Assessment of Right Atrial Function Measured with Cardiac MRI Feature Tracking for Predicting Outcomes in Patients with Dilated Cardiomyopathy.

Background Right atrial (RA) function strain is increasingly acknowledged as an important predictor of adverse events in patients with diverse cardiovascular conditions. However, the prognostic value of RA strain in patients with dilated cardiomyopathy (DCM) remains uncertain. Purpose To evaluate the prognostic value of RA strain derived from cardiac MRI (CMR) feature tracking (FT) in patients with DCM. Materials and Methods This multicenter, retrospective study included consecutive adult patients with DCM who underwent CMR between June 2010 and May 2022. RA strain parameters were obtained using CMR FT. The primary end points were sudden or cardiac death or heart transplant. Cox regression analysis was used to determine the association of variables with outcomes. Incremental prognostic value was evaluated using C indexes and likelihood ratio tests. Results A total of 526 patients with DCM (mean age, 51 years ± 15 [SD]; 381 male) were included. During a median follow-up of 41 months, 79 patients with DCM reached the primary end points. At univariable analysis, RA conduit strain was associated with the primary end points (hazard ratio [HR], 0.82 [95% CI: 0.76, 0.87]; P < .001). In multivariable Cox analysis, RA conduit strain was an independent predictor for the primary end points (HR, 0.83 [95% CI: 0.77, 0.90]; P < .001). A model combining RA conduit strain with other clinical and conventional imaging risk factors (C statistic, 0.80; likelihood ratio, 92.54) showed improved discrimination and calibration for the primary end points compared with models with clinical variables (C statistic, 0.71; likelihood ratio, 37.12; both P < .001) or clinical and imaging variables (C statistic, 0.75; likelihood ratio, 64.69; both P < .001). Conclusion CMR FT-derived RA conduit strain was an independent predictor of adverse outcomes among patients with DCM, providing incremental prognostic value when combined in a model with clinical and conventional CMR risk factors. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Optimizing Clinical Cardiac MRI Workflow through Single Breath-Hold Compressed Sensing Cine: An Evaluation of Feasibility and Efficiency.

BACKGROUND: Although compressed sensing (CS) accelerated cine holds immense potential to replace conventional cardiovascular magnetic resonance (CMR) cine, how to use CS-based cine appropriately during clinical CMR examinations still needs exploring. METHODS: A total of 104 patients (46.5 ± 17.1 years) participated in this prospective study. For each participant, a balanced steady state free precession (bSSFP) cine was acquired as a reference, followed by two CS accelerated cine sequences with identical parameters before and after contrast injection. Lastly, a CS accelerated cine sequence with an increased flip angle was obtained. We subsequently compared scanning time, image quality, and biventricular function parameters between these sequences. RESULTS: All CS cine sequences demonstrated significantly shorter acquisition times compared to bSSFPref cine (p < 0.001). The bSSFPref cine showed higher left ventricular ejection fraction (LVEF) than all CS cine sequences (all p < 0.001), but no significant differences in LVEF were observed among the three CS cine sequences. Additionally, CS cine sequences displayed superior global image quality (p < 0.05) and fewer artifacts than bSSFPref cine (p < 0.005). Unenhanced CS cine and enhanced CS cine with increased flip angle showed higher global image quality than other cine sequences (p < 0.005). CONCLUSION: Single breath-hold CS cine delivers precise biventricular function parameters and offers a range of benefits including shorter scan time, better global image quality, and diminished motion artifacts. This innovative approach holds great promise in replacing conventional bSSFP cine and optimizing the CMR examination workflow.

Nonlocal based FISTA network for noninvasive cardiac transmembrane potential imaging.

Objective. The primary aim of our study is to advance our understanding and diagnosis of cardiac diseases. We focus on the reconstruction of myocardial transmembrane potential (TMP) from body surface potential mapping.Approach. We introduce a novel methodology for the reconstruction of the dynamic distribution of TMP. This is achieved through the integration of convolutional neural networks with conventional optimization algorithms. Specifically, we utilize the subject-specific transfer matrix to describe the dynamic changes in TMP distribution and ECG observations at the body surface. To estimate the TMP distribution, we employ LNFISTA-Net, a learnable non-local regularized iterative shrinkage-thresholding network. The coupled estimation processes are iteratively repeated until convergence.Main results. Our experiments demonstrate the capabilities and benefits of this strategy. The results highlight the effectiveness of our approach in accurately estimating the TMP distribution, thereby providing a reliable method for the diagnosis of cardiac diseases.Significance. Our approach demonstrates promising results, highlighting its potential utility for a range of applications in the medical field. By providing a more accurate and dynamic reconstruction of TMP, our methodology could significantly improve the diagnosis and treatment of cardiac diseases, thereby contributing to advancements in healthcare.

