Font Size: a A A

Value Of Cardiac Magnetic Resonance Feature Tracking Technique In Diagnosis And Prediction Of Chronic Myocardial Infarction

Posted on:2024-03-25Degree:MasterType:Thesis
Country:ChinaCandidate:J ChenFull Text:PDF
GTID:2544306932972929Subject:Imaging and nuclear medicine
Abstract/Summary:PDF Full Text Request
Objective: Cardiac magnetic resonance feature tracking(CMR-FT)is a new technique for non-invasive quantitative evaluation of myocardial strain based on film sequence images,which can be used for subclinical evaluation of atrial ventricular myocardial deformation,and can objectively reflect the changes of ventricular structure and function after myocardial infarction in the early stage.The objective of this study was to investigate the value of CMR-FT in evaluating the degree of myocardial injury,the degree of scar tissue penetration,and the long-term prognosis after myocardial infarction.Method: A retrospective analysis was performed on 42 patients with chronic myocardial infarction(n=42)and 26(n=26)in the healthy control group in Dalian Central Hospital and all patients with myocardial infarction were confirmed by coronary angiography,and the diseased blood vessels were all single.All subjects were examined on a 1.5T MR scanner that included rapid equilibrium steady-state free sequence(SSFP)film sequences(left ventricular short-axis,two-,three-,and four-chamber long-axis levels)and advanced gadolinium-enhanced(LGE)imaging.CMR-FT technology was used to measure the left ventricular myocardial strain of the subjects,including global peak longitudinal strain(GPLS),global peak circumferential strain(GPCS),global peak radial strain(GPRS)and 16-segment peak strain(PLS,PCS,PRS),the left ventricular function index(LVEF,EDV,ESV)was calculated by the left ventricular short axis sequence,and the size of myocardial infarction area(IS)was measured by the grayscale threshold 5standard deviation method.According to the results of LGE display,a total of 672(16*42)myocardial segments in the myocardial infarction group were classified as follows: LGE showed negative as normal myocardial segment,LGE showed scar tissue less than 50%of the corresponding myocardial thickness,defined as non-transmural infarction myocardial segment,LGE showed scar tissue greater than or equal to 50% of the corresponding segment myocardial thickness,defined as transmural infarction myocardial segment.Patients in the chronic myocardial infarction group who had longterm adverse endpoint events,including all-cause mortality,heart failure,recurrent myocardial infarction,and malignant arrhythmias.The differences between cardiac function indexes and overall peak strain between the two groups were compared,the correlation between strain parameters and cardiac function indicators and infarct area was analyzed,the difference and recognition ability of segmental peak strain in normal and infarcted myocardial segments,transmural myocardial and non-transmural myocardial segments were analyzed,the changes of cardiac function were examined by echocardiography before and after two times,and the prediction of adverse endpoint events in myocardial infarction group was analyzed by different parameters.Results:1.The comparison of cardiac function indexes and overall peak strain between the chronic myocardial infarction group and the control group showed that LVEF,GPLS,GPCS and GPRS were significantly impaired,and the overall strain parameters were strongly correlated with LVEF(r respectively-0.731,-0.778,0.791,P <0.001),where GPLS and GPCS are negatively correlated with LVEF,while GPRS is positively correlated with LVEF.The IS size in the chronic myocardial infarction group was 16.00%(11.00%,29.74%).And the correlation between IS and GPLS,and GPCS is weak.2.PCS was statistically different between normal and infarcted myocardial segments.PLS and PRS were statistically different between groups with transmural infarction myocardial segments and non-transmural infarction,transmural infarction myocardial segments and normal myocardial segments.When the PCS threshold was-8.8%,the sensitivity and specificity for identifying transmural infarct myocardial segments were76% and 71% respectively(AUC=0.77,95% CI 0.72-0.82,P<0.001),and when the PLS threshold was-8.9%,the sensitivity and specificity for identifying transmural infarct myocardial segments were 75% and 60% respectively(AUC=0.69,95% CI 0.64-0.74,P<0.001).3.The chronic myocardial infarction group was followed up from CMR examination to December 31,2021,with a follow-up of 8 to 24 months,with an average follow-up of13 months,and 15 of the 42 patients had long-term adverse endpoint events,all of which were heart failure.The prediction of GPLS,GPCS,LVEF,and infarct area(IS)were all valuable for the prediction of long-term adverse endpoint events,with area under the curve(AUC)of 0.80(95% CI 0.66-0.93,P=0.002),0.75(95% CI 0.60-0.91,P=0.007),0.68(95% CI 0.50-0.86,P=0.045),and 0.60(95% CI 0.40-0.80,P= 0.036).The AUC of GPLS and GPCS is better than that of IS and LVEF,and GPLS has the best detection efficiency,with an optimal identification threshold of-7.35%.In multivariate logistic stepwise regression,the occurrence of adverse cardiovascular events after follow-up was taken as the dependent variable,and the global strain indicators(GPLS,GPCS,GPRS),cardiac function indicators(LVEF,EDV,ESV),IS were taken as the independent variables that might affect the prognosis.Univariate logistic regression was performed to screen out P<0.05 indicators.Further forward Wald method was used to screen independent variables.The results showed that only GPLS could predict the occurrence of long-term adverse end events(0R:1.352,95% CI 1.078-1.695,P=0.009).Conclusions: For patients with chronic myocardial infarction,CMR-FT technology provides a simple and reliable means of myocardial strain analysis,which can identify myocardial injury,and the degree of scar penetration,and predict long-term adverse end events.In particular,GPLS parameters have good potential application value in the future.
Keywords/Search Tags:Cardiac magnetic resonance, Myocardial infarction, Feature tracking, Myocardial strain
PDF Full Text Request
Related items