Deep Learning for Discrimination of Hypertrophic Cardiomyopathy and Hypertensive Heart Disease on MRI Native T1 Maps.

BACKGROUND: Native T1 and radiomics were used for hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) differentiation previously. The current problem is that global native T1 remains modest discrimination performance and radiomics requires feature extraction beforehand. Deep learning (DL) is a promising technique in differential diagnosis. However, its feasibility for discriminating HCM and HHD has not been investigated. PURPOSE: To examine the feasibility of DL in differentiating HCM and HHD based on T1 images and compare its diagnostic performance with other methods. STUDY TYPE: Retrospective. POPULATION: 128 HCM patients (men, 75; age, 50 years ± 16) and 59 HHD patients (men, 40; age, 45 years ± 17). FIELD STRENGTH/SEQUENCE: 3.0T; Balanced steady-state free precession, phase-sensitive inversion recovery (PSIR) and multislice native T1 mapping. ASSESSMENT: Compare HCM and HHD patients baseline data. Myocardial T1 values were extracted from native T1 images. Radiomics was implemented through feature extraction and Extra Trees Classifier. The DL network is ResNet32. Different input including myocardial ring (DL-myo), myocardial ring bounding box (DL-box) and the surrounding tissue without myocardial ring (DL-nomyo) were tested. We evaluate diagnostic performance through AUC of ROC curve. STATISTICAL TESTS: Accuracy, sensitivity, specificity, ROC, and AUC were calculated. Independent t test, Mann-Whitney U-test and Chi-square test were adopted for HCM and HHD comparison. P < 0.05 was considered statistically significant. RESULTS: DL-myo, DL-box, and DL-nomyo models showed an AUC (95% confidential interval) of 0.830 (0.702-0.959), 0.766 (0.617-0.915), 0.795 (0.654-0.936) in the testing set. AUC of native T1 and radiomics were 0.545 (0.352-0.738) and 0.800 (0.655-0.944) in the testing set. DATA CONCLUSION: The DL method based on T1 mapping seems capable of discriminating HCM and HHD. Considering diagnostic performance, the DL network outperformed the native T1 method. Compared with radiomics, DL won an advantage for its high specificity and automated working mode. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Left Ventricular Vertical Run-Length Nonuniformity MRI Adds Prognostic Value to MACE in Patients with End-Stage Renal Disease.

BACKGROUND: Vertical run-length nonuniformity (VRLN) is a texture feature representing heterogeneity within native T1 images and reflects the extent of cardiac fibrosis. In uremic cardiomyopathy, interstitial fibrosis was the major histological alteration. The prognostic value of VRLN in patients with end-stage renal disease (ESRD) remains unclear. PURPOSE: To evaluate the prognostic value of VRLN MRI in patients with ESRD. STUDY TYPE: Prospective. POPULATION: A total of 127 ESRD patients (30 participants in the major adverse cardiac events, MACE group). FIELD STRENGTH/SEQUENCE: 3.0 T/steady-state free precession sequence, modified Look-Locker imaging. ASSESSMENT: MRI image qualities were assessed by three independent radiologists. VRLN values were measured in the myocardium on the mid-ventricular short-axis slice of T1 mapping. Left ventricular (LV) mass, LV end-diastolic and end-systolic volume, as well as LV global strain cardiac parameters were measured. STATISTICAL TESTS: The primary endpoint was the incident of MACE from enrollment time to January 2023. MACE is a composite endpoint consisting of all-cause mortality, acute myocardial infarction, stroke, heart failure hospitalization, and life-threatening arrhythmia. Cox proportional-hazards regression was performed to test whether VRLN independently correlated with MACE. The intraclass correlation coefficients of VRLN were calculated to evaluate intraobserver and interobserver reproducibility. The C-index was computed to examine the prognostic value of VRLN. P-value <0.05 were considered statistically significant. RESULTS: Participants were followed for a median of 26 months. VRLN, age, LV end-systolic volume index, and global longitudinal strain remained significantly associated with MACE in the multivariable model. Adding VRLN to a baseline model containing clinical and conventional cardiac MRI parameters significantly improved the accuracy of the predictive model (C-index of the baseline model: 0.781 vs. the model added VRLN: 0.814). DATA CONCLUSION: VRLN is a novel marker for risk stratification toward MACE in patients with ESRD, superior to native T1 mapping and LV ejection fraction. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 2.

3D Fractal Dimension Analysis: Prognostic Value of Right Ventricular Trabecular Complexity in Participants with Arrhythmogenic Cardiomyopathy.