The effects of flip angle and gadolinium contrast agent on single breath-hold compressed sensing cardiac magnetic resonance cine for biventricular global strain assessment.

Background: Due to its potential to significantly reduce scanning time while delivering accurate results for cardiac volume function, compressed sensing (CS) has gained traction in cardiovascular magnetic resonance (CMR) cine. However, further investigation is necessary to explore its feasibility and impact on myocardial strain results. Materials and methods: A total of 102 participants [75 men, 46.5 ± 17.1 (SD) years] were included in this study. Each patient underwent four consecutive cine sequences with the same slice localization, including the reference multi-breath-hold balanced steady-state free precession (bSSFPref) cine, the CS cine with the same flip angle as bSSFPref before (CS45) and after (eCS45) contrast enhancement, and the CS cine (eCS70) with a 70-degree flip angle after contrast enhancement. Biventricular strain parameters were derived from cine images. Two-tailed paired t-tests were used for data analysis. Results: Global radial strain (GRS), global circumferential strain (GCS), and global longitudinal strain (GLS) were observed to be significantly lower in comparison to those obtained from bSSFPref sequences for both the right and left ventricles (all p < 0.001). No significant difference was observed on biventricular GRS-LAX (long-axis) and GLS values derived from enhanced and unenhanced CS cine sequences with the same flip angle, but remarkable reductions were noted in GRS-SAX (short-axis) and GCS values (p < 0.001). After contrast injection, a larger flip angle caused a significant elevation in left ventricular strain results (p < 0.001) but did not affect the right ventricle. The increase in flip angle appeared to compensate for contrast agent affection on left ventricular GRS-SAX, GCS values, and right ventricular GRS-LAX, GLS values. Conclusion: Despite incorporating gadolinium contrast agents and applying larger flip angles, single breath-hold CS cine sequences consistently yielded diminished strain values for both ventricles when compared with conventional cine sequences. Prior to employing this single breath-hold CS cine sequence to refine the clinical CMR examination procedure, it is crucial to consider its impact on myocardial strain results.

Identification of fibrosis in hypertrophic cardiomyopathy: a radiomic study on cardiac magnetic resonance cine imaging.

OBJECTIVES: Hypertrophic cardiomyopathy (HCM) often requires repeated enhanced cardiac magnetic resonance (CMR) imaging to detect fibrosis. We aimed to develop a practical model based on cine imaging to help identify patients with high risk of fibrosis and screen out patients without fibrosis to avoid unnecessary injection of contrast. METHODS: A total of 273 patients with HCM were divided into training and test sets at a ratio of 7:3. Logistic regression analysis was used to find predictive image features to construct CMR model. Radiomic features were derived from the maximal wall thickness (MWT) slice and entire left ventricular (LV) myocardium. Extreme gradient boosting was used to build radiomic models. Integrated models were established by fusing image features and radiomic models. The model performance was validated in the test set and assessed by ROC and calibration curve and decision curve analysis (DCA). RESULTS: We established five prediction models, including CMR, R1 (based on the MWT slice), R2 (based on the entire LV myocardium), and two integrated models (ICMR+R1 and ICMR+R2). In the test set, ICMR+R2 model had an excellent AUC value (0.898), diagnostic accuracy (89.02%), sensitivity (92.54%), and F1 score (93.23%) in identifying patients with positive late gadolinium enhancement. The calibration plots and DCA indicated that ICMR+R2 model was well-calibrated and presented a better net benefit than other models. CONCLUSIONS: A predictive model that fused image and radiomic features from the entire LV myocardium had good diagnostic performance, robustness, and clinical utility. KEY POINTS: • Hypertrophic cardiomyopathy is prone to fibrosis, requiring patients to undergo repeated enhanced cardiac magnetic resonance imaging to detect fibrosis over their lifetime follow-up. • A predictive model based on the entire left ventricular myocardium outperformed a model based on a slice of the maximal wall thickness. • A predictive model that fused image and radiomic features from the entire left ventricular myocardium had excellent diagnostic performance, robustness, and clinical utility.

