The role of cardiovascular magnetic resonance imaging in heart failure

Advancements in electrochemical biosensing of cardiovascular disease biomarkers

Cardiovascular diseases (CVDs) stand as a predominant global health concern, introducing vast socioeconomic challenges. In addressing this pressing dilemma, enhanced diagnostic modalities have become paramount, positioning electrochemical biosensing as an instrumental innovation. This comprehensive review navigates the multifaceted terrain of CVDs, elucidating their defining characteristics, clinical manifestations, therapeutic avenues, and intrinsic risk factors. Notable emphasis is placed on pivotal diagnostic tools, spotlighting cardiac biomarkers distinguished by their unmatched clinical precision in terms of relevance, sensitivity, and specificity. Highlighting the broader repercussions of CVDs, there emerges an accentuated need for refined diagnostic strategies. Such an exploration segues into a profound analysis of electrochemical biosensing, encapsulating its foundational principles, diverse classifications, and integral components, notably recognition molecules and transducers. Contemporary advancements in biosensing technologies are brought to the fore, emphasizing pioneering electrode architectures, cutting-edge signal amplification processes, and the synergistic integration of biosensors with microfluidic platforms. At the core of this discourse is the demonstrated proficiency of biosensors in detecting cardiovascular anomalies, underpinned by empirical case studies, systematic evaluations, and clinical insights. As the narrative unfolds, it addresses an array of inherent challenges, spanning intricate technicalities, real-world applicability constraints, and regulatory considerations, finally, by casting an anticipatory gaze upon the future of electrochemical biosensing, heralding a new era of diagnostic tools primed to revolutionize cardiovascular healthcare.

Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.

Left ventricular hypertrophy: do not forget Fabry disease. Diagnostic work-up and differential diagnosis

BACKGROUND

Left ventricular (LV) hypertrophy is a common clinical finding. Differential diagnosis includes Fabry disease, a rare and progressive, but treatable storage disease caused by deficiency of α-galactosidase A. However, diagnosis of Fabry is often hampered by its clinical heterogeneity, LV hypertrophy phenocopies and unawareness of the clinician.

METHODS

This review summarises clinical data, family history, electrocardiogram (ECG) and imaging (echocardiogram and cardiovascular magnetic resonance (CMR)) characteristics to differentiate aetiologies of LV hypertrophy including clues for the diagnosis of Fabry.

RESULTS

LV hypertrophy is a consequence of pressure overload mostly, but differential diagnosis includes hypertrophic cardiomyopathy and infiltrative diseases. Clinical data, ECG, type and degree of LV hypertrophy, functional and tissue characteristics differ among aetiologies. LV hypertrophy in Fabry is progressive and mostly concentric but may copy any hypertrophic cardiomyopathy. Dependent on residual alfa-galactosidase A enzyme activity, degree of LV hypertrophy in Fabry may vary. Initially, low myocardial CMR T1-map values are calculated. At a later stage, midwall late gadolinium enhancement of the inferolateral LV wall may occur. Global longitudinal strain may be depressed in the inferolateral wall. Voltage criteria for LV hypertrophy and short PQ interval are common. Right ventricular (RV) hypertrophy is frequent. In addition, multisystemic symptoms including neuropathic pain, hypohidrosis, proteinuria, renal insufficiency and familial young stroke are pointing to Fabry.

CONCLUSIONS

LV hypertrophy should raise suspicion of Fabry disease, especially if LV hypertrophy is unexplained and/or associated with RV hypertrophy. In Fabry, LV hypertrophy may be heterogeneous and mimic any hypertrophic cardiomyopathy. ECG, multisystemic symptoms and imaging may provide clues for Fabry.

Biocompatible Electronic Skins for Cardiovascular Health Monitoring

Cardiovascular diseases represent a significant threat to the overall well-being of the global population. Continuous monitoring of vital signs related to cardiovascular health is essential for improving daily health management. Currently, there has been remarkable proliferation of technology focused on collecting data related to cardiovascular diseases through daily electronic skin monitoring. However, concerns have arisen regarding potential skin irritation and inflammation due to the necessity for prolonged wear of wearable devices. To ensure comfortable and uninterrupted cardiovascular health monitoring, the concept of biocompatible electronic skin has gained substantial attention. In this review, biocompatible electronic skins for cardiovascular health monitoring are comprehensively summarized and discussed. The recent achievements of biocompatible electronic skin in cardiovascular health monitoring are introduced. Their working principles, fabrication processes, and performances in sensing technologies, materials, and integration systems are highlighted, and comparisons are made with other electronic skins used for cardiovascular monitoring. In addition, the significance of integrating sensing systems and the updating wireless communication for the development of the smart medical field is explored. Finally, the opportunities and challenges for wearable electronic skin are also examined.

Magnetic Resonance Imaging Characterization and Clinical Outcomes of Dilated and Arrhythmogenic Left Ventricular Cardiomyopathies

BACKGROUND

Nondilated left ventricular cardiomyopathy (NDLVC) has been recently differentiated from dilated cardiomyopathy (DCM). A comprehensive characterization of these 2 entities using cardiac magnetic resonance (CMR) and genetic testing has never been performed.

OBJECTIVES

This study sought to provide a thorough characterization and assess clinical outcomes in a large multicenter cohort of patients with DCM and NDLVC.

METHODS

A total of 462 patients with DCM (227) or NDLVC (235) with CMR data from 4 different referral centers were retrospectively analyzed. The study endpoint was a composite of sudden cardiac death or major ventricular arrhythmias.

RESULTS

In comparison to DCM, NDLVC had a higher prevalence of pathogenic or likely pathogenic variants of arrhythmogenic genes (40% vs 23%; P < 0.001), higher left ventricular (LV) systolic function (LV ejection fraction: 51% ± 12% vs 36% ± 15%; P < 0.001) and higher prevalence of free-wall late gadolinium enhancement (LGE) (27% vs 14%; P < 0.001). Conversely, DCM showed higher prevalence of pathogenic or likely pathogenic variants of nonarrhythmogenic genes (23% vs 12%; P = 0.002) and septal LGE (45% vs 32%; P = 0.004). Over a median follow-up of 81 months (Q1-Q3: 40-132 months), the study outcome occurred in 98 (21%) patients. LGE with septal location (HR: 1.929; 95% CI: 1.033-3.601; P = 0.039) was independently associated with the risk of sudden cardiac death or major ventricular arrhythmias together with LV dilatation, older age, advanced NYHA functional class, frequent ventricular ectopic activity, and nonsustained ventricular tachycardia.

CONCLUSIONS

In a multicenter cohort of patients with DCM and NDLVC, septal LGE together with LV dilatation, age, advanced disease, and frequent and repetitive ventricular arrhythmias were powerful predictors of major arrhythmic events.

Role of Nuclear Imaging in Cardiac Stereotactic Body Radiotherapy for Ablation of Ventricular Tachycardia

Ventricular tachycardia (VT) is a life-threatening arrhythmia common in patients with structural heart disease or nonischemic cardiomyopathy. Many VTs originate from regions of fibrotic scar tissue, where delayed electrical signals exit scar and re-enter viable myocardium. Cardiac stereotactic body radiotherapy (SBRT) has emerged as a completely noninvasive alternative to catheter ablation for the treatment of recurrent or refractory ventricular tachycardia. While there is no common consensus on the ideal imaging workflow, therapy planning for cardiac SBRT often combines information from a plurality of imaging modalities including MRI, CT, electroanatomic mapping and nuclear imaging. MRI and CT provide detailed anatomic information, and late enhancement contrast imaging can indicate regions of fibrosis. Electroanatomic maps indicate regions of heterogenous conduction voltage or early activation which are indicative of arrhythmogenic tissue. Some early clinical adopters performing cardiac SBRT report the use of myocardial perfusion and viability nuclear imaging to identify regions of scar. Nuclear imaging of hibernating myocardium, inflammation and sympathetic innervation have been studied for ventricular arrhythmia prognosis and in research relating to catheter ablation of VT but have yet to be studied in their potential applications for cardiac SBRT. The integration of information from these many imaging modalities to identify a target for ablation can be challenging. Multimodality image registration and dedicated therapy planning tools may enable higher target accuracy, accelerate therapy planning workflows and improve patient outcomes. Understanding the pathophysiology of ventricular arrhythmias, and localizing the arrhythmogenic tissues, is vital for successful ablation with cardiac SBRT. Nuclear imaging provides an arsenal of imaging strategies to identify regional scar, hibernation, inflammation, and sympathetic denervation with some advantages over alternative imaging strategies.

