Scar heterogeneity on cardiovascular magnetic resonance as a predictor of appropriate implantable cardioverter defibrillator therapy

Prognostic Value of Different Thresholds for Myocardial Scar Quantification on Cardiac MRI Late Gadolinium Enhancement Images in Patients Receiving Implantable Cardioverter Defibrillators

Purpose

To compare the predictive value of different myocardial scar quantification thresholds using cardiac MRI for appropriate implantable cardioverter defibrillator (ICD) shock and mortality.

Materials and Methods

In this retrospective, two-center observational cohort study, patients with ischemic or nonischemic cardiomyopathy underwent cardiac MRI prior to ICD implantation. Late gadolinium enhancement (LGE) was first determined visually and then quantified by blinded cardiac MRI readers using different SDs above the mean signal of normal myocardium, full-width half-maximum, and manual thresholding. The intermediate signal "gray zone" was calculated as the differences between different SDs.

Results

Among 374 consecutive eligible patients (mean age, 61 years ± 13 [SD]; mean left ventricular ejection fraction, 32% ± 14; secondary prevention, 62.7%), those with LGE had a higher rate of appropriate ICD shock or death than those without (37.5% vs 26.6%, log-rank P = .04) over a median follow-up of 61 months. In multivariable analysis, none of the thresholds for quantifying scar was a significant predictor of mortality or appropriate ICD shock, while the extent of gray zone was an independent predictor (adjusted hazard ratio per 1 g = 1.025; 95% CI: 1.008, 1.043; P = .005) regardless of the presence or absence of ischemic heart disease (P interaction = .57). Model discrimination was highest for the model incorporating the gray zone (between 2 SD and 4 SD).

Conclusion

Presence of LGE was associated with a higher rate of appropriate ICD shock or death. Although none of the scar quantification techniques predicted outcomes, the gray zone both in infarct and nonischemic scar was an independent predictor and may refine risk stratification.Keywords: MRI, Scar Quantification, Implantable Cardioverter Defibrillator, Sudden Cardiac Death Supplemental material is available for this article. © RSNA, 2023.

Prognostic relevance of peri-infarct zone measured by cardiovascular magnetic resonance in patients with ST-segment elevation myocardial infarction

BACKGROUND

Cardiac magnetic resonance (CMR) imaging provides valuable prognostic information in patients with ST-elevation myocardial infarction (STEMI). The peri-infarct zone (PIZ) is a potential marker for post-infarction risk stratification. The aim of this study was to assess the prognostic impact of PIZ in a large multicenter STEMI-trial.

METHODS

The study population consisted of 704 consecutive patients undergoing CMR within 10 days after STEMI to assess established parameters of myocardial injury and additionally the extent of PIZ. The primary clinical endpoint was major adverse cardiac events (MACE) consisting of death, re-infarction and new congestive heart failure within 1 year after infarction.

RESULTS

The median heterogeneous PIZ-volume in the overall population was 14 ml (interquartile range [IQR] 7 to 24 ml). Male sex, infarct size, and left ventricular ejection fraction were identified as independent predictors of larger PIZ alterations. Patients with MACE had a significantly larger PIZ volume compared to patients without adverse events (21 ml [IQR 12 to 35 ml] versus 14 ml [IQR 7 to 23 ml]; p = 0.001). In stepwise multivariable Cox regression analysis, PIZ > median (>14 ml) emerged as an independent predictor of MACE (hazard ratio [HR] 2.84; 95% confidence interval [CI] 1.34 to 6.00; p = 0.006) in addition to the Thrombolysis In Myocardial Infarction (TIMI) risk score (HR 1.53; 95% CI 1.19 to 1.53; p < 0.001). Addition of PIZ to a CMR risk model comprising LVEF, infarct size and microvascular obstruction resulted in net reclassification improvement of 0.46 (0.19-0.73, p < 0.001).

CONCLUSION

In this currently largest prospective, multicenter CMR study assessing PIZ, the extent of PIZ emerged as an independent predictor of MACE and a potential novel marker for optimized risk stratification in STEMI patients. ClinicalTrials.gov: NCT00712101.

