A method for predicting graft permeability model based on wall shear stress image features in heart bypass surgery

A technology of image features and predictive models, applied in the field of machine learning and model establishment, can solve the problems of decreased permeability of graft vessels

Active Publication Date: 2021-05-14
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Especially for the wall shear stress, the wall shear stress is too low or too high, and the wall shear stress gradient is too high will lead to the decrease of the permeability of the graft vessel

Method used

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  • A method for predicting graft permeability model based on wall shear stress image features in heart bypass surgery
  • A method for predicting graft permeability model based on wall shear stress image features in heart bypass surgery
  • A method for predicting graft permeability model based on wall shear stress image features in heart bypass surgery

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Experimental program
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Embodiment 1

[0038] For each graft vessel, its waveform is intercepted from the real-time blood flow waveform picture and processed digitally, and a three-dimensional bypass surgery model suitable for the graft vessel is constructed according to the type of graft vessel and the size of the ultrasound probe. The digitized flow waveform was added to the entrance of the bridge vessel, and the pressure of 0mmHg was added to the outlet of the coronary artery as boundary conditions, and the finite element software was used for calculation.

[0039] After the calculation, the image features of the wall shear stress cloud image of the anastomotic site of the graft vessel were extracted and dimensionally reduced, and used as features to build a prediction model using a support vector machine. The RBF kernel function is selected, and the (C, g) coefficients are optimized by means of grid search and cross-validation, and the optimal (C, g) is selected as the coefficient of the prediction model (see th...

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Abstract

The invention relates to a method for establishing a predictive bridge vessel permeability model based on wall shear stress image features in heart bypass surgery, belonging to the field of model establishment. The real-time blood flow waveform of the bridge vessel measured during the operation is digitally processed, and assigned as a boundary condition to the 3D model of the bypass surgery, and the wall shear stress cloud image of the anastomotic site is obtained by the finite element method, and the color features and texture of the image are extracted After the features, the principal component analysis method is used to reduce the dimensionality of the features, and then the features after dimensionality reduction are used to build a prediction model based on support vector machines. This method can be used to help doctors and patients understand the effect of surgery, determine the strategy of further surgery or the plan of postoperative review.

Description

Technical field: [0001] The invention belongs to the technical field of model establishment, and essentially belongs to the field of machine learning. In particular, the invention relates to a method for establishing a model for predicting the permeability of a graft vessel based on wall surface shear stress image features in heart bypass surgery. Background technique: [0002] Coronary artery bypass grafting (CABG) is a commonly used surgical method for the treatment of coronary heart disease. The main problem at present is the risk of graft failure after surgery. According to statistics, the failure rate of vein grafts in the early postoperative period is 15-30%, and the failure rate will reach 50% after 10 years. The 10-year patency rate of arterial grafts was 95%, and 15 years was 88%. After the graft fails, the patient will suffer from myocardial ischemia again, which can be life-threatening in severe cases. Therefore, for each specific patient, how to predict the pe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B34/10
CPCA61B34/10A61B2034/105
Inventor 刘有军毛伯䶮李鲍冯月
Owner BEIJING UNIV OF TECH
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