From Compressed-Sensing to Deep Learning MR: Comparative Biventricular Cardiac Function Analysis in a Patient Cohort

BACKGROUND

Conventional segmented, retrospectively gated cine (Conv-cine) is challenged in patients with breath-hold difficulties. Compressed sensing (CS) has shown values in cine imaging but generally requires long reconstruction time. Recent artificial intelligence (AI) has demonstrated potential in fast cine imaging.

PURPOSE

To compare CS-cine and AI-cine with Conv-cine in quantitative biventricular functions, image quality, and reconstruction time.

STUDY TYPE

Prospective human studies.

SUBJECTS

70 patients (age, 39 ± 15 years, 54.3% male).

FIELD STRENGTH/SEQUENCE

3T; balanced steady state free precession gradient echo sequences.

ASSESSMENT

Biventricular functional parameters of CS-, AI-, and Conv-cine were measured by two radiologists independently and compared. The scan and reconstruction time were recorded. Subjective scores of image quality were compared by three radiologists.

STATISTICAL TESTS

Paired t-test and two related-samples Wilcoxon sign test were used to compare biventricular functional parameters between CS-, AI-, and Conv-cine. Intraclass correlation coefficient (ICC), Bland-Altman analysis, and Kendall's W method were applied to evaluate agreement of biventricular functional parameters and image quality of these three sequences. A P-value <0.05 was considered statistically significant, and standardized mean difference (SMD) < 0. 100 was considered no significant difference.

RESULTS

Compared to Conv-cine, no statistically significant differences were identified in CS- and AI-cine function results (all P > 0.05), except for very small differences in left ventricle end-diastole volumes of 2.5 mL (SMD = 0.082) and 4.1 mL (SMD = 0.096), respectively. Bland-Altman scatter plots revealed that biventricular function results were mostly distributed within the 95% confidence interval. All parameters had acceptable to excellent interobserver agreements (ICC: 0.748-0.989). Compared with Conv-cine (84 ± 13 sec), both CS (14 ± 2 sec) and AI (15 ± 2 sec) techniques reduced scan time. Compared with CS-cine (304 ± 17 sec), AI-cine (24 ± 4 sec) reduced reconstruction time. CS-cine demonstrated significantly lower quality scores than Conv-cine, while AI-cine demonstrated similar scores (P = 0.634).

CONCLUSION

CS- and AI-cine can achieve whole-heart cardiac cine imaging in a single breath-hold. Both CS- and AI-cine have the potential to supplement the gold standard Conv-cine in studying biventricular functions and benefit patients having difficulties with breath-holds.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 1.

SCMR expert consensus statement for cardiovascular magnetic resonance of patients with a cardiac implantable electronic device

Cardiovascular magnetic resonance (CMR) is a proven imaging modality for informing diagnosis and prognosis, guiding therapeutic decisions, and risk stratifying surgical intervention. Patients with a cardiac implantable electronic device (CIED) would be expected to derive particular benefit from CMR given high prevalence of cardiomyopathy and arrhythmia. While several guidelines have been published over the last 16 years, it is important to recognize that both the CIED and CMR technologies, as well as our knowledge in MR safety, have evolved rapidly during that period. Given increasing utilization of CIED over the past decades, there is an unmet need to establish a consensus statement that integrates latest evidence concerning MR safety and CIED and CMR technologies. While experienced centers currently perform CMR in CIED patients, broad availability of CMR in this population is lacking, partially due to limited availability of resources for programming devices and appropriate monitoring, but also related to knowledge gaps regarding the risk-benefit ratio of CMR in this growing population. To address the knowledge gaps, this SCMR Expert Consensus Statement integrates consensus guidelines, primary data, and opinions from experts across disparate fields towards the shared goal of informing evidenced-based decision-making regarding the risk-benefit ratio of CMR for patients with CIEDs.

Liver T1 Mapping Derived From Cardiac Magnetic Resonance Imaging: A Potential Prognostic Marker in Idiopathic Dilated Cardiomyopathy

BACKGROUND

Hepatic alterations are common aftereffects of heart failure (HF) and ventricular dysfunction. The prognostic value of liver injury markers derived from cardiac MRI studies in nonischemic dilated cardiomyopathy (DCM) patients is unclear.

PURPOSE

Evaluate the prognostic performance of liver injury markers derived from cardiac MRI studies in DCM patients.

STUDY TYPE

Prospective.

POPULATION

Three hundred fifty-six consecutive DCM patients diagnosed according to ESC guidelines (age 48.7 ± 14.2 years, males 72.6%).

FIELD STRENGTH/SEQUENCE

Steady-state free precession, modified Look-Locker inversion recovery T1 mapping and phase sensitive inversion recovery late gadolinium enhancement (LGE) sequences at 3 T.

ASSESSMENT

Clinical characteristics, conventional MRI parameters (ventricular volumes, function, mass), native myocardial and liver T1, liver extracellular volume (ECV), and myocardial LGE presence were assessed. Patients were followed up for a median duration of 48.3 months (interquartile range 42.0-69.9 months). Primary endpoints included HF death, sudden cardiac death, heart transplantation, and HF readmission; secondary endpoints included HF death, sudden cardiac death, and heart transplantation. Models were developed to predict endpoints and the incremental value of including liver parameters assessed.

STATISTICAL TESTS

Optimal cut-off value was determined using receiver operating characteristic curve and Youden method. Survival analysis was performed using Kaplan-Meier and Cox proportional hazard. Discriminative power of models was compared using net reclassification improvement and integrated discriminatory index. P value <0.05 was considered statistically significant.

RESULTS

47.2% patients reached primary endpoints; 25.8% patients reached secondary endpoints. Patients with elevated liver ECV (cut-off 34.4%) had significantly higher risk reaching primary and secondary endpoints. Cox regression showed liver ECV was an independent prognostic predictor, and showed independent prognostic value for primary endpoints and long-term HF readmission compared to conventional clinical and cardiac MRI parameters.

DATA CONCLUSIONS

Liver ECV is an independent prognostic predictor and may serve as an innovative approach for risk stratification for DCM.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Diagnostic Value of T1 Mapping in Detecting Iron Overload in Indian Patients with Thalassemia Major: A Comparison with T2* Mapping

Purpose  T2* is the gold standard for iron quantification in liver as well as myocardium. In this study, we evaluated the diagnostic accuracy of myocardial T1 mapping for the assessment of myocardial iron overload (MIO) as compared to the T2* mapping in patients with thalassemia major (TM). Methods  Consecutive TM patients attending the thalassemia clinic were prospectively enrolled. Magnetic resonance imaging was performed on a 1.5 T scanner (Siemens Healthineers, Germany) using a gradient echo T2* as well as a T1 mapping (MOLLI) sequence done at a mid-ventricular short-axis single 8 mm slice of the left ventricle. Values were analyzed by manually drawing a region of interest in the mid-septum. T2*less than 20ms was used as the cutoff for significant MIO. Results  One-hundred three patients (58 males, mean age: 17 ± 7.8 years, mean ferritin: 2009.5 µg/L) underwent cardiovascular magnetic resonance. Median T2* of myocardium was 33.45ms. Nineteen patients (18.4%) had T2*less than 20ms. T1 value was low (<850ms) in all the patients with T2* less than 20 ms. Receiver operating characteristic curve analysis revealed the best cutoff of native T1 mapping value as 850 ms which had high specificity (95.2%), sensitivity (94.2%) and negative predictive value (98.8%) for T2* less than 20ms. There was excellent agreement between T1 and T2* for diagnosis of MIO (Kappa-0.848, p <0.001). We did not find any patient who had normal T1 mapping values but had MIO on T2*. Conclusion  T1 and T2* correlate well and normal T1 values may rule out presence of MIO. T1 mapping can act as additional imaging marker for MIO and may be helpful in centers with nonavailability or limited experience of T2*.