Prognostic Value of Late Enhanced Cardiac Magnetic Resonance Imaging Derived Texture Features in Dilated Cardiomyopathy Patients With Severely Reduced Ejection Fractions

Background: Late enhanced cardiac magnetic resonance (CMR) images of the left ventricular myocardium contain an enormous amount of information that could provide prognostic value beyond that of late gadolinium enhancements (LGEs). With computational postprocessing and analysis, the heterogeneities and variations of myocardial signal intensities can be interpreted and measured as texture features. This study aimed to evaluate the value of texture features extracted from late enhanced CMR images of the myocardium to predict adverse outcomes in patients with dilated cardiomyopathy (DCM) and severe systolic dysfunction.

Methods: This single-center study retrospectively enrolled patients with DCM with severely reduced left ventricular ejection fractions (LVEFs &lt; 35%). Texture features were extracted from enhanced late scanning images, and the presence and extent of LGEs were also measured. Patients were followed-up for clinical endpoints composed of all-cause deaths and cardiac transplantation. Cox proportional hazard regression and Kaplan–Meier analyses were used to evaluate the prognostic value of texture features and conventional CMR parameters with event-free survival.

Results: A total of 114 patients (37 women, median age 47.5 years old) with severely impaired systolic function (median LVEF, 14.0%) were followed-up for a median of 504.5 days. Twenty-nine patients experienced endpoint events, 12 died, and 17 underwent cardiac transplantations. Three texture features from a gray-level co-occurrence matrix (GLCM) (GLCM_contrast, GLCM_difference average, and GLCM_difference entropy) showed good prognostic value for adverse events when analyzed using univariable Cox hazard ratio regression (p = 0.007, p = 0.011, and p = 0.007, retrospectively). When each of the three features was analyzed using a multivariable Cox regression model that included the clinical parameter (systolic blood pressure) and LGE extent, they were found to be independently associated with adverse outcomes.

Conclusion: Texture features related LGE heterogeneities and variations (GLCM_contrast, GLCM_difference average, and GLCM_difference entropy) are novel markers for risk stratification toward adverse events in DCM patients with severe systolic dysfunction.

Whole-Heart High-Resolution Late Gadolinium Enhancement: Techniques and Clinical Applications

In cardiovascular magnetic resonance, late gadolinium enhancement (LGE) has become the cornerstone of myocardial tissue characterization. It is widely used in clinical routine to diagnose and characterize the myocardial tissue in a wide range of ischemic and nonischemic cardiomyopathies. The recent growing interest in imaging left atrial fibrosis has led to the development of novel whole‐heart high‐resolution late gadolinium enhancement (HR‐LGE) techniques. Indeed, conventional LGE is acquired in multiple breath‐holds with limited spatial resolution: ~1.4–1.8 mm in plane and 6–8 mm slice thickness, according to the Society for Cardiovascular Magnetic Resonance standardized guidelines. Such large voxel size prevents its use in thin structures such as the atrial or right ventricular walls. Whole‐heart 3D HR‐LGE images are acquired in free breathing to increase the spatial resolution (up to 1.3 × 1.3 × 1.3 mm³) and offer a better detection and depiction of focal atrial fibrosis. The downside of this increased resolution is the extended scan time of around 10 min, which hampers the spread of HR‐LGE in clinical practice. Initially introduced for atrial fibrosis imaging, HR‐LGE interest has evolved to be a tool to detect small scars in the ventricles and guide ablation procedures. Indeed, the detection of scars, nonvisible with conventional LGE, can be crucial in the diagnosis of myocardial infarction with nonobstructed coronary arteries, in the detection of the arrhythmogenic substrate triggering ventricular arrhythmia, and improve the confidence of clinicians in the challenging diagnoses such as the arrhythmogenic right ventricular cardiomyopathy. HR‐LGE also offers a precise visualization of left ventricular scar morphology that is particularly useful in planning ablation procedures and guiding them through the fusion of HR‐LGE images with electroanatomical mapping systems. In this narrative review, we attempt to summarize the technical particularities of whole‐heart HR‐LGE acquisition and provide an overview of its clinical applications with a particular focus on the ventricles.