BACKGROUND: Arrhythmogenic cardiomyopathy (ACM) is characterized by progressive myocardial fibro-fatty infiltration accompanied by trabecular disarray. Traditionally, two-dimensional (2D) instead of 3D fractal dimension (FD) analysis has been used to evaluate trabecular disarray. However, the prognostic value of trabecular disorder assessed by 3D FD measurement remains unclear. PURPOSE: To investigate the prognostic value of right ventricular trabecular complexity in ACM patients using 3D FD analysis based on cardiac MR cine images. STUDY TYPE: Retrospective. POPULATION: 85 ACM patients (mean age: 45 ± 17 years, 52 male). FIELD STRENGTH/SEQUENCE: 3.0T/cine imaging, T2-short tau inversion recovery (T2-STIR), and late gadolinium enhancement (LGE). ASSESSMENT: Using cine images, RV (right ventricular) volumetric and functional parameters were obtained. RV trabecular complexity was measured with 3D fractal analysis by box-counting method to calculate 3D-FD. Cox and logistic regression models were established to evaluate the prognostic value of 3D-FD for major adverse cardiac events (MACE). STATISTICAL TESTS: Cox regression and logistic regression to explore the prognostic value of 3D-FD. C-index, time-dependent receiver operating characteristic (ROC) curves and area under the ROC curve (AUC) to evaluate the incremental value of 3D-FD. Intraclass correlation coefficient for interobserver variability. P < 0.05 indicated statistical significance. RESULTS: 26 MACE were recorded during the 60 month follow-up (interquartile range: 48-67 months). RV 3D-FD significantly differed between ACM patients with MACE (2.67, interquartile range: 2.51 ~ 2.81) and without (2.52, interquartile range: 2.40 ~ 2.67) and was a significant independent risk factor for MACE (hazard ratio, 1.02; 95% confidence interval: 1.01, 1.04). In addition, prognostic model fitness was significantly improved after adding 3D-FD to RV global longitudinal strain, LV involvement, and 5-year risk score separately. DATA CONCLUSION: The myocardial trabecular complexity assessed through 3D FD analysis was found associated with MACE and provided incremental prognostic value beyond conventional ACM risk factors. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Fractal Analysis of Left Ventricular Trabeculae in Patients with End-Stage Renal Disease: A Random Survival Tree Analysis.

BACKGROUND: The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. PURPOSE: To evaluate the prognostic value of LV trabecular complexity in patients with end-stage renal disease (ESRD). STUDY TYPE: Prospective outcome study. POPULATION: 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. FIELD STRENGTH: 3.0T, steady-state free precession (SSFP) and modified Look-Locker imaging sequences. ASSESSMENT: All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low- and high-risk groups based on scores derived from the RF model and survival compared. STATISTICAL TESTS: Receiver operating characteristic curve analysis; Kaplan-Meier survival analysis with log rank tests; Harrel's C-index to assess model performance. A P value <0.05 was considered statistically significant. RESULTS: Fifty-five patients (26.57%) experienced MACE during a median follow-up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C-index: 0.81) had significantly better discrimination than the Cox regression model (C-index: 0.74). Participants of the external validation dataset classified into the high-risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low-risk group. DATA CONCLUSION: LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Prognostic value of right ventricular trabecular complexity in patients with arrhythmogenic cardiomyopathy.

OBJECTIVES: The present study aimed to investigate the incremental prognostic value of the right ventricular fractal dimension (FD), a novel marker of myocardial trabecular complexity by cardiac magnetic resonance (CMR) in patients with arrhythmogenic cardiomyopathy (ACM). METHODS: Consecutive patients with ACM undergoing CMR were followed up for major cardiac events, including sudden cardiac death, aborted cardiac arrest, and appropriate implantable cardioverter defibrillator intervention. Prognosis prediction was compared by Cox regression analysis. We established a multivariable model supplemented with RV FD and evaluated its discrimination by Harrell's C-statistic. We compared the category-free, continuous net reclassification improvement (cNRI) and integrated discrimination index (IDI) before and after the addition of FD. RESULTS: A total of 105 patients were prospectively included from three centers and followed up for a median of 60 (48, 66) months; experienced 36 major cardiac events were recorded. Trabecular FD displayed a strong unadjusted association with major cardiac events (p < 0.05). In the multivariable Cox regression analysis, RV maximal apical FD maintained an independent association with major cardiac events (hazard ratio, 1.31 (1.11-1.55), p < 0.002). The Hosmer-Lemeshow goodness of fit test displayed good fit (X2 = 0.68, p = 0.99). Diagnostic performance was significantly improved after the addition of RV maximal apical FD to the multivariable baseline model, and the continuous net reclassification improvement increased 21% (p = 0.001), and the integrated discrimination index improved 16% (p = 0.045). CONCLUSIONS: In patients with ACM, CMR-assessed myocardial trabecular complexity was independently correlated with adverse cardiovascular events and provided incremental prognostic value. CLINICAL RELEVANCE STATEMENT: The application of FD values for assessing RV myocardial trabeculae may become an accessible and promising parameter in monitoring and early diagnosis of risk factors for adverse cardiovascular events in patients with ACM. KEY POINTS: • Ventricular trabecular morphology, a novel quantitative marker by CMR, has been explored for the first time to determine the severity of ACM. • Patients with higher maximal apical fractal dimension of RV displayed significantly higher cumulative incidence of major cardiac events. • RV maximal apical FD was independently associated with major cardiac events and provided incremental prognostic value in patients with ACM.

Coronary artery wall contrast enhancement imaging impact on disease activity assessment in IgG4-RD: a direct marker of coronary involvement.