Cardiac magnetic resonance assessment of athletic myocardial fibrosis; Benign bystander or malignant marker?

The benefits of exercise are irrefutable with a well-established dose-dependent relationship between exercise intensity and reduction in cardiovascular disease. Differentiating the physiological adaptation to exercise, termed the "athlete's heart" from cardiomyopathies, has been advanced by the advent of more sophisticated imaging modalities such as cardiac magnetic resonance imaging (CMR). Myocardial fibrosis on CMR is a mutual finding amongst seemingly healthy endurance athletes and individuals with cardiomyopathy. As a substrate for arrhythmias, fibrosis is traditionally associated with increased cardiovascular risk. In this article, we discuss the aetiologies, distribution and potential implications of myocardial fibrosis in athletes.

Correlation of myocardial strain by CMR-feature tracking with substrate abnormalities detected by electro-anatomical mapping in patients with nonischemic cardiomyopathy

BACKGROUND

Late gadolinium enhancement (LGE) detected by cardiac MRI (CMR) has low correlation with low voltage zones (LVZs) detected by electroanatomical mapping (EAM). We aim to study correlation of myocardial strain by CMR- Feature Tracking (FT) alongside LGE with LVZs detected by EAM.

METHODS

Nineteen consecutive CMRs of patients with EAM were analyzed offline by CMR-FT. Peak value of circumferential strain (CS), longitudinal strain (LS), and LGE was measured in each segment of the left ventricle (17-segment model). The percentage of myocardial segments with CS and LS > -17% was determined. Percentage area of LGE-scar was calculated. Global and segment-wise bipolar and unipolar voltage was collected. Percentage area of bipolar LVZ (<1.5 mV) and unipolar LVZ (<8.3 mV) was calculated.

RESULTS

Mean age was 62±11 years. Mean LVEF was 37±13%. Mean global CS was -11.8±5%. Mean global LS was -11.2±4%. LGE-scar was noted in 74% of the patients. Mean percentage area of LGE-scar was 5%. There was significant correlation between percentage abnormality detected by LS with percentage bipolar LVZ (r = +0.5, p = 0.03) and combined percentage CS+LS abnormality with percentage unipolar LVZ (r = +0.5, p = 0.02). Per-unit increase in CS increased the percentage area of unipolar LVZ by 2.09 (p = 0.07) and per-unit increase in LS increased the percentage area of unipolar LVZ by 2.49 (p = 0.06). The concordance rates between CS and LS to localize segments with bipolar/unipolar LVZ were 79% and 95% compared to 63% with LGE.

CONCLUSIONS

Myocardial strain detected by CMR-FT has a better correlation with electrical low voltage zones than the conventional LGE.

Predictive value for mortality of left ventricular wall thickness in dilated cardiomyopathy

AIMS

The purpose of this study was to explore the predictive value of wall thickness measured by cardiac magnetic resonance (CMR) for all-cause mortality in dilated cardiomyopathy (DCM) patients.

METHODS AND RESULTS

DCM patients who underwent CMR and completed the regular follow-up were included in this study. The left ventricular end-diastolic diameter (LVDd), left ventricular end-diastolic volume (LVEDV), left ventricular posterior wall thickness (PWT), interventricular septum thickness (IVST), left ventricular ejection fraction, and left ventricular mass (LVM) were measured by CMR. The presence and extent of late gadolinium enhancement (LGE) were also assessed. The relative posterior wall thickness (RWTPW ) and relative interventricular septum wall thickness (RWTIVS ) were defined by the following equations: RWTPW  = (2 × PWT)/LVDd, and RWTIVS  = (2 × IVST)/LVDd. All patients received regular telephone and outpatient follow-up. The primary endpoint was all-cause mortality. A total of 161 patients were enrolled in this study, including 126 (78.3%) males. The mean age was 52.3 ± 13.6 years. During the median follow-up of 47 months (interquartile range 32-57 months), 41 (24.8%) patients died. Compared with the non-death group, LVDd (75.2 ± 11.9 vs. 70.5 ± 8.8 mm; P = 0.025) was greater in the death group, while PWT [5.2 mm (3.7-6.8) vs. 6.9 mm (5.3-8.6); P < 0.001], IVST [8.2 mm (6.5-9.5) vs. 9.3 mm (7.4-10.5); P = 0.005], RWTPW [0.15 (0.11-0.19) vs. 0.20 (0.15-0.25); P < 0.001], RWTIVS [0.22 (0.17-0.26) vs. 0.26 (0.22-0.31); P < 0.001], and LVM/LVEDV ratio (0.5 ± 0.2 vs. 0.7 ± 0.2 g/mL; P < 0.001) were lower. The presence of LGE [LGE(+)] was more frequent in the death group (75.6% vs. 58.3%; P = 0.048). However, the LGE extent was not significantly different between the two groups [4 (1-7) vs. 2 (0-6); P = 0.096]. Multivariate Cox regression analysis showed that PWT [hazard ratio (HR) 0.086, 95% confidence interval (CI) 0.665-0.976; P < 0.05] and RWTPW (HR 0.001, 95% CI 0.000-0.502; P < 0.05) were independent predictors of all-cause death. In contrast, IVST, RWTIVS , and the presence of LGE were not clearly associated with death.

CONCLUSIONS

PWT measured by CMR is an independent predictor of all-cause mortality in DCM patients. However, there was no significant correlation between septum wall thickness and mortality.

Cardiac Autonomic Dysfunction and Risk of Silent Myocardial Infarction Among Adults With Type 2 Diabetes

Background There is a paucity of large-scale epidemiological studies on the link between cardiac autonomic neuropathy (CAN) and the risk of silent myocardial infarction (SMI) in type 2 diabetes. We evaluated the association between CAN and the risk of SMI in a large sample of adults with type 2 diabetes. Methods and Results Participants with type 2 diabetes from the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study without atherosclerotic cardiovascular disease at baseline were included. CAN was ascertained using heart rate variability indices calculated from 10-s resting electrocardiograms. The heart rate variability indices included standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals. CAN was defined as both the standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals less than the fifth percentile of the general population. We used Cox proportional hazards regression to generate hazard ratios (HRs) for incident SMI in relation to CAN measures. Among 4842 participants (mean age, 62.5 years; 46.6% women; 60.2% White), there were 73 incident SMI cases over a median follow-up of 4.9 years (incidence rate 3.1 out of 1000 person-years [95% CI, 2.5-3.9]). After adjusting for confounders, low heart rate variability was associated with a higher risk of SMI (HR, 1.67 [95% CI, 1.02-2.72] and HR, 1.56 [95% CI, 0.94-2.58] for low standard deviation of all normal-to-normal R-R intervals and root mean square of successive differences between normal-to-normal R-R intervals, respectively). Participants with CAN had a 1.9-fold greater risk of SMI (HR, 1.91 [95% CI, 1.14-3.20]). Conclusions In a large cohort of adults with type 2 diabetes, CAN was significantly associated with an increased risk of incident SMI.

Comprehensive assessment of molecular function, tissue characterization, and hemodynamic performance by non-invasive hybrid imaging: Potential role of cardiac PETMR

Noninvasive cardiovascular imaging plays a key role in diagnosis and patient management including monitoring treatment efficacy. The usefulness of noninvasive cardiovascular imaging has been extensively studied and shown to have high diagnostic reliability and prognostic significance, while the nondiagnostic results frequently encountered with single imaging modality require complementary or alternative imaging techniques. Hybrid cardiac imaging was initially introduced to integrate anatomical and functional information to enhance the diagnostic performance, and lately employed as a strategy for comprehensive assessment of the underlying pathophysiology of diseases. More recently, the utility of computed tomography has grown in diversity, and emerged from being an exploratory technique allowing functional measurement such as stress dynamic perfusion. Cardiac magnetic resonance imaging (CMR) is widely accepted as a robust tool for evaluation of cardiac function, fibrosis, and edema, yielding high spatial resolution and soft-tissue contrast. However, the use of intravenous contrast materials is typically required for accurate diagnosis with these imaging modalities, despite the associated risk of renal toxicity. Nuclear cardiology, established as a molecular imaging technique, has advantages in visualization of the disease-specific biological process at cellular level using numerous probes without requiring contrast materials. Various imaging modalities should be appropriately used sequentially to assess concomitant disease and the progression over time. Therefore, simultaneous evaluation combining high spatial resolution and disease-specific imaging probe is a useful approach to identify the regional activity and the stage of the disease. Given the recent advance and potential of multiparametric CMR and novel nuclide tracers, hybrid positron emission tomography MR is becoming an ideal tool for disease-specific imaging.