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies

The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac magnetic resonance, and nuclear imaging plays an important role in diagnosis and management of cardiomyopathies and provides useful prognostic information. Most molecular factors exert their functions by interacting with other cellular components, thus many diseases reflect perturbations of intracellular networks. Indeed, complex diseases and traits such as cardiomyopathies are caused by perturbations of biological networks. The network medicine approach, by integrating systems biology, aims to identify pathological interacting genes and proteins, revolutionizing the way to know cardiomyopathies and shifting the understanding of their pathogenic phenomena from a reductionist to a holistic approach. In addition, artificial intelligence tools, applied to morphological and functional imaging, could allow imaging scans to be automatically analyzed to extract new parameters and features for cardiomyopathy evaluation. The aim of this review is to discuss the tools of network medicine in cardiomyopathies that could reveal new candidate genes and artificial intelligence imaging-based features with the aim to translate into clinical practice as diagnostic, prognostic, and predictive biomarkers and shed new light on the clinical setting of cardiomyopathies. The integration and elaboration of clinical habits, molecular big data, and imaging into machine learning models could provide better disease phenotyping, outcome prediction, and novel drug targets, thus opening a new scenario for the implementation of precision medicine for cardiomyopathies.

Multi-contrast volumetric imaging with isotropic resolution for assessing infarct heterogeneity: Initial clinical experience

BACKGROUND

To evaluate accelerated multi-contrast volumetric imaging with isotropic resolution reconstructed using low-rank and spatially varying edge-preserving constrained compressed sensing parallel imaging reconstruction (CP-LASER), for assessing infarct heterogeneity on post-infarction patients as a precursor to studies of utility for predicting ventricular arrhythmias.

METHODS

Eleven patients with prior myocardial infarction were included in the study. All subjects underwent cardiovascular magnetic resonance (CMR) scans including conventional two-dimensional late gadolinium enhancement (2D LGE) and three-dimensional multi-contrast late enhancement (3D MCLE) post-contrast. The extent of the infarct core and peri-infarct gray zone of a limited mid-ventricular slab were derived respectively by analyzing MCLE images with an isotropic resolution of 2.2 mm and an anisotropic resolution of 2.2×2.2×8.8 mm 3 , and LGE images with a resolution of 1.37×2.7×8 mm 3 ; the respective measures across all subjects were statistically compared.

RESULTS

Using 3D MCLE, the infarct core size measured with isotropic resolution was similar to that measured with anisotropic resolution, while the peri-infarct gray zone size measured with isotropic resolution was smaller than that measured with anisotropic resolution ( p<0.001 , Cohen's dz=1.33 ). Isotropic 3D MCLE yielded a significantly smaller measure of the peri-infarct gray zone size than conventional 2D LGE ( p=0.0016 , Cohen's dz=1.20 ). Overall, we have successfully shown the utility of isotropic 3D MCLE in a pilot patient study. Our results suggest that smaller voxels lead to more accurate differentiation between isotropic 3D MCLE-derived gray zone and core infarct because of diminished partial volume effect.

CONCLUSION

The CP-LASER accelerated 3D MCLE with isotropic resolution can be used in patients and yields excellent delineation of infarct and peri-infarct gray zone characteristics.

Improving Clinical Translation of Machine Learning Approaches Through Clinician-Tailored Visual Displays of Black Box Algorithms: Development and Validation

BACKGROUND

Despite the promise of machine learning (ML) to inform individualized medical care, the clinical utility of ML in medicine has been limited by the minimal interpretability and black box nature of these algorithms.

OBJECTIVE

The study aimed to demonstrate a general and simple framework for generating clinically relevant and interpretable visualizations of black box predictions to aid in the clinical translation of ML.

METHODS

To obtain improved transparency of ML, simplified models and visual displays can be generated using common methods from clinical practice such as decision trees and effect plots. We illustrated the approach based on postprocessing of ML predictions, in this case random forest predictions, and applied the method to data from the Left Ventricular (LV) Structural Predictors of Sudden Cardiac Death (SCD) Registry for individualized risk prediction of SCD, a leading cause of death.

RESULTS

With the LV Structural Predictors of SCD Registry data, SCD risk predictions are obtained from a random forest algorithm that identifies the most important predictors, nonlinearities, and interactions among a large number of variables while naturally accounting for missing data. The black box predictions are postprocessed using classification and regression trees into a clinically relevant and interpretable visualization. The method also quantifies the relative importance of an individual or a combination of predictors. Several risk factors (heart failure hospitalization, cardiac magnetic resonance imaging indices, and serum concentration of systemic inflammation) can be clearly visualized as branch points of a decision tree to discriminate between low-, intermediate-, and high-risk patients.

