Accurate diagnosis of apical hypertrophic cardiomyopathy using explainable advanced electrocardiogram analysis

AIMS

Typical electrocardiogram (ECG) features of apical hypertrophic cardiomyopathy (ApHCM) include tall R waves and deep or giant T-wave inversion in the precordial leads, but these features are not always present. The ECG is used as the gatekeeper to cardiac imaging for diagnosis. We tested whether explainable advanced ECG (A-ECG) could accurately diagnose ApHCM.

METHODS AND RESULTS

Advanced ECG analysis was performed on standard resting 12-lead ECGs in patients with ApHCM [n = 75 overt, n = 32 relative (<15 mm hypertrophy); a subgroup of which underwent cardiovascular magnetic resonance (n = 92)], and comparator subjects (n = 2449), including healthy volunteers (n = 1672), patients with coronary artery disease (n = 372), left ventricular electrical remodelling (n = 108), ischaemic (n = 114) or non-ischaemic cardiomyopathy (n = 57), and asymmetrical septal hypertrophy HCM (n = 126). Multivariable logistic regression identified four A-ECG measures that together discriminated ApHCM from other diseases with high accuracy [area under the receiver operating characteristic (AUC) curve (bootstrapped 95% confidence interval) 0.982 (0.965-0.993)]. Linear discriminant analysis also diagnosed ApHCM with high accuracy [AUC 0.989 (0.986-0.991)].

CONCLUSION

Explainable A-ECG has excellent diagnostic accuracy for ApHCM, even when the hypertrophy is relative, with A-ECG analysis providing incremental diagnostic value over imaging alone. The electrical (ECG) and anatomical (wall thickness) disease features do not completely align, suggesting that future diagnostic and management strategies may incorporate both features.

Quality assurance of late gadolinium enhancement cardiac MRI images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimisation

BACKGROUND

Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images is usually straightforward; but diagnostic uncertainty arises when reporters are not sure whether the observed LGE is genuine or not. This uncertainty might be resolved by repetition (to remove artefact) or further acquisition of intersecting images, but this must take place before the scan finishes. Real-time quality assurance by humans is a complex task requiring training and experience, so being able to identify which images have an intermediate likelihood of LGE while the scan is ongoing, without the presence of an expert is of high value. This decision-support could prompt immediate image optimisation or acquisition of supplementary images to confirm or refute the presence of genuine LGE. This could reduce ambiguity in reports.

METHODS

Short-axis, phase sensitive inversion recovery (PSIR) late gadolinium images were extracted from our clinical CMR database and shuffled. Two, independent, blinded experts scored each individual slice for 'LGE likelihood' on a visual analogue scale, from 0 (absolute certainty of no LGE) to 100 (absolute certainty of LGE), with 50 representing clinical equipoise. The scored images were split into 2 classes - either "high certainty" of whether LGE was present or not, or "low certainty". The dataset was split into training, validation and test sets (70:15:15). A deep learning binary classifier based on the EfficientNetV2 convolutional neural network architecture was trained to distinguish between these categories. Classifier performance on the test set was evaluated by calculating the accuracy, precision, recall, F1-score, and area under the receiver operating characteristics curve (ROC AUC). Performance was also evaluated on an external test set of images from a different centre.

RESULTS

1645 images (from 272 patients) were labelled and split at the patient level into training (1151 images), validation (247 images) and test (247 images) sets for the deep learning binary classifier. Of these, 1208 images were 'high certainty' (255 for LGE, 953 for no LGE), and 437 were 'low certainty'). An external test comprising 247 images from 41 patients from another centre was also employed. After 100 epochs the performance on the internal test set was: accuracy = 94%, recall = 0.80, precision = 0.97, F1-score = 0.87 and ROC AUC = 0.94. The classifier also performed robustly on the external test set (accuracy = 91%, recall = 0.73, precision = 0.93, F1-score = 0.82 and ROC AUC = 0.91). These results were benchmarked against a reference inter-expert accuracy of 86%.

CONCLUSIONS

Deep learning shows potential to automate quality control of late gadolinium imaging in CMR. The ability to identify short-axis images with intermediate LGE likelihood in real-time may serve as a useful decision support tool. This approach has the potential to guide immediate further imaging while the patient is still in the scanner, thereby reducing the frequency of recalls and inconclusive reports due to diagnostic indecision.

APOE ε4 carriage associates with improved myocardial performance from adolescence to older age

BACKGROUND

Although APOE ε4 allele carriage confers a risk for coronary artery disease, its persistence in humans might be explained by certain survival advantages (antagonistic pleiotropy).

METHODS

Combining data from ~ 37,000 persons from three older age British cohorts (1946 National Survey of Health and Development [NSHD], Southall and Brent Revised [SABRE], and UK Biobank) and one younger age cohort (Avon Longitudinal Study of Parents and Children [ALSPAC]), we explored whether APOE ε4 carriage associates with beneficial or unfavorable left ventricular (LV) structural and functional metrics by echocardiography and cardiovascular magnetic resonance (CMR).

RESULTS

Compared to the non-APOE ε4 group, APOE ε4 carriers had similar cardiac phenotypes in terms of LV ejection fraction, E/e', posterior wall and interventricular septal thickness, and LV mass. However, they had improved myocardial performance resulting in greater LV stroke volume generation per 1 mL of myocardium (higher myocardial contraction fraction). In NSHD (n = 1467) and SABRE (n = 1187), ε4 carriers had a 4% higher MCF (95% CI 1-7%, p = 0.016) using echocardiography. Using CMR data, in UK Biobank (n = 32,972), ε4 carriers had a 1% higher MCF 95% (CI 0-1%, p = 0.020) with a dose-response relationship based on the number of ε4 alleles. In addition, UK Biobank ε4 carriers also had more favorable radial and longitudinal strain rates compared to non APOE ε4 carriers. In ALSPAC (n = 1397), APOE ε4 carriers aged < 24 years had a 2% higher MCF (95% CI 0-5%, p = 0.059).

CONCLUSIONS

By triangulating results in four independent cohorts, across imaging modalities (echocardiography and CMR), and in ~ 37,000 individuals, our results point towards an association between ε4 carriage and improved cardiac performance in terms of LV MCF. This potentially favorable cardiac phenotype adds to the growing number of reported survival advantages attributed to the pleiotropic effects APOE ε4 carriage that might collectively explain its persistence in human populations.

Electrophysiological Characterization of Subclinical and Overt Hypertrophic Cardiomyopathy by Magnetic Resonance Imaging-Guided Electrocardiography

BACKGROUND

Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)-guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties.

OBJECTIVES

The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]-), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G-LVH+) and structural phenotype.

METHODS

This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH-, 104 LVH+ (51 G+/53 G-), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH- from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia.

RESULTS

Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P < 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P < 0.05), and G+LVH+ had more fractionation than G-LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]).

CONCLUSIONS

In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status.

The effect of CTCA guided selective invasive graft assessment on coronary angiographic parameters and outcomes: Insights from the BYPASS-CTCA trial

BACKGROUND

Computed tomography cardiac angiography (CTCA) is recommended for the evaluation of patients with prior coronary artery bypass graft (CABG) surgery. The BYPASS-CTCA study demonstrated that CTCA prior to invasive coronary angiography (ICA) in CABG patients leads to significant reductions in procedure time and contrast-induced nephropathy (CIN), alongside improved patient satisfaction. However, whether CTCA information was used to facilitate selective graft cannulation at ICA was not protocol mandated. In this post-hoc analysis we investigated the influence of CTCA facilitated selective graft assessment on angiographic parameters and study endpoints.

METHODS

BYPASS-CTCA was a randomized controlled trial in which patients with previous CABG referred for ICA were randomized to undergo CTCA prior to ICA, or ICA alone. In this post-hoc analysis we assessed the impact of selective ICA (grafts not invasively cannulated based on the CTCA result) following CTCA versus non-selective ICA (imaging all grafts irrespective of CTCA findings). The primary endpoints were ICA procedural duration, incidence of CIN, and patient satisfaction post-ICA. Secondary endpoints included the incidence of procedural complications and 1-year major adverse cardiac events.

RESULTS

In the CTCA cohort (n ​= ​343), 214 (62.4%) patients had selective coronary angiography performed, whereas 129 (37.6%) patients had non-selective ICA. Procedure times were significantly reduced in the selective CTCA ​+ ​ICA group compared to the non-selective CTCA ​+ ​ICA group (-5.82min, 95% CI -7.99 to -3.65, p ​< ​0.001) along with reduction of CIN (1.5% vs 5.8%, OR 0.26, 95% CI 0.10 to 0.98). No difference was seen in patient satisfaction with the ICA, however procedural complications (0.9% vs 4.7%, OR 0.21, 95% CI 0.09-0.87) and 1-year major adverse cardiac events (13.1% vs 20.9%, HR 0.55, 95% CI 0.32-0.96) were significantly lower in the selective group.

CONCLUSIONS

In patients with prior CABG, CTCA guided selective angiographic assessment of bypass grafts is associated with improved procedural parameters, lower complication rates and better 12-month outcomes. Taken in addition to the main findings of the BYPASS-CTCA trial, these results suggest a synergistic approach between CTCA and ICA should be considered in this patient group.

REGISTRATION

ClinicalTrials.gov, NCT03736018.