Endomyocardial substrate of ventricular arrhythmias in patients with autoimmune rheumatic diseases

INTRODUCTION

Delayed enhancement-magnetic resonance imaging (DE-MRI) has demonstrated that nonischemic cardiomyopathy is mainly characterized by intramural or epicardial fibrosis whereas global endomyocardial fibrosis suggests cardiac involvement in autoimmune rheumatic diseases or amyloidosis. Conduction disorders and sudden cardiac death are important manifestations of autoimmune rheumatic diseases with cardiac involvement but the substrates of ventricular arrhythmias in autoimmune rheumatic diseases have not been fully elucidated.

METHODS AND RESULTS

20 patients with autoimmune rheumatic diseases presenting with ventricular tachycardia (VT) (n = 11) or frequent ventricular extrasystoles (n = 9) underwent DE-MRI and/or endocardial electroanatomical mapping of the left ventricle (LV). Ten patients with autoimmune rheumatic diseases underwent VT ablation. Global endomyocardial fibrosis without myocardial thickening and unrelated to coronary territories was detected by DE-MRI or electroanatomical voltage mapping in 9 of 20 patients with autoimmune rheumatic diseases. In the other patients with autoimmune rheumatic diseases, limited regions of predominantly epicardial (n = 4) and intramyocardial (n = 5) fibrosis or only minimal fibrosis (n = 2) were found using DE-MRI. Endocardial low-amplitude diastolic potentials and pre-systolic Purkinje or fascicular potentials, mostly within fibrotic areas, were identified as the targets of successful VT ablation in 7 of 10 patients with autoimmune rheumatic diseases.

CONCLUSION

Global endomyocardial fibrosis can be a tool to diagnose severe cardiac involvement in autoimmune rheumatic diseases and may serve as the substrate of ventricular arrhythmias in a substantial part of patients.

Prognostic implications of left ventricular inward displacement assessed by cardiac magnetic resonance imaging in patients with myocardial infarction

Risk stratification of patients with ischemic heart disease (IHD) still depends mainly on the left ventricular ejection fraction (LVEF). LV inward displacement (InD) is a novel parameter of LV systolic function, derived from feature tracking cardiac magnetic resonance (CMR) imaging. We aimed to investigate the prognostic impact of InD in patients with IHD and prior myocardial infarction. A total of 111 patients (mean age 57 ± 10, 86% male) with a history of myocardial infarction who underwent CMR were included. LV InD was quantified by measuring the displacement of endocardially tracked points towards the centreline of the LV during systole with feature tracking CMR. The endpoint was a composite of all-cause mortality, heart failure hospitalization and arrhythmic events. During a median follow-up of 142 (IQR 107-159) months, 31 (27.9%) combined events occurred. Kaplan-Meier analysis demonstrated that patients with LV InD below the study population median value (23.0%) had a significantly lower event-free survival (P < 0.001). LV InD remained independently associated with outcomes (HR 0.90, 95% CI 0.84-0.98, P = 0.010) on multivariate Cox regression analysis. InD also provided incremental prognostic value to LVEF, LV global radial strain and CMR scar burden. LV InD, measured with feature tracking CMR, was independently associated with outcomes in patients with IHD and prior myocardial infarction. LV InD also provided incremental prognostic value, in addition to LVEF and LV global radial strain. LV InD holds promise as a pragmatic imaging biomarker for post-infarct risk stratification.

Quantitative left ventricular mechanical dyssynchrony by magnetic resonance imaging predicts the prognosis of dilated cardiomyopathy

PURPOSE

Left ventricular (LV) dyssynchrony is believed to be associated with the prognosis of dilated cardiomyopathy (DCM) mainly assessed by echocardiography. This study sought to explore whether quantitative LV mechanical dyssynchrony by cardiovascular magnetic resonance imaging (CMR) tissue feature tracking could predict the prognosis of DCM.

METHOD

Patients undergoing CMR between January 2016 and December 2017 were reviewed to identify DCM patients. Quantitative LV mechanical dyssynchrony was assessed by CMR strain analysis. The outcomes of these DCM patients were followed up. The association between LV mechanical dyssynchrony and outcomes was analyzed by Cox proportional regression analysis.

RESULTS

A total of 417 patients with DCM were enrolled. At a median follow-up of 57 months, 109 patients reached endpoints: 19, sudden cardiac death; 34, heart failure death; 41, heart transplantation; 9, malignant ventricular arrhythmias; 2, LV assist devices; and 4, appropriate shocks of defibrillators. After adjustment for confounding variables, the 16-segment standard deviation of the time-to-peak radial strain (16SDTTPRS) (HR, 1.932 [95% CI: 1.079, 3.461]; P = 0.027), LV end-diastolic diameter index (HR, 1.049 [95% CI: 1.020, 1.080]; P = 0.001), NYHA classes (HR, 2.131 [95% CI: 1.597-2.844]; P < 0.001) and late gadolinium enhancement (HR, 3.219 [95% CI: 2.164, 4.787]; P < 0.001) were independently associated with composite endpoints.

CONCLUSIONS

The quantitative LV mechanical dyssynchrony parameter 16SDTTPRS derived from CMR was independently associated with adverse outcomes in patients with DCM.

Cardiovascular Magnetic Resonance from Fetal to Adult Life-Indications and Challenges: A State-of-the-Art Review

Cardiovascular magnetic resonance (CMR) imaging offers a comprehensive, non-invasive, and radiation-free imaging modality, which provides a highly accurate and reproducible assessment of cardiac morphology and functions across a wide spectrum of cardiac conditions spanning from fetal to adult life. It minimises risks to the patient, particularly the risks associated with exposure to ionising radiation and the risk of complications from more invasive haemodynamic assessments. CMR utilises high spatial resolution and provides a detailed assessment of intracardiac and extracardiac anatomy, ventricular and valvular function, and flow haemodynamic and tissue characterisation, which aid in the diagnosis, and, hence, with the management of patients with cardiac disease. This article aims to discuss the role of CMR and the indications for its use throughout the different stages of life, from fetal to adult life.

Prognostic Utility of Cardiac MRI Myocardial Strain Parameters in Patients With Ischemic and Nonischemic Dilated Cardiomyopathy: A Multicenter Study

BACKGROUND. Prior small single-center studies have yielded conflicting results regarding the prognostic significance of myocardial strain parameters derived from feature tracking (FT) on cardiac MRI in patients with dilated cardiomyopathy (DCM). OBJECTIVE. The purpose of this study was to evaluate the prognostic utility of FT parameters on cardiac MRI in patients with ischemic and nonischemic DCM and to determine the optimal strain parameter for outcome prediction. METHODS. This retrospective study included 471 patients (median age, 61 years; 365 men, 106 women) with ischemic (n = 233) or nonischemic (n = 238) DCM and left ventricular (LV) ejection fraction (EF) less than 50% who underwent cardiac MRI at any of four centers from January 2011 to December 2019. Cardiac MRI parameters were determined by manual contouring. In addition, software-based FT was used to calculate six myocardial strain parameters (LV and right ventricular [RV] global radial strain, global circumferential strain, and global longitudinal strain [GLS]). Late gadolinium enhancement (LGE) was also evaluated. Patients were assessed for a composite outcome of all-cause mortality and/or heart-failure hospitalization. Cox regression models were used to determine associations between strain parameters and the composite outcome. RESULTS. Mean LV EF was 27.5% and mean LV GLS was -6.9%. The median follow-up period was 1328 days. The composite outcome occurred in 220 patients (125 deaths, 95 heart-failure hospitalizations). All six myocardial strain parameters were significant independent predictors of the composite outcome (hazard ratio [HR] = 0.92-1.16; all p < .05). In multivariable models that included age, corrected LV and RV end-diastolic volume, LV and RV EF, and presence of LGE, the only strain parameter that was a significant independent predictor of the composite outcome was LV GLS (HR = 1.13, p = .006); LV EF and presence of LGE were not independent predictors of the composite outcome in the models (p > .05). A LV GLS threshold of -6.8% had sensitivity of 62.6% and specificity of 62.6% in predicting the composite outcome rate at 4.0 years. CONCLUSION. LV GLS, derived from FT on cardiac MRI, is a significant independent predictor of adverse outcomes in patients with DCM. CLINICAL IMPACT. This study strengthens the body of evidence supporting the clinical implementation of FT when performing cardiac MRI in patients with DCM.