CONCLUSIONS

Through a clinically important example, we illustrate a general and simple approach to increase the clinical translation of ML through clinician-tailored visual displays of results from black box algorithms. We illustrate this general model-agnostic framework by applying it to SCD risk prediction. Although we illustrate the methods using SCD prediction with random forest, the methods presented are applicable more broadly to improving the clinical translation of ML, regardless of the specific ML algorithm or clinical application. As any trained predictive model can be summarized in this manner to a prespecified level of precision, we encourage the use of simplified visual displays as an adjunct to the complex predictive model. Overall, this framework can allow clinicians to peek inside the black box and develop a deeper understanding of the most important features from a model to gain trust in the predictions and confidence in applying them to clinical care.

Characterization of interstitial diffuse fibrosis patterns using texture analysis of myocardial native T1 mapping

Background

The pattern of myocardial fibrosis differs significantly between different cardiomyopathies. Fibrosis in hypertrophic cardiomyopathy (HCM) is characteristically as patchy and regional but in dilated cardiomyopathy (DCM) as diffuse and global. We sought to investigate if texture analyses on myocardial native T₁ mapping can differentiate between fibrosis patterns in patients with HCM and DCM.

Methods

We prospectively acquired native myocardial T₁ mapping images for 321 subjects (55±15 years, 70% male): 65 control, 116 HCM, and 140 DCM patients. To quantify different fibrosis patterns, four sets of texture descriptors were used to extract 152 texture features from native T₁ maps. Seven features were sequentially selected to identify HCM- and DCM-specific patterns in 70% of data (training dataset). Pattern reproducibility and generalizability were tested on the rest of data (testing dataset) using support vector machines (SVM) and regression models.

Results

Pattern-derived texture features were capable to identify subjects in HCM, DCM, and controls cohorts with 202/237(85.2%) accuracy of all subjects in the training dataset using 10-fold cross-validation on SVM (AUC = 0.93, 0.93, and 0.93 for controls, HCM and DCM, respectively), while pattern-independent global native T₁ mapping was poorly capable to identify those subjects with 121/237(51.1%) accuracy (AUC = 0.78, 0.51, and 0.74) (P<0.001 for all). The pattern-derived features were reproducible with excellent intra- and inter-observer reliability and generalizable on the testing dataset with 75/84(89.3%) accuracy.

Conclusion

Texture analysis of myocardial native T₁ mapping can characterize fibrosis patterns in HCM and DCM patients and provides additional information beyond average native T₁ values.

Validation of black blood late gadolinium enhancement (LGE) for evaluation of myocardial infarction in patients with or without pathological Q-wave on electrocardiogram (ECG)

Background

The pathological Q-wave (QW) is an important indicator of infarcted myocardial volume indicating a worse prognosis compared to non-Q-wave (NQW) infarctions. Traditional classification divides infarcts into transmural and non-transmural based on QW and NQW. This view has been challenged by the advent of late gadolinium enhancement (LGE) MR imaging. Conventional LGE (Conv-LGE) detection of subendocardial MI is limited by bright blood pool. Dark Blood LGE imaging (DB-LGE) nulls the blood pool improving the conspicuity and accuracy of detection of subendocardial infarcts. We hypothesize that improved detection of subendocardial enhancement with DB-LGE will result in improved correlation of electrocardiogram (ECG) and extent of infarction.

Methods

Sixty-four clinically confirmed infarction patients were enrolled in this prospective study. All the participants underwent cardiac MR imaging including conv-LGE and DB-LGE. Twelve-lead ECG were performed on the same day. The patients were divided into QW and NQW groups by one experienced cardiologist. MI quantitation was by MI% (the ratio of MI volume to whole myocardial volume) and transmural grading, compared using paired t-test and Wilcoxon-test, respectively. The image quality obtained by Conv-LGE and DB-LGE were evaluated according to the signal intensity ratio (SIR) and contrast-to-noise ratio (CNR).