Efficacy of human experts and an automated segmentation algorithm in quantifying disease pathology in coronary computed tomography angiography: A head-to-head comparison with intravascular ultrasound imaging

BACKGROUND

Coronary computed tomography angiography (CCTA) analysis is currently performed by experts and is a laborious process. Fully automated edge-detection methods have been developed to expedite CCTA segmentation however their use is limited as there are concerns about their accuracy. This study aims to compare the performance of an automated CCTA analysis software and the experts using near-infrared spectroscopy-intravascular ultrasound imaging (NIRS-IVUS) as a reference standard.

METHODS

Fifty-one participants (150 vessels) with chronic coronary syndrome who underwent CCTA and 3-vessel NIRS-IVUS were included. CCTA analysis was performed by an expert and an automated edge detection method and their estimations were compared to NIRS-IVUS at a segment-, lesion-, and frame-level.

RESULTS

Segment-level analysis demonstrated a similar performance of the two CCTA analyses (conventional and automatic) with large biases and limits of agreement compared to NIRS-IVUS estimations for the total atheroma (ICC: 0.55 vs 0.25, mean difference:192 (-102-487) vs 243 (-132-617) and percent atheroma volume (ICC: 0.30 vs 0.12, mean difference: 12.8 (-5.91-31.6) vs 20.0 (0.79-39.2). Lesion-level analysis showed that the experts were able to detect more accurately lesions than the automated method (68.2 ​% and 60.7 ​%) however both analyses had poor reliability in assessing the minimal lumen area (ICC 0.44 vs 0.36) and the maximum plaque burden (ICC 0.33 vs 0.33) when NIRS-IVUS was used as the reference standard.

CONCLUSIONS

Conventional and automated CCTA analyses had similar performance in assessing coronary artery pathology using NIRS-IVUS as a reference standard. Therefore, automated segmentation can be used to expedite CCTA analysis and enhance its applications in clinical practice.

Meta-Analysis of Penetrance and Systematic Review on Transition to Disease in Genetic Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is characterized by unexplained left ventricular hypertrophy and is classically caused by pathogenic or likely pathogenic variants (P/LP) in genes encoding sarcomere proteins. Not all subclinical variant carriers will manifest clinically overt disease because penetrance (proportion of sarcomere or sarcomere-related P/LP variant carriers who develop disease) is variable, age dependent, and not reliably predicted.

METHODS

A systematic search of the literature was performed. We used random-effects generalized linear mixed model meta-analyses to contrast the cross-sectional prevalence and penetrance of sarcomere or sarcomere-related genes in 2 different contexts: clinically-based studies on patients and families with HCM versus population or community-based studies. Longitudinal family/clinical studies were additionally analyzed to investigate the rate of phenotypic conversion from subclinical to overt HCM during follow-up.

RESULTS

In total, 455 full-text manuscripts and articles were assessed. In family/clinical studies, the prevalence of sarcomere variants in patients diagnosed with HCM was 34%. The penetrance across all genes in nonproband relatives carrying P/LP variants identified during cascade screening was 57% (95% CI, 52%-63%), and the mean age at HCM diagnosis was 38 years (95% CI, 36%-40%). Penetrance varied from ≈32% for MYL3 (myosin light chain 3) to ≈55% for MYBPC3 (myosin-binding protein C3), ≈60% for TNNT2 (troponin T2) and TNNI3 (troponin I3), and ≈65% for MYH7 (myosin heavy chain 7). Population-based genetic studies demonstrate that P/LP sarcomere variants are present in the background population but at a low prevalence of <1%. The penetrance of HCM in incidentally identified P/LP variant carriers was also substantially lower at ≈11%, ranging from 0% in Atherosclerosis Risk in Communities to 18% in UK Biobank. In longitudinal family studies, the pooled phenotypic conversion across all genes was 15% over an average of ≈8 years of follow-up, starting from a mean of ≈16 years of age. However, short-term gene-specific phenotypic conversion varied between ≈12% for MYBPC3 and ≈23% for MYH7.

CONCLUSIONS

The penetrance of P/LP variants is highly variable and influenced by currently undefined and context-dependent genetic and environmental factors. Additional longitudinal studies are needed to improve our understanding of true lifetime penetrance in families and in the community and to identify drivers of the transition from subclinical to overt HCM.

Systolic anterior motion of the anterior mitral valve leaflet begins in subclinical hypertrophic cardiomyopathy

AIMS

Anterior mitral valve leaflet (AMVL) elongation is detectable in overt and subclinical hypertrophic cardiomyopathy (HCM). We sought to investigate the dynamic motion of the aorto-mitral apparatus to understand the behaviour of the AMVL and the mechanisms of left ventricular outflow tract obstruction (LVOTO) predisposition in HCM.

METHODS AND RESULTS

Cardiovascular magnetic resonance imaging using a 1.5 Tesla scanner was performed on 36 HCM sarcomere gene mutation carriers without left ventricular hypertrophy (G+LVH-), 31 HCM patients with preserved ejection fraction carrying a pathogenic sarcomere gene mutation (G+LVH+), and 53 age-, sex-, and body surface area-matched healthy volunteers. Dynamic excursion of the aorto-mitral apparatus was assessed semi-automatically on breath-held three-chamber cine steady-state free precession images. Four pre-defined regions of interest (ROIs) were tracked: ROIPMVL: hinge point of the posterior mitral valve leaflet; ROITRIG: intertrigonal mitral annulus; ROIAMVL: AMVL tip; and ROIAAO: anterior aortic annulus. Compared with controls, normalized two-dimensional displacement-vs.-time plots in G+LVH- revealed subtle but significant systolic anterior motion (SAM) of the AMVL (P < 0.0001) and reduced longitudinal excursion of ROIAAO (P = 0.014) and ROIPMVL (P = 0.048). In overt and subclinical HCM, excursion of the ROITRIG/AMVL/PMVL was positively associated with the burden of left ventricular fibrosis (P < 0.028). As expected, SAM was observed in G+LVH+ together with reduced longitudinal excursion of ROITRIG (P = 0.049) and ROIAAO (P = 0.008).

CONCLUSION

Dyskinesia of the aorto-mitral apparatus, including SAM of the elongated AMVL, is detectable in subclinical HCM before the development of LVH or left atrial enlargement. These data have the potential to improve our understanding of early phenotype development and LVOTO predisposition in HCM.

Prognostic utility and characterization of left ventricular hypertrophy using global thickness

Cardiovascular magnetic resonance (CMR) can accurately measure left ventricular (LV) mass, and several measures related to LV wall thickness exist. We hypothesized that prognosis can be used to select an optimal measure of wall thickness for characterizing LV hypertrophy. Subjects having undergone CMR were studied (cardiac patients, n = 2543; healthy volunteers, n = 100). A new measure, global wall thickness (GT, GTI if indexed to body surface area) was accurately calculated from LV mass and end-diastolic volume. Among patients with follow-up (n = 1575, median follow-up 5.4 years), the most predictive measure of death or hospitalization for heart failure was LV mass index (LVMI) (hazard ratio (HR)[95% confidence interval] 1.16[1.12-1.20], p < 0.001), followed by GTI (HR 1.14[1.09-1.19], p < 0.001). Among patients with normal findings (n = 326, median follow-up 5.8 years), the most predictive measure was GT (HR 1.62[1.35-1.94], p < 0.001). GT and LVMI could characterize patients as having a normal LV mass and wall thickness, concentric remodeling, concentric hypertrophy, or eccentric hypertrophy, and the three abnormal groups had worse prognosis than the normal group (p < 0.05 for all). LV mass is highly prognostic when mass is elevated, but GT is easily and accurately calculated, and adds value and discrimination amongst those with normal LV mass (early disease).

Clinical utilisation of implantable loop recorders in adults with Fabry disease-a multi-centre snapshot study

Fabry disease (FD) is an X-linked deficiency of alpha-galactosidase-A, leading to lysosomal storage of sphingolipids in multiple organs. Myocardial accumulation contributes to arrhythmia and sudden death, the most common cause of FD mortality. Therefore, there is a need for risk stratification and prediction to target device therapy. Implantable loop recorders (ILRs) allow for continual rhythm monitoring for up to 3 years. Here, we performed a retrospective study to evaluate current ILR utilisation in FD and quantify the burden of arrhythmia that was detected, which resulted in a modification of therapy. This was a snapshot assessment of 915 patients with FD across three specialist centres in England during the period between 1 January 2000 and 1 September 2022. In total, 22 (2.4%) patients underwent clinically indicated ILR implantation. The mean implantation age was 50 years and 13 (59%) patients were female. Following implantation, nine (41%) patients underwent arrhythmia detection, requiring intervention (six on ILR and three post-ILR battery depletion). Three patients experienced sustained atrial high-rate episodes and were started on anticoagulation. Three had non-sustained tachyarrhythmia and were started on beta blockers. Post-ILR battery depletion, one suffered complete heart block and two had sustained ventricular tachycardia, all requiring device therapy. Those with arrhythmia had a shorter PR interval on electrocardiography. This study demonstrates that ILR implantation in FD uncovers a high burden of arrhythmia. ILRs are likely to be underutilised in this pro-arrhythmic cohort, perhaps restricted to those with advanced FD cardiomyopathy. Following battery depletion in three patients as mentioned above, greater vigilance and arrhythmia surveillance are advised for those experiencing major arrhythmic events post-ILR monitoring. Further work is required to establish who would benefit most from implantation.

Technical development and feasibility of a reusable vest to integrate cardiovascular magnetic resonance with electrocardiographic imaging

BACKGROUND

Electrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo.

METHODS

CMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests.

RESULTS

77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively).

CONCLUSION

Our high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification.

CLINICAL TRIAL REGISTRATION

Title: Multimorbidity Life-Course Approach to Myocardial Health-A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1.