Delta radiomics model for the prediction of progression-free survival time in advanced non-small-cell lung cancer patients after immunotherapy.

Objective: To assess the validity of pre- and posttreatment computed tomography (CT)-based radiomics signatures and delta radiomics signatures for predicting progression-free survival (PFS) in stage III-IV non-small-cell lung cancer (NSCLC) patients after immune checkpoint inhibitor (ICI) therapy. Methods: Quantitative image features of the largest primary lung tumours were extracted on CT-enhanced imaging at baseline (time point 0, TP0) and after the 2nd-3rd immunotherapy cycles (time point 1, TP1). The critical features were selected to construct TP0, TP1 and delta radiomics signatures for the risk stratification of patient survival after ICI treatment. In addition, a prediction model integrating the clinicopathologic risk characteristics and phenotypic signature was developed for the prediction of PFS. Results: The C-index of TP0, TP1 and delta radiomics models in the training and validation cohort were 0.64, 0.75, 0.80, and 0.61, 0.68, 0.78, respectively. The delta radiomics score exhibited good accuracy for distinguishing patients with slow and rapid progression to ICI treatment. The predictive accuracy of the combined prediction model was higher than that of the clinical prediction model in both training and validation sets (P<0.05), with a C-index of 0.83 and 0.70, respectively. Additionally, the delta radiomics model (C-index of 0.86) had a higher predictive accuracy compared to PD-L1 expression (C-index of 0.50) (P<0.0001). Conclusions: The combined prediction model including clinicopathologic characteristics (tumour anatomical classification and brain metastasis) and the delta radiomics signature could achieve the individualized prediction of PFS in ICIs-treated NSCLC patients.

Correlation analysis of epicardial adipose tissue and ventricular myocardial strain in Chinese amateur marathoners using cardiac magnetic resonance.

BACKGROUND: The volume of epicardial adipose tissue (EAT) is associated with an increased incidence of cardiovascular disease (CVD); however, only a few studies have examined its effect on the myocardial function of endurance in athletes. The association between the EAT and the variation of myocardial function is still unclear in amateur marathoners. Consequently, by using some sedentary individuals as the control, this study aims to evaluate the correlation between the EAT volume and the myocardial strain in the left and right ventricles of Chinese amateur marathoners by cardiac magnetic resonance (CMR). METHODS: A total of 30 amateur marathoners were included as the exercise group and 20 sedentary people as a control group. All participants received the cardiac magnetic resonance (CMR) to measure the left and right ventricular end-diastolic volume, end-systolic volume and volume index, stroke volume and index, cardiac output index, ejection fraction and myocardial mass, the EAT volume, global radial, circumferential, and longi-tudinal strains, and the strain rates of left and right ventricular myocardium. RESULTS: There was a significant difference in the EAT volume (EATV) index between the exercise group and the control group (26.82±11.76ml/m2 vs 37.82±17.15ml/m2, P = 0.01). Results from the multivariate linear regression analysis showed that BMI (standardized ß = 0.458; P < 0.001) had an independent positive correlation with the EATV index. The EATV index was negatively correlated with the left ventricular global radial strain (GRS) (r = -0.505; P = 0.004) in the exercise group, while it is negatively correlated with right ventricular GRS (r = -0.492; P = 0.027) and positively correlated with global longitudinal strain (GLS) (r = 0.601; P = 0.005) in the control group. In the exercise group, the multivariate linear regression analysis showed that the EATV index (standardized ß = -0.429; P = 0.021) was an independent determinant of the left ventricular GRS, and being a male (standardized ß = 0.396; P = 0.029) was an independent determinant of the right ventricular GLS. CONCLUSION: The EATV index is independently correlated with the left ventricular GRS in the amateur Chinese marathoners, also, the amateur marathon reduces the EATV index and increases the left ventricular myocardial mass, which consequently reduces the adverse effects on myocardial function.

A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis.