Results

Fifty-six subjects were enrolled in the final analysis [23 (41%) QW and 33 (59%) NQW infarcts]. For the QW cohort, both sequences classified infarcts as transmural in 21/23 (91%) subjects and subendocardial in 2/23 (9%). For the NQW cohort, both sequences classified infarcts as transmural in 16/33 (48%) subjects and subendocardial in 17/33 (52%). Using BB-LGE there were significant differences in detecting subendocardial infarcts in QW and NQW cohorts (Z=-5.85, P<0.001). The MI% of QW group was greater than in NQW group (24.2±10.3 vs.15.9±9.8, P=0.003). Compared to Conv-LGE, BB-LGE provided higher CNR and SIR between infarcted myocardium and blood pool (6.3±2.6 vs. 2.1±1.3, P<0.001; 5.4±1.9 vs. 1.3±0.2, P<0.001). BB-LGE detected more subendocardial infarcted segments in the QW group and NQW group (Z=-4.24, P<0.001; Z=-5.57, P<0.001). The larger MI% was displayed in BB-LGE than in Conv-LGE in both QW group and NQW group (24.2±10.3 vs. 22.6±10.3, P<0.001; 15.9±9.8 vs.14.6±9.6, P=0.001).

Conclusions

Compared to conventional LGE, DB-LGE can provide more accurate detection and characterization of infarction in terms of transmurality and subendocardial extent. This is important for evaluating QW and NQW MIs. Due to nulling the high signal of blood pool, DB-LGE can effectively improve the identification of subendocardial MI which may be missed on conventional LGE. Therefore, in both QW and NQW MIs, DB-LGE detects more subendocardial MIs and larger MI% is found. This may facilitate more accurate quantitative MR assessment of both QW and NQW MIs and further empower LGE volume as a predictive biomarker.

Non-contrast myocardial infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence at 1.5T

PURPOSE

To develop a gadolinium-free cardiac MR technique that simultaneously exploits native T₁ and magnetization transfer (MT) contrast for the imaging of myocardial infarction.

METHODS

A novel hybrid T one and magnetization transfer (HYTOM) method was developed based on the modified look-locker inversion recovery (MOLLI) sequence, with a train of MT-prep pulses placed before the balanced SSFP (bSSFP) readout pulses. Numerical simulations, based on Bloch-McConnell equations, were performed to investigate the effects of MT induced by (1) the bSSFP readout pulses, and (2) the MT-prep pulses, on the measured, "apparent," native T₁ values. The HYTOM method was then tested on 8 healthy adult subjects, 6 patients, and a swine with prior myocardial infarction (MI). The resulting imaging contrast between normal myocardium and infarcted tissues was compared with that of MOLLI. Late gadolinium enhancement (LGE) images were also obtained for infarct assessment in patients and swine.

RESULTS

Numerical simulation and in vivo studies in healthy volunteers demonstrated that MT effects, resulting from on-resonance bSSFP excitation pulses and off-resonance MT-prep pulses, reduce the measured T₁ in both MOLLI and HTYOM. In vivo studies in patients and swine showed that the HYTOM sequence can identify locations of MI, as seen on LGE. Furthermore, the HYTOM method yields higher myocardium-to-scar contrast than MOLLI (contrast-to-noise ratio: 7.33 ± 1.67 vs. 3.77 ± 0.66, P < 0.01).

CONCLUSION

The proposed HYTOM method simultaneously exploits native T₁ and MT contrast and significantly boosts the imaging contrast for myocardial infarction.

Nonbinary quantification technique accounting for myocardial infarct heterogeneity: Feasibility of applying percent infarct mapping in patients

BACKGROUND

Binary threshold-based quantification techniques ignore myocardial infarct (MI) heterogeneity, yielding substantial misquantification of MI.

PURPOSE

To assess the technical feasibility of MI quantification using percent infarct mapping (PIM), a prototype nonbinary algorithm, in patients with suspected MI.

STUDY TYPE

Prospective cohort POPULATION: Patients (n = 171) with suspected MI referred for cardiac MRI.

FIELD STRENGTH/SEQUENCE

Inversion recovery balanced steady-state free-precession for late gadolinium enhancement (LGE) and modified Look-Locker inversion recovery (MOLLI) T1 -mapping on a 1.5T system.

ASSESSMENT

Infarct volume (IV) and infarct fraction (IF) were quantified by two observers based on manual delineation, binary approaches (2-5 standard deviations [SD] and full-width at half-maximum [FWHM] thresholds) in LGE images, and by applying the PIM algorithm in T1 and LGE images (PIMT1 ; PIMLGE ).