Computed Tomography Cardiac Angiography Before Invasive Coronary Angiography in Patients With Previous Bypass Surgery: The BYPASS-CTCA Trial

BACKGROUND

Patients with previous coronary artery bypass grafting often require invasive coronary angiography (ICA). However, for these patients, the procedure is technically more challenging and has a higher risk of complications. Observational studies suggest that computed tomography cardiac angiography (CTCA) may facilitate ICA in this group, but this has not been tested in a randomized controlled trial.

METHODS

This study was a single-center, open-label randomized controlled trial assessing the benefit of adjunctive CTCA in patients with previous coronary artery bypass grafting referred for ICA. Patients were randomized 1:1 to undergo CTCA before ICA or ICA alone. The co-primary end points were procedural duration of the ICA (defined as the interval between local anesthesia administration for obtaining vascular access and removal of the last catheter), patient satisfaction after ICA using a validated questionnaire, and the incidence of contrast-induced nephropathy. Linear regression was used for procedural duration and patient satisfaction score; contrast-induced nephropathy was analyzed using logistic regression. We applied the Bonferroni correction, with P<0.017 considered significant and 98.33% CIs presented. Secondary end points included incidence of procedural complications and 1-year major adverse cardiac events.

RESULTS

Over 3 years, 688 patients were randomized with a median follow-up of 1.0 years. The mean age was 69.8±10.4 years, 108 (15.7%) were women, 402 (58.4%) were White, and there was a high burden of comorbidity (85.3% hypertension and 53.8% diabetes). The median time from coronary artery bypass grafting to angiography was 12.0 years, and there were a median of 3 (interquartile range, 2 to 3) grafts per participant. Procedure duration of the ICA was significantly shorter in the CTCA+ICA group (CTCA+ICA, 18.6±9.5 minutes versus ICA alone, 39.5±16.9 minutes [98.33% CI, -23.5 to -18.4]; P<0.001), alongside improved mean ICA satisfaction scores (1=very good to 5=very poor; -1.1 difference [98.33% CI, -1.2 to -0.9]; P<0.001), and reduced incidence of contrast-induced nephropathy (3.4% versus 27.9%; odds ratio, 0.09 [98.33% CI, 0.04-0.2]; P<0.001). Procedural complications (2.3% versus 10.8%; odds ratio, 0.2 [95% CI, 0.1-0.4]; P<0.001) and 1-year major adverse cardiac events (16.0% versus 29.4%; hazard ratio, 0.4 [95% CI, 0.3-0.6]; P<0.001) were also lower in the CTCA+ICA group.

CONCLUSIONS

For patients with previous coronary artery bypass grafting, CTCA before ICA leads to reductions in procedure time and contrast-induced nephropathy, with improved patient satisfaction. CTCA before ICA should be considered in this group of patients.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03736018.

Accelerated DNA methylation age plays a role in the impact of cardiovascular risk factors on the human heart

BACKGROUND

DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and cardiac aging, respectively. We aimed to explore the relationships between DNAm age and A-ECG heart age and to understand the extent to which DNAm AgeAccel relates to cardiovascular (CV) risk factors in a British birth cohort from 1946.

RESULTS

We studied four DNAm ages (AgeHannum, AgeHorvath, PhenoAge, and GrimAge) and their corresponding AgeAccel. Outcomes were the results from two publicly available ECG-based cardiac age scores: the Bayesian A-ECG-based heart age score of Lindow et al. 2022 and the deep neural network (DNN) ECG-based heart age score of Ribeiro et al. 2020. DNAm AgeAccel was also studied relative to results from two logistic regression-based A-ECG disease scores, one for left ventricular (LV) systolic dysfunction (LVSD), and one for LV electrical remodeling (LVER). Generalized linear models were used to explore the extent to which any associations between biological cardiometabolic risk factors (body mass index, hypertension, diabetes, high cholesterol, previous cardiovascular disease [CVD], and any CV risk factor) and the ECG-based outcomes are mediated by DNAm AgeAccel. We derived the total effects, average causal mediation effects (ACMEs), average direct effects (ADEs), and the proportion mediated [PM] with their 95% confidence intervals [CIs]. 498 participants (all 60-64 years) were included, with the youngest ECG heart age being 27 and the oldest 90. When exploring the associations between cardiometabolic risk factors and Bayesian A-ECG cardiac age, AgeAccelPheno appears to be a partial mediator, as ACME was 0.23 years [0.01, 0.52] p = 0.028 (i.e., PM≈18%) for diabetes, 0.34 [0.03, 0.74] p = 0.024 (i.e., PM≈15%) for high cholesterol, and 0.34 [0.03, 0.74] p = 0.024 (PM≈15%) for any CV risk factor. Similarly, AgeAccelGrim mediates ≈30% of the relationship between diabetes or high cholesterol and the DNN ECG-based heart age. When exploring the link between cardiometabolic risk factors and the A-ECG-based LVSD and LVER scores, it appears that AgeAccelPheno or AgeAccelGrim mediate 10-40% of these associations.

CONCLUSION

By the age of 60, participants with accelerated DNA methylation appear to have older, weaker, and more electrically impaired hearts. We show that the harmful effects of CV risk factors on cardiac age and health, appear to be partially mediated by DNAm AgeAccelPheno and AgeAccelGrim. This highlights the need to further investigate the potential cardioprotective effects of selective DNA methyltransferases modulators.

The atrial and ventricular myocardial proteome of end-stage lamin heart disease

Lamins A/C (encoded by LMNA gene) can lead to dilated cardiomyopathy (DCM). This pilot study sought to explore the postgenomic phenotype of end-stage lamin heart disease. Consecutive patients with end-stage lamin heart disease (LMNA-group, n = 7) and ischaemic DCM (ICM-group, n = 7) undergoing heart transplantation were prospectively enrolled. Samples were obtained from left atrium (LA), left ventricle (LV), right atrium (RA), right ventricle (RV) and interventricular septum (IVS), avoiding the infarcted myocardial segments in the ICM-group. Samples were analysed using a discovery 'shotgun' proteomics approach. We found that 990 proteins were differentially abundant between LMNA and ICM samples with the LA being most perturbed (16-fold more than the LV). Abundance of lamin A/C protein was reduced, but lamin B increased in LMNA LA/RA tissue compared to ICM, but not in LV/RV. Carbonic anhydrase 3 (CA3) was over-abundant across all LMNA tissue samples (LA, LV, RA, RV, and IVS) when compared to ICM. Transthyretin was more abundant in the LV/RV of LMNA compared to ICM, while sarcomeric proteins such as titin and cardiac alpha-cardiac myosin heavy chain were generally less abundant in RA/LA of LMNA. Protein expression profiling and enrichment analysis pointed towards sarcopenia, extracellular matrix remodeling, deficient myocardial energetics, redox imbalances, and abnormal calcium handling in LMNA samples. Compared to ICM, end-stage lamin heart disease is a biventricular but especially a biatrial disease appearing to have an abundance of lamin B, CA3 and transthyretin, potentially hinting to compensatory responses.

Improved Diagnostic Criteria for Apical Hypertrophic Cardiomyopathy

BACKGROUND

There is no acceptable maximum wall thickness (MWT) threshold for diagnosing apical hypertrophic cardiomyopathy (ApHCM), with guidelines referring to ≥15 mm MWT for all hypertrophic cardiomyopathy subtypes. A normal myocardium naturally tapers apically; a fixed diagnostic threshold fails to account for this. Using cardiac magnetic resonance, "relative" ApHCM has been described with typical electrocardiographic features, loss of apical tapering, and cavity obliteration but also with MWT <15 mm.

OBJECTIVES

The authors aimed to define normal apical wall thickness thresholds in healthy subjects and use these to accurately identify ApHCM.

METHODS

The following healthy subjects were recruited: healthy UK Biobank imaging substudy subjects (n = 4,112) and an independent healthy volunteer group (n = 489). A clinically defined disease population of 104 ApHCM subjects was enrolled, with 72 overt (MWT ≥15 mm) and 32 relative (MWT <15 mm but typical electrocardiographic/imaging findings) ApHCM subjects. Cardiac magnetic resonance-derived MWT was measured in 16 segments using a published clinically validated machine learning algorithm. Segmental normal reference ranges were created and indexed (for age, sex, and body surface area), and diagnostic performance was assessed.

RESULTS

In healthy cohorts, there was no clinically significant age-related difference for apical wall thickness. There were sex-related differences, but these were not clinically significant after indexing to body surface area. Therefore, segmental reference ranges for apical hypertrophy required indexing to body surface area only (not age or sex). The upper limit of normal (the largest of the 4 apical segments measured) corresponded to a maximum apical MWT in healthy subjects of 5.2 to 5.6 mm/m2 with an accuracy of 0.94 (the unindexed equivalent being 11 mm). This threshold was categorized as abnormal in 99% (71/72) of overt ApHCM patients, 78% (25/32) of relative ApHCM patients, 3% (122/4,112) of UK Biobank subjects, and 3% (13/489) of healthy volunteers.

CONCLUSIONS

Per-segment indexed apical wall thickness thresholds are highly accurate for detecting apical hypertrophy, providing confidence to the reader to diagnose ApHCM in those not reaching current internationally recognized criteria.

