Association of stress hyperglycemia ratio with left ventricular function and microvascular obstruction in patients with ST-segment elevation myocardial infarction: a 3.0 T cardiac magnetic resonance study.

BACKGROUND: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. METHODS: Consecutive patients who underwent CMR at index admission (3-7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). RESULTS: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = - 0.252; r = - 0.261; and r = - 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. CONCLUSION: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO.

Cardiac magnetic resonance feature tracking derived left atrial strain in the diagnosis of patients with constrictive pericarditis and restrictive cardiomyopathy.

Objective: To explore the diagnostic value of cardiac magnetic resonance feature tracking (CMR-FT) divided left atrial (LA) strain in differentiating constrictive pericarditis (CP) and restrictive cardiomyopathy (RCM). Methods: Patients with CP (n = 40) and RCM (n = 40), and another 40 normal control group were retrospectively enrolled over a period of 8 years at a tertiary cardiac centre. Left ventricular (LV) and biatrial strain and strain rate (SR) were measured. Atrial strain was used to differentiate between patients with CP and RCM. Then, patients were grouped according to their left ventricular ejection fraction (LVEF), either ≥50% or < 50%. A deeper analysis was done to evaluate the diagnostic value of atrial strain in these subgroups. Receiver operating characteristic curves (ROC) were used to assess the accuracy of myocardial strain based on CMR FT for the differential diagnosis of CP and RCM. Results: LV and LA strain and SR were significantly lower in patients with CP and RCM than those in the normal controls (P < 0.05). LA strain and SR were significantly lower in the RCM group than in the CP group (P < 0.05). In patients with either LVEF≥50% or＜50%, LA strain were lower in the RCM group than in the CP group (P < 0.05). ROC analysis showed that LA stored strain (LA-εs) had a good differential diagnostic value for CP and RCM, with an area under the curve (AUC) of 0.811 and an optimal cutoff value of 6.98%, above this value it tends to develop CP. Further, an excellent differential diagnostic value was found in patients with LVEF＜50%, with an AUC of 0.955. Conclusion: LA strain analysis obtained by CMR-FT provides good differential diagnostic value for distinguishing CP from RCM, especially in patients with LVEF＜50%.

Cardiac magnetic resonance analysis of left atrium function in patients with pre-apical hypertrophic cardiomyopathy.

Background: Patients presenting with unexplained T wave inversion on electrocardiogram combined with thickened left ventricular apex but less than 15 mm had been proposed as a preclinical scope of apical hypertrophy cardiomyopathy (pre-ApHCM). However, analysis of left atrial (LA) function in these patients has not been studied. This study aims to evaluate the LA function in pre-ApHCM patients and compare it with patients with ApHCM using cardiac magnetic resonance (CMR) imaging. Methods: In this retrospective case-control study, a total of 3,593 CMR reports from Beijing Anzhen Hospital, Capital Medical University, China were reviewed. Finally, 31 pre-ApHCM patients were identified and 40 ApHCM and 31 normal controls were included for comparison. LA volumetric and strain were analyzed by CMR. Two-tailed one-way ANOVA was used to analyze the difference of three groups. Pearson correlation test was used for correlation analysis. Results: All of the volumetric parameters in pre-ApHCM group were higher than those in control group. LA reservoir (LA total EF, εs) and conduit function (LA passive EF, εe) parameters, were significantly different among the three groups, which were the lowest in the ApHCM group, intermediate in the pre-ApHCM group, and the highest in the control group ((all P<0.001). Compared with the control group, the LA booster pump function, both the booster EF and booster pump strain (εa) in ApHCM were impaired (P=0.003 and P=0.002 respectively). Meanwhile, only the εa was impaired (P=0.016) while LA booster EF was not (P=0.064) in the pre-ApHCM group, neither εa nor the booster EF show difference between the ApHCM and pre-ApHCM (P=0.272 and P=0.518 respectively). Conclusions: LA function features in pre-ApHCM patients were similar to ApHCM but different from the normal controls. In pre-ApHCM and ApHCM patients, LA reservoir and conduit function impaired earlier before left atrium enlarged and decreased progressively as apex thickens. These findings may help to understand the LA functional change from pre-ApHCM to ApHCM, and to detect subclinical changes in patients with pre-ApHCM before overt hypertrophy or clinical symptoms develop.