Cardiac magnetic resonance radiomics for disease classification

OBJECTIVES

This study investigated the discriminability of quantitative radiomics features extracted from cardiac magnetic resonance (CMR) images for hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and healthy (NOR) patients.

METHODS

The data of two hundred and eighty-three patients with HCM (n = 48) or DCM (n = 52) and NOR (n = 123) were extracted from two publicly available datasets. Ten feature selection methods were first performed on twenty-one different sets of radiomics features extracted from the left ventricle, right ventricle, and myocardium segmented from CMR images in the end-diastolic frame, end-systolic frame, and a combination of both; then, nine classical machine learning methods were trained with the selected radiomics features to distinguish HCM, DCM, and NOR. Ninety classification models were constructed based on combinations of the ten feature selection methods and nine classifiers. The classification models were evaluated, and the optimal model was selected. The diagnostic performance of the selected model was also compared to that of state-of-the-art methods.

RESULTS

The random forest minimum redundancy maximum relevance model with features based on LeastAxisLength, Maximum2DDiameterSlice, Median, MinorAxisLength, Sphericity, VoxelVolume, Kurtosis, Flatness, and Skewness was the highest performing model, achieving 91.2% classification accuracy. The cross-validated areas under the curve on the test dataset were 0.938, 0.966, and 0.936 for NOR, DCM, and HCM, respectively. Furthermore, compared with those of the state-of-the-art methods, the sensitivity and accuracy of this model were greatly improved.

CONCLUSIONS

A predictive model was proposed based on CMR radiomics features for classifying HCM, DCM, and NOR patients. The model had good discriminability.

KEY POINTS

• The first-order features and the features extracted from the LOG-filtered images have potential in distinguishing HCM patients from DCM patients. • The features extracted from the RV play little role in distinguishing DCM from HCM. • The VoxelVolume of the myocardium in the ED frame is important in the recognition of DCM.

COVID-19 mRNA Vaccines: The Molecular Basis of Some Adverse Events

Each injection of any known vaccine results in a strong expression of pro-inflammatory cytokines. This is the result of the innate immune system activation, without which no adaptive response to the injection of vaccines is possible. Unfortunately, the degree of inflammation produced by COVID-19 mRNA vaccines is variable, probably depending on genetic background and previous immune experiences, which through epigenetic modifications could have made the innate immune system of each individual tolerant or reactive to subsequent immune stimulations.We hypothesize that we can move from a limited pro-inflammatory condition to conditions of increasing expression of pro-inflammatory cytokines that can culminate in multisystem hyperinflammatory syndromes following COVID-19 mRNA vaccines (MIS-V). We have graphically represented this idea in a hypothetical inflammatory pyramid (IP) and we have correlated the time factor to the degree of inflammation produced after the injection of vaccines. Furthermore, we have placed the clinical manifestations within this hypothetical IP, correlating them to the degree of inflammation produced. Surprisingly, excluding the possible presence of an early MIS-V, the time factor and the complexity of clinical manifestations are correlated to the increasing degree of inflammation: symptoms, heart disease and syndromes (MIS-V).

Cardiovascular Magnetic Resonance Demonstrates Myocardial Inflammation of Differing Etiologies and Acuities in Patients with Genetic and Inflammatory Myopathies

INTRODUCTION

Myopathies are heterogeneous neuromuscular diseases of genetic and/or inflammatory etiology that affect both cardiac and skeletal muscle. We investigated the prevalence of cardiac inflammation in patients with myopathies, cardiovascular symptoms, and normal echocardiography using cardiovascular magnetic resonance (CMR).

METHODS

We prospectively evaluated 51 patients with various genetic (n = 23) and inflammatory (n = 28) myopathies (median age, IQR: 12 (11-15) years, 22% girls; 61 (55-65) years, 46% women, respectively) and compared their CMR findings to corresponding age- and sex-matched controls (n = 21 and 20, respectively) and to each other.

RESULTS

Patients with genetic myopathy had similar biventricular morphology and function to healthy controls but showed higher late gadolinium enhancement (LGE), native T1 mapping, extracellular volume fraction (ECV), and T2 mapping values. Collectively, 22 (95.7%) patients with genetic myopathy had a positive T1-criterion and 3 (13.0%) had a positive T2-criterion according to the updated Lake Louise criteria. Compared with healthy controls, patients with inflammatory myopathy showed preserved left ventricular (LV) function and reduced LV mass, while all CMR-derived tissue characterization indices were significantly higher (p < 0.001 for all). All patients had a positive T1-criterion, and 27 (96.4%) had a positive T2-criterion. A positive T2-criterion or T2-mapping > 50 ms could discriminate between patients with genetic and inflammatory myopathies with a sensitivity of 96.4% and a specificity of 91.3% (AUC = 0.9557).

CONCLUSIONS

The vast majority of symptomatic patients with inflammatory myopathies and normal echocardiography show evidence of acute myocardial inflammation. In contrast, acute inflammation is rare in patients with genetic myopathies, who show evidence of chronic low-grade inflammation.

The Role of Strain by Cardiac Magnetic Resonance Imaging in Predicting the Prognosis of Patients with Chronic Thromboembolic Pulmonary Hypertension

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by thrombotic obstruction of the pulmonary arteries, and right ventricular (RV) dysfunction is a major cause of death. Cardiac magnetic resonance (CMR) is the gold standard for assessing heart wall deformation; therefore, we aimed to determine the prognostic value of CMR strain in patients with CTEPH. Strain derived by CMR was measured at the time of diagnosis in 45 patients with CTEPH, and the relationship between RV strain and prognosis was determined through follow-up. The value of RV strain in the prognostic model was compared with that of pulmonary arterial hypertension (PAH) risk stratification. The RV global peak longitudinal strain (GLS) and global peak circumferential strain (GCS) in CTEPH patients were lower than the normal references of RV strain in the control group. GLS and longitudinal strain in the basal segment were independent risk factors for adverse events (P < .050). Adding CMR parameters to PAH risk stratification improved its predictive power in patients with CTEPH. GLS and GCS scores were impaired in patients with chronic RV overload. RV strain derived by CMR imaging is a promising noninvasive tool for the follow-up of patients with CTEPH.

Multilevel comparison of deep learning models for function quantification in cardiovascular magnetic resonance: On the redundancy of architectural variations

Background

Cardiac function quantification in cardiovascular magnetic resonance requires precise contouring of the heart chambers. This time-consuming task is increasingly being addressed by a plethora of ever more complex deep learning methods. However, only a small fraction of these have made their way from academia into clinical practice. In the quality assessment and control of medical artificial intelligence, the opaque reasoning and associated distinctive errors of neural networks meet an extraordinarily low tolerance for failure.

Aim

The aim of this study is a multilevel analysis and comparison of the performance of three popular convolutional neural network (CNN) models for cardiac function quantification.

Methods

U-Net, FCN, and MultiResUNet were trained for the segmentation of the left and right ventricles on short-axis cine images of 119 patients from clinical routine. The training pipeline and hyperparameters were kept constant to isolate the influence of network architecture. CNN performance was evaluated against expert segmentations for 29 test cases on contour level and in terms of quantitative clinical parameters. Multilevel analysis included breakdown of results by slice position, as well as visualization of segmentation deviations and linkage of volume differences to segmentation metrics via correlation plots for qualitative analysis.

Results

All models showed strong correlation to the expert with respect to quantitative clinical parameters (r_{z '} = 0.978, 0.977, 0.978 for U-Net, FCN, MultiResUNet respectively). The MultiResUNet significantly underestimated ventricular volumes and left ventricular myocardial mass. Segmentation difficulties and failures clustered in basal and apical slices for all CNNs, with the largest volume differences in the basal slices (mean absolute error per slice: 4.2 ± 4.5 ml for basal, 0.9 ± 1.3 ml for midventricular, 0.9 ± 0.9 ml for apical slices). Results for the right ventricle had higher variance and more outliers compared to the left ventricle. Intraclass correlation for clinical parameters was excellent (≥0.91) among the CNNs.