Microstructural and Microvascular Phenotype of Sarcomere Mutation Carriers and Overt Hypertrophic Cardiomyopathy

BACKGROUND

In hypertrophic cardiomyopathy (HCM), myocyte disarray and microvascular disease (MVD) have been implicated in adverse events, and recent evidence suggests that these may occur early. As novel therapy provides promise for disease modification, detection of phenotype development is an emerging priority. To evaluate their utility as early and disease-specific biomarkers, we measured myocardial microstructure and MVD in 3 HCM groups-overt, either genotype-positive (G+LVH+) or genotype-negative (G-LVH+), and subclinical (G+LVH-) HCM-exploring relationships with electrical changes and genetic substrate.

METHODS

This was a multicenter collaboration to study 206 subjects: 101 patients with overt HCM (51 G+LVH+ and 50 G-LVH+), 77 patients with G+LVH-, and 28 matched healthy volunteers. All underwent 12-lead ECG, quantitative perfusion cardiac magnetic resonance imaging (measuring myocardial blood flow, myocardial perfusion reserve, and perfusion defects), and cardiac diffusion tensor imaging measuring fractional anisotropy (lower values expected with more disarray), mean diffusivity (reflecting myocyte packing/interstitial expansion), and second eigenvector angle (measuring sheetlet orientation).

RESULTS

Compared with healthy volunteers, patients with overt HCM had evidence of altered microstructure (lower fractional anisotropy, higher mean diffusivity, and higher second eigenvector angle; all P<0.001) and MVD (lower stress myocardial blood flow and myocardial perfusion reserve; both P<0.001). Patients with G-LVH+ were similar to those with G+LVH+ but had elevated second eigenvector angle (P<0.001 after adjustment for left ventricular hypertrophy and fibrosis). In overt disease, perfusion defects were found in all G+ but not all G- patients (100% [51/51] versus 82% [41/50]; P=0.001). Patients with G+LVH- compared with healthy volunteers similarly had altered microstructure, although to a lesser extent (all diffusion tensor imaging parameters; P<0.001), and MVD (reduced stress myocardial blood flow [P=0.015] with perfusion defects in 28% versus 0 healthy volunteers [P=0.002]). Disarray and MVD were independently associated with pathological electrocardiographic abnormalities in both overt and subclinical disease after adjustment for fibrosis and left ventricular hypertrophy (overt: fractional anisotropy: odds ratio for an abnormal ECG, 3.3, P=0.01; stress myocardial blood flow: odds ratio, 2.8, P=0.015; subclinical: fractional anisotropy odds ratio, 4.0, P=0.001; myocardial perfusion reserve odds ratio, 2.2, P=0.049).

CONCLUSIONS

Microstructural alteration and MVD occur in overt HCM and are different in G+ and G- patients. Both also occur in the absence of hypertrophy in sarcomeric mutation carriers, in whom changes are associated with electrocardiographic abnormalities. Measurable changes in myocardial microstructure and microvascular function are early-phenotype biomarkers in the emerging era of disease-modifying therapy.

Novel near-infrared spectroscopy-intravascular ultrasound-based deep-learning methodology for accurate coronary computed tomography plaque quantification and characterization

Aims

Coronary computed tomography angiography (CCTA) is inferior to intravascular imaging in detecting plaque morphology and quantifying plaque burden. We aim to, for the first time, train a deep-learning (DL) methodology for accurate plaque quantification and characterization in CCTA using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS).

Methods and results

Seventy patients were prospectively recruited who underwent CCTA and NIRS-IVUS imaging. Corresponding cross sections were matched using an in-house developed software, and the estimations of NIRS-IVUS for the lumen, vessel wall borders, and plaque composition were used to train a convolutional neural network in 138 vessels. The performance was evaluated in 48 vessels and compared against the estimations of NIRS-IVUS and the conventional CCTA expert analysis. Sixty-four patients (186 vessels, 22 012 matched cross sections) were included. Deep-learning methodology provided estimations that were closer to NIRS-IVUS compared with the conventional approach for the total atheroma volume (ΔDL-NIRS-IVUS: -37.8 ± 89.0 vs. ΔConv-NIRS-IVUS: 243.3 ± 183.7 mm3, variance ratio: 4.262, P < 0.001) and percentage atheroma volume (-3.34 ± 5.77 vs. 17.20 ± 7.20%, variance ratio: 1.578, P < 0.001). The DL methodology detected lesions more accurately than the conventional approach (Area under the curve (AUC): 0.77 vs. 0.67, P < 0.001) and quantified minimum lumen area (ΔDL-NIRS-IVUS: -0.35 ± 1.81 vs. ΔConv-NIRS-IVUS: 1.37 ± 2.32 mm2, variance ratio: 1.634, P < 0.001), maximum plaque burden (4.33 ± 11.83% vs. 5.77 ± 16.58%, variance ratio: 2.071, P = 0.004), and calcific burden (-51.2 ± 115.1 vs. -54.3 ± 144.4, variance ratio: 2.308, P < 0.001) more accurately than conventional approach. The DL methodology was able to segment a vessel on CCTA in 0.3 s.

Conclusions

The DL methodology developed for CCTA analysis from co-registered NIRS-IVUS and CCTA data enables rapid and accurate assessment of lesion morphology and is superior to expert analysts (Clinicaltrials.gov: NCT03556644).

Persistent symptoms after COVID-19 are not associated with differential SARS-CoV-2 antibody or T cell immunity

Among the unknowns in decoding the pathogenesis of SARS-CoV-2 persistent symptoms in Long Covid is whether there is a contributory role of abnormal immunity during acute infection. It has been proposed that Long Covid is a consequence of either an excessive or inadequate initial immune response. Here, we analyze SARS-CoV-2 humoral and cellular immunity in 86 healthcare workers with laboratory confirmed mild or asymptomatic SARS-CoV-2 infection during the first wave. Symptom questionnaires allow stratification into those with persistent symptoms and those without for comparison. During the period up to 18-weeks post-infection, we observe no difference in antibody responses to spike RBD or nucleoprotein, virus neutralization, or T cell responses. Also, there is no difference in the profile of antibody waning. Analysis at 1-year, after two vaccine doses, comparing those with persistent symptoms to those without, again shows similar SARS-CoV-2 immunity. Thus, quantitative differences in these measured parameters of SARS-CoV-2 adaptive immunity following mild or asymptomatic acute infection are unlikely to have contributed to Long Covid causality. ClinicalTrials.gov (NCT04318314).

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.

Sex- and age-specific normal values for automated quantitative pixel-wise myocardial perfusion cardiovascular magnetic resonance

AIMS

Recently developed in-line automated cardiovascular magnetic resonance (CMR) myocardial perfusion mapping has been shown to be reproducible and comparable with positron emission tomography (PET), and can be easily integrated into clinical workflows. Bringing quantitative myocardial perfusion CMR into routine clinical care requires knowledge of sex- and age-specific normal values in order to define thresholds for disease detection. This study aimed to establish sex- and age-specific normal values for stress and rest CMR myocardial blood flow (MBF) in healthy volunteers.

METHODS AND RESULTS

A total of 151 healthy volunteers recruited from two centres underwent adenosine stress and rest myocardial perfusion CMR. In-line automatic reconstruction and post processing of perfusion data were implemented within the Gadgetron software framework, creating pixel-wise perfusion maps. Rest and stress MBF were measured, deriving myocardial perfusion reserve (MPR) and were subdivided by sex and age. Mean MBF in all subjects was 0.62 ± 0.13 mL/g/min at rest and 2.24 ± 0.53 mL/g/min during stress. Mean MPR was 3.74 ± 1.00. Compared with males, females had higher rest (0.69 ± 0.13 vs. 0.58 ± 0.12 mL/g/min, P < 0.01) and stress MBF (2.41 ± 0.47 vs. 2.13 ± 0.54 mL/g/min, P = 0.001). Stress MBF and MPR showed significant negative correlations with increasing age (r = -0.43, P < 0.001 and r = -0.34, P < 0.001, respectively).

CONCLUSION

Fully automated in-line CMR myocardial perfusion mapping produces similar normal values to the published CMR and PET literature. There is a significant increase in rest and stress MBF, but not MPR, in females and a reduction of stress MBF and MPR with advancing age, advocating the use of sex- and age-specific reference ranges for diagnostic use.

Developing a medical device-grade T2 phantom optimized for myocardial T2 mapping by cardiovascular magnetic resonance

INTRODUCTION

A long T2 relaxation time can reflect oedema, and myocardial inflammation when combined with increased plasma troponin levels. Cardiovascular magnetic resonance (CMR) T2 mapping therefore has potential to provide a key diagnostic and prognostic biomarkers. However, T2 varies by scanner, software, and sequence, highlighting the need for standardization and for a quality assurance system for T2 mapping in CMR.

AIM

To fabricate and assess a phantom dedicated to the quality assurance of T2 mapping in CMR.

METHOD

A T2 mapping phantom was manufactured to contain 9 T1 and T2 (T1|T2) tubes to mimic clinically relevant native and post-contrast T2 in myocardium across the health to inflammation spectrum (i.e., 43-74 ms) and across both field strengths (1.5 and 3 T). We evaluated the phantom's structural integrity, B0 and B1 uniformity using field maps, and temperature dependence. Baseline reference T1|T2 were measured using inversion recovery gradient echo and single-echo spin echo (SE) sequences respectively, both with long repetition times (10 s). Long-term reproducibility of T1|T2 was determined by repeated T1|T2 mapping of the phantom at baseline and at 12 months.