BACKGROUND: Coronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment. METHODS: A total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study. Coronary artery wall imaging was performed in a 3.0 T MRI scanner. Serological markers and IgG4-RD Responder Index (IgG4-RD-RI) scores were collected for correlation analysis. RESULTS: Coronary wall CE was observed in 29 (94 %) IgG4-RD patients and 22 (76 %) SLE patients. Contrast-to-noise ratio (CNR) and total CE area were significantly higher in patient groups compared to controls (CNR: 6.1 ± 2.7 [IgG4-RD] v. 4.2 ± 2.3 [SLE] v. 1.9 ± 1.5 [control], P < 0.001; Total CE area: 3.0 [3.0-6.6] v. 1.7 [1.5-2.6] v. 0.3 [0.3-0.9], P < 0.001). In the IgG4-RD group, CNR and total CE area were correlated with the RI (CNR: r = 0.55, P = 0.002; total CE area: r = 0.39, P = 0.031). RI´ scored considering coronary involvement by CE, differed significantly from RI scored without consideration of CE (RI v. RI´: 15 ± 6 v. 16 ± 6, P < 0.001). CONCLUSIONS: Visualization and quantification of CMR coronary CE by CNR and total CE area could be utilized to detect subclinical and clinical coronary wall involvement, which is prevalent in IgG4-RD. The potential inclusion of small and medium-sized vessel involvements in the assessment of disease activity in IgG4-RD is worthy of further investigation.

Prognostic value of left ventricular trabeculae fractal analysis in patients with dilated cardiomyopathy.

BACKGROUND: The prognostic value of left ventricular (LV) myocardial trabecular complexity on cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) remains unknown. This study aimed to evaluate the prognostic value of LV myocardial trabecular complexity using fractal analysis in patients with DCM. METHODS: Consecutive patients with DCM who underwent CMR between March 2017 and November 2021 at two hospitals were prospectively enrolled. The primary endpoints were defined as the combination of all-cause death and heart failure hospitalization. The events of cardiac death alone were defined as the secondary endpoints.LV trabeculae complexity was quantified by measuring the fractal dimension (FD) of the endocardial border based on fractal geometry on CMR. Cox proportional hazards regression and Kaplan-Meier survival analysis were used to examine the association between variables and outcomes. The incremental prognostic value of FD was assessed in nested models. RESULTS: A total of 403 patients with DCM (49.31 ± 14.68 years, 69% male) were recruited. After a median follow-up of 43 months (interquartile range, 28-55 months), 87 and 24 patients reached the primary and secondary endpoints, respectively. Age, heart rate, New York Heart Association functional class >II, N-terminal pro-B-type natriuretic peptide, LV ejection fraction, LV end-diastolic volume index, LV end-systolic volume index, LV mass index, presence of late gadolinium enhancement, global FD, LV mean apical FD, and LV maximal apical FD were univariably associated with the outcomes (all P < 0.05). After multivariate adjustment, LV maximal apical FD remained a significant independent predictor of outcome [hazard ratio = 1.179 (1.116, 1.246), P < 0.001]. The addition of LV maximal apical FD in the nested models added incremental prognostic value to other common clinical and imaging risk factors (all <0.001; C-statistic: 0.84-0.88, P < 0.001). CONCLUSION: LV maximal apical FD was an independent predictor of the adverse clinical outcomes in patients with DCM and provided incremental prognostic value over conventional clinical and imaging risk factors.

The association between cardiac T2*BOLD and quantitative flow ratio (QFR) in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease.

BACKGROUND: T2*BOLD is based on myocardial deoxyhemoglobin content to reflect the state of myocardial oxygenation. Quantitative flow ratio is a tool for assessing coronary blood flow based on invasive coronary angiography. PURPOSE: This study aimed to evaluate the correlation between T2*BOLD and QFR in the diagnosis of stenotic coronary arteries in patients with multi-vessel coronary artery disease. METHODS: Fifty patients with MVCAD with at least 1 significant coronary artery stenosis (diameter stenosis > 50%) and 21 healthy control subjects underwent coronary angiography combined with QFR measurements and cardiovascular magnetic resonance (CMR). QFR ≤ 0.80 was considered to indicate the presence of hemodynamic obstruction. RESULTS: Totally 60 (54%) obstructive vessels had hemodynamic change. Between stenotic coronary arteries (QFR ≤ 0.8) and normal vessels, T2*BOLD showed AUCs of 0.97, 0.69, and 0.91 for left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries and PI displayed AUCs of 0.89, 0.77 and 0.90 (all p > 0.05, except for LAD). The AUCs of T2*BOLD between stenotic coronary arteries (QFR > 0.8) and normal vessels were 0.86, 0.72, and 0.85 for LAD, LCX and RCA; while, PI showed AUCs of 0.93, 0.86, and 0.88, respectively (p > 0.05). Moreover, T2*BOLD displayed AUCs of 0.96, 0.74, and 0.91 for coronary arteries as before between coronary arteries with stenosis (QFR ≤ 0.8 and > 0.8), but the mean PI of LAD, LCX and RCA showed no significant differences between them. CONCLUSION: T2* BOLD and QFR have good correlation in diagnosing stenotic coronary arteries with hemodynamic changes in patients with stable multi-vessel CAD. T2* BOLD is superior to semi-quantitative perfusion imaging in analyzing myocardial ischemia without stress.