Conclusion

Modifications to CNN architecture were not critical to the quality of error for our dataset. Despite good overall agreement with the expert, errors accumulated in basal and apical slices for all models.

Eosinophilic myocarditis: Case report and brief review of the literature

Eosinophilic myocarditis (EM) is a cardiac manifestation of hypereosinophilic syndrome with a high mortality rate. EM shares imaging features similar to other restrictive cardiopathies, and include patchy intramural late gadolinium enhancement on cardiac magnetic resonance with or without presence of biventricular thrombus. Diagnosis is confirmed on histopathology, and is the current gold standard. Here we report clinical presentation and imaging findings of EM in a 70-year-old woman who presented with fever and chills.

Improving Outcomes in Ventricular Tachycardia Ablation Using Imaging to Identify Arrhythmic Substrates

Ventricular tachycardia (VT) ablation is limited by modest acute and long-term success rates, in part due to the challenges in accurately identifying the arrhythmogenic substrate. The combination of multimodality imaging along with information from electroanatomic mapping allows for a more comprehensive assessment of the arrhythmogenic substrate which facilitates VT ablation, and the use of preprocedural imaging has been shown to improve long-term ablation outcomes. Beyond regional recognition of the arrhythmogenic substrate, advanced imaging techniques can be used to create tailored ablation strategies preprocedurally. This review will focus on how imaging can be used to guide ablation planning and execution with a focus on clinical applications aimed at improving the outcome of VT ablation procedures.

Efficient Combination of CNN and Transformer for Dual-Teacher Uncertainty-guided Semi-supervised Medical Image Segmentation

BACKGROUND AND OBJECTIVE

Deep learning-based methods for fast target segmentation of magnetic resonance imaging (MRI) have become increasingly popular in recent years. Generally, the success of deep learning methods in medical image segmentation tasks relies on a large amount of labeled data. The time-consuming and labor-intensive problem of data annotation is a major challenge in medical image segmentation tasks. The aim of this work is to enhance the segmentation of MR images using a semi-supervised learning-based method using a small amount of labeled data and a large amount of unlabeled data.

METHODS

To utilize the effective information of the unlabeled data, we designed the method of guiding the Student segmentation model simultaneously by the Dual-Teacher structure of CNN and transformer forming the subject network. Both Teacher A and Student models are CNNs, and the TA-S module they form is a mean teacher structure with added data noise. In the TB-S module formed by the combination of Student and Teacher B models, their backbone networks CNN and transformer capture the local and global information of the image at the same time, respectively, to create pseudo labels for each other and perform cross-supervision. The Dual-Teacher guides the Student through synchronous training and performs knowledge rectification and communication with each other through consistent regular constraints, which better utilizes the valid information in the unlabeled data. In addition, the segmentation predictions of Teacher A and Student and Teacher A and Teacher B are screened for uncertainty assessment during the training process to enhance the prediction accuracy and generalization of the model. This method uses the mechanism of simultaneous training of the synthetic structure composed of TA-S and TB-S modules to jointly guide the optimization of the Student model to obtain better segmentation ability.

RESULTS

We evaluated the proposed method on a publicly available MRI dataset from a cardiac segmentation competition organized by MICCAI in 2017. Compared with several existing state-of-the-art semi-supervised segmentation methods, the method achieves better segmentation results in terms of Dice coefficient and HD distance evaluation metrics of 0.878 and 4.9 mm and 0.886 and 5.0 mm, respectively, using a training set containing only 10% and 20% of labeled data.

CONCLUSION

This method fuses CNN and transformer to design a new Teacher-Student semi-supervised learning optimization strategy, which greatly improves the utilization of a large number of unlabeled medical images and the effectiveness of model segmentation results.

Prognostic value of myocardial strain by magnetic resonance imaging in nonischemic dilated cardiomyopathy: a systematic review and meta-analysis

Aim    This study was aimed at performing a systematic review and meta-analysis to investigate the prognostic role of left ventricular (LV) myocardial strain variables as determined by magnetic-resonance imaging in non-ischemic dilated cardiomyopathy.Material and methods    A search was performed in PubMed (MEDLINE), Google Scholar, and EMBASE databases for studies on the prognostic role of LV myocardial strain based on MR feature-tracking in non-ischemic dilated cardiomyopathy. Uncorrected odds ratio (OR) values reported by the studies where similar evaluation criteria of myocardial strain were available, were combined for a meta-analysis.Results    Nine studies were selected from 351 publications for this systematic review and meta-analysis. The analysis included a totality of 2139 patients (mean age, 52.3 years; mean follow-up duration, 42.5 months). The meta-analysis showed that the worsening of the LV global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS) was associated with increased risk of major adverse cardiovascular events (MACE): OR, 1.13  per each % of GLS; 95 % CI: 1.050–1.225; p=0.001; OR, 1.16 per each % of GCS; 95 % CI: 1.107–1.213; p<0.0001; OR, 0.95 per each % of GRS; 95 % CI: 0.92–0.97; p<0.0001.Conclusion    The LV GLS, GCS, and GRS variables by MR feature-tracking data are powerful predictors for the development of MACE. Evaluation of myocardial strain can be used as an effective instrument for risk stratification in patients with non-ischemic dilated cardiomyopathy.

 

The prognostic value of right ventricular ejection fraction by cardiovascular magnetic resonance in heart failure: A systematic review and meta-analysis

BACKGROUND

Cardiac magnetic resonance (CMR) is considered the gold standard for the assessment of right ventricular ejection fraction (RVEF). Previous studies have suggested that RVEF may be a predictor of adverse outcomes in heart failure (HF). In this study, we aimed to systematically review the prognostic value of RVEF, evaluated by CMR, across the spectrum of left ventricular systolic function in patients with HF.

METHODS

Electronic databases were searched for studies investigating the prognostic value of RVEF in HF, irrespective of left ventricular ejection fraction (LVEF). A random-effects meta-analysis was conducted for mortality and HF hospitalization. Subgroup analyses were also performed based on the presence of reduced (<50%) or preserved LVEF (≥50%).

RESULTS

In total, 46 studies enrolling 14,344 patients were included. In the pooled analyses, impaired RVEF was a powerful predictor of mortality (HR: 1.26, 95% CI: 1.18-1.33, I²: 13%, per 10% decrease in RVEF) and death or HF hospitalization (HR: 1.31, 95% Cl: 1.2-1.42, I²: 27%, per 10% decrease in RVEF). A decrease in RVEF was strongly associated with increased risk of mortality or hospitalization both in HF with reduced EF (HR: 1.24, 95% CI: 1.13-1.36, I²: 2%, per 10% decrease in RVEF) and in HF with preserved EF (HR: 1.24, 95% CI: 1.09-1.40, I²: 0%, per 10% decrease in RVEF).

CONCLUSION

Impaired RVEF on CMR strongly predicts adverse outcomes in patients with HF regardless of LVEF. RV systolic function should be carefully evaluated in these patients. Prospero Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021256967.

Current view on radiation-induced heart disease and methods of its diagnosis

In recent years, cardiologists and cardiovascular surgeons are increasingly encountering radiation-induced heart disease (RIHD) in their practice. This complication is described in literature but is poorly understood and clinically challenging. Radiation therapy (RT) is widely used in the treatment of many cancers. Despite the considerable risk of RT complications, it is used in 20–55% of cancer patients. Radiation-associated cardiotoxicity appears to be delayed, typically 10 to 30 years following treatment. Mediastinal irradiation significantly increases the risk of non-ischemic cardiomyopathy. Recent reviews estimate the prevalence of radiation-induced cardiomyopathy at more than 10%. Therefore, it is important to understand the pathophysiology of RIHD, consider risk factors associated with radiation injury, and detect the condition early.