Dynamic changes in cardiac morphology, function, and diffuse myocardial fibrosis duration of diabetes in type 1 and type 2 diabetic mice models using 7.0 T CMR and echocardiography.

Background: Diabetes mellitus (DM) is associated with an increased risk of cardiovascular disease (CVD). Hence, early detection of cardiac changes by imaging is crucial to reducing cardiovascular complications. Purpose: Early detection of cardiac changes is crucial to reducing cardiovascular complications. The study aimed to detect the dynamic change in cardiac morphology, function, and diffuse myocardial fibrosis(DMF) associated with T1DM and T2DM mice models. Materials and methods: 4-week-old C57Bl/6J male mice were randomly divided into control (n=30), T1DM (n=30), and T2DM (n=30) groups. A longitudinal study was conducted every 4 weeks using serial 7.0T CMR and echocardiography imaging. Left ventricular ejection fraction (LV EF), tissue tracking parameters, and DMF were measured by cine CMR and extracellular volume fraction (ECV). Global peak circumferential strain (GCPS), peak systolic strain rate (GCPSSR) values were acquired by CMR feature tracking. LV diastolic function parameter (E/E') was acquired by echocardiography. The correlations between the ECV and cardiac function parameters were assessed by Pearson's test. Results: A total of 6 mice were included every 4 weeks in control, T1DM, and T2DM groups for analysis. Compared to control group, an increase was detected in the LV mass and E/E' ratio, while the values of GCPS, GCPSSR decreased mildly in DM. Compared to T2DM group, GCPS and GCPSSR decreased earlier in T1DM(GCPS 12W,P=0.004; GCPSSR 12W,P=0.04). ECV values showed a significant correlation with GCPS and GCPSSR in DM groups. Moreover, ECV values showed a strong positive correlation with E/E'(T1DM,r=0.757,P<0.001;T2DM, r=0.811,P<0.001). Conclusion: The combination of ECV and cardiac mechanical parameters provide imaging biomakers for pathophysiology, early diagnosis of cardiac morphology, function and early intervention in diabetic cardiomyopathy in the future.

Impaired cardiac pump function assessment with normalized cardiac power using cardiac magnetic resonance in patients with hypertrophic cardiomyopathy.

Background: Cardiac power (CP; CP = 0.222 × cardiac output × mean blood pressure) output in patients with heart failure has been studied previously, but its importance in patients with hypertrophic cardiomyopathy (HCM) remains unclear. The present study aimed to explore the role of normalized CP (normalized CP = CP/ventricle mass) in assessing cardiac function in patients with HCM with normal ejection fraction using cardiac magnetic resonance (CMR). Methods: This cross-sectional study enrolled 99 patients with HCM who underwent CMR from December 2020 to January 2022 at Beijing Anzhen Hospital, and these patients were classified into heart failure or non-heart failure subgroups. Meanwhile, a control group comprising 65 gender- and age-matched healthy volunteers was also enrolled. The baseline clinical characteristics and cardiac functional parameters were compared between the patients with HCM and the controls, and multivariable linear regression analysis was performed to analyze the relationship between normalized CP and the relevant factors. Results: Significantly higher CP (1.19 vs. 1.01 W; P=0.03) but lower normalized CP (0.73 vs. 1.12 W/100 g; P<0.001) were found in patients with HCM as compared with the controls. Multivariable analysis showed that HCM correlated well with normalized CP [ß=-0.235; 95% confidence interval (CI): -0.341 to -0.129; P<0.001]. In the HCM group, there were 34 cases with heart failure and 65 with non-heart failure, and the patients with HCM with heart failure showed similar CP (1.14 vs. 1.24 W; P=0.06) but significantly lower normalized CP (0.54 vs. 0.78 W/100 g; P<0.001). The correlation analysis of normalized CP and functional parameters revealed that normalized CP was inversely correlated with left ventricle mass/body surface area (R=-0.509; 95% CI: -0.646 to -0.341; P<0.001) in patients with HCM. Conclusions: Normalized CP decreased significantly and was negatively correlated with ventricle mass, indicating impaired cardiac pump function in patients with HCM. Normalized CP might play a critical role in detecting and evaluating impaired cardiac pump function in patients with HCM with preserved ejection fraction.