RESULTS

The phantom embodies 9 internal agarose-containing T1|T2 tubes doped with nickel di-chloride (NiCl2) as the paramagnetic relaxation modifier to cover the clinically relevant spectrum of myocardial T2. The tubes are surrounded by an agarose-gel matrix which is doped with NiCl2 and packed with high-density polyethylene (HDPE) beads. All tubes at both field strengths, showed measurement errors up to ≤ 7.2 ms [< 14.7%] for estimated T2 by balanced steady-state free precession T2 mapping compared to reference SE T2 with the exception of the post-contrast tube of ultra-low T1 where the deviance was up to 16 ms [40.0%]. At 12 months, the phantom remained free of air bubbles, susceptibility, and off-resonance artifacts. The inclusion of HDPE beads effectively flattened the B0 and B1 magnetic fields in the imaged slice. Independent temperature dependency experiments over the 13-38 °C range confirmed the greater stability of shorter vs longer T1|T2 tubes. Excellent long-term (12-month) reproducibility of measured T1|T2 was demonstrated across both field strengths (all coefficients of variation < 1.38%).

CONCLUSION

The T2 mapping phantom demonstrates excellent structural integrity, B0 and B1 uniformity, and reproducibility of its internal tube T1|T2 out to 1 year. This device may now be mass-produced to support the quality assurance of T2 mapping in CMR.

Increased cardiac involvement in Fabry disease using blood-corrected native T1 mapping

Fabry disease (FD) is a rare lysosomal storage disorder resulting in myocardial sphingolipid accumulation which is detectable by cardiovascular magnetic resonance as low native T1. However, myocardial T1 contains signal from intramyocardial blood which affects variability and consequently measurement precision and accuracy. Correction of myocardial T1 by blood T1 increases precision. We therefore deployed a multicenter study of FD patients (n = 218) and healthy controls (n = 117) to investigate if blood-correction of myocardial native T1 increases the number of FD patients with low T1, and thus reclassifies FD patients as having cardiac involvement. Cardiac involvement was defined as a native T1 value 2 standard deviations below site-specific means in healthy controls for both corrected and uncorrected measures. Overall low T1 was 135/218 (62%) uncorrected vs. 145/218 (67%) corrected (p = 0.02). With blood-correction, 13/83 previously normal patients were reclassified to low T1. This reclassification appears clinically relevant as 6/13 (46%) of reclassified had focal late gadolinium enhancement or left ventricular hypertrophy as signs of cardiac involvement. Blood-correction of myocardial native T1 increases the proportion of FD subjects with low myocardial T1, with blood-corrected results tracking other markers of cardiac involvement. Blood-correction may potentially offer earlier detection and therapy initiation, but merits further prospective studies.

Apical Ischemia Is a Universal Feature of Apical Hypertrophic Cardiomyopathy

BACKGROUND

Apical hypertrophic cardiomyopathy (ApHCM) accounts for ≈10% of hypertrophic cardiomyopathy cases and is characterized by apical hypertrophy, apical cavity obliteration, and tall ECG R waves with ischemic-looking deep T-wave inversion. These may be present even with <15 mm apical hypertrophy (relative ApHCM). Microvascular dysfunction is well described in hypertrophic cardiomyopathy. We hypothesized that apical perfusion defects would be common in ApHCM.

METHODS

A 2-center study using cardiovascular magnetic resonance short- and long-axis quantitative adenosine vasodilator stress perfusion mapping. One hundred patients with ApHCM (68 overt hypertrophy [≥15 mm] and 32 relative ApHCM) were compared with 50 patients with asymmetrical septal hypertrophy hypertrophic cardiomyopathy and 40 healthy volunteer controls. Perfusion was assessed visually and quantitatively as myocardial blood flow and myocardial perfusion reserve.

RESULTS

Apical perfusion defects were present in all overt ApHCM patients (100%), all relative ApHCM patients (100%), 36% of asymmetrical septal hypertrophy hypertrophic cardiomyopathy, and 0% of healthy volunteers (P<0.001). In 10% of patients with ApHCM, perfusion defects were sufficiently apical that conventional short-axis views missed them. In 29%, stress myocardial blood flow fell below rest values. Stress myocardial blood flow was most impaired subendocardially, with greater hypertrophy or scar, and with apical aneurysms. Impaired apical myocardial blood flow was most strongly predicted by thicker apical segments (β-coefficient, -0.031 mL/g per min [CI, -0.06 to -0.01]; P=0.013), higher ejection fraction (-0.025 mL/g per min [CI, -0.04 to -0.01]; P<0.005), and ECG maximum R-wave height (-0.023 mL/g per min [CI, -0.04 to -0.01]; P<0.005).

CONCLUSIONS

Apical perfusion defects are universally present in ApHCM at all stages. Its ubiquitous presence along with characteristic ECG suggests ischemia may play a disease-defining role in ApHCM.

Evaluating semi-supervision methods for medical image segmentation: applications in cardiac magnetic resonance imaging

Purpose

Neural networks have potential to automate medical image segmentation but require expensive labeling efforts. While methods have been proposed to reduce the labeling burden, most have not been thoroughly evaluated on large, clinical datasets or clinical tasks. We propose a method to train segmentation networks with limited labeled data and focus on thorough network evaluation.

Approach

We propose a semi-supervised method that leverages data augmentation, consistency regularization, and pseudolabeling and train four cardiac magnetic resonance (MR) segmentation networks. We evaluate the models on multiinstitutional, multiscanner, multidisease cardiac MR datasets using five cardiac functional biomarkers, which are compared to an expert's measurements using Lin's concordance correlation coefficient (CCC), the within-subject coefficient of variation (CV), and the Dice coefficient.

Results

The semi-supervised networks achieve strong agreement using Lin's CCC ( > 0.8 ), CV similar to an expert, and strong generalization performance. We compare the error modes of the semi-supervised networks against fully supervised networks. We evaluate semi-supervised model performance as a function of labeled training data and with different types of model supervision, showing that a model trained with 100 labeled image slices can achieve a Dice coefficient within 1.10% of a network trained with 16,000+ labeled image slices.

Conclusion

We evaluate semi-supervision for medical image segmentation using heterogeneous datasets and clinical metrics. As methods for training models with little labeled data become more common, knowledge about how they perform on clinical tasks, how they fail, and how they perform with different amounts of labeled data is useful to model developers and users.

Strengths and weaknesses of alternative noninvasive imaging approaches for microvascular ischemia

Structural and functional abnormalities of coronary microvasculature are highly prevalent in several clinical settings and often associated with worse clinical outcomes. Therefore, there is a growing interest in the detection and treatment of this, often overlooked, disease. Coronary angiography allows the assessment of the Coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR). However, the measurement of these parameters is not always feasible because of limited technical availability and the need for a cardiac catheterization with a small but real risk of potential complications. Recent advances in non-invasive imaging techniques allow the assessment of coronary microvascular function with good accuracy and reproducibility. The objective of this review is to discuss the strengths and weaknesses of alternative non-invasive approaches used in the diagnosis of coronary microvascular dysfunction (CMD), highlighting the most recent advances for each imaging modality.

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar

BACKGROUND AND OBJECTIVES

Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent.

METHODS

DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) models based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo- and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality.

RESULTS

The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets. Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker (<1 min versus 7 ± 3 min), and required minimal user interaction.

CONCLUSIONS

Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report.

Myocardial Involvement After Hospitalization for COVID-19 Complicated by Troponin Elevation: A Prospective, Multicenter, Observational Study

BACKGROUND

Acute myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) has a poor prognosis. Its associations and pathogenesis are unclear. Our aim was to assess the presence, nature, and extent of myocardial damage in hospitalized patients with troponin elevation.

METHODS

Across 25 hospitals in the United Kingdom, 342 patients with COVID-19 and an elevated troponin level (COVID+/troponin+) were enrolled between June 2020 and March 2021 and had a magnetic resonance imaging scan within 28 days of discharge. Two prospective control groups were recruited, comprising 64 patients with COVID-19 and normal troponin levels (COVID+/troponin-) and 113 patients without COVID-19 or elevated troponin level matched by age and cardiovascular comorbidities (COVID-/comorbidity+). Regression modeling was performed to identify predictors of major adverse cardiovascular events at 12 months.

RESULTS

Of the 519 included patients, 356 (69%) were men, with a median (interquartile range) age of 61.0 years (53.8, 68.8). The frequency of any heart abnormality, defined as left or right ventricular impairment, scar, or pericardial disease, was 2-fold greater in cases (61% [207/342]) compared with controls (36% [COVID+/troponin-] versus 31% [COVID-/comorbidity+]; P<0.001 for both). More cases than controls had ventricular impairment (17.2% versus 3.1% and 7.1%) or scar (42% versus 7% and 23%; P<0.001 for both). The myocardial injury pattern was different, with cases more likely than controls to have infarction (13% versus 2% and 7%; P<0.01) or microinfarction (9% versus 0% and 1%; P<0.001), but there was no difference in nonischemic scar (13% versus 5% and 14%; P=0.10). Using the Lake Louise magnetic resonance imaging criteria, the prevalence of probable recent myocarditis was 6.7% (23/342) in cases compared with 1.7% (2/113) in controls without COVID-19 (P=0.045). During follow-up, 4 patients died and 34 experienced a subsequent major adverse cardiovascular event (10.2%), which was similar to controls (6.1%; P=0.70). Myocardial scar, but not previous COVID-19 infection or troponin, was an independent predictor of major adverse cardiovascular events (odds ratio, 2.25 [95% CI, 1.12-4.57]; P=0.02).

CONCLUSIONS

Compared with contemporary controls, patients with COVID-19 and elevated cardiac troponin level have more ventricular impairment and myocardial scar in early convalescence. However, the proportion with myocarditis was low and scar pathogenesis was diverse, including a newly described pattern of microinfarction.

