Determination of predictors of successful recanalization of the chronic occlusions of coronary arteries by means of CT-coronarography method

The Value of Iterative Reconstruction of Algorithm-Based Coronary Artery Computed Tomography Imaging in the Diagnosis of Old Myocardial Infarction

The objective of this study was to compare the diagnostic value of computed tomography (CT) based on iterative reconstruction algorithm in old myocardial infarction (OMI), thereby providing theoretical guidance and practical basis for clinical treatment. In this study, in order to provide theoretical guidance and practical basis for the diagnosis and treatment of clinical OMI, 10 patients with OMI were selected and divided into two groups, with 5 patients in each group. In addition, an algebraic iterative reconstruction algorithm is constructed, which starts from the initial estimation value, compares, and corrects the estimation results and the measured results continuously until the error between the two results is less than the predetermined value. The experimental group was optimized by algebraic iterative reconstruction algorithm, and the control group was reconstructed by the hospital original method. The image quality parameters under different iteration times were analyzed and compared to obtain the optimal iteration times. The value of iterative reconstruction algorithm in clinical diagnosis was investigated by analyzing the time of drawing and the accuracy of diagnosis after drawing. Through the analysis and comparison of the image quality parameters of the patients from the experimental group, it was found that the image quality firstly increased with the increase in the number of iterations but decreased with the increase of the number of iterations after a certain number of iterations. The results showed that the optimal number of iterations was 13 times. The drawing time of the experimental group and the control group was 54.27 minutes and 117.87 minutes in turn, so the difference between the two groups was significant (P < 0.05). Besides, there was a statistically marked difference in the accuracy rate of the experimental group (93.33%) and the control group (73.33%) (P < 0.05). In conclusion, the time required for coronary artery CT imaging using algebraic iterative reconstruction algorithm was greatly reduced and the diagnostic accuracy was hugely improved. Therefore, the coronary artery CT imaging based on iterative reconstruction algorithm could make more effective use of medical resources and improve the diagnostic accuracy in the diagnosis of OMI.

Predictors of unsuccessful endovascular recanalization of coronary chronic total occlusion

The prevalence of endovascular interventions for coronary chronic total occlusion (CTO) remains small worldwide. This is due to the complexity of procedure and the risk of intraoperative complications. In this regard, the search for predictors of unsuccessful endovascular intervention in CTO plays a special role. This will allow for a careful selection of patients with the most favorable expectation effect of the operation. Aim. To identify predictors of unsuccessful endovascular recanalization of CTO.

Material and methods. This retrospective study included 180 patients with chronic coronary artery disease (CAD) in the period from November 2017 to June 2019, who had multivessel lesion in combination with CTO. In all patients, an attempt was made to achieve complete myocardial revascularization. Depending on the success of procedure, the patients were divided into two groups: complete and incomplete myocardial revascularization. The follow-up period was 12 months.

Results. All baseline characteristics of patients in the compared groups were similar. The successful recanalization rate of occlusion was 79,5%. Multivariate regression analysis showed that calcified CTO (p<0,001), baseline SYNTAX (Synergy between Percutaneous Coronary Intervention with TAXUS and Cardiac Surgery) score >32 (p=0,006), CTO length >30 mm (p=0,046) and CTO of circumflex artery (p<0,01) are significant predictors of unsuccessful endovascular recanalization of CTO. To assess the predictive value of the model, a ROC analysis was carried out, and the area under the curve (AUC) was calculated. The AUC was 0,87, which indicates a high predictive quality of the model. The sensitivity and specificity of the model were 78 and 81%, respectively.

Conclusion. The study showed that the presence of calcified CTO, SYNTAX score >32 points, CTO length >30 mm, and CTO of circumflex artery are significant predictors of unsuccessful CTO recanalization.