Deep learning-based prognostic model using non-enhanced cardiac cine MRI for outcome prediction in patients with heart failure.

OBJECTIVES: To evaluate the performance of a deep learning-based multi-source model for survival prediction and risk stratification in patients with heart failure. METHODS: Patients with heart failure with reduced ejection fraction (HFrEF) who underwent cardiac magnetic resonance between January 2015 and April 2020 were retrospectively included in this study. Baseline electronic health record data, including clinical demographic information, laboratory data, and electrocardiographic information, were collected. Short-axis non-contrast cine images of the whole heart were acquired to estimate the cardiac function parameters and the motion features of the left ventricle. Model accuracy was evaluated using the Harrell's concordance index. All patients were followed up for major adverse cardiac events (MACEs), and survival prediction was assessed using Kaplan-Meier curves. RESULTS: A total of 329 patients were evaluated (age 54 ± 14 years; men, 254) in this study. During a median follow-up period of 1041 days, 62 patients experienced MACEs and their median survival time was 495 days. When compared with conventional Cox hazard prediction models, deep learning models showed better survival prediction performance. Multi-data denoising autoencoder (DAE) model reached the concordance index of 0.8546 (95% CI: 0.7902-0.8883). Furthermore, when divided into phenogroups, the multi-data DAE model could significantly discriminate between the survival outcomes of the high-risk and low-risk groups compared with other models (p < 0.001). CONCLUSIONS: The proposed deep learning (DL) model based on non-contrast cardiac cine magnetic resonance imaging could independently predict the outcome of patients with HFrEF and showed better prediction efficiency than conventional methods. CLINICAL RELEVANCE STATEMENT: The proposed multi-source deep learning model based on cardiac magnetic resonance enables survival prediction in patients with heart failure. KEY POINTS: • A multi-source deep learning model based on non-contrast cardiovascular magnetic resonance (CMR) cine images was built to make robust survival prediction in patients with heart failure. • The ground truth definition contains electronic health record data as well as DL-based motion data, and cardiac motion information is extracted by optical flow method from non-contrast CMR cine images. • The DL-based model exhibits better prognostic value and stratification performance when compared with conventional prediction models and could aid in the risk stratification in patients with HF.

A Novel CT Perfusion-Based Fractional Flow Reserve Algorithm for Detecting Coronary Artery Disease.

