Study on the Diagnostic Efficacy of Super Resolution Reconstructed Image Omics Model in Diagnosis of Traditional Chinese Medicine Syndromes of Primary Liver Cancer
WANG Ying
LI Yingxin
ZHANG Xirong
Abstract：Objective:To explore the efficacy of super resolution reconstructed image omics model in the diagnosis of traditional Chinese medicine(TCM)syndromes of primary liver cancer.Methods:A total of 128 patients with primary liver cancer were retrospectively collected and randomly divided into the training group and the test group according to ratio of 8:2.All cases underwent MRI scanning.The clinical data and imaging signs of patients with primary liver cancer were analyzed by single factor analysis.The regions of interest were mapped semi-automatically on diffusion weighted imaging(DWI)images before and after super resolution reconstruction.Then,the minimum redundancy and maximum correlation were used to reduce dimension and construct the model by Select K Best and LASSO regression.The receiver operating characteristic(ROC)curve and decision curve were drawn to evaluate the performance of the model.Results:There were no significant differences in clinical data and imaging signs among different types of primary liver cancer(P＞0.05).The AUC value,sensitivity,specificity and accuracy of liver depression and spleen deficiency syndrome model NR in the test group were 0.585,58.3％,46.7％and 53.0％,respectively,and the AUC value,sensitivity,specificity and accuracy of model SR in the test group were 0.639,50.0％,69.4％and 64.6％,respectively.The AUC value,sensitivity,specificity and accuracy of qi-stagnation and blood-stasis syndrome model NR in the test group were 0.608,66.7％,43.3％and 56.1％,respectively,and the AUC value,sensitivity,specificity and accuracy of model SR in the test group were 0.644,53.3％,63.6％and 61.0％,respectively.The AUC value,sensitivity,specificity and accuracy of liver-kidney yin deficiency syndrome model NR in the test group were 0.612,47.2％,63.3％and 54.5％,respectively,and the AUC value,sensitivity,specificity and accuracy of model SR in the test group were 0.644,60.0％,61.4％and 61.0％,respectively.The decision curve showed that model SR had higher net income.Conclusion:Compared with model NR,model SR has good predictive performance in judging TCM syndrome type of primary liver cancer.
Keywords：super resolution reconstructionimage omicsprimary liver cancertraditional Chinese medicine syndromesliver depression and spleen deficiency syndromeqi-stagnation and blood-stasis syndromeliver-kidney yin deficiency syndrome
Publication Date：2024-08-05
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：9( 853-860,912 )