The aim of the study was to identify new anatomical landmarks of the aortic root and the relationship between the sizes of anatomical structures using the method of computed tomography angiography to improve models of heart valves and the methods for their selection in clinical practice.
Materials and methods: The dataset of computed tomography angiography prior to aortic valve replacement in 262 patients was analyzed. The mean age was 75.0±5.9 years. 99 (37.8±3.0%) men and 163 (62.2±3.0%) women took part in the study. The annulus fibrosus, sinotubular junction, and height of the sinuses of Valsalva were measured.
Results: In the tricuspid aortic valve group (n=251), in more than 50% of the cases, the diameter of the annulus fibrosus ranged from 23 to 26 mm. No significant association between the diameter of the annulus fibrosus and patient height (r=0.35; p=0.01) or body surface area (r=0.25; p=0.01) and the height of the sinuses of Valsalva (r=0.34; p=0.01) were revealed. Based on the ratio of the height of the sinuses of Valsalva and the diameter of the annulus fibrosus, three variants of the structure of the aortic root were identified: type A - K>1.05; type B- 0.95≤K≤1.05; type C- K<0.95. Type C of the aortic root was found to predominate in most cases, namely, in 98.0±0.9% (n=246).In the bicuspid aortic valve group (n=11), 2 patients had a type A of the aortic root, 1 patient had a type B, and 8 patients had a type C.
Conclusion: A classification of variants of the aortic root structure has been proposed, which will be useful not only for practitioners when choosing a treatment method, but also for researchers to understand the structural characteristics of the aortic root in patients with its pathology.
The aim of the study is to assess the possibilities of the combined approach to using multimodal MRI, neuronavigation, and awake craniotomy in resecting tumors of eloquent areas.
Materials and methods: The results of 30 successive awake surgical interventions performed in 2017-2019 years in patients with tumors of eloquent areas have been analyzed. The main selection criterion for this type of operations was the location of the tumor in the projection or in the immediate proximity to the cortical centers of speech and motion. To minimize the damage, patients underwent functional MRI and DTI tractography at the prehospital stage to identify cortical regions and white matter tracts involved in the motor and language functions; immediately before the operation the acquired data was loaded into the navigation StealthStation S7 (Medtronic, USA) to plan and monitor surgery stages; during the surgery, direct cortical and subcortical stimulation was performed to identify the motor and speech centers (asleep-awake-asleep technique) with neurolinguistic testing. Karnofsky performance status, assessment of the patient's neurological status, frequency of epileptic seizures before and after the operation, the extent of the tumor resection, and the data analysis after the linguistic testing were used to determine the patients' condition and surgery outcomes.
Results: Improvement of the general state after the operation has been noted in 30% of patients compared to the preoperative condition, no neurological deficit dynamics has been observed in 33% of patients. Postoperative multimodal MRI showed that total tumor removal was achieved in 37% of cases, subtotal in 40%, partial removal resection in 23% of cases.
Conclusion: The combined approach to the brain tumor resection using multimodal MRI, neuronavigation, and awake craniotomy with motor and language areas mapping allows neurosurgeons to minimize the risk of persistent neurological deficit occurrence and provides the possibility to perform maximal resection possible preserving the patients' functional status. The presented methodology is reproducible, permitting one to expand the options of surgical treatment when lesions are localized in eloquent areas.
Using mathematic criteria for image processing (radiomics) makes it possible to more accurately assess the nature of therapy-associated changes and determine the sites of maximal response. Comparison of the acquired quantitative and clinical data may assist radiologists in making the optimal decision. The aim of the study was to assess the capabilities of software operators for an in-depth analysis of metastatic spine lesion images in breast cancer.
Materials and methods: MRI data of three patients with breast cancer T2N2-3M1 receiving treatment in accordance with the accepted clinical protocols were used in our work. Spinal metastases were assessed by a radiologist and machine analysis using the Arzela variation operators. Twelve MRI examinations (4 per each patient) excluding the baseline examination have been analyzed with a follow-up period of about 3 months.
Results: The structure of the metastatically modified spine was analysed segment by segment in the sagittal and axial projections using machine image analysis operators. Rapid changes in the "complexity" of vertebrae images have been found, allowing one to suggest the efficacy of treatment in one of the three options - stabilization, improvement, progression. Changes in the vertebrae structure with a positive response to the treatment in the form of the formation of bone objects, calderas, reduction of the contrast agent circulation at the microlevel, confirmed by mathematical analysis, have been monitored. A correlation was obtained between the established changes and the level of the CA 15-3 cancer marker.