Background: Cardiac light-chain amyloidosis (AL CA) portends poor prognosis. Contrast cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) imaging is an important tool in recognizing AL CA. But contraindications to contrast CMR would significantly restrict its clinical application value. Our study aims to construct a convenient risk score to help identify cardiac involvement in patients at risk of AL CA. Moreover, we also investigate whether this risk score could provide prognosis information. Materials and Methods: Sixty-three patients at risk of AL CA were retrospectively included in our study. Basic clinical characters, lab results, 12-lead electrocardiogram data, and cardiac magnetic resonance image data were collected. AL CA was diagnosed according to typical CA LGE pattern. Logistic analysis was used to figure out predictive parameters of AL CA and their ß coefficients, further constructing the risk score. Receiver operating characteristics (ROC) curve was used to find the cut-off point best distinguishing AL CA+ from AL CA-patients. Bootstrapping was used for internal validation. All patients were divided into high-risk and low-risk group according to the diagnostic cut-off point, and followed up for survival information. Kaplan-Meier plots and log-rank test were performed to analyze if this score had prognostic value. Results: The risk score finally consisted of 4 parameters: pericardial effusion (PE) (1 point), low electrocardiographic QRS voltages (LQRSV) (1 point), CMR-derived impaired global radial strain (GRS) (<15.14%) (1 point) and increased left ventricular maximum wall thickness (LVMWT) (>13 mm) (2 points). Total score ranged from 0 to 5 points. A cut-off point of 1.5 showed highest accuracy in diagnosing AL CA with an AUC of 0.961 (95% CI: 0.924-0.997, sensitivity: 90.6%, specificity: 83.9%). Kaplan-Meier plots and log-rank test showed that the high-risk group had significantly poor overall survival rates. Conclusion: In patients at risk of AL CA, a risk score incorporating the presence of PE, LQRSV, and CMR-derived impaired GRS and increased LVMWT is predictive of a diagnosis of AL CA by LGE criteria. This risk score may be helpful especially when contrast CMR is not available or contraindicated, and further studies should be considered to validate this score.

Mean Scar Entropy by Late Gadolinium Enhancement Cardiac Magnetic Resonance Is Associated With Ventricular Arrhythmias Events in Hypertrophic Cardiomyopathy.

Background: Ventricular arrhythmias are associated with sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM). Previous studies have found the late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) was independently associated with ventricular arrhythmia (VA) in HCM. The risk stratification of VA remains complex and LGE is present in the majority of HCM patients. This study was conducted to determine whether the scar heterogeneity from LGE-derived entropy is associated with the VAs in HCM patients. Materials and Methods: Sixty-eight HCM patients with scarring were retrospectively enrolled and divided into VA (31 patients) and non-VA (37 patients) groups. The left ventricular ejection fraction (LVEF) and percentage of the LGE (% LGE) were evaluated. The scar heterogeneity was quantified by the entropy within the scar and left ventricular (LV) myocardium. Results: Multivariate analyses showed that a higher scar [hazard ratio (HR) 2.682; 95% CI: 1.022-7.037; p = 0.039] was independently associated with VA, after the adjustment for the LVEF, %LGE, LV maximal wall thickness (MWT), and left atrium (LA) diameter. Conclusion: Scar entropy and %LGE are both independent risk indicators of VA. A high scar entropy may indicate an arrhythmogenic scar, an identification of which may have value for the clinical status assessment of VAs in HCM patients.

Global Circumferential Strain by Cardiac Magnetic Resonance Tissue Tracking Associated With Ventricular Arrhythmias in Hypertrophic Cardiomyopathy Patients.

Background: Hypertrophic cardiomyopathy (HCM) is prone to myocardial heterogeneity and fibrosis, which are the substrates of ventricular arrhythmias (VAs). Cardiac magnetic resonance tissue tracking (CMR-TT) can quantitatively reflect global and regional left ventricular strain from different directions. It is uncertain whether the change of myocardial strain detected by CMR-TT is associated with VAs. The aim of the study is to explore the differential diagnostic value of VAs in HCM by CMR-TT. Materials and Methods: We retrospectively included 93 HCM patients (38 with VAs and 55 without VAs) and 30 healthy cases. Left ventricular function, myocardial strain parameters and percentage of late gadolinium enhancement (%LGE) were evaluated. Results: Global circumferential strain (GCS) and %LGE correlated moderately (r = 0.51, P < 0.001). HCM patients with VAs had lower left ventricular ejection fraction (LVEF), global radial strain (GRS), GCS, and global longitudinal strain (GLS), but increased %LGE compared with those without VAs (P < 0.01 for all). %LGE and GCS were indicators of VAs in HCM patients by multivariate logistic regression analysis. HCM patients with %LGE >5.35% (AUC 0.81, 95% CI 0.70-0.91, P < 0.001) or GCS >-14.73% (AUC 0.79, 95% CI 0.70-0.89, P < 0.001) on CMR more frequently had VAs. %LGE + GCS were able to better identify HCM patients with VAs (AUC 0.87, 95% CI 0.79-0.95, P < 0.001). Conclusion: GCS and %LGE were independent risk indicators of VAs in HCM. GCS is expected to be a good potential predictor in identifying HCM patients with VAs, which may provide important values to improve risk stratification in HCM in clinical practice.

