Method for establishing bypass vessel permeability prediction model based on wall surface cutting stress image features during heart bypass surgery

An image feature and heart bypass technology, applied in the field of machine learning and model building, can solve the problem of decreased permeability of bridge vessels, and achieve the effect of improving accuracy and high accuracy

Active Publication Date: 2019-10-11
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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  • Method for establishing bypass vessel permeability prediction model based on wall surface cutting stress image features during heart bypass surgery
  • Method for establishing bypass vessel permeability prediction model based on wall surface cutting stress image features during heart bypass surgery
  • Method for establishing bypass vessel permeability prediction model based on wall surface cutting stress image features during 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 ultrasonic 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 bypass vessel permeability prediction model based on wall surface cutting stress image features during heart bypass surgery, and belongs to the field of model building. A bypass vessel instant blood flow waveform measured during the surgery is digitally processed to serve as a boundary condition to be assigned to a bypass surgery three-dimensional model, a wall surface cutting stress cloud diagram of the anastomotic opening part is obtained through a finite element method, color features and texture features of the image are extracted, thendimension reduction processing is conducted on the features by using a principal component analysis method, and then the features obtained after dimension reduction are used for constructing the prediction model based on a support vector machine. The method can be used for helping a doctor and a patient to know surgical effects to determine a strategy for further surgeries or a scheme for postoperative re-examination.

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 Applications(China)
IPC IPC(8): A61B34/10
CPCA61B34/10A61B2034/105
Inventor 刘有军毛伯李鲍冯月
Owner BEIJING UNIV OF TECH
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