REGISTRATION

URL: https://www.isrctn.com; Unique identifier: 58667920.

Implications of computed tomography reconstruction algorithms on coronary atheroma quantification: Comparison with intravascular ultrasound

BACKGROUND

Advances in coronary computed tomography angiography (CCTA) reconstruction algorithms are expected to enhance the accuracy of CCTA plaque quantification. We aim to evaluate different CCTA reconstruction approaches in assessing vessel characteristics in coronary atheroma using intravascular ultrasound (IVUS) as the reference standard.

METHODS

Matched cross-sections (n ​= ​7241) from 50 vessels in 15 participants with chronic coronary syndrome who prospectively underwent CCTA and 3-vessel near-infrared spectroscopy-IVUS were included. Twelve CCTA datasets per patient were reconstructed using two different kernels, two slice thicknesses (0.75 ​mm and 0.50 ​mm) and three different strengths of advanced model-based iterative reconstruction (IR) algorithms. Lumen and vessel wall borders were manually annotated in every IVUS and CCTA cross-section which were co-registered using dedicated software. Image quality was sub-optimal in the reconstructions with a sharper kernel, so these were excluded. Intraclass correlation coefficient (ICC) and repeatability coefficient (RC) were used to compare the estimations of the 6 CT reconstruction approaches with those derived by IVUS.

RESULTS

Segment-level analysis showed good agreement between CCTA and IVUS for assessing atheroma volume with approach 0.50/5 (slice thickness 0.50 ​mm and highest strength 5 ADMIRE IR) being the best (total atheroma volume ICC: 0.91, RC: 0.67, p ​< ​0.001 and percentage atheroma volume ICC: 0.64, RC: 14.06, p ​< ​0.001). At lesion-level, there was no difference between the CCTA reconstructions for detecting plaques (accuracy range: 0.64-0.67; p ​= ​0.23); however, approach 0.50/5 was superior in assessing IVUS-derived lesion characteristics associated with plaque vulnerability (minimum lumen area ICC: 0.64, RC: 1.31, p ​< ​0.001 and plaque burden ICC: 0.45, RC: 32.0, p ​< ​0.001).

CONCLUSION

CCTA reconstruction with thinner slice thickness, smooth kernel and highest strength advanced IR enabled more accurate quantification of the lumen and plaque at a segment-, and lesion-level analysis in coronary atheroma when validated against intravascular ultrasound.

CLINICALTRIALS

gov (NCT03556644).

Cardiovascular magnetic resonance phenotyping of heart failure with mildly reduced ejection fraction

AIMS

The 2016 European Society of Cardiology Heart Failure Guidelines defined a new category: heart failure with mid-range ejection fraction (HFmrEF) of 40-49%. This new category was highlighted as having limited evidence and research was advocated into underlying characteristics, pathophysiology, and diagnosis. We used multi-parametric cardiovascular magnetic resonance (CMR) to define the cardiac phenotype of presumed non-ischaemic HFmrEF.

METHODS AND RESULTS

Patients (N = 300, 62.7 ± 13 years, 63% males) with a clinical diagnosis of heart failure with no angina symptoms, history of myocardial infarction, or coronary intervention were prospectively recruited. Patients underwent clinical assessment and CMR including T1 mapping, extracellular volume (ECV) mapping, late gadolinium enhancement, and measurement of myocardial blood flow at rest and maximal hyperaemia. Of 273 patients in the final analysis, 93 (34%) patients were categorized as HFmrEF, 46 (17%) as heart failure with preserved ejection fraction (HFpEF), and 134 (49%) as heart failure with reduced ejection fraction (HFrEF). Nineteen (20%) patients with HFmrEF had evidence of occult ischaemic heart disease. Diffuse fibrosis and hyperaemic myocardial blood flow were similar in HFmrEF and HFpEF, but HFmrEF showed significantly lower native T1 (1311 ± 32 vs. 1340 ± 45 ms, P < 0.001), ECV (24.6 ± 3.2 vs. 26.3 ± 3.1%, P < 0.001), and higher myocardial perfusion reserve (2.75 ± 0.84 vs. 2.28 ± 0.84, P < 0.001) compared with HFrEF.

CONCLUSION

Patients with HFmrEF share most phenotypic characteristics with HFpEF, including the degree of microvascular impairment and fibrosis, but have a high prevalence of occult ischaemic heart disease similar to HFrEF. Further work is needed to confirm how the phenotype of HFmrEF responds to medical therapy.

Cardiovascular magnetic resonance in light-chain amyloidosis to guide treatment

AIMS

To assess the ability of cardiovascular magnetic resonance (CMR) to (i) measure changes in response to chemotherapy; (ii) assess the correlation between haematological response and changes in extracellular volume (ECV); and (iii) assess the association between changes in ECV and prognosis over and above existing predictors.

METHODS AND RESULTS

In total, 176 patients with cardiac AL amyloidosis were assessed using serial N-terminal pro-B-type natriuretic peptide (NT-proBNP), echocardiography, free light chains and CMR with T1 and ECV mapping at diagnosis and subsequently 6, 12, and 24 months after starting chemotherapy. Haematological response was graded as complete response (CR), very good partial response (VGPR), partial response (PR), or no response (NR). CMR response was graded by changes in ECV as progression (≥0.05 increase), stable (<0.05 change), or regression (≥0.05 decrease). At 6 months, CMR regression was observed in 3% (all CR/VGPR) and CMR progression in 32% (61% in PR/NR; 39% CR/VGPR). After 1 year, 22% had regression (all CR/VGPR), and 22% had progression (63% in PR/NR; 37% CR/VGPR). At 2 years, 38% had regression (all CR/VGPR), and 14% had progression (80% in PR/NR; 20% CR/VGPR). Thirty-six (25%) patients died during follow-up (40 ± 15 months); CMR response at 6 months predicted death (progression hazard ratio 3.82; 95% confidence interval 1.95-7.49; P < 0.001) and remained prognostic after adjusting for haematological response, NT-proBNP and longitudinal strain (P < 0.01).

CONCLUSIONS

Cardiac amyloid deposits frequently regress following chemotherapy, but only in patients who achieve CR or VGPR. Changes in ECV predict outcome after adjusting for known predictors.

Extracellular Volume Fraction by Computed Tomography Predicts Long-Term Prognosis Among Patients With Cardiac Amyloidosis

BACKGROUND

Light chain (AL) and transthyretin (ATTR) amyloid fibrils are deposited in the extracellular space of the myocardium, resulting in heart failure and premature mortality. Extracellular expansion can be quantified by computed tomography, offering a rapid, cheaper, and more practical alternative to cardiac magnetic resonance, especially among patients with cardiac devices or on renal dialysis.

OBJECTIVES

This study sought to investigate the association of extracellular volume fraction by computed tomography (ECV_CT), myocardial remodeling, and mortality in patients with systemic amyloidosis.

METHODS

Patients with confirmed systemic amyloidosis and varying degrees of cardiac involvement underwent electrocardiography-gated cardiac computed tomography. Whole heart and septal ECV_CT was analyzed. All patients also underwent clinical assessment, electrocardiography, echocardiography, serum amyloid protein component, and/or technetium-99m (^99mTc) 3,3-diphosphono-1,2-propanodicarboxylic acid scintigraphy. ECV_CT was compared across different extents of cardiac infiltration (ATTR Perugini grade/AL Mayo stage) and evaluated for its association with myocardial remodeling and all-cause mortality.

RESULTS

A total of 72 patients were studied (AL: n = 35, ATTR: n = 37; median age: 67 [IQR: 59-76] years, 70.8% male). Mean septal ECV_CT was 42.7% ± 13.1% and 55.8% ± 10.9% in AL and ATTR amyloidosis, respectively, and correlated with indexed left ventricular mass (r = 0.426; P < 0.001), left ventricular ejection fraction (r = 0.460; P < 0.001), N-terminal pro-B-type natriuretic peptide (r = 0.563; P < 0.001), and high-sensitivity troponin T (r = 0.546; P < 0.001). ECV_CT increased with cardiac amyloid involvement in both AL and ATTR amyloid. Over a mean follow-up of 5.3 ± 2.4 years, 40 deaths occurred (AL: n = 14 [35.0%]; ATTR: n = 26 [65.0%]). Septal ECV_CT was independently associated with all-cause mortality in ATTR (not AL) amyloid after adjustment for age and septal wall thickness (HR: 1.046; 95% CI: 1.003-1.090; P = 0.037).

CONCLUSIONS

Cardiac amyloid burden quantified by ECV_CT is associated with adverse cardiac remodeling as well as all-cause mortality among ATTR amyloid patients. ECV_CT may address the need for better identification and risk stratification of amyloid patients, using a widely accessible imaging modality.

Plasma proteomic signature predicts who will get persistent symptoms following SARS-CoV-2 infection

BACKGROUND

The majority of those infected by ancestral Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during the UK first wave (starting March 2020) did not require hospitalisation. Most had a short-lived mild or asymptomatic infection, while others had symptoms that persisted for weeks or months. We hypothesized that the plasma proteome at the time of first infection would reflect differences in the inflammatory response that linked to symptom severity and duration.

METHODS

We performed a nested longitudinal case-control study and targeted analysis of the plasma proteome of 156 healthcare workers (HCW) with and without lab confirmed SARS-CoV-2 infection. Targeted proteomic multiple-reaction monitoring analysis of 91 pre-selected proteins was undertaken in uninfected healthcare workers at baseline, and in infected healthcare workers serially, from 1 week prior to 6 weeks after their first confirmed SARS-CoV-2 infection. Symptom severity and antibody responses were also tracked. Questionnaires at 6 and 12 months collected data on persistent symptoms.