Radiological insights of ectopic thyroid in the porta hepatis: A case report and review of the literature.

BACKGROUND: Ectopic thyroid is defined as a rare developmental anomaly where thyroid tissues are atypically found in locations other than its normal anatomical position: Anterolateral to the second, third, and fourth tracheal cartilages. An intemperate descent or a migration failure of the thyroid anlage results in sub-diaphragmatic thyroid ectopia, a sparse clinical entity. CASE SUMMARY: This case portrays a 63-year-old female patient presenting with chronic abdominal discomfort at a local hospital whereby a computed tomography (CT) scan revealed a well-defined mass in the hepatic entrance. For further examination, the patient underwent a CT scan with contrast, magnetic resonance imaging (MRI), and CT-angiography (CTA) at our department. The CT scan showed a well-defined and high attenuated mass measuring 43 mm × 38 mm in the hepatic entrance with calcification. The CTA revealed an additional finding: Blood supply to the mass from the right hepatic artery. MRI of the upper abdomen demonstrated a mass with mixed signal intensity on T1 and T2 weighted images in the hepatic entrance. The patient underwent surgery with resection of the mass which was sent for histopathology. Ectopic thyroid at the level of porta hepatis with nodules was the definitive diagnosis since histopathological report revealed presence of thyroid tissue in the resected liver mass. CONCLUSION: This case delivers a rare insight of pre-operative radiological imaging of an ectopic thyroid located in the liver. These findings can aid in narrowing down potential differential diagnosis when managing a patient with those subsequent findings.

CT differentiation of gastric ectopic pancreas from gastric stromal tumor.

BACKGROUND: Gastric ectopic pancreas (GEPs) is a rare developmental anomaly which is difficult to differentiate it from submucosal tumor such as gastric stromal tumor (GST) by imaging methods. Since the treatments of the GEPs and GST are totally different, a correct diagnosis is essential. Therefore, we retrospectively investigated the CT features of them to help us deepen the understanding of GEPs and GST. METHODS: This study enrolled 17 GEPs and 119 GST, which were proven pathologically. We assessed clinical and CT features to identify significant differential features of GEPs from GST using univariate and multivariate analyses. RESULTS: In univariate analysis, among all clinicoradiologic features, features of age, symptom, tumor marker, location, contour, peritumoral infiltration or fat-line of peritumor, necrosis, calcification, CT attenuation value of unenhancement phase/arterial phase/portal venous phase (CTu/CTa/CTp), the CT attenuation value of arterial phase/portal venous phase minus that of unenhanced phase (DEAP/DEPP), long diameter (LD), short diameter (SD) were considered statistically significant for the differentiation of them. And the multivariate analysis revealed that location, peritumoral infiltration or fat-line of peritumor, necrosis and DEPP were independent factors affecting the identification of them. In addition, ROC analysis showed that the test efficiency of CTp was perfect (AUC = 0.900). CONCLUSION: Location, the presence of peritumoral infiltration or fat-line of peritumor, necrosis and DEPP are useful CT differentiators of GEPs from GST. In addition, the test efficiency of CTp in differentiating them was perfect (AUC = 0.900).

Corrigendum: Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma.

[This corrects the article DOI: 10.3389/fonc.2020.00872.].

Radiomic-Based Quantitative CT Analysis of Pure Ground-Glass Nodules to Predict the Invasiveness of Lung Adenocarcinoma.

