The Value Of Epicardial And Pericoronary Adipose Tissue Radiomics Based On Coronary Computed Tomography Angiography In Identifying Patients With Non-ST-segment Elevation Myocardial Infarction

Objective: This study sought to ascertain if the radiomics features of epicardial adipose tissue and pericoronary adipose tissue based on coronary computed tomography angiography could identify NSTEMIfromunstableangina UA.Materialsand Methods:Thisretrospectivecase-controlstudyincluded 83 patients with NSTEMI and83 controls with UA who were matched based on age,gender,cardiovascular risk factors,body mass index,andmedications.Allpatientswereseparatedintotraining(n=116)andvalidationcohorts(n=50)at a ratio of 7 :3 based on the time order of admission.After selecting features from EAT and PCAT,logistic regression models were created.Finally,we developed an EAT radiomics model,three vessel-based PCATradiomicsmodels,andacombinedmodelbycombiningthethree PCATradiomics models.To evaluate the performance of each model,classification,calibration,and clinical application wereused.Results:Eightradiomicsfeaturesof EAT,sixteenof RCA-PCAT,fifteenof LAD-PCAT,andeighteen of LCX-PCAT were selected and used to construct radiomics models.The area under the curves(AUCs)of the EAT,RCA-PCAT,LAD-PCAT,LCX-PCAT and the combined models were 0.708(95% CI: 0.614-0.802),0.833(95% CI:0.759-0.906),0.720(95% CI:0.628-0.813),0.713(95%CI:0.619-0.807),0.889(95% CI:0.832-0.946)in the training cohort,and 0.693(95% CI:0.546-0.840),0.837(95% CI: 0.729-0.945),0.766(95% CI: 0.625-0.907),0.675(95% CI: 0.521-0.829),0.898(95%CI:0.802-0.993)inthevalidationcohort,respectively.Conclusion: The capacity of the EAT radiomics model to distinguish NSTEMI from UA is limited.However,the combination of the three vessel-based PCAT radiomics may have the potential to distinguishbetween NSTEMIand UA.