BACKGROUND: The diagnostic accuracy of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA) (FFR-CT) needs to be further improved despite promising results available in the literature. While an innovative myocardial computed tomographic perfusion (CTP)-derived fractional flow reserve (CTP-FFR) model has been initially established, the feasibility of CTP-FFR to detect coronary artery ischemia in patients with suspected coronary artery disease (CAD) has not been proven. METHODS: This retrospective study included 93 patients (a total of 103 vessels) who received CCTA and CTP for suspected CAD. Invasive coronary angiography (ICA) was performed within 2 weeks after CCTA and CTP. CTP-FFR, CCTA (stenosis ≥ 50% and ≥70%), ICA, FFR-CT and CTP were assessed by independent laboratory experts. The diagnostic ability of the CTP-FFR grouped by quantitative coronary angiography (QCA) in mild (30-49%), moderate (50-69%) and severe stenosis (≥70%) was calculated. The effect of calcification of lesions, grouped by FFR on CTP-FFR measurements, was also assessed. RESULTS: On the basis of per-vessel level, the AUCs for CTP-FFR, CTP, FFR-CT and CCTA were 0.953, 0.876, 0.873 and 0.830, respectively (all p < 0.001). The sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of CTP-FFR for per-vessel level were 0.87, 0.88, 0.87, 0.85 and 0.89 respectively, compared with 0.87, 0.54, 0.69, 0.61, 0.83 and 0.75, 0.73, 0.74, 0.70, 0.77 for CCTA ≥ 50% and ≥70% stenosis, respectively. On the basis of per-vessel analysis, CTP-FFR had higher specificity, accuracy and AUC compared with CCTA and also higher AUC compared with FFR-CT or CTP (all p < 0.05). The sensitivity and accuracy of CTP-FFR + CTP + FFR-CT were also improved over FFR-CT alone (both p < 0.05). It also had improved specificity compared with FFR-CT or CTP alone (p < 0.01). A strong correlation between CTP-FFR and invasive FFR values was found on per-vessel analysis (Pearson's correlation coefficient 0.89). The specificity of CTP-FFR was higher in the severe calcification group than in the low calcification group (p < 0.001). CONCLUSIONS: A novel CTP-FFR model has promising value to detect myocardial ischemia in CAD, particularly in mild-to-moderate stenotic lesions.

Prognosis evaluation of chronic inflammatory cardiomyopathy with ring-like late gadolinium enhancement.

AIMS: Ring-like late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging is a special LGE pattern in patients with chronic inflammatory cardiomyopathy (infl-CMP), which is associated with cardiac dysfunction and ventricular remodelling and attributed to viral infection followed by bacterial and parasitic infections. Data on the combination of CMR imaging and clinical parameters that can add long-term prognostic value in patients with infl-CMP are still rare. We aimed to evaluate the prognostic value of CMR in risk stratification in this kind of patients. METHODS AND RESULTS: A total of 319 consecutive patients with clinically suspected myocarditis were retrospectively identified. Forty-seven patients with ring-like LGE on CMR who diagnosed as infl-CMP, and 72 patients with other LGE pattern were eligible for standardized follow-up. The left ventricle (LV) and right ventricle function and mass were analyses by CMR. Myocardial strain of the ventricles was evaluated by feature tracking. Major (cardiac death, resuscitated cardiac arrest, ventricular assist device, transplantation, and appropriate implantable cardioverter-defibrillator shock) and minor (rehospitalization due to heart failure and sustained atrial fibrillation) adverse cardiovascular events were assessed during follow-up since the date of nCMR examination. Cox proportional hazards model was used to investigate which of the prognostic factors identified by univariable analysis were significantly associated with cardiac events. In the ring-like LGE group, adverse cardiac events occurred in 14 (31.11%) patients, including 7 deaths (15.56%), 6 (13.33%) heart-failure hospitalizations, and 1 (2.22%) case of sustained atrial fibrillation during the mean follow-up period of 70.15 ± 45.68 months (interquartile range: 32.83-103.71 months). No major or minor adverse cardiac event occurred in the other LGE pattern group, except rehospitalization in one patient due to arrhythmia. Further analyses of ring-like LGE group by univariable and Multivariable Cox proportional hazard regression analysis showed that body mass index (BMI) (hazard ratio [HR]: 0.54, 95% confidence interval [CI]: 0.40-0.73, P = 0.000), right ventricle cardiac index (RVCI) (HR: 0.31, 95% CI: 0.14-0.71, P = 0.002), LV basal peak circumferential strain (LV-PCSbasal ) (HR: 1.26, 95% CI: 1.11-1.43, P = 0.000) were independently associated with the long-term outcome. Receiver operator characteristic curve indicated that the cut-off of LV-PCSBasal was -7.95%, and it has added prognostic value to BMI and RVCI. CONCLUSIONS: For infl-CMP patients with ring-like LGE on CMR, low BMI and RVCI were associated with a poor prognosis. LV-PCSBasal with a cut-off of -7.95% can add prognostic value for patients with infl-CMP who have ring-like LGE.