Usefulness of Cardiovascular Magnetic Resonance Imaging in a Patient with Cardiac Involvement of Systemic Sclerosis

A 72-year-old Japanese woman with systemic sclerosis was admitted to our hospital because of symptoms of heart failure. Cardiovascular magnetic resonance (CMR) imaging had shown that extensive myocardial fibrosis secondary to systemic sclerosis was the main cause of heart failure. One month after CMR, she had complete atrioventricular (AV) block. It was suggested that the progression of fibrosis to the AV node caused complete AV block. This case report has clinical implications in highlighting the fact that CMR is useful for not only evaluating the present pathophysiology but also predicting future adverse events in patients with systemic sclerosis.

The role of multimodality imaging in patients with heart failure with reduced and preserved ejection fraction

PURPOSE OF REVIEW

The burden of clinical heart failure, both heart failure with a reduced ejection fraction (HFrEF) and with a preserved ejection fraction (HFpEF), continues to increase both nationally and globally. This review summarizes the expanding role of multimodality imaging techniques in the evaluation and management these patients.

RECENT FINDINGS

Echocardiographic assessment for heart failure continues to expand and should include a robust hemodynamic and strain assessment. Nuclear techniques have also continued to evolve and advances including computed tomography attenuation correction for single photon emission-computed tomography positron-emission tomography increase diagnostic accuracy as well as provide information such as myocardial blood flow and viability assessment. Computed tomography imaging, already well established in the assessment of coronary and valvular disease, has increasing utility in the characterization of myopathy, and cardiac magnetic resonance imaging (MRI) continues to expand its role in tissue characterization to a wider breadth of diseases, including right ventricular cardiomyopathy and left ventricle noncompaction.

SUMMARY

Although heart failure remains a clinical diagnosis based on history and examination, early imaging is critical for further assessment. Due to its widespread availability, affordability, and safety, transthoracic echocardiography has long been the mainstay tool for both initial evaluation as well as for periodic surveillance of heart failure patients, but advances in multimodality imaging are occurring at a rapid pace and promise to provide an increasing wealth of data to help manage such patients.

Real-Time Spiral CMR Is Superior to Conventional Segmented Cine-Imaging for Left-Ventricular Functional Assessment in Patients with Arrhythmia

(1) Background: Segmented Cartesian Cardiovascular magnetic resonance (CMR) often fails to deliver robust assessment of cardiac function in patients with arrhythmia. We aimed to assess the performance of a tiny golden-angle spiral real-time CMR sequence at 1.5 T for left-ventricular (LV) volumetry in patients with irregular heart rhythm; (2) Methods: We validated the real-time sequence against the standard breath-hold segmented Cartesian sequence in 32 patients, of whom 11 presented with arrhythmia. End-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and ejection fraction (EF) were assessed. In arrhythmic patients, real-time and standard Cartesian acquisitions were compared against a reference echocardiographic modality; (3) Results: In patients with sinus rhythm, good agreements and correlations were found between the segmented and real-time methods, with only minor, non-significant underestimation of EDV for the real-time sequence (135.95 ± 30 mL vs. 137.15 ± 31, p = 0.164). In patients with arrhythmia, spiral real-time CMR yielded superior image quality to the conventional segmented imaging, allowing for excellent agreement with the reference echocardiographic volumetry. In contrast, in this cohort, standard Cartesian CMR showed significant underestimation of LV-ESV (106.72 ± 63.51 mL vs. 125.47 ± 72.41 mL, p = 0.026) and overestimation of LVEF (42.96 ± 10.81% vs. 39.02 ± 11.72%, p = 0.039); (4) Conclusions: Real-time spiral CMR improves image quality in arrhythmic patients, allowing reliable assessment of LV volumetry.

T1 Mapping and Extracellular Volume in Cardiomyopathy Showing Left Ventricular Hypertrophy: Differentiation Between Hypertrophic Cardiomyopathy and Hypertensive Heart Disease

Background

Methods

Results

Conclusion

Prevalence and prognostic significance of ischemic late gadolinium enhancement pattern in non-ischemic dilated cardiomyopathy

BACKGROUND

Typical late gadolinium enhancement (LGE) patterns in dilated cardiomyopathy (DCM) include intramyocardial and subepicardial distribution. However, the ischemic pattern of LGE (subendocardial and transmural) has also been reported in DCM without coronary artery disease (CAD), but its correlates and prognostic significance are still not known. On these bases, this study sought to describe the prevalence and prognostic significance of the ischemic LGE pattern in DCM.

METHODS

A total of 611 DCM patients with available cardiac magnetic resonance were retrospectively analyzed. A composite of all-cause-death, major ventricular arrhythmias (MVAs), heart transplantation (HTx) or ventricular assist device (VAD) implantation was the primary outcome of the study. Secondary outcomes were a composite of sudden cardiac death or MVAs and a composite of death for refractory heart failure, HTx or VAD implantation.

RESULTS

Ischemic LGE was found in 7% of DCM patients without significant CAD or history of myocardial infarction, most commonly inferior/inferolateral/anterolateral. Compared to patients with non-ischemic LGE, those with ischemic LGE had higher prevalence of hypertension and atrial fibrillation or flutter. Ischemic LGE was associated with worse long-term outcomes compared to non-ischemic LGE (36% vs 23% risk of primary outcome events at 5 years respectively, P = .006), and remained an independent predictor of primary outcome after adjustment for clinically and statistically significant variables (adjusted hazard ratio 2.059 [1.055-4.015], P = .034 with respect to non-ischemic LGE).

CONCLUSIONS

The ischemic pattern of LGE is not uncommon among DCM patients without CAD and is independently associated with worse long-term outcomes.

Relation of Left Atrial Flow, Volume, and Strain to Paroxysmal Atrial Fibrillation in Patients With Hypertrophic Cardiomyopathy

This study aims to characterize flow, volume, and strain of the left atrium in hypertrophic cardiomyopathy (HC) with atrial fibrillation (AF) using cine cardiovascular magnetic resonance (CMR) imaging. Cine CMR data for 144 patients with HC, including 29 patients with episodes of paroxysmal AF and 13 patients with persistent AF, were retrospectively analyzed. The vortex flow of the left atrial (LA, %) was measured using a vortex flow map and was used as an estimate of flow. The LA end-systolic volume index (ml/m²), LA ejection fraction (%) and global peak longitudinal LA strain (%) derived from a feature-tracking method were used as estimates of volume and strain. Vortex flow of the LA in patients with paroxysmal AF was significantly smaller than in patients without AF (vertical long-axis view; 26.7 ± 10.8% vs 33.2 ± 12.2%, p <0.005). The patients with paroxysmal AF had greater LA end-systolic volume index and global peak longitudinal LA strain and lower LA ejection fraction compared with those without AF. In conclusion, patients with HC with paroxysmal AF are characterized by small vortex flow, large volume, and decreased strain of LA on cine CMR.

Ensemble of 2D Residual Neural Networks Integrated with Atrous Spatial Pyramid Pooling Module for Myocardium Segmentation of Left Ventricle Cardiac MRI

Cardiac disease diagnosis and identification is problematic mostly by inaccurate segmentation of the cardiac left ventricle (LV). Besides, LV segmentation is challenging since it involves complex and variable cardiac structures in terms of components and the intricacy of time-based crescendos. In addition, full segmentation and quantification of the LV myocardium border is even more challenging because of different shapes and sizes of the myocardium border zone. The foremost purpose of this research is to design a precise automatic segmentation technique employing deep learning models for the myocardium border using cardiac magnetic resonance imaging (MRI). The ASPP module (Atrous Spatial Pyramid Pooling) was integrated with a proposed 2D-residual neural network for segmentation of the myocardium border using a cardiac MRI dataset. Further, the ensemble technique based on a majority voting ensemble method was used to blend the results of recent deep learning models on different set of hyperparameters. The proposed model produced an 85.43% dice score on validation samples and 98.23% on training samples and provided excellent performance compared to recent deep learning models. The myocardium border was successfully segmented across diverse subject slices with different shapes, sizes and contrast using the proposed deep learning ensemble models. The proposed model can be employed for automatic detection and segmentation of the myocardium border for precise quantification of reflow, myocardial infarction, myocarditis, and h cardiomyopathy (HCM) for clinical applications.