Objectives: To investigate the performance of radiomic-based quantitative analysis on CT images in predicting invasiveness of lung adenocarcinoma manifesting as pure ground-glass nodules (pGGNs). Methods: A total of 275 lung adenocarcinoma cases, with 322 pGGNs resected surgically and confirmed pathologically, from January 2015 to October 2017 were enrolled in this retrospective study. All nodules were split into training and test cohorts randomly with a ratio of 4:1 to establish models to predict between pGGN-like adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IVA). Radiomic feature extraction was performed using Pyradiomics with semi-automatically segmented tumor regions on CT scans that were contoured with an in-house plugin for 3D-Slicer. Random forest (RF) and support vector machine (SVM) were used for feature selection and predictive model building in the training cohort. Three different predictive models containing conventional, radiomic, and combined models were built on the basis of the selected clinical, radiological, and radiomic features. The predictive performance of each model was evaluated through the receiver operating characteristic curve (ROC) and the area under the curve (AUC). The predictive performance of two radiologists (A and B) and our radiomic predictive model were further investigated in the test cohort to see if radiomic predictive model could improve radiologists' performance in prediction between pGGN-like AIS/MIA and IVA. Results: Among 322 nodules, 48 (14.9%) were AIS and 102 (31.7%) were MIA with 172 (53.4%) for IVA. Age, diameter, density, and nine meaningful radiomic features were selected for model building in the training cohort. Three predictive models showed good performance in prediction between pGGN-like AIS/MIA and IVA (AUC > 0.8, P < 0.05) in both training and test cohorts. The AUC values in the test cohort were 0.824 (95% CI, 0.723-0.924), 0.833 (95% CI, 0.733-0.934), and 0.848 (95% CI, 0.750-0.946) for conventional, radiomic, and combined models, respectively. The predictive accuracy was 73.44 and 59.38% for radiologist A and radiologist B in the test cohort and was improved dramatically to 79.69 and 75.00% with the aid of our radiomic predictive model. Conclusion: The predictive models built in our study showed good predictive power with good accuracy and sensitivity, which provided a non-invasive, convenient, economic, and repeatable way for the prediction between IVA and AIS/MIA representing as pGGNs. The radiomic predictive model outperformed two radiologists in predicting pGGN-like AIS/MIA and IVA, and could significantly improve the predictive performance of the two radiologists, especially radiologist B with less experience in medical imaging diagnosis. The selected radiomic features in our research did not provide more useful information to improve the combined predictive model's performance.

On/off switchable epicatechin-based ultra-sensitive MRI-visible nanotheranostics - see it and treat it.

Nanotechnology has a remarkable impact on the preclinical development of future medicines. However, the complicated preparation and systemic toxicity to living systems prevent them from translation to clinical applications. In the present report, we developed a polyepicatechin-based on/off switchable ultra-sensitive magnetic resonance imaging (MRI) visible theranostic nanoparticle (PEMN) for image-guided photothermal therapy (PTT) using our strategy of integrating polymerization and biomineralization into the protein template. We have exploited natural polyphenols as the near infra-red (NIR) switchable photothermal source and MnO2 for the MRI-guided theranostics. PEMN demonstrates excellent MRI contrast ability with a longitudinal relaxivity value up to 30.01 mM-1 s-1. PEMN has shown great tumor inhibition on orthotopic breast tumors and the treatment could be made switchable with an on/off interchangeable mode as needed. PEMN was found to be excretable mainly through the kidneys, avoiding potential systemic toxicity. Thus, PEMN could be extremely useful for developing on-demand therapeutics via'see it and treat it' means with distinguished MRI capability and on/off switchable photothermal properties.

[Value of myocardial scar in predicting malignant ventricular arrhythmia in patients with chronic myocardial infarction].

OBJECTIVE: To assess the predictive value of myocardial scar mass in malignant ventricular arrhythmia (MVA) after myocardial infarction. METHODS: Thirty myocardial infarction patients with complete electrophysiology and cardiac MRI data admitted from January 2012 to August 2017 were enrolled in the study. According to the results of intracavitary electrophysiological study, MVA developed in 16 patients (MVA group) and not developed in 14 patients (non-MVA group). The qualitative and quantitative analysis of left ventricular ejection fraction (LVFE) and scar mass was performed with CVI42 post-processing software and predictive value of myocardial scar and LVEF for MVA after myocardial infarction was analyzed using ROC curves. RESULTS: LVEF in MVA group was significantly lower than that in non-MVA group, and scar mass in MVA group was significantly higher than that in non-MVA group (all P<0.05). Regression analysis showed that LVEF (OR=1.580) and scar mass (OR=6.270) were risk factors for MVA after myocardial infarction. For predicting MVA, the area under ROC curve (AUC) of LVEF was 0.696 with a sensitivity of 0.786 and the specificity of 0.685; the AUC of the scar mass was 0.839 with a sensitivity was 0.618 and the specificity of 0.929; the AUC of LVEF combined with scar mass was 0.848 with a sensitivity of 0.688 and specificity of 0.857. CONCLUSIONS: Myocardial scar assessed by late gadolinium enhancement MRI is more effective than LVEF in predicting MVA after myocardial infarction.