Artificial intelligence-based full aortic CT angiography imaging with ultra-low-dose contrast medium: a preliminary study.

OBJECTIVES: To further reduce the contrast medium (CM) dose of full aortic CT angiography (ACTA) imaging using the augmented cycle-consistent adversarial framework (Au-CycleGAN) algorithm. METHODS: We prospectively enrolled 150 consecutive patients with suspected aortic disease. All received ACTA scans of ultra-low-dose CM (ULDCM) protocol and low-dose CM (LDCM) protocol. These data were randomly assigned to the training datasets (n = 100) and the validation datasets (n = 50). The ULDCM images were reconstructed by the Au-CycleGAN algorithm. Then, the AI-based ULDCM images were compared with LDCM images in terms of image quality and diagnostic accuracy. RESULTS: The mean image quality score of each location in the AI-based ULDCM group was higher than that in the ULDCM group but a little lower than that in the LDCM group (all p < 0.05). All AI-based ULDCM images met the diagnostic requirements (score ≥ 3). Except for the image noise, the AI-based ULDCM images had higher attenuation value than the ULDCM and LDCM images as well as higher SNR and CNR in all locations of the aorta analyzed (all p < 0.05). Similar results were also seen in obese patients (BMI > 25, all p < 0.05). Using the findings of LDCM images as the reference, the AI-based ULDCM images showed good diagnostic parameters and no significant differences in any of the analyzed aortic disease diagnoses (all K-values > 0.80, p < 0.05). CONCLUSIONS: The required dose of CM for full ACTA imaging can be reduced to one-third of the CM dose of the LDCM protocol while maintaining image quality and diagnostic accuracy using the Au-CycleGAN algorithm. KEY POINTS: • The required dose of contrast medium (CM) for full ACTA imaging can be reduced to one-third of the CM dose of the low-dose contrast medium (LDCM) protocol using the Au-CycleGAN algorithm. • Except for the image noise, the AI-based ultra-low-dose contrast medium (ULDCM) images had better quantitative image quality parameters than the ULDCM and LDCM images. • No significant diagnostic differences were noted between the AI-based ULDCM and LDCM images regarding all the analyzed aortic disease diagnoses.

Incremental prognostic value of left atrial strain in patients with heart failure.

AIMS: The present study aimed to evaluate the prognostic value of atrial strain and strain rate (SR) parameters derived from cardiac magnetic resonance (CMR) feature tracking (FT) in patients with ischaemic and non-ischaemic dilated cardiomyopathy with heart failure with reduced ejection fraction (HFrEF) but without atrial fibrillation. METHODS AND RESULTS: A total of 300 patients who underwent CMR with left ventricular ejection fraction (LVEF) ≤ 40% and ischaemic or non-ischaemic dilated cardiomyopathy were analysed in this retrospective study. Major adverse cardiac events (MACEs) include cardiovascular death, heart transplantation, and rehospitalization for worsening HF. Ninety-four patients had MACEs during median follow-up of 3.84 years. Multivariate Cox regression models adjusted for common clinical and CMR risk factors detected a significant association between LA-εs and MACE in ischaemic (HR = 0.94/%; P = 0.002), non-ischaemic dilated cardiomyopathy (HR = 0.88/%; P = 0.001), or all included patients (HR = 0.87; P < 0.001). LA-εs provided incremental prognostic value over conventional outcome predictors (Uno C statistical comparison model: from 0.776 to 0.801, P < 0.0001; net reclassification improvement: 0.075, 95% CI: 0.0262-0.1301). Kaplan-Meier analysis revealed that the risk of MACE occurrence increased significantly with lower tertiles of left atrial reservoir strain (LA-εs) (log-rank P < 0.0001). Patients in the worst LA-εs tertile faced a significantly increased risk of MACEs irrespective of late gadolinium enhancement (LGE) (log-rank P < 0.0001). CONCLUSIONS: LA-εs derived from CMR FT has a significant prognostic impact on patients with ischaemic or non-ischaemic dilated cardiomyopathy, incremental to common clinical and CMR risk-factors.

Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.

OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstruction Veo (ASiR-V). METHODS: We prospectively evaluated 60 obese patients (body mass index [BMI] ≥ 30 kg/m2) who underwent coronary CT angiography in a single center. All CT scans were performed with GE Revolution 256-row CT at 120 kV (group A; 20 men, 10 women; mean age = 54.3 years; mean BMI = 33.4 kg/m2) or 100 kV (group B; 18 men; 12 women; mean age = 56.8 years; mean BMI = 32.9 kg/m2). Images in group A were reconstructed using ASiR-V, whereas images in group B were reconstructed using ASiR-V, DLIR-medium (DLIR-M), and DLIR-high (DLIR-H). Three blinded independent readers assessed the subjective image quality and measured the objective image quality. Radiation dose estimates were calculated and compared between patients by using 0.014 and 0.026 mSv·mGy-1 cm-1 corresponding to chest and heart conversion coefficients, respectively. RESULTS: The subjective score was significantly higher for images reconstructed using 120-kV ASiR-V (3.8), DLIR-M (3.9), and DLIR-H (4.0) compared with those reconstructed using 100-kV ASiR-V (3.5). Image noise was significantly lower in images reconstructed using DLIR-H compared with those reconstructed using other reconstruction algorithm (P < 0.001, respectively). The contrast-to-noise ratio was significantly higher in the DLIR-H group than in the groups using other reconstruction algorithm (P < 0.001). The effective radiation dose was significantly lower in group B than in group A (P < 0.001). CONCLUSIONS: Compared with ASiR-V, DLIR improved image quality in obese individuals without comprising image quality or increasing the radiation dose.

Association Between Left Ventricular Global Function Index and Outcomes in Patients With Dilated Cardiomyopathy.

Purpose: Left ventricular global function index (LVGFI) assessed using cardiac magnetic resonance (CMR) seems promising in the prediction of clinical outcomes. However, the role of the LVGFI is uncertain in patients with heart failure (HF) with dilated cardiomyopathy (DCM). To describe the association of LVGFI and outcomes in patients with DCM, it was hypothesized that LVGFI is associated with decreased major adverse cardiac events (MACEs) in patients with DCM. Materials and Methods: This prospective cohort study was conducted from January 2015 to April 2020 in consecutive patients with DCM who underwent CMR. The association between outcomes and LVGFI was assessed using a multivariable model adjusted with confounders. LVGFI was the primary exposure variable. The long-term outcome was a composite endpoint, including death or heart transplantation. Results: A total of 334 patients (mean age: 55 years) were included in this study. The average of CMR-LVGFI was 16.53%. Over a median follow-up of 565 days, 43 patients reached the composite endpoint. Kaplan-Meier analysis revealed that patients with LVGFI lower than the cutoff values (15.73%) had a higher estimated cumulative incidence of the endpoint compared to those with LVGFI higher than the cutoff values (P = 0.0021). The hazard of MACEs decreased by 38% for each 1 SD increase in LVGFI (hazard ratio 0.62[95%CI 0.43-0.91]) and after adjustment by 46% (HR 0.54 [95%CI 0.32-0.89]). The association was consistent across subgroup analyses. Conclusion: In this study, an increase in CMR-LVGFI was associated with decreasing the long-term risk of MACEs with DCM after adjustment for traditional confounders.