STATISTICAL TEST

IV and IF were analyzed using repeated measures analysis of variance (ANOVA). Agreement between the approaches was determined with Bland-Altman analysis. Interobserver agreement was assessed by intraclass correlation coefficient (ICC) analysis.

RESULTS

MI was observed in 89 (54.9%) patients, and 185 (38%) short-axis slices. IF with 2, 3, 4, 5SDs and FWHM techniques were 15.7 ± 6.6, 13.4 ± 5.6, 11.6 ± 5.0, 10.8 ± 5.2, and 10.0 ± 5.2%, respectively. The 5SD and FWHM techniques had the best agreement with manual IF (9.9 ± 4.8%) determination (bias 1.0 and 0.2%; P = 0.1426 and P = 0.8094, respectively). The 2SD and 3SD algorithms significantly overestimated manual IF (9.9 ± 4.8%; both P < 0.0001). PIMLGE measured significantly lower IF (7.8 ± 3.7%) compared to manual values (P < 0.0001). PIMLGE , however, showed the best agreement with the PIMT1 reference (7.6 ± 3.6%, P = 0.3156). Interobserver agreement was rated good to excellent for IV (ICCs between 0.727-0.820) and fair to good for IF (0.589-0.736).

DATA CONCLUSION

The application of the PIMLGE technique for MI quantification in patients is feasible. PIMLGE , with its ability to account for voxelwise MI content, provides significantly smaller IF than any thresholding technique and shows excellent agreement with the T1 -based reference.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Left ventricular geometry predicts ventricular tachyarrhythmia in patients with left ventricular systolic dysfunction: a comprehensive cardiovascular magnetic resonance study

BACKGROUND

Most patients with implantable cardioverter-defibrillator (ICD) implantation fail to utilize the device resulting in increasing societal costs and patient exposure to device morbidity. We sought to determine whether volumetric cardiovascular magnetic resonance (CMR) left ventricular (LV) spherical remodeling predicts future ventricular arrhythmias in primary ICD patients with reduced LV ejection fraction (EF).

METHODS

Sixty-eight consecutive patients with transthoracic echocardiographic LVEF <35% referred for CMR prior to ICD implantation for primary prevention of sudden death were identified. Sphericity index was measured as the ratio of LV end-diastolic volume (from cine short axis stack) to the volume of a sphere with a LV end-diastolic 4-chamber length diameter.

RESULTS

During a median follow-up of 55 months (interquartile range; 28-88), 15 patients (22%) received appropriate ICD therapy. Multivariable Cox's proportional hazard modeling identified increased CMR-derived sphericity index as the strongest independent predictor of appropriate ICD therapy (hazard ratio [HR], 1.09; 95% confidence interval [CI], 1.02 to 1.16; p = 0.007). In addition, dichotomized volumetric CMR-derived sphericity index ≥0.57 carried a 4-fold hazard risk for appropriate ICD therapy, controlling for age and LVEF (HR, 4.49; 95% CI, 1.53 to 13.21; p = 0.006). When sphericity index, LVEF and mass index were used in combination, important incremental prognostic information was achieved (net reclassification improvement, 0.42; 95% CI, 0.06 to 0.77).

CONCLUSIONS

The combined assessment of LV geometry, mass index and systolic function may provide incremental prognostic information regarding ventricular arrhythmia requiring appropriate ICD therapy in primary prevention patients with reduced LVEF.

Cardiovascular Magnetic Resonance to Predict Appropriate Implantable Cardioverter Defibrillator Therapy in Ischemic and Nonischemic Cardiomyopathy Patients Using Late Gadolinium Enhancement Border Zone: Comparison of Four Analysis Methods

BACKGROUND

Late gadolinium enhancement (LGE) border zone on cardiac magnetic resonance imaging has been proposed as an independent predictor of ventricular arrhythmias. The purpose was to determine whether size and heterogeneity of LGE predict appropriate implantable cardioverter defibrillator (ICD) therapy in ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM) patients and to evaluate 4 LGE border-zone algorithms.

