Research on the differential diagnosis of phlegm and blood stasis pattern and qi deficiency and blood stasis pattern in stable angina pectoris based on coronary artery CT angiography radiomics.

Autor: WEI Dongsheng, QI Jiajie, LIU Xiaosheng, LI Luzhen, LI Han, LIU Yuting, DENG Chengkang, DAI Xu, ZHAO Baoying, ZHANG Zhe
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Zdroj: Journal of Beijing University of Traditional Chinese Medicine; 2024, Vol. 47 Issue 4, p545-554, 10p
Abstrakt: Objective To establish a differential model of phlegm and blood stasis pattern and qi deficiency and blood stasis pattern in stable angina pectoris using radiomics. Methods A total of 91 patients with stable angina pectoris who underwent coronary artery CT angiography in Affiliated Hospital of Liaoning University of Traditional Chinese Medicine from January 2021 to January 2022 were collected, including 47 cases of phlegm and blood stasis pattern and 44 cases of qi deficiency and blood stasis pattern. The patients were divided into train set(64 cases) and test set(27 cases) according to the ratio of 7:3 by stratified random sampling method. 3D-slicer software was used to extract the radiomics features of pericoronary adipose tissue(PCAT) images. Principal component analysis was used to visualize the distribution of radiomics features of pattern of phlegm and blood stasis and pattern of qi deficiency and blood stasis. The least absolute shrinkage and selection operator regression analysis and support vector machine decreasing feature elimination were used for feature selection. The multinomial logistics regression was used for model construction. The receiver operating characteristic (ROC) curve was used to verify the model in the train set and the test set to evaluate the effectiveness of the radiomics features in differentiating phlegm and blood stasis pattern and qi deficiency and blood stasis pattern. Finally, Spearman coefficient was used to analyze the correlation between the differential features and clinical physicochemical data. Results A total of 837 radiomics features were extracted from PCAT images by 3D-slicer software. In the principal component analysis, PC1 and PC2 explained 77.9% and 8.1% of the total variance, respectively, and there was a relatively obvious separation trend between the two pattern groups. After feature screening, 7 radiomics features were used to construct the differential model of phlegm and blood stasis pattern and qi deficiency and blood stasis pattern. The area under the ROC curve (AUC) of the differential model was 0.844 in the train set and 0.834 in the test set. Spearman correlation analysis showed that the differential features were significantly correlated with cTnI, neutrophil, triglyceride, total cholesterol, and leukocyte. Conclusion The CT radiomics model based on PCAT has a high discrimination efficiency for stable angina pectoris with phlegm and blood stasis pattern and qi deficiency and blood stasis pattern. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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