Conclusion: The study has shown a high effectiveness of machine image analysis algorithms, high correlation of the obtained results with the radiologist's report and clinical and laboratory data in 9 cases out of 12. The Pearson correlation coefficient between the classical marker and matrix filter curve was 0.8.
The review summarizes findings from the studies based on the application of technologies for transcriptome analysis to modern cellular model systems of human papillomavirus-associated cancer (HPV) (cervical cancer, head and neck tumors). A diversity of three-dimensional cancer models, such as spheroids, organoids (organotypic cultures), explants, mouse xenografts, are addressed. Particular attention is paid to the use of patient-derived biomaterial for establishing short-term cultures of primary tumor cells, as well as generating multicomponent (heterocellular) systems that comprise, together with the tumor component, other elements of its microenvironment. A number of unique biological properties of HPV-induced neoplasia are discussed, which make generating cell models a unique task. The novel findings in the field of molecular mechanisms of the onset and progression of HPV-associated cancer achieved by using RNA sequencing are presented for each variant of the model systems. These findings are considered in regard to applied aspects of their use, in terms of the opportunities for preclinical testing of new drugs, personalized diagnostics and selection of individual, most effective treatment regimens. The issues of drug resistance development, molecular-cellular heterogeneity, epigenetic reprogramming, and the role of the stromal microenvironment are reviewed. The paper accentuates the problems related to the limitations of the applicability of a particular model system. The areas with a significant lagging behind in omics research of virus-associated cancer in comparison with other types of oncological pathology and possible causes of this lag are noted. The future prospects for the development of model systems of HPV-associated tumors in the field of high-tech tissue engineering, in particular, the use of bioprinting and microfluidic biochips, are also outlined. The combination of these techniques with the methods of whole genome profiling will significantly increase the translational potential of the described model cell systems.
The aim of the study was to assess the suitability of endothelial colony-forming cells in the development of tissue engineering constructs based on the study of the gene expression profile compared to mature endothelial cells.
Materials and methods: In the experiment, we used the endothelial colony-forming cells (ECFC) obtained from the peripheral blood of patients who underwent percutaneous coronary intervention. The cells were isolated on a Histopaque 1077 density gradient (Sigma-Aldrich, USA), and then cultured in EGM-2MV culture medium (Lonza, Switzerland). A commercial culture of primary human coronary artery endothelial cells (HCAEC) was used as a control. The cells were unfrozen and cultured according to the manufacturer's recommendations in MesoEndo Cell Growth Medium (Cell Applications, USA).The experiment was carried out in specialized μ-Luer plates in the perfusion system (IBIDI, Germany), which provided a continuous unidirectional flow of the culture medium with a shear stress of 5 dyn/cm2. Control plates were cultured under standard conditions for a similar period of time. Total RNA was isolated from cell samples. The expression of the genes NOTCH4, NRP2, PLAT, PLAU, NOTCH1, FLT1, COL4A2, CD34, SERPINE1, HEY2, MKI67, KLF4, LYVE1, FLT4 was assessed using a quantitative real-time polymerase chain reaction. The expression of the genes was calculated by the ΔCt method and expressed on a logarithmic (log10) scale as a fold change relating to the control samples.
Results: In mature endothelial cells HCAEC when exposed to a laminar flow, only the transcription factor KLF4 and venous differentiation NRP2 marker values increased significantly. ECFC showed statistically significant growth in KLF4, NRP2, CD34, and LYVE1, as well as PLAU expression decrease. In addition, we observed the overexpression of FLT4, LYVE1, NOTCH4, and NRP2 in ECFC in relation to HCAEC and HEY2 hypoexpression. CD34 overexpression characteristic of progenitor cells was also found. An increase in COL4A2 expression associated with type IV collagen synthesis was a characteristic feature of ECFC.
Conclusion: The gene expression profile of endothelial colony-forming cells is quite close to that of primary endothelial cells of the human coronary artery, and thus, the cells obtained from patients' peripheral blood can be used to develop personalized tissue-engineered constructs.
The aim of the study was to experimentally evaluate the applicability and effectiveness of two variants of the technology of adaptive neurostimulation with feedback from a person's own rhythmic processes to increase the functional reliability and to reach cognitive rehabilitation of high-tech specialists.