METHODS AND RESULTS

ICM and NICM patients who underwent LGE cardiac magnetic resonance imaging prior to ICD implantation were retrospectively included. Two semiautomatic algorithms, expectation maximization, weighted intensity, a priori information and a weighted border zone algorithm, were compared with a modified full-width half-maximum and a 2-3SD threshold-based algorithm (2-3SD). Hazard ratios were calculated per 1% increase in LGE. A total of 74 ICM and 34 NICM were followed for 63 months (1-140) and 52 months (0-133), respectively. ICM patients had 27 appropriate ICD events, and NICM patients had 7 ICD events. In ICM patients with primary prophylactic ICD, LGE border zone predicted ICD therapy in univariable and multivariable analysis measured by the expectation maximization, weighted intensity, a priori information, weighted border zone, and modified full-width half-maximum algorithms (hazard ratios 1.23, 1.22, and 1.05, respectively; P<0.05; negative predictive value 92%). For NICM, total LGE by all 4 methods was the strongest predictor (hazard ratios, 1.03-1.04; P<0.05), though the number of events was small.

CONCLUSIONS

Appropriate ICD therapy can be predicted in ICM patients with primary prevention ICD by quantifying the LGE border zone. In NICM patients, total LGE but not LGE border zone had predictive value for ICD therapy. However, the algorithms used affects the predictive value of these measures.

Clinical performance of high-resolution late gadolinium enhancement imaging with compressed sensing

PURPOSE

To evaluate diagnostic image quality of 3D late gadolinium enhancement (LGE) with high isotropic spatial resolution (∼1.4 mm³ ) images reconstructed from randomly undersampled k-space using LOw-dimensional-structure Self-learning and Thresholding (LOST).

MATERIALS AND METHODS

We prospectively enrolled 270 patients (181 men; 55 ± 14 years) referred for myocardial viability assessment. 3D LGE with isotropic spatial resolution of 1.4 ± 0.1 mm³ was acquired at 1.5T using a LOST acceleration rate of 3 to 5. In a subset of 121 patients, 3D LGE or phase-sensitive LGE were acquired with parallel imaging with an acceleration rate of 2 for comparison. Two readers evaluated image quality using a scale of 1 (poor) to 4 (excellent) and assessed for scar presence. The McNemar test statistic was used to compare the proportion of detected scar between the two sequences. We assessed the association between image quality and characteristics (age, gender, torso dimension, weight, heart rate), using generalized linear models.

RESULTS

Overall, LGE detection proportions for 3D LGE with LOST were similar between readers 1 and 2 (16.30% vs. 18.15%). For image quality, readers gave 85.9% and 80.0%, respectively, for images categorized as good or excellent. Overall proportion of scar presence was not statistically different from conventional 3D LGE (28% vs. 33% [P = 0.17] for reader 1 and 26% vs. 31% [P = 0.37] for reader 2). Increasing subject heart rate was associated with lower image quality (estimated slope = -0.009 (P = 0.001)).

CONCLUSION

High-resolution 3D LGE with LOST yields good to excellent image quality in >80% of patients and identifies patients with LV scar at the same rate as conventional 3D LGE.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1829-1838.

The Prognostic Role of Tissue Characterisation using Cardiovascular Magnetic Resonance in Heart Failure

Despite significant advances in heart failure diagnostics and therapy, the prognosis remains poor, with one in three dying within a year of hospital admission. This is at least in part due to the difficulties in risk stratification and personalisation of therapy. The use of left ventricular systolic function as the main arbiter for entrance into clinical trials for drugs and advanced therapy, such as implantable defibrillators, grossly simplifies the complex heterogeneous nature of the syndrome. Cardiovascular magnetic resonance offers a wealth of data to aid in diagnosis and prognostication. The advent of novel cardiovascular magnetic resonance mapping techniques allows us to glimpse some of the pathophysiological mechanisms underpinning heart failure. We review the growing prognostic evidence base using these techniques.

Associations between scar characteristics by cardiac magnetic resonance and changes in left ventricular ejection fraction in primary prevention defibrillator recipients

BACKGROUND

Left ventricular ejection fraction (LVEF) improves over time in 25%-40% of patients with cardiomyopathy with primary prevention implantable cardioverter-defibrillator (ICD). The determinants of LVEF improvement, however, are not well characterized.

OBJECTIVES

We sought to examine the associations of clinical risk factors and cardiac imaging markers with changes in LVEF after ICD implantation.