An Integrated Algorithm for Differentiating Hypertrophic Cardiomyopathy From Hypertensive Heart Disease.

BACKGROUND: Differentiating hypertrophic cardiomyopathy (HCM) from hypertensive heart disease (HHD) is challenging. PURPOSE: To identify differences between HCM and HHD on a patient basis using MRI. STUDY TYPE: Retrospective. POPULATION: A total of 219 subjects, 148 in phase I (baseline data and algorithm development: 75 HCM, 33 HHD, and 40 controls) and 71 in phase II (algorithm validation: 56 HCM and 15 HHD). FIELD STRENGTH/SEQUENCE: Contrast-enhanced inversion-prepared gradient echo and cine-balanced steady-state free precession sequences at 3.0 T. ASSESSMENT: MRI parameters assessed included left ventricular (LV) ejection fraction (LVEF), LV end systolic and end diastolic volumes (LVESV and LVEDV), mean maximum LV wall thickness (MLVWT), LV global longitudinal and circumferential strain (GRS, GLS, and GCS), and native T1. Parameters, which were significantly different between HCM and HHD in univariable analysis, were entered into a principal component analysis (PCA). The selected components were then introduced into a multivariable regression analysis to model an integrated algorithm (IntA) for screening the two disorders. IntA performance was assessed for patients with and without LGE in phase I (development) and phase II (validation). STATISTICAL TESTS: Univariable regression, PCA, receiver operating curve (ROC) analysis. A P value <0.05 was considered statistically significant. RESULTS: Derived IntA formulation included LVEF, LVESV, LVEDV, MLVWT, and GCS. In LGE-positive subjects in phase l, the cutoff point of IntA ≥81 indicated HCM (83% sensitivity and 91% specificity), with the area under the ROC curve (AUC) of 0.900. In LGE-negative subjects, a higher possibility of HCM was indicated by a cutoff point of IntA ≥84 (100% sensitivity and 82% specificity), with an AUC of 0.947. Validation of IntA in phase II resulted in an AUC of 0.846 in LGE-negative subjects and 0.857 in LGE-positive subjects. DATA CONCLUSION: A per-patient-based IntA algorithm for differentiating HCM and HHD was generated from MRI data and incorporated FT, LGE and morphologic parameters. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Assessment of the Prognostic Value of MRI Left Ventricular Global Function Index (LVGFI) in Patients With End-Stage Renal Disease Under Maintenance Dialysis.

BACKGROUND: Left ventricular global function index (LVGFI) integrates LV volumetric and functional parameters. In patients with end-stage renal disease (ESRD), cardiac injury manifests as LV hypertrophy and dysfunction. However, the prognostic value of LVGFI in this population remains unclear. PURPOSE: To investigate the association of LVGFI with major adverse cardiac events (MACE) in patients with ESRD. STUDY TYPE: Prospective. POPULATION: One hundred fifty-eight ESRD patients (mean age: 54.1 ± 14.4 years; 105 male) on maintenance dialysis. FILED STRENGTH/SEQUENCE: 3.0 T, balanced steady-state free precession (bSSFP) cine and modified Look-Locker inversion recovery (MOLLI) sequences. ASSESSMENT: LV volumetric and functional parameters were determined from bSSFP images. LVGFI was calculated as the ratio of stroke volume to global volume and native T1 was determined from MOLLI T1 maps. MACE was recorded on follow up. Models were developed to predict MACE from conventional risk factors combined with LVGFI, GLS, native T1, and LV mass index (LVMI), respectively. Subgroup analyses were further performed in participants with LVEF above median. STATISTICAL TESTS: Cox proportional hazard regression and log-rank test were used to investigate the association between LVGFI and MACE. The predictive models were evaluated and compared using Harrell's C-statistics and DeLong tests. A P value <0.05 was considered statistically significant. RESULTS: Thirty-four MACE occurred during the median follow-up period of 26 months. The hazard of MACE increased by 114% for each 10% decrease in LVGFI in univariable analysis. The predictive model consisting of LVGFI (C-statistic: 0.724) had significantly better predictive performance than the others (all P < 0.001). These results were consistent in patients (N = 79) with LVEF > median (63.54%). DATA CONCLUSION: LVGFI is a novel marker for MACE risk stratification in patients with ESRD and was better able to predict MACE than native T1 mapping and GLS. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Creatine chemical exchange saturation transfer (CEST) CMR imaging reveals myocardial early involvement in idiopathic inflammatory myopathy at 3T: feasibility and initial experience.

