decreased visual acuity or vision loss. Existing diagnostic methods need systematization and detailed comparison, identifying the advantages and disadvantages of each. This review considers causative agents and their influence on pathogenesis of the disease, describes difficulties of fungal keratitis diagnosis and possible ways of overcoming these problems using new developments, and also outlines further prospects of research in this direction.

The scope of diagnostic medical examinations increases from year to year causing a reasonable desire to develop and implement new technologies to diagnostics and medical data analysis. Artificial intelligence (AI) algorithms became one of the most promising solutions to this problem and proved themselves in the course of mass practical application. During the three-year Moscow experiment started in 2020, the possibility was achieved to develop methodologies of AI use and to successfully implement it into the regional level healthcare system. In this article, the authors share their experience in developing a medical AI service using the example of PhthisisBioMed AI service and the results of its application in real clinical activities environment. This AI service has shown its quality and reliability confirmed by technological monitoring. Clinical trials of PhthisisBioMed AI service were conducted on a specially prepared verified data set (n=1536) considering epidemiological indicators of the thoracic organs major diseases prevalence. The mean sensitivity of the service was 0.975 (95% CI: 0.966-0.984). PhthisisBioMed medical AI service is registered as a medical device (medical device registration certificate No.RZN 2022/17406 dated May 31, 2022) and is actively used in the Russian Federation as a diagnostic tool to reduce the burden on radiologists and to accelerate the process of medical report obtaining.

Biodegradable and biocompatible polymers are actively used in tissue engineering to manufacture scaffolds. Biomedical properties of polymer scaffolds depend on the physical and chemical characteristics and biodegradation kinetics of the polymer material, 3D microstructure and topography of the scaffold surface, as well as availability of minerals, medicinal agents, and growth factors loaded into the scaffold. However, in addition to the above, the intrinsic biological activity of the polymer and its biodegradation products can also become evident. This review provides studies demonstrating that scaffolds made of poly(3-hydroxybutyrate) (PHB) and its copolymers have their own biological activity, and namely, osteoinductive properties. PHB can induce differentiation of mesenchymal stem cells in the osteogenic direction in vitro and stimulates bone tissue regeneration during the simulation of critical and non-critical bone defects in vivo.

Ultrasound shear wave elastography is a modern method that is based on measuring the shear wave velocity making it possible to determine stiffness of soft biological tissues at an arbitrary point (point elastography) or to construct a two-dimensional color image with a subsequent point measurement of stiffness (two-dimensional elastography) and therefore to compare the stiffness of an object with a medium or objects with each other. The aim of the study is to develop a new criterion for the comparative assessment of objects with different stiffness during shear wave elastometry: modulus of stiffness difference between object and environment.

Materials and methods: Using the original technology of building two-dimensional color elastogram, point and two-dimensional shear wave elastography were performed using linear sensors on commercial ultrasound scanners: Aixplorer (SuperSonic Imagine, France), Acuson S2000 (Siemens, Germany), and Verasonics acoustic system (Verasonics Inc., USA) with an open architecture to determine the stiffness values of focal inclusions and compare them with each other with the help of a new comparative elastomeric assessment criterion: modulus of stiffness difference between object and environment. First, the accuracy of the scanners under test was compared on a calibrated Elasticity QA Phantom, model 049 (Computerized Imaging Reference Systems Company, USA) with a known stiffness of various inclusions and thereafter on an uncalibrated BP1901 phantom (Blue Phantom, USA) with unknown stiffness of inclusions. The obtained values were compared to determine the influence of subjective factors on the measurement results.

Results: To assess the stiffness of the foci and compare the values with each other taking into account the rigidity of the environment, it is proposed to use a new criterion for the comparative assessment - the modulus of stiffness difference between focus and environment, which quantitatively characterizes the difference between these values. According to this criterion, all three ultrasound scanners have been established to show high and comparable accuracy in determining the stiffness of inclusions within the homogeneous medium in the experiments on phantoms. Two-dimensional shear wave elastography has revealed the effect of the control volume size and the correctness of the color scale setting, especially in the heterogeneous objects, on the results of elastometry. Methodological techniques to reduce the influence of subjective factors have also been proposed.

Conclusion: The study has showed the possibility of using the modulus of stiffness difference between object and environment as a new criterion for comparative assessment of objects in shear wave elastometry taking into account stiffness of the environment. To reduce operator-dependence, it is necessary to take into consideration both the way of realizing elastometry (

The aim of the study is to develop and verify an algorithm for automatic generation of leaflet apparatus models for prosthetic heart valves, to optimize the basic parameters of the models in order to minimize the stress-strain state and maximize the geometric area of the orifice.

Materials and methods: The suggested algorithm consists of three blocks: "Generator", "Modeling", "Analysis". The first block creates a three-dimensional model of the leaflet apparatus using the specified parameters (height, radius, thickness, degree of "sagging", angle of the free edge deviation). Numerical simulation of the apparatus functioning is further performed using the finite element method. Then, the statistical analysis of the von Mises stresses is done and the opening area of the design in question is calculated.Verification was performed by comparing quantitatively the lumen areas of the leaflet apparatus in the open state, obtained from the literature data for the Trifecta bioprosthesis (19, 21, and 23 mm in diameter), with the results of the described algorithm operation.

Results: The verification of the algorithm has demonstrated the following deviations in the lumen area in the open state: 2.85% for 19 mm, 14.81% for 21 mm, and 23.17% for 23 mm models. This difference is due to the choice of the model material (no data could be found on the physical and mechanical properties of the pericardium used for the fabrication of the Trifecta bioprostheses).The generation of a large number of designs (n=1517) without fixation of certain geometry parameters has shown that thickness of the leaflet apparatus makes the greatest contribution to the degree of opening; its dependence on the thickness and arising peak von Mises stresses has been demonstrated. Of the valvular models obtained, 278 showed the opening degree greater than 80% and maximum peak von Mises stresses below 4 MPa for the proposed model of the pericardium, which is 65% below the ultimate strength of the material.Out of 278 leaflet models, 3 "optimal" designs were selected meeting the diameter criteria of 19, 21, and 23 mm. The loss index for them was 0.24, 0.19, 0.20 with the opening degrees of 88.28, 84.48, 88.12%, and maximum peak von Mises stresses of 3.62, 1.21, 1.87 MPa, respectively.

Conclusion: The developed algorithm makes it possible to automatically generate three-dimensional models of the leaflet apparatus, numerically simulate the opening process using the finite element method, statistically analyze the results obtained, and calculate the lumen area. The algorithm was verified based on the data for the Trifecta bioprosthesis of three standard sizes. The presented algorithm can be used both for the research and development of various designs and for obtaining "optimal" models of sash devices.

The aim of the study is to assess the possibility of using artificial intelligence to determine the most significant predictors of the operative correction outcomes for patients with damaged coronary and carotid arteries.

Materials and methods: The retrospective study of the simultaneous (or single-stage) surgical intervention results has been carried out in patients with combined atherosclerotic damage of the coronary bed and cerebral arteries (n=42), which was severe and extensive. The parameters which may be predictors of the cardiovascular risk were analyzed using the TADA program. Ten models were built for program learning. The model with 92% predictive accuracy appeared to be the most successful.

Results: Simultaneous correction resulted in the absence of 30-day coronary complications in all patients. With respect to the cerebral vascular territory, acute ischemic stroke developed in 2 patients. The lethality rate was 2.4%, the fatal outcome was caused by postoperative gastrointestinal bleeding.The TADA program model considered the following parameters to be the most significant predictors: internal carotid artery cross-clamping time in minutes (51.24%); damage to the left coronary artery stem (30.42%); diastolic AP (18.28%). If cross-clamping of the internal carotid artery lasts for less than 18 min, complications are not likely to occur, while they are practically inevitable if the time exceeds 46 min. The probability of complications grows nonlinearly with the increase of the extent of the left coronary artery stem injury. A high diastolic AP never virtually coincides with the presence of complications, nor does the low one. The highest probability of complications is at the values from 70 to 80 mm Hg.In patients with a triple vessel injury of the coronary arteries, a representative picture of a nonsignificant feature is observed.

Conclusion: Application of artificial intelligence for determining risk predictors for patients with concurrent atherosclerotic damage of the coronary and carotid arteries is an effective method for prognosticating the risks of simultaneous interventions.

The development of high-throughput technologies has sharply increased the opportunities to research the human body at the molecular, cellular, and organismal levels in the last decade. Rapid progress in biotechnology has caused a paradigm shift in population-based studies. Advances in modern biomedical sciences, including genomic, genome-wide, post-genomic research and bioinformatics, have contributed to the emergence of molecular epidemiology focused on the study of the personalized molecular mechanism of disease development and its extrapolation to the population level. The work of research teams at the intersection of information technology and medicine has become the basis for highlighting digital epidemiology, the important tools of which are machine learning, the ability to work with real world data, and accumulated big data. The developed approaches accelerate the process of collecting and processing biomedical data, testing new scientific hypotheses. However, new methods are still in their infancy, they require testing of application under various conditions, as well as standardization. This review highlights the role of omics and digital technologies in population-based studies.

As early as 50 years ago, bisphosphonates turned from a water treatment agent into one of the most widely used groups of drugs for the treatment of various diseases of calcium metabolism (bone tissue resorption, oncological complications of neurodegenerative diseases and others). Years of research on bisphosphonates have contributed to the understanding of their molecular and cellular pathways of their action. All bisphosphonates have a similar structure and common properties, however, there are obvious chemical, biochemical, and pharmacological differences between them. Each bisphosphonate has its own unique profile. This review summarizes data on the mechanisms of action of bisphosphonates, demonstrates the experience and prospects for their use for the modification of cardiovascular bioprostheses, since the issue of preventing bisphosphonate calcification has not been settled yet.