METHODS

We conducted a retrospective analysis of cardiac magnetic resonance images in 202 patients who underwent primary prevention ICD implantation to quantify the amount of heterogeneous myocardial tissue (gray zone), dense core, and total scar. LVEF was reassessed at least once after ICD implantation.

RESULTS

Over a mean follow-up of 3 years, LVEF decreased in 43 (21.3%), improved in 88 (43.6%), and was unchanged in 71 (35.1%) of the patients. Baseline LVEF and myocardial scar characteristics were the strongest determinants of LVEF trajectory with high scar burden and increasing lack of myocardial viability associated with a greater decline in LVEF. There was a trend toward an association between both changes in LVEF and scar extent with subsequent appropriate ICD shock. Changes in LVEF were also strongly associated with heart failure hospitalizations.

CONCLUSION

Scar burden and characteristics were strong determinants, independent of baseline LVEF and other traditional cardiovascular risk factors, of changes in LVEF. Both worsened LVEF and high scar extent were associated with a trend toward increased risk of appropriate shock. These findings suggest that baseline cardiac magnetic resonance imaging of the myocardial substrate may provide important prognostic information on subsequent left ventricular remodeling and adverse events.

Review of Journal of Cardiovascular Magnetic Resonance 2014

There were 102 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2014, which is a 6% decrease on the 109 articles published in 2013. The quality of the submissions continues to increase. The 2013 JCMR Impact Factor (which is published in June 2014) fell to 4.72 from 5.11 for 2012 (as published in June 2013). The 2013 impact factor means that the JCMR papers that were published in 2011 and 2012 were cited on average 4.72 times in 2013. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25% and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality papers to JCMR for publication.

Review of Journal of Cardiovascular Magnetic Resonance 2013

There were 109 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2013, which is a 21% increase on the 90 articles published in 2012. The quality of the submissions continues to increase. The editors are delighted to report that the 2012 JCMR Impact Factor (which is published in June 2013) has risen to 5.11, up from 4.44 for 2011 (as published in June 2012), a 15% increase and taking us through the 5 threshold for the first time. The 2012 impact factor means that the JCMR papers that were published in 2010 and 2011 were cited on average 5.11 times in 2012. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25% and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality manuscripts to JCMR for publication.

Free-breathing combined three-dimensional phase sensitive late gadolinium enhancement and T1 mapping for myocardial tissue characterization

PURPOSE

To develop a novel MR sequence for combined three-dimensional (3D) phase-sensitive (PS) late gadolinium enhancement (LGE) and T1 mapping to allow for simultaneous assessment of focal and diffuse myocardial fibrosis.

METHODS

In the proposed sequence, four 3D imaging volumes are acquired with different T1 weightings using a combined saturation and inversion preparation, after administration of a gadolinium contrast agent. One image is acquired fully sampled with the inversion time selected to null the healthy myocardial signal (the LGE image). The other three images are three-fold under-sampled and reconstructed using compressed sensing. An acquisition scheme with two interleaved imaging cycles and joint navigator-gating of those cycles ensures spatial registration of the imaging volumes. T1 maps are generated using all four imaging volumes. The signal-polarity in the LGE image is restored using supplementary information from the T1 fit to generate PS-LGE images. The accuracy of the proposed method was assessed with respect to a inversion-recovery spin-echo sequence. In vivo T1 maps and LGE images were acquired with the proposed sequence and quantitatively compared with 2D multislice Modified Look-Locker inversion recovery (MOLLI) T1 maps. Exemplary images in a patient with focal scar were compared with conventional LGE imaging.

RESULTS

The deviation of the proposed method and the spin-echo reference was < 11 ms in phantom for T1 times between 250 and 600 ms, regardless of the inversion time selected in the LGE image. There was no significant difference in the in vivo T1 times of the proposed sequence and the 2D MOLLI technique (myocardium: 292 ± 75 ms versus 310 ± 49 ms, blood-pools: 191 ± 75 ms versus 182.0 ± 33). The LGE images showed proper nulling of the healthy myocardium in all subjects and clear depiction of scar in the patient.

CONCLUSION

The proposed sequence enables simultaneous acquisition of 3D PS-LGE images and spatially registered 3D T1 maps in a single scan.