OBJECTIVES: To measure creatine distribution in idiopathic inflammatory myopathy (IIM) patients' myocardial segments and investigate whether cardiovascular magnetic resonance (CMR) chemical exchange saturation transfer (CEST) creatine mapping can detect subclinical myocardial changes, CEST's ability was further compared with other conventional CMR mapping sequences. METHODS: Forty IIM patients (53.5 ± 10.5 years, 26 males) and eight healthy controls (35.4 ± 6 years, 5 males) underwent CMR scans on a 3.0-T MR scanner. Patients with IIM were further classified into two subgroups according to cardiac troponin T (cTn-T) values: the elevated cTn-T subgroup (n = 14) and the normal cTn-T subgroup (n = 26). Cine imaging, T2 SPAIR, LGE imaging, T1 mapping, T2 mapping, and Cr (creatine) CEST were performed. RESULTS: Cr mapping showed significantly reduced creatine in IIM patients among global myocardium (IIM: 0.109 ± 0.063, controls: 0.121 ± 0.021, p < 0.05), and decreased creatine signals were detected in all 16 cardiac segments (p < 0.05). Patients also had significantly prolonged native T1 and decreased enhanced T1 values in each cardiac segment (p < 0.05). There was no significant difference of LVEF and T2 values between IIM patients and controls. Between the two subgroups, elevated cTn-T was linked with creatine and extracellular volume fraction (ECV) values, providing a global average creatine signal of 0.107 vs 0.112 (p < 0.05) and 24.7 vs 32.4 (p < 0.05). CONCLUSION: Creatine CEST mapping can detect early-stage heart involvement with negative LGE findings in IIM. Compared with T1 mapping, CEST provides increased sensitivity to ECV measurement, making it significantly better than T1, and a promising CMR sequence for screening subclinical myocardial damage. KEY POINTS: • IIM patients with potential or ongoing heart involvement, elevated ECV, and reduced Cr CEST values could provide valuable information. • ECV and Cr CEST values were closely related to elevated cTn-T.

Myocardial extracellular volume quantified by cardiac magnetic resonance predicts left ventricular aneurysm following acute myocardial infarction.

OBJECTIVE: This study aimed to investigate the correlation between increased extracellular matrix estimated by cardiac magnetic resonance (CMR) and left ventricular aneurysm after acute myocardial infarction. METHODS: A total of 175 patients from 3 centers with an isolated left anterior descending culprit vessel underwent CMR examinations within 1 week and at a 6-month follow-up. Of these, 92 were identified to have left ventricular aneurysms (LVAs): 74 with functional aneurysm and 18 with anatomical aneurysm. The predictive significance of acute extracellular volume (ECV), left gadolinium enhancement (LGE), and other characteristics were analyzed using binary logistic regression analysis. RESULTS: Patients with LVA were more likely to present with left ventricular adverse remodeling (LVAR) than those without (p = 0.009). With optimal cutoff values of 30.90% for LGE and 33% for ECV to discriminate LVA from non-LVA, the area under the curve (AUC) by receiver operator characteristic curve (ROC) analysis was 0.92 (95% CI: 0.87-0.96; p < 0.001) and 0.93 (95% CI: 0.88-0.96; p < 0.001), respectively. ECV was significantly better than LGE at discriminating between functional and anatomical LVA (p < 0.001). Both acute LGE and ECV were predictors of LVA, with an odds ratio of 1.35 (95% CI: 1.21-1.52, p < 0.001) and 1.23 (95% CI: 1.13-1.33, p < 0.001), respectively, by multivariable logistic regression analysis. CONCLUSIONS: Acute LGE and ECV of the myocardium provided predictive significance for LVA. The discriminative significance of ECV for functional versus anatomical LVA was better than the discriminative significance of LGE. KEY POINTS: • Patients with LVA were more likely to present with LVAR. • Acute LGE and ECV of the myocardium provided the strongest predictive significance for LVA. • The discriminative significance of ECV for functional versus anatomical LVA was better than that of LGE.

Texture analysis of native T1 images as a novel method for non-invasive assessment of heart failure with preserved ejection fraction in end-stage renal disease patients.

OBJECTIVES: To explore the diagnostic potential of texture analysis applied to native T1 maps obtained from cardiac magnetic resonance (CMR) images for the assessment of heart failure with preserved ejection fraction (HFpEF) among patients with end-stage renal disease (ESRD). METHODS: This study, conducted from June 2018 to November 2020, included 119 patients (35 on hemodialysis, 55 on peritoneal dialysis, and 29 with kidney transplants) in Renji Hospital. Native T1 maps were assessed with texture analysis, using a freely available software package, in participants who underwent cardiac MRI at 3.0 T. Four texture features, selected by dimension reduction specific to the diagnosis of HFpEF, were analyzed. Multivariate logistic regression was performed to examine the independent association between the selected features and HFpEF in ESRD patients. RESULTS: Seventy-six of 119 patients were diagnosed with HFpEF. Demographic, laboratory, cardiac MRI, and echocardiogram characteristics were compared between HFpEF and non-HFpEF groups. The four texture features that were analyzed showed statistically significant differences between groups. In multivariate analysis, age, left atrial volume index (LAVI), and sum average 4 (SA4) turned out to be independent predictors for HFpEF in ESRD patients. Combining the texture feature, SA4, with typical predictive factors resulted in higher C-index (0.923 vs. 0.898, p = 0.045) and a sensitivity and specificity of 79.2% and 95.2%, respectively. CONCLUSIONS: Texture analysis of T1 maps adds diagnostic value to typical clinical parameters for the assessment of heart failure with preserved ejection fraction in patients with end-stage renal disease. KEY POINTS: • Non-invasive assessment of HFpEF can help predict prognosis in ESRD patients and help them take timely preventative measures. • Texture analysis of native T1 maps adds diagnostic value to the typical clinical parameters for the assessment of HFpEF in patients with ESRD.

A deep learning method for the automated assessment of paradoxical pulsation after myocardial infarction using multicenter cardiac MRI data.

OBJECTIVE: The current study aimed to explore a deep convolutional neural network (DCNN) model that integrates multidimensional CMR data to accurately identify LV paradoxical pulsation after reperfusion by primary percutaneous coronary intervention with isolated anterior infarction. METHODS: A total of 401 participants (311 patients and 90 age-matched volunteers) were recruited for this prospective study. The two-dimensional UNet segmentation model of the LV and classification model for identifying paradoxical pulsation were established using the DCNN model. Features of 2- and 3-chamber images were extracted with 2-dimensional (2D) and 3D ResNets with masks generated by a segmentation model. Next, the accuracy of the segmentation model was evaluated using the Dice score and classification model by receiver operating characteristic (ROC) curve and confusion matrix. The areas under the ROC curve (AUCs) of the physicians in training and DCNN models were compared using the DeLong method. RESULTS: The DCNN model showed that the AUCs for the detection of paradoxical pulsation were 0.97, 0.91, and 0.83 in the training, internal, and external testing cohorts, respectively (p < 0.001). The 2.5-dimensional model established using the end-systolic and end-diastolic images combined with 2-chamber and 3-chamber images was more efficient than the 3D model. The discrimination performance of the DCNN model was better than that of physicians in training (p < 0.05). CONCLUSIONS: Compared to the model trained by 2-chamber or 3-chamber images alone or 3D multiview, our 2.5D multiview model can combine the information of 2-chamber and 3-chamber more efficiently and obtain the highest diagnostic sensitivity. CLINICAL RELEVANCE STATEMENT: A deep convolutional neural network model that integrates 2-chamber and 3-chamber CMR images can identify LV paradoxical pulsation which correlates with LV thrombosis, heart failure, ventricular tachycardia after reperfusion by primary percutaneous coronary intervention with isolated anterior infarction. KEY POINTS: • The epicardial segmentation model was established using the 2D UNet based on end-diastole 2- and 3-chamber cine images. • The DCNN model proposed in this study had better performance for discriminating LV paradoxical pulsation accurately and objectively using CMR cine images after anterior AMI compared to the diagnosis of physicians in training. • The 2.5-dimensional multiview model combined the information of 2- and 3-chamber efficiently and obtained the highest diagnostic sensitivity.

CMR Manifestations, Influencing Factors and Molecular Mechanism of Myocarditis Induced by COVID-19 Mrna Vaccine.

Although immunization with the 2019 coronavirus disease (COVID-19) mRNA vaccine is considered to be an effective measure to reduce the number of serious cases or deaths associated with COVID-19, rare cases of cardiac complications have been reported in the literature, encompassing acute myocardial injury, arrhythmia, vasculitis, endothelial dysfunction, thrombotic myocardial infarction and myocarditis. Interestingly, patients diagnosed with myocarditis after receiving the COVID-19 mRNA vaccine exhibit abnormal cardiac magnetic resonance (CMR) findings, suggesting CMR can be a valuable non-invasive diagnostic tool. In populations immunized with the COVID-19 mRNA vaccine, the risk in teenagers and young men is significantly higher. Myocardial injury in male patients is mainly myocarditis, while in female patients, myocarditis and pericardial effusion are predominantly found. Generally, the symptoms of myocarditis are relatively mild and complete recovery can be achieved. Moreover, the incidence rate associated with the second dose is significantly higher than with the first or third dose. This article brings together the latest evidence on CMR characteristics, influencing factors and pathogenesis of myocarditis caused by the COVID-19 mRNA vaccine. At the same time, we make recommendations for populations requiring immunization with the COVID-19 mRNA vaccine.

A Radiomic MRI based Nomogram for Prediction of Heart Failure with Preserved Ejection Fraction in Systemic Lupus Erythematosus Patients: Insights From a Three-Center Prospective Study.

BACKGROUND: Myocardial T1 and extracellular volume (ECV) fraction values have important roles in the prognostication of heart failure with preserved ejection fraction (HFpEF). However, the traditional mean quantification of intensity levels is not sufficient. PURPOSE: To evaluate a T1 map-based radiomic nomogram as a long-term prognosticator for HFpEF in systemic lupus erythematosus (SLE) patients. STUDY TYPE: Prospective. POPULATION: A total of 115 SLE patients and 50 age- and gender-matched controls. FIELD STRENGTH/SEQUENCE: A 3.0 T scanner; cine imaging, precontrast and post-contrast T1 mapping and T2 mapping sequences. ASSESSMENT: A radiomic nomogram was developed based on precontrast T1 mapping. Three independent readers assessed and compared the ECV value and the value of the radiomic nomogram for predicting HFpEF in SLE patients. STATISTICAL TEST: Cox proportional hazard models, Youden index for determining cut-off values for high HFpEF risk vs. low HFpEF risk classification, Kaplan-Meier analysis, intraclass correlation (ICC), and Uno C statistic test. RESULTS: During a median follow-up of 27 (interquartile range, 19-37) months, 31 SLE patients developed HFpEF. Patients with elevated ECV (≥31%) and a higher output (≥42.7) from the radiomic feature "S_33_sum average" of the precontrast T1 map had a significantly higher risk of developing HFpEF than those who had lower ECV (<31%) and an output <42.7. Patients with a higher "S_33_sum average" value on precontrast T1 map had a significantly increased risk for HFpEF (hazard ratio, 1.363, 95% CI, 1.130-1.645), after adjusting for covariates including ECV and LVEF. Finally, "S_33_sum average" from precontrast T1 mapping had modest but significantly incremental prognostic value over the mean ECV value (Uno C statistic comparing models, 0.860 vs. 0.835). DATA CONCLUSION: The precontrast T1 map-based radiomic nomogram, as a measure of diffuse myocardial fibrosis was associated with HFpEF and provided modest prognostic value for predicting HFpEF in SLE patients. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Magnetic Resonance Imaging Quantification of Accumulation of Epicardial Adipose Tissue Adds Independent Risks for Diastolic Dysfunction among Dialysis Patients.

BACKGROUND: Diastolic dysfunction (DD) frequently occurs in dialysis patients; however, the risk factors of DD remain to be further explored in such a population. Epicardial adipose tissue (EAT) volume has proven to be an independent clinical risk factor for multiple cardiac disorders. PURPOSE: To assess whether EAT volume is an independent risk factor for DD in dialysis patients. STUDY TYPE: Case-control study. POPULATION: A total of 113 patients (mean age: 54.5 ± 14.4 years; 41 women) who had underwent dialysis for at least 3 months due to uremia. FIELD STRENGTH: A 3 T, steady-state free precession (SSFP) sequence for cine imaging, modified Look-Locker imaging (MOLLI) for T1 mapping and gradient-recalled-echo for T2*. ASSESSMENT: All participants were performed cardiac magnetic resonance imaging (MRI) and echocardiogram. For MRI images analysis, borders of the EAT were manually delineated, as well as, pericardial adipose tissue (PeAT) and paracardial adipose tissue (PaAT), T1 mapping, T2* mapping, global longitudinal strain (GLS), and left atrial strain. For echocardiogram assessments, the thickness of PaAT, e' velocity, E velocity, E/e ratio, A velocity, and deceleration time were measured. STATISTICAL TESTS: Univariate and multivariate logistic regressions were performed to explore the independent risk factors for DD. P value less than 0.05 was considered as significant. RESULTS: Compared with the DD(-) group, the DD(+) group had significantly more epicardial tissue fat (18.5 ± 1.3 vs. 30.9 ± 2.3) In addition, EAT volumes increased significantly with the grades of DD (grade 1 vs. grade 2 and 3: 27.9 ± 15.9 vs. 35.4 ± 13.1). Moreover, EAT had significant correlations with T1 mapping, T2* mapping, GLS, left atrial strain, e' velocity, and E/e ratio. EAT accumulation added an independent risk for DD (Odds Ratio = 1.03) over conventional clinical risk factors including age, diabetes mellitus, and hemodialysis. DATA CONCLUSION: EAT was associated with diastolic function, and its accumulation may be an independent risk factor for DD among dialysis patients. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Diagnostic Utility of the Simplified Perfusion Fraction for Identifying Myocardial Injury in Patients With Reperfused ST-segment Elevation Myocardial Infarction.

BACKGROUND: Acute myocardial infarction (AMI) is a disease with high morbidity and mortality worldwide and the evaluation of myocardial injury and perfusion status following myocardial ischemia and reperfusion is of clinical value. PURPOSE: To assess the diagnostic utility of simplified perfusion fraction (SPF) in differentiating salvage and infarcted myocardium and its predictive value for left ventricular remodeling in patients with reperfusion ST-segment elevation myocardial infarction (STEMI). STUDY TYPE: Prospective. POPULATION: Forty-one reperfused STEMI patients and 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: 3.0T MRI. The MR examination included cine, T2 -short tau inversion recovery (T2 -STIR), first pass perfusiong (FPP)，phase sensitive inversion recovery (PSIR), and diffusion-weighted imaging (DWI). ASSESSMENT: SPF values among different myocardium regions (infarcted, salvaged, remote, and MVO) and stages of reperfused STEMI patients as well as normal controls were measured. The diagnostic utility of SPF values in differentiating salvaged and infarcted myocardium was assessed. STATISTICAL ANALYSIS: Independent t-test and the Mann-Whitney U-test. Logistic regression. RESULTS: SPF values in healthy controls were not significantly different than SPF values in the remote myocardium of patients (40.09 ± 1.47% vs. 40.28 ± 1.93%, P = 0.698). In reperfusion STEMI patients, SPF values were lower in infarcted myocardium compared to remote and salvaged myocardium (32.15 ± 2.36% vs. 40.28 ± 1.93%, P < 0.001; 32.15 ± 2.36% vs. 36.68 ± 2.71%, P < 0.001). SPF values of infarcted myocardium showed a rebound increase from acute to convalescent stages (32.15 ± 2.36% vs. 34.69 ± 3.69%, P < 0.001). When differentiating infarcted and salvaged myocardium, SPF values demonstrated an area under the curve (AUC) of 0.89 (sensitivity 85.4%, specificity 80.5%, cutoff 34.42%). Lower SPF values were associated with lower odds ratio (OR = 0.304) of left ventricular remodeling after adjusting for potential confounders with a confidence interval (CI) of 0.129-0.717, P = 0.007. DATA CONCLUSION: SPF might be able to differentiate salvaged and infarcted myocardium and is a strong predictor of left ventricular remodeling in reperfused STEMI patients. Level of Evidence 2 Technical Efficacy Stage 2.