FINDINGS

Within this cohort (median age 39 years, interquartile range 30-47 years), 54 healthcare workers (44% male) had PCR or antibody confirmed infection, with the remaining 102 (38% male) serving as uninfected controls. Following the first confirmed SARS-CoV-2 infection, perturbation of the plasma proteome persisted for up to 6 weeks, tracking symptom severity and antibody responses. Differentially abundant proteins were mostly coordinated around lipid, atherosclerosis and cholesterol metabolism pathways, complement and coagulation cascades, autophagy, and lysosomal function. The proteomic profile at the time of seroconversion associated with persistent symptoms out to 12 months. Data are available via ProteomeXchange with identifier PXD036590.

INTERPRETATION

Our findings show that non-severe SARS-CoV-2 infection perturbs the plasma proteome for at least 6 weeks. The plasma proteomic signature at the time of seroconversion has the potential to identify which individuals are more likely to suffer from persistent symptoms related to SARS-CoV-2 infection.

FUNDING INFORMATION

The COVIDsortium is supported by funding donated by individuals, charitable Trusts, and corporations including Goldman Sachs, Citadel and Citadel Securities, The Guy Foundation, GW Pharmaceuticals, Kusuma Trust, and Jagclif Charitable Trust, and enabled by Barts Charity with support from University College London Hospitals (UCLH) Charity. This work was additionally supported by the Translational Mass Spectrometry Research Group and the Biomedical Research Center (BRC) at Great Ormond Street Hospital.

The use of attention-deficit hyperactivity disorder medications in cardiac disease

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with onset usually in childhood characterized by inattention, impulsivity, and hyperactivity causing a functional impairment. Untreated ADHD, or treatment delay is associated with adverse outcomes and poor quality of life. Although conservative management strategies such as behavioral and psychological interventions are important, pharmacological treatment has a strong evidence base with improved outcomes. ADHD medications are broadly divided into stimulant and non-stimulant medications. Stimulant medications are generally more effective than non-stimulants. Cardiovascular safety of ADHD medication has been a matter of debate for decades. Treatment guidelines advise the careful consideration of risks and benefits in people with cardiovascular diseases such as congenital heart disease or cardiomyopathy. Although stimulants can increase systemic blood pressure and heart rate, no significant associations were found between their use and serious cardiovascular events. Concerns regarding QT effects and attendant sudden cardiac death risks deter clinicians from initiating much-needed ADHD medications in patients with heart disease. This overly cautious approach is potentially depriving low-risk individuals from significant benefits associated with timely ADHD drug treatment. This review discusses the cardiovascular risks reportedly associated with ADHD medications, the evidence base for their safe usage in persons with established cardiovascular disease, and highlights future research directions.

Exercise induced coronary inflammation in masters athletes

Background

Chronic endurance exercise has been linked to increased prevalence of coronary artery disease (CAD) in male master athletes. Data are limited regarding the presence of exercise-induced coronary inflammation and its association with atherosclerosis in master endurance athletes. Human coronary inflammation can be detected non-invasively by imaging pericoronary adipose tissue (PCAT). We tested the hypothesis that chronic endurance exercise leads to increased prevalence of atherosclerosis via coronary inflammation.

Methods

Computed tomography coronary angiogram CTCA scans from 2 cohorts of master athletes and age-matched controls, without known risk factors for CAD, were analysed post-hoc and the PCAT attenuation index was calculated around the proximal right coronary artery (FAIRCA). The athletes and the healthy controls also underwent an electrocardiogram, an echocardiogram, a cardiopulmonary exercise test (CPET), a 24-hour Holter tape and a Cardiac Magnetic Resonance (CMR) scan.

Results

Scans from 243 masters endurance athletes (62% females) and 58 age and Framingham CAD risk score matched healthy controls were analysed. FAIRCA was significantly higher (less negative) in male masters athletes vs female masters athletes [−61.3 Hounsfield Units (HU) vs −62.8 HU, p=0.01], in male athletes vs male controls (−61.3 HU vs −68.6 HU, p&lt;0.001) and in female athletes vs female controls (−62,8 HU vs −67.5 HU, p=0.005). In female masters athletes, peak oxygen consumption during CPET (peak VO2) statistically significantly predicted the FAIRCA, F(1,146) = 22.62, p&lt;0.0001. There was no correlation between the FAIRCA and presence of atherosclerosis in male masters athletes.

Conclusions

Masters athletes show increased markers of coronary inflammation. This effect appears to be greater in male masters athletes and is associated with a higher peak VO2 in female masters athletes. However, we did not identify a link between coronary inflammation and coronary atherosclerosis in this cohort.

Funding Acknowledgement

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Cardiac Risk in the Young, UK

Advanced microstructural substrate detection in pre-hypertrophic HCM and its relationship to arrhythmogenesis; a hybrid CMR-ECG-Imaging study

Background

Hypertrophic cardiomyopathy is defined in three domains; clinically by unexplained hypertrophy, genetically by sarcomeric gene mutations and histologically by disarray, small vessel disease and fibrosis. Both ischaemia and myocyte disarray have been implicated in arrhythmogenesis and sudden cardiac death but whether disarray occurs before hypertrophy and its relationship to ischaemia is unknown.

Diffusion-tensor CMR, perfusion mapping & ECG Imaging (ECGI) can measure disarray, ischaemia and electrical aberrance respectively in vivo. We aimed to investigate these in genotype positive (G+) subjects without hypertrophy (LVH−) to identify further subclinical manifestations of gene expression and whether these relate to ventricular arrhythmia formation.

Methods

Diffusion-tensor CMR (3-Tesla) using a motion-compensated spin-echo sequence was acquired in 3 short-axis slices. Quantitative adenosine stress perfusion mapping was performed using standard clinical protocols. A novel ECGI vest, containing 256 unipolar electrodes acquired a 5-minute recording of body-surface potentials to quantify conduction and repolarisation dynamics intervals.

Results

ECGI/CMR was performed on 68 mutation carriers from 64 families and 24 age sex and ethnicity matched healthy controls. Of the mutation carriers, median age was 33 (24–41 years), 57% (39) were female, and 79% (54) were white. Mutations were 39 (57%) MYBPC3, 19 (28%) MYH7, 1 (1%) MYL2 and 9 (12%) were thin filament/non-sarcomeric mutations. There was no significant difference in ejection fraction or LV mass, however G+LVH− had a higher maximum wall thickness (9 (9–10) vs 8 (7–9) mm p=0.003).

Compared to healthy volunteers, G+LVH− individuals had more perfusion defects (18/64 (30%) vs 0, p=0.004), lower Fractional Anisotropy (FA) (suggestive of more disarray) (0.32±0.02 vs 0.34±0.02, p&lt;0.0001) and more prolonged Activation–Recovery Intervals (ARI, a surrogate for action potential duration (259±40 vs 240±31 ms, p=0.03).

In G+LVH−, patients with perfusion defects had more prolonged ARI (263 (248 vs 292) vs 246 (225–283) ms, p=0.03) and lower FA suggestive of more disarray (0.32±0.2 vs 0.31±0.1, p=0.04).

Conclusion

Ischaemia, myocyte disarray and electrical abnormalities occur even in the absence of hypertrophy in HCM. These abnormalities associate to form a complex a clinical phenotype.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): British Heart FoundationBarts Charity

Quantitative myocardial blood flow as a prognostic marker for cardiovascular outcomes in patients with Type 2 Diabetes Mellitus: a multicentre study

 

Introduction: Patients with Type 2 Diabetes Mellitus (T2DM) are at increased risk of cardiovascular disease, including epicardial coronary heart disease, silent myocardial infarction (MI), and coronary microvascular dysfunction (CMD) [1]. All of these can be assessed and quantified using cardiac magnetic resonance (CMR), including most recently quantitative myocardial blood flow (MBF). We aimed to determine the prognostic relevance of MBF in patients with T2DM and test the hypothesis that impaired stress MBF and myocardial perfusion reserve (MPR) have independent prognostic value over standard clinical and imaging parameters.

Methods

A 4-centre study of patients with T2DM who underwent quantitative perfusion assessment using CMR. Diagnosis of T2DM was based on Hba1c &gt;48mmol/l or a known diagnosis of T2DM. Image analysis was performed automatically using an artificial intelligence approach deriving global MBF and MPR [2]. Cox proportional hazard models adjusting for comorbidities and CMR parameters sought associations between stress MBF and MPR with death and major adverse cardiovascular events (MACE), including MI, non-fatal stroke, heart failure hospitalisation and death.

Results

A total of 630 patients with T2DM were included with a median follow-up of 722 days (interquartile range 493) days. There were 27 (4.3%) deaths and 76 MACE events in 62 (12.1%) patients. Patient data was represented into groups depending on threshold stress MBF values of 1.94ml/g/min and MPR thresholds of 1.96 using validated data from invasive coronary physiology [3]. Patient demographics and CMR data are seen in table 1. Kaplan-Meier curves are seen in figure 1. Stress MBF was associated with mortality and MACE after adjusting for age, LV ejection fraction and HbA1c. The stress MBF adjusted hazard ratios for all cause death and death and MACE were 0.35 (95% CI, 0.13–0.95, P=0.04) and 0.54 (95% CI, 0.30–0.96, P=0.04), respectively. MPR was not significantly associated with death and MACE after adjusting for age, LV ejection fraction and HbA1c; hazard ratio for all cause death and death and MACE was 0.83 (95% CI, 0.41–1.69, P=0.60) and 0.81 (95% CI, 0.53–1.23, p=0.32) respectively.