Materials and methods: The study involved specialists who applied to the clinic with complaints of occupational pain syndromes and work stress. For the treatment of pain syndromes, analgesic electrical nerve stimulation was used with the parameters automatically modulated by feedback signals from the subject's breathing rhythm. To correct stress-induced states, musical stimulation was used, automatically modulated by feedback signals from the narrow-band rhythmic components of the electroencephalogram (EEG) of the subject - alpha EEG oscillators. Treatment procedures without feedback from rhythmic processes were used as а control.
Results: In the control sessions without the feedback from human rhythmic processes, no significant effects of stimulation were noted. With electrical stimulation controlled by the patient's breathing (experiment 1), the most significant changes were observed in subjective pain scores, which dropped by half. A significant increase was noted in the power of the EEG alpha rhythm, respiration amplitude, and subjective ratings of well-being and mood. With music stimulation automatically modulated by the rhythmic components of the patient's EEG (experiment 2), there was a significant increase in the power of the EEG alpha rhythm, as well as a decrease in the level of emotional disadaptation and stress.
Conclusion: The data obtained clearly indicate that the developed and tested technologies of adaptive neurostimulation can be used for the timely correction of the functional state and cognitive rehabilitation of high-tech specialists by effectively eliminating the risks of their functional reliability caused by occupational pain and stress.
The aim of the study is to create, train, and test the algorithm for the analysis of brain CT text reports using a decision tree model to solve the task of simple binary classification of presence/absence of intracranial hemorrhage (ICH) signs.
Materials and methods: The initial data is a download from the Unified Radiological Information Service of the Unified Medical Information and Analytical System (URIS UMIAS) containing 34,188 studies obtained by a non-contrast CT of the brain in 56 inpatient medical settings. Data analysis and preprocessing were carried out using NLTK (Natural Language Toolkit, version 3.6.5), a library for symbolic and statistical processing of natural language, and scikit-learn, a machine learning library containing tools for classification tasks. According to 14 selected ICH-related key words, as well as 33 stop-phrases with key words denoting absence of ICH, an automatic selection of the CT investigations and their subsequent expert verification were carried out. Two classes of investigations were formed based on the sample from 3980 protocol descriptions: containing descriptions of ICH and without them. The problem of binary classification was solved using the decision tree algorithm as a model. To evaluate the performance of the model, the CT investigations were divided randomly into samples in the ratio of 7:3. Of 3980 protocols, 2786 were assigned to the training data set, 1194 - to the test one.
Results: According to the test results, the designed and trained algorithm in the binary classification of the CT reports "with signs of ICH" and "without signs of ICH" has shown sensitivity of 0.94, specificity of 0.88, F-score of 0.83.
Conclusion: The developed and trained algorithm for the analysis of radiology reports has demonstrated high accuracy in relation to brain CT with signs of intracranial hemorrhage and can be used to solve binary classification problems and create appropriate data sets. However, it is limited by the need for manual revision of CT studies to ensure quality control.
Intraoperative recording of cortico-cortical evoked potentials (CCEPs) enables studying effective connections between various functional areas of the cerebral cortex. The fundamental possibility of postoperative speech dysfunction prediction in neurosurgery based on CCEP signal variations could serve as a basis to develop the criteria for the physiological permissibility of intracerebral tumors removal for maximum preservation of the patients' quality of life. The aim of the study was to test the possibility of predicting postoperative speech disorders in patients with glial brain tumors by using the CCEP data recorded intraoperatively before the stage of tumor resection.
Materials and methods: CCEP data were reported for 26 patients. To predict the deterioration of speech functions in the postoperative period, we used four options for presenting CCEP data and several machine learning models: a random forest of decision trees, logistic regression, and support vector machine method with different types of kernels: linear, radial, and polynomial. Twenty variants of models were trained: each in 300 experiments with resampling. A total of 6000 tests were performed in the study.
Results: The prediction quality metrics for each model trained in 300 tests with resampling were averaged to eliminate the influence of "successful" and "unsuccessful" data grouping. The best result with F1-score = 0.638 was obtained by the support vector machine with a polynomial kernel. In most tests, a high sensitivity score was observed, and in the best model, it reached a value of 0.993; the specificity of the best model was 0.370.
Conclusion: This pilot study demonstrated the possibility of predicting speech dysfunctions based on CCEP data taken before the main stage of glial tumors resection; the data were processed using traditional machine learning methods. The best model with high sensitivity turned out to be insufficiently specific. Further studies will be aimed at assessing the changes in CCEP during the operation and their relationship with the development of postoperative speech deficit.
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