Clinically, fractional flow reserve (FFR)-guided coronary artery bypass grafting (CABG) is more effective than CABG guided by coronary angiography alone. However, no scholars have explained the mechanism from the perspective of hemodynamics. Two patients were clinically selected; their angiography showed 70% coronary stenosis, and the FFRs were 0.7 (patient 1) and 0.95 (patient 2). The FFR non-invasive computational model of the two patients was constructed by a 0–3D coupled multiscaled model, in order to verify that the model can accurately calculate the FFR results. Virtual bypass surgery was performed on these two stenoses, and a CABG multiscaled model was constructed. The flow rate of the graft and the stenosis coronary artery, as well as the wall shear stress (WSS) and the oscillatory shear index (OSI) in the graft were calculated. The non-invasive calculation results of FFR are 0.67 and 0.91, which are close to the clinical results, which proves that our model is accurate. According to the CABG model, the flow ratios of the stenosis coronary artery to the graft of patient 1 and patient 2 were 0.12 and 0.42, respectively. The time-average wall shear stress (TAWSS) results of patient 1 and patient 2 grafts were 2.09 and 2.16 Pa, respectively, and WSS showed uniform distribution on the grafts. The OSI results of patients 1 and 2 grafts were 0.0375 and 0.1264, respectively, and a significantly high OSI region appeared at the anastomosis of patient 2. The FFR value of the stenosis should be considered when performing bypass surgery. When the stenosis of high FFR values is grafted, a high OSI region is created at the graft, especially at the anastomosis. In the long term, this can cause anastomotic blockage and graft failure.
Purpose A common surgical methods for the treatment of coronary heart disease is coronary artery bypass grafting ( CABG ). The most important concern is the graft patency. When restenosis or occlusion occurs on the graft, the blood supply to the downstream will be reduced, and serious myocardial ischemia will occur again. Hemodynamics are the key factors affecting the graft patency. If the hemodynamic results of the graft under different surgical methods can be known before coronary artery bypass grafting, it can help doctors to choose the optimal operation method. Methods In this study, the modeling and simulation method of multi-scaled model of coronary had been designed. The 3D model of the bypass surgery region is constructed by the 3D reconstruction of the patient's medical imaging and the virtual bypass surgery. The individuation lumped parameter model is constructed by the basic physiological information of the patients. Finally, the two models are connected by a special boundary surface coupling algorithm to construct a 0D-3D coupled multi-scaled model that can be used to calculate the hemodynamic environment. Through calculation, the flow waveform, wall shear stress(WSS), oscillating shear index(OSI) and other hemodynamic parameters in the graft under different bypass methods were compared, and the optimal operation method with the best hemodynamic environment was selected. Results The method was used to calculate two clinical cases, and the effectiveness of the method was proved by the comparison of calculated graft flow and real graft flow, and the comparison of hemodynamic environment and graft outcomes after one year. Conclusion This method can realize preoperative evaluation of the hemodynamic environment of the graft under different bypass methods, and then select the optimal operation method for the patients and improve the graft patency after operation.
Background: Different Traditional Chinese medicine (TCM) constitution types have different disease susceptibility and tendency, and TCM constitution identification is of great significance in TCM clinical practice. The TCM constitution identification method based on observation and consultation is subjective, and the objective identification technique opens up a new way to modernize TCM treatment. Our study aimed to build a TCM constitution identification model based on tongue feature data and machine learning algorithms, which provides a new fast and accurate method for TCM constitution identification.Methods: We use TFDA-1 tongue diagnostic instrument to collect standardized tongue images of people with Yang deficiency constitution, Yin deficiency constitution and balanced constitution. and use tongue image analysis software (TDAS) to quantitatively analyze tongue color, tongue texture and tongue coating area. Pearson correlation analysis was used to explore the correlation between tongue characteristics and TCM constitution. Four machine learning algorithms, including SVM, decision tree, random forest, and XGboost were used to build a TCM constitution identification model based on tongue features and evaluate the model's effectiveness.Results: The results show that XGboost has the highest accuracy rate among the four machine learning algorithms and the best performance in model evaluation. Pearson correlation analysis found a specific correlation between TCM constitution and tongue features. Significant correlations existed between the Yang deficiency constitution, Yin deficiency constitution, and the balanced constitution with 16 tongue features. In addition, the model's accuracy for the group 2 containing 16 tongue features was higher than that of the whole feature group (Group 1). XGboost was the most effective in this study for identifying TCM constitution, and the tongue features filtered by correlation analysis led to higher accuracy of TCM constitution identification.Conclusions: Tongue feature information can be an essential reference for TCM constitution identification. Machine learning provides a method for rapid identification of TCM constitution types. The XGboost TCM constitution identification model with good performance gives a new way for clinical " Identifying TCM Constitution by Tongue Image" implementation offers a reference and contributes to the performance of " Preventive Treatment of Disease" of TCM and individualized diagnosis and treatment and health preservation. In addition, Objective identification technology has opened up a new way to modernize TCM diagnosis and treatment.
Objective: After coronary artery bypass grafting (CABG) surgery, the main causes of poor instant patency of left internal mammary arteries (LIMAs) are competitive flow and anastomotic stenosis, but how to determine the cause of LIMA non-patency without interfering with the native coronary artery is still a difficult problem to be solved urgently.Methods: In this study, a 0D-3D coupled multiscaled CABG model of anastomotic stenosis and competitive flow was constructed. After calculation, the flow waveform of the LIMA was extracted, and the waveform shape, common clinical parameters (average flow, PI, and DF), and graft flow FFT ratio results (F0/H1 and F0/H2) were analyzed.Results: For LIMA, these three common clinical parameters did not differ significantly between the anastomotic stenosis group and competitive flow group. However, the waveform shape and FFT ratio (especially F0/H2) of the competitive flow group were significantly different from those of the anastomotic stenosis group. When the cause was competitive flow, there was systolic backflow, and F0/H2 was too high (>14.89). When the cause was anastomotic stenosis, the waveform maintained a bimodal state and F0/H2 was in a normal state (about 1.17).Conclusion: When poor instant patency of the LIMA is found after CABG, the causes can be determined by graft flow waveform shape and F0/H2.
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