Texture Analysis of Native T1 Images as a Novel Method for Noninvasive Assessment of Uremic Cardiomyopathy.

BACKGROUND: Noncontrast cardiac T1 times are increased in dialysis patients which might indicate fibrotic alterations in uremic cardiomyopathy. PURPOSE: To explore the application of the texture analysis (TA) of T1 images in the assessment of myocardial alterations in dialysis patients. STUDY TYPE: Case-control study. POPULATION: A total of 117 subjects, including 22 on hemodialysis, 44 on peritoneal dialysis, and 51 healthy controls. FIELD STRENGTH: A 3 T, steady-state free precession (SSFP) sequence, modified Look-Locker imaging (MOLLI). ASSESSMENT: Two independent, blinded researchers manually delineated endocardial and epicardial borders of the left ventricle (LV) on midventricular T1 maps for TA. STATISTICAL TESTS: Texture feature selection was performed, incorporating reproducibility verification, machine learning, and collinearity analysis. Multivariate linear regressions were performed to examine the independent associations between the selected texture features and left ventricular function in dialysis patients. Texture features' performance in discrimination was evaluated by sensitivity and specificity. Reproducibility was estimated by the intraclass correlation coefficient (ICC). RESULTS: Dialysis patients had greater T1 values than normal (P < 0.05). Five texture features were filtered out through feature selection, and four showed a statistically significant difference between dialysis patients and healthy controls. Among the four features, vertical run-length nonuniformity (VRLN) had the most remarkable difference among the control and dialysis groups (144 ± 40 vs. 257 ± 74, P < 0.05), which overlap was much smaller than Global T1 times (1268 ± 38 vs. 1308 ± 46 msec, P < 0.05). The VRLN values were notably elevated (cutoff = 170) in dialysis patients, with a specificity of 97% and a sensitivity of 88%, compared with T1 times (specificity = 76%, sensitivity = 60%). In dialysis patients, VRLN was significantly and independently associated with left ventricular ejection fraction (P < 0.05), global longitudinal strain (P < 0.05), radial strain (P < 0.05), and circumferential strain (P < 0.05); however, T1 was not. DATA CONCLUSION: The texture features obtained by TA of T1 images and VRLN may be a better parameter for assessing myocardial alterations than T1 times. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Myocardial extracellular volume fraction radiomics analysis for differentiation of reversible versus irreversible myocardial damage and prediction of left ventricular adverse remodeling after ST-elevation myocardial infarction.

OBJECTIVES: Our study sought to explore the prognostic value of radiomic TA (texture analysis) on quantitative ECV (extracellular volume) fraction mapping to differentiate between reversible and irreversible myocardial damage and to predict left ventricular adverse remodeling in patients with reperfused STEMI (ST-elevation myocardial infarction). METHODS: This observational prospective cohort study identified 70 patients (62 ± 9 years, 62 men [85.70%]) with STEMI for TA who consecutively performed native and contrast T1 mapping. Texture features were extracted from each stack of ECV mapping based on ROI (region of interest) analysis. RESULTS: After texture feature selection and dimension reduction, five selected texture features were found to be statistically significant for differentiating the extent of myocardial injury. ROC (receiver operating characteristic) curve analysis for the differentiation of unsalvageable infarction and salvageable myocardium demonstrated a significantly higher AUC (area under the curve) (0.91 [95% CI, 0.86-0.96], p < 0.0001) for horizontal fraction than other texture features (p < 0.05). LVAR (left ventricular adverse remodeling) was predicted by those selected features. The differences in qualitative and quantitative baseline parameters and horizontal fractions were significant between the patients with and without LVAR. LGE (late gadolinium enhancement) and horizontal fraction features of infarcted myocardium in acute STEMI were the only two parameters selected in forming the optimal overall multivariable model for LVAR at 6 months. CONCLUSIONS: Radiomic analysis of ECV could discriminate reversible from irreversible myocardial injury after STEMI. LGE as well as radiomics TA (texture analysis) of ECV may provide an alternative to predict LVAR and functional recovery. KEY POINTS: • ECV quantification was able to differentiate between infarcted myocardium and non-infarcted myocardium. • Radiomics analysis of ECV could discriminate reversible from irreversible myocardial injury. • Radiomics TA analysis shows a promising similarity with LGE findings which could aid the prognosis of myocardial infarction patients.