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This study was performed to assess the size, structure and functional features of the reconstructed alveolar ridge using the autologous stromal and vascular fraction of adipose tissue (SVF-AT) up to 10 years. Materials and methods. This study evaluates 141 patients (61 males, 80 females) aged range 45 to 78 years (Moda 57 years) with jaw alveolar ridge regression. 112 osteoplastic surgical procedures in the test (TG) were performed using SVF-AT with subsequent placement of 297 dental implants in the reconstructed ridge; in the control (CG)-117 osteoplastic surgical procedures were performed using generally approach with subsequent placement of 323 dental implants. The alveolar ridge size and reconstructed bone features was evaluated in terms of up to 10 years. Histologic and histomorphometric study of 27 reconstructed bonecor-biopsies was conducted. The data were statistically analyzed. Results. The results of this comparative study confirm the advantages of the proposed cell-potentiated approach over the current generally accepted methods for the reconstruction of the alveolar jaw ridge. The use of SVF-AT with osteoplastic material allows to achieve new and sufficient bone growth with an insignificant risk of complications and reoperations (8% and 21% of cases in TG and CG, respectively, p = 0,231), optimal morphological properties of the regenerate (40,14 ± 3,36 and 24,23 ± 2,63% of bone tissue in TG and KG respectively, p = 0,001), that provides reliable fixture integration in the reconstructed alveolar ridge and high efficiency of the implant-supported restorations (97% and 88% in TG and KG, respectively, up to 10 years, p ˂0,001). Conclusion. The proposed innovative approach can be recommended as a basis for a valid surgical protocol with a pronounced of the jaw bones regression transformation. This will allow more successful and predictable use the implantsupported prosthetic restorations in reconstructed ridges in this category of patients. K E Y w o r d s-regression bone transformation, stromal and vascular fraction of adipose tissue, reconstruction of the alveolar ridge, dental implantation

Aim. This study was conducted to assess the outcome of the results obtained in the treatment of patients with longterm current periodontitis with individual characteristics of the cytological picture of the microenvironment of damaged periodontal tissues.Materials and methods. The main study group included 40 patients with chronical periodontitis of the moderate degree (Mo 56, 7 years). The selection of the regenerative treatment in the main group was carried out in accordance with the preliminary express assessment of the cytological picture of the damaged periodontal tissues. The control group, whose indicators were compared with the main clinical indicators, included 43 patients with randomly selected regenerative treatment.Results. The cell-potential surgical approach statistically induces the growth of new dentogingival junction in patients with critically small amount of morphologically altered neutrophil granulocytes and small cell forms with intense basophilic coloring (≤20%) in cytological samples in comparison with the control decreasing the amount of residual loss of teeth supporting tissues by 2 times.Conclusion. The preliminary express assessment of the cytological picture of the microenvironment of periodontal pockets indirectly indicates the potential of the patient with periodontitis to restore the missing structures of the periodontal membrane. The choice of the surgical tactics of regenerative treatment, taking into account the characteristics of cellular behavior in cytological samples of patients with periodontitis, is advisable to use as a prognostic test to improve the final results.

Background. Currently accepted risk assessments of periodontitis progression are determinants of indirect stability: periodontal pockets, persistent bleeding of the gums, tooth mobility, local risk factors. In the era of case-oriented medicine, a relevant solution would be to choose periodontal therapy according to one-time consideration of the maximum available range of individual risk factors rather than on general clinical guidelines.Objectives. The study was aimed at determining the relative risk of periodontitis progression after active basic therapy using neural network modeling.Methods. A cohort retrospective study was performed on 109 patients of both sexes, aged 30 to 70 years, after basic treatment of chronic periodontitis (mild, moderate and severe) in the period from 1999 to 2016, who were on supportive periodontal therapy (SPT) for 5 years ≤SPT≤ 20 years. The authors considered data from objective examination of the periodontium and categorical indices (24 in total) assessed before treatment, 4–6 months after basic (active) treatment and 5 years ≤SPT≤ 20 years. Following the analysis of descriptive statistics, target quantitative indices were determined for prognostic modeling of treatment outcomes in periodontitis patients and calculating the residual risk of disease progression. Statistical processing of obtained data was carried out using the Statistica 13.3 package (Tibco, USA). Mean values of the indicators at different time points were compared by means of Wilcoxon’s and Signs criteria; Spearman’s rank correlation coefficient was used to evaluate relevance between predictors and target indicators. The level of statistical significance p = 0.05 was accepted in all cases of analysis. DataMining, an automated neural network of Statistica software, was used as a tool to build neural network models. The task of classifying the level of risk of disease progression was solved by means of ROC analysis. The prognostic potential of the model was assessed using sensitivity and specificity measures.Results. The heterogeneous dynamics of predictor variables describing the state of the periodontium was determined. The outcomes of regenerative periodontal surgery, regardless of gender, age of patients and comorbidities, significantly outperformed those of other approaches, due to the formation of a new dentogingival attachment, although to different extent. Another positive functional outcome was recorded in restoring the dentition integrity by implantation, without any mutually damaging effects. Since revealing the interrelationships between indicators is not equivalent to the predictive value, prognostic models were built for target indicators and stratification of the relative risk of periodontitis progression using automated neural networks. The networks with the best prognostic properties were selected out of 1000 automatically built and trained neural networks — double-layer perceptrons. The sensitivity of the relative risk prognostic model on the training, control and test samples made up 90%, 67%, 80%; the specificity of the model made up 81.481%, 85.714%, 100%. Overall, in the cohort, the sensitivity and specificity accounted for 85.937% and 86.666%. The area under the curve (ROC AUC) is 0.859.Conclusion. The use of an artificial intelligence algorithm for the construction of neural networks for target predictors and stratification of the relative risk of periodontitis progression has advantages over classical methods — it is instrumental in solving classification and regression problems with categorical and quantitative predictor variables using data of arbitrary nature of large and small volumes. The practical implementation of the study results is reflected in the development of a relative risk calculator based on a written computer program.

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