Image-Based Computational Hemodynamics Analysis of Systolic Obstruction in Hypertrophic Cardiomyopathy

Hypertrophic Cardiomyopathy (HCM) is a pathological condition characterized by an abnormal thickening of the myocardium. When affecting the medio-basal portion of the septum, it is named Hypertrophic Obstructive Cardiomyopathy (HOCM) because it induces a flow obstruction in the left ventricular outflow tract. In any type of HCM, the myocardial function can become compromised, possibly resulting in cardiac death. In this study, we investigated with computational analysis the hemodynamics of patients with different types of HCM. The aim was quantifying the effects of this pathology on the intraventricular blood flow and pressure gradients, and providing information potentially useful to guide the indication and the modality of the surgical treatment (septal myectomy). We employed an image-based computational approach, integrating fluid dynamics simulations with geometric and functional data, reconstructed from standard cardiac cine-MRI acquisitions. We showed that with our approach we can better understand the patho-physiological behavior of intraventricular blood flow dynamics due to the abnormal morphological and functional aspect of the left ventricle. The main results of our investigation are: (a) a detailed patient-specific analysis of the blood velocity, pressure and stress distribution associated to HCM; (b) a computation-based classification of patients affected by HCM that can complement the current clinical guidelines for the diagnosis and treatment of HOCM.

Imaging in Women with Heart Failure: Sex-specific Characteristics and Current Challenges

Cardiovascular disease (CVD) represents a significant threat to women's health. Heart failure (HF) is one CVD that still has an increasing incidence and about half of all cases involve women. HF is characterised by strong sex-specific features in aetiology, clinical manifestation and outcomes. Women are more likely to have hypertensive heart disease and HF with preserved ejection fraction, they experience worse quality of life but have a better overall survival rate. Women's hearts also have unique morphological characteristics that should be considered during cardiovascular assessment. It is important to understand and highlight these sex-specific features to be able to provide a tailored diagnostic approach and therapeutic management. The aim of this article is to review these aspects together with the challenges and the unique characteristics of different imaging modalities used for the diagnosis and follow-up of women with HF.

Prognostic role of global longitudinal strain by feature tracking in patients with hypertrophic cardiomyopathy: The STRAIN-HCM study

BACKGROUND

The assessment of myocardial fiber deformation with cardiac magnetic resonance feature tracking (CMR-FT) has shown to be promising in terms of prognostic information in several structural heart diseases. However, little is known about its role in hypertrophic cardiomyopathy (HCM). Aims of the present study were: 1) to assess the prognostic role of CMR-FT derived strain parameters in patients with HCM.

METHODS

CMR was performed in 130 consecutive HCM patients (93 males, mean age (54 ± 17 years) with an estimated 5-year risk of sudden cardiac death (SCD) <6% according to the HCM Risk-SCD calculator. 2D- and 3D-Global Radial (GRS), Longitudinal (GLS) and Circumferential (GCS) Strain was evaluated by FT analysis. The primary outcome of the study was a composite of major adverse cardiac events (MACE) including SCD, resuscitated cardiac arrest due to ventricular fibrillation (VF) or hemodynamically unstable ventricular tachycardia (VT), and hospitalization for heart failure.

RESULTS

After a median follow-up of 51.7 (37.1-68.8) months, 4 (3%) patients died (all of them suffered from SCD) and 36 (28%) were hospitalized for heart failure. After multivariable adjustment for clinical and imaging covariates, among all strain parameters, only GLS remained a significant independent predictor of outcome events in both the model including 2D strain (HR 1.12, 95% CI 1.03-1.23, p = 0.01) and the model including 3D strain (HR 1.14, 95% CI 1.01-1.30, p = 0.04). The addition of 2D-GLS into the model with clinical and imaging predictors resulted in a significant increase in the C-statistic (from 0.48 to 0.65, p = 0.03).

CONCLUSION

CMR-FT derived GLS is a powerful independent predictor of MACE in patients with HCM, incremental to common clinical and CMR risk factors including left ventricular ejection fraction and late gadolinium enhancement.

Unsupervised Domain Adaptation With Variational Approximation for Cardiac Segmentation

Unsupervised domain adaptation is useful in medical image segmentation. Particularly, when ground truths of the target images are not available, domain adaptation can train a target-specific model by utilizing the existing labeled images from other modalities. Most of the reported works mapped images of both the source and target domains into a common latent feature space, and then reduced their discrepancy either implicitly with adversarial training or explicitly by directly minimizing a discrepancy metric. In this work, we propose a new framework, where the latent features of both domains are driven towards a common and parameterized variational form, whose conditional distribution given the image is Gaussian. This is achieved by two networks based on variational auto-encoders (VAEs) and a regularization for this variational approximation. Both of the VAEs, each for one domain, contain a segmentation module, where the source segmentation is trained in a supervised manner, while the target one is trained unsupervisedly. We validated the proposed domain adaptation method using two cardiac segmentation tasks, i.e., the cross-modality (CT and MR) whole heart segmentation and the cross-sequence cardiac MR segmentation. Results show that the proposed method achieved better accuracies compared to two state-of-the-art approaches and demonstrated good potential for cardiac segmentation. Furthermore, the proposed explicit regularization was shown to be effective and efficient in narrowing down the distribution gap between domains, which is useful for unsupervised domain adaptation. The code and data have been released via https://zmiclab.github.io/projects.html.

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

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

Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data

Automatic quantification of the left ventricle (LV) from cardiac magnetic resonance (CMR) images plays an important role in making the diagnosis procedure efficient, reliable, and alleviating the laborious reading work for physicians. Considerable efforts have been devoted to LV quantification using different strategies that include segmentation-based (SG) methods and the recent direct regression (DR) methods. Although both SG and DR methods have obtained great success for the task, a systematic platform to benchmark them remains absent because of differences in label information during model learning. In this paper, we conducted an unbiased evaluation and comparison of cardiac LV quantification methods that were submitted to the Left Ventricle Quantification (LVQuan) challenge, which was held in conjunction with the Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop at the MICCAI 2018. The challenge was targeted at the quantification of 1) areas of LV cavity and myocardium, 2) dimensions of the LV cavity, 3) regional wall thicknesses (RWT), and 4) the cardiac phase, from mid-ventricle short-axis CMR images. First, we constructed a public quantification dataset Cardiac-DIG with ground truth labels for both the myocardium mask and these quantification targets across the entire cardiac cycle. Then, the key techniques employed by each submission were described. Next, quantitative validation of these submissions were conducted with the constructed dataset. The evaluation results revealed that both SG and DR methods can offer good LV quantification performance, even though DR methods do not require densely labeled masks for supervision. Among the 12 submissions, the DR method LDAMT offered the best performance, with a mean estimation error of 301 mm 2 for the two areas, 2.15 mm for the cavity dimensions, 2.03 mm for RWTs, and a 9.5% error rate for the cardiac phase classification. Three of the SG methods also delivered comparable performances. Finally, we discussed the advantages and disadvantages of SG and DR methods, as well as the unsolved problems in automatic cardiac quantification for clinical practice applications.

Cardiomyopathies: An Overview

Background: Cardiomyopathies are a heterogeneous group of pathologies characterized by structural and functional alterations of the heart. Aims: The purpose of this narrative review is to focus on the most important cardiomyopathies and their epidemiology, diagnosis, and management. Methods: Clinical trials were identified by Pubmed until 30 March 2021. The search keywords were “cardiomyopathies, sudden cardiac arrest, dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy, arrhythmogenic cardiomyopathy (ARCV), takotsubo syndrome”. Results: Hypertrophic cardiomyopathy (HCM) is the most common primary cardiomyopathy, with a prevalence of 1:500 persons. Dilated cardiomyopathy (DCM) has a prevalence of 1:2500 and is the leading indication for heart transplantation. Restrictive cardiomyopathy (RCM) is the least common of the major cardiomyopathies, representing 2% to 5% of cases. Arrhythmogenic cardiomyopathy (ARCV) is a pathology characterized by the substitution of the myocardium by fibrofatty tissue. Takotsubo cardiomyopathy is defined as an abrupt onset of left ventricular dysfunction in response to severe emotional or physiologic stress. Conclusion: In particular, it has been reported that HCM is the most important cause of sudden death on the athletic field in the United States. It is needless to say how important it is to know which changes in the heart due to physical activity are normal, and when they are pathological.