Conclusion

In patients with T2DM, reduced stress MBF measured automatically inline using artificial intelligence quantification of cardiovascular magnetic resonance perfusion mapping provides a strong, independent predictor of adverse cardiovascular outcome.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): 1. REC ID 14/EE/0007 (Barts Heart Centre funding). 2. For PREDICT (Leicester data) ethical approval was provided by the UK Health Research Authority Research Ethics Committee (reference 17/WM/0192). 3. MATCH Study, Leeds - British Heart Foundation - 17/YH/0300. 4. LEAN-DM, Leeds - British Heart Foundation - 18/YH/01685. CEED, Leeds: British Heart Foundation - REC reference - 18/YH/0190

Heterozygous APOE ε4 carriage associates with improved myocardial efficiency in older age

Background

Carriage of the ancestral APOE ε4 allele confers a risk of developing Alzheimer's and coronary artery disease, but its persistence in human populations also suggests some potential survival advantages. To date it remains unclear whether APOE ε4 carriage independently associates with a better or worse long-term cardiac phenotype.

Purpose

Using data from the 1946 National Survey of Health and Development (NSHD) birth cohort, we investigated whether APOE ε4 carriage associates with adverse or beneficial left ventricular (LV) size and function parameters by echocardiography in older age.

Methods

Based on the presence or absence of APOE ε4, genotypes were divided into: non-APOE ε4 (ε2ε2, ε2ε3, ε3ε3), heterozygous-APOE ε4 (ε2ε4 and ε3ε4) and homozygous-APOE ε4 (ε4ε4). Echocardiographic data at 60–64 years included: left ventricular ejection fraction (LV EF), E/e', systolic and diastolic LV posterior wall and interventricular septal thickness (LVPWTs/d, IVSs/d), and body-surface area indexed LV mass (LVmassi) and myocardial contraction fraction (MCFi). Generalized linear models explored associations between APOE ε4 genotypes as exposures and echocardiographic biomarkers as outcomes. As a combination of gene variants, APOE ε genotype is expected to be an instrumental variable and therefore unconfounded. Thus, Model 1 was unadjusted. To obtain more precise regression estimates, Model 2 was adjusted for factors associated with the outcome, namely sex and socio-economic position (SEP). To explore the mechanistic pathway downstream of APOE ε genotype but upstream of the echocardiographic outcomes, subsequent models were adjusted for mediators as follows: Model 3 for body mass index, Model 4 for the presence of cardiovascular disease (CVD), Model 5 for diabetes, Model 6 for high cholesterol and Model 7 for hypertension.

Results

1464 participants were included. Compared to non-APOE ε4 and homozygous groups, heterozygous-APOE ε4 individuals had similar cardiac phenotypes in terms of EF, E/e', LVPWTs/d, IVSs/d and LVmassi but had a 7% higher MCFi 95% confidence interval [CI]: 1%-13%, p=0.017) which persisted even after adjustment for sex and SEP (95% CI 1%-12%, p=0.026) that was attenuated to 6% after adjustment for CVD (95% CI 0–13% p=0.050) and hypertension (95% CI 1–13% p=0.022).

Conclusion

The heterozygous-APOE ε4 state associates with improved myocardial shortening in older age resulting in greater LV stroke volume generation per 1 mL of myocardium. As we found no association between APOE ε4 carriage and LVPWTs/d, IVSs/d or LVmassi, MCFi enhancement may be mediated by improved myocardial energetics and contractility, with calcium and androgens potentially implicated, rather than through pathological ventricular thickening. Although a dose relationship is normally expected with ε4 carriage, any benefit from increased energetics and contractility is likely to be counterbalances by the higher risk of CVD and cardiovascular risk factors.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UK Medical Research Council British Heart Foundation

Multimodality Imaging for Cardiotoxicity: State of the Art and Future Perspectives

ABSTRACT

Modern cancer therapies have significantly improved survival leading to a growing population of cancer survivors. Similarly, both conventional and newer treatments are associated with a spectrum of cardiovascular disorders with potential long-term sequelae. Prompt detection and treatment of these complications is, therefore, pivotal to enable healthy survivorship and reduce cardiovascular morbidity. Advanced multimodality imaging is a valuable tool for stratifying patient risk, identifying cardiovascular toxicity during and after therapy, and predicting recovery. This review summarizes the potential cardiotoxic complications of anticancer therapies and the multimodality approaches available in each case with special focus on newer techniques and the added value of biomarkers ultimately leading to earlier diagnosis and better prognostication.

Quantitative, multiplexed, targeted proteomics for ascertaining variant specific SARS-CoV-2 antibody response

Determining the protection an individual has to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants of concern (VoCs) is crucial for future immune surveillance, vaccine development, and understanding of the changing immune response. We devised an informative assay to current ELISA-based serology using multiplexed, baited, targeted proteomics for direct detection of multiple proteins in the SARS-CoV-2 anti-spike antibody immunocomplex. Serum from individuals collected after infection or first- and second-dose vaccination demonstrates this approach and shows concordance with existing serology and neutralization. Our assays show altered responses of both immunoglobulins and complement to the Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.1) VoCs and a reduced response to Omicron (B1.1.1529). We were able to identify individuals who had prior infection, and observed that C1q is closely associated with IgG1 (r > 0.82) and may better reflect neutralization to VoCs. Analyzing additional immunoproteins beyond immunoglobulin (Ig) G, provides important information about our understanding of the response to infection and vaccination.

Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging

Funding Acknowledgements

Type of funding sources: None.

Background

Real-time cine imaging does not require breath-holding and is a robust cine imaging technique in the presence of irregular heartbeats. It is a good alternative to the conventional breath-hold retro-gated cine for simplified acquisition and improved patient comfort. Real-time acquisition is achieved with the single-shot BSSFP readout without retro-gating. To maintain good temporal and spatial resolution, higher acceleration (e.g. &gt;4x parallel imaging) is required. As a result, the real-time cine images experience reduced signal-to-noise ratio (SNR), which limits its clinical acceptance.

Purpose

We developed a novel deep learning model architecture, the Convolutional Neural Network Transformer (CNNT), to improve the quality of real-time cine, under 4x, 5x and 6x acceleration.

Method

Convolutional Neural Networks (CNN) are widely used in CMR research to process cardiac images. Cardiac images are often acquired as a time series with strong inter-phase correlation. We combined the CNN with the more recent transformer model to develop a novel CNNT architecture. It takes in the entire 2D+T time series as input and has advantages of CNN for efficient computation and spatial invariance. It further inherits the advantages of attention layer in the transformer and is able to efficiently utilize the temporal correlation within a time series.

A CNNT model is developed to improve the SNR of real-time cine imaging. N=10 patients were scanned at a heart center, with 4x, 5x and 6x acceleration. Typical imaging parameters are: FOV 360×270mm2, flip angle 50°, acquired matrix size 160×90 for R=4 acceleration, 192×108 for R=5 and 6, temporal resolution 40ms for R=4, 42ms for R=5 and 35ms for R=6. The real-time images went through a TGRAPPA reconstruction [1] and the CNNT model. The SNR of TGRAPPA was measured with SNR units [2]. The Monte-Carlo pseudo-replica test was used to measure SNR for the CNNT model. For every cine series, two phases were picked for the end-systole and end-diastole. For every image picked, two region-of-interests were drawn in the myocardium and in the LV blood pool. The CNNT model was deployed inline on the MR scanner using the Gadgetron InlineAI [3].

Results

Figure 1 gives real-time cine images for three accelerations, reconstructed with TGRAPPA and CNNT. The parallel imaging TGRAPPA reconstruction suffers significant SNR loss from elevated g-factor and less acquired data. The deep learning CNNT model recovered SNR even at the very high 6x acceleration, without observed loss of boundary sharpness.

Table 1 lists the SNR measurement results. The TGRAPPA SNR decreased ∼4x from R=4 to R=6 for both the blood and myocardium. For the blood, the CNNT increased the SNR by 170%, 335%, 371% at R=4, 5 and 6. For the myocardium, the SNR increases were 335%, 634% and 828%.

Conclusion

We developed a convolutional neural network transformer model to recover the SNR for real-time cine imaging at higher acceleration.

Asymmetric septal thickening is observed in hypertrophic cardiomyopathy mutation carriers without left ventricular hypertrophy: insights from AI analysis

Funding Acknowledgements

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).

Background

Hypertrophic cardiomyopathy (HCM) is a common inherited cardiac disease characterised by left ventricular hypertrophy (LVH), often, with asymmetric septal thickening. Despite the prevalence of inherited mutations present in &gt;50% of cases, there is variable phenotypic expression in those with abnormal sarcomere protein genes. In individuals with abnormal genes but without LVH, we hypothesised that there is subtle asymmetric septal hypertrophy, detectable by the increased precision offered by an artificial intelligence (AI) tool for measuring wall thickness.

Purpose

We explored the septal-lateral ratio measured by AI in individuals with an identified genotype but no left ventricular hypertrophy as a component of sub-clinical HCM.

Methods

43 individuals with identified genotype, but no left ventricular hypertrophy (G+LVH-) and 97 age-, sex- and disease-matched controls underwent CMR. Patients were excluded if they had a maximum wall thickness (MWT) of ≥13mm. A clinically validated AI tool was used to measure the MWT, for each segment in the 16-segment AHA model. The septal-lateral ratio was calculated using the septal segment with the largest MWT and the lateral segment with the largest MWