Radiomics-based hepatic venous pressure gradient (rHVPG) calculation model construction method

A technology of pressure gradient and calculation model, applied in calculation, computer parts, character and pattern recognition, etc., can solve the problems of many interference factors, ignoring blood rheology changes, and large numerical variation.

Active Publication Date: 2017-12-15
祁小龙
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Problems solved by technology

However, the main problems of research in this field at home and abroad are: the scope of assessment is limited to the main portal vein, and the overall influence of the hepatic vein-portal system is not considered; only portal hemodynamic factors are considered, and blood in patients with cirrhosis is ignored. Rheological changes, such as changes in blood viscosity and a decrease in the deformability of red blood cells, contribute to an increase in portal resistance
[0006] Various measurement techniques of portal pressure are still affected by their own interference factors, or they are highly invasive, difficult to operate, or have many interference factors and large value variations
At present, in the relevant reports at home and abroad, the diagnostic methods of portal hypertension, especially the early non-invasive diagnostic techniques, still need further research and improvement.

Method used

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  • Radiomics-based hepatic venous pressure gradient (rHVPG) calculation model construction method
  • Radiomics-based hepatic venous pressure gradient (rHVPG) calculation model construction method
  • Radiomics-based hepatic venous pressure gradient (rHVPG) calculation model construction method

Examples

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Embodiment 1

[0100] Example 1: R language glmnet toolkit for feature screening, modeling and calculation rHVPG

[0101] In the R language programming interface, first use library (glmnet) to import the glmnet toolkit, and use read.table("D: / train_list.csv", header=TRUE, sep=',') to include 189 examples of the training set The csv data of image features is imported into the variable train. Use as.matrix(train[,1:20648]) and as.matrix(train[,20649]) to store the feature matrix and outcome data in the train in the variables train_x and train_y respectively. Set the parameters of the glmnet function: x=train_x, y=train_y, family='binomial', nfold=10, the entire glmnet function call process uses lasso dimensionality reduction, and draws a feature screening map (such as Figure 31 shown) and the error curve (as Figure 32 shown), and then perform 10-fold cross-validation through the cv.glmnet function, and select the parameter lambda.min to select the optimal linear model. At this time, it cor...

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Abstract

The invention provides a radiomics-based hepatic venous pressure gradient (rHVPG) calculation model construction method, on this basis, a more advantageous hepatic venous pressure gradient calculation model can be constructed, and a new way is provided for the calculation of the early stage non-invasive index of a patient with portal hypertension. The invention also provides a radiomics-based hepatic venous pressure gradient calculation system. The invention overcomes the many limitations of current non-invasive measurement methods. The rHVPG calculation system proposed by the invention is feasible, is expected to provide a new idea for noninvasive measurement of portal pressure, and plays a positive role in improving the quality of life of the patient with portal hypertension and alleviating the disease burden of families and society.

Description

technical field [0001] The invention relates to a method for constructing a hepatic venous pressure gradient calculation model based on radiomics. Background technique [0002] Globally, liver disease (viral infection, alcoholic liver disease, nonalcoholic fatty liver and related cirrhosis, hepatocellular carcinoma) is one of the leading causes of death, and in China alone, liver disease threatens nearly 3 The health and lives of 100 million people, seriously exacerbating the global burden of disease. Take chronic liver disease caused by hepatitis B virus infection as an example. According to the report of the World Health Organization, about 2 billion people in the world have been infected with hepatitis B virus, of which 240 million people are chronic hepatitis B virus infected people, and about 650,000 people die of hepatitis B virus infection every year. Liver cirrhosis, hepatocellular carcinoma, etc. Among patients with liver cirrhosis worldwide, 30% are caused by hep...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/46G06T7/40
CPCG06T7/40G06T2207/30101G06T2207/30056G06V10/25G06V10/40
Inventor 祁小龙张煜宁振源杨永平黄义飞邹佳良刘川惠佳亮侯金林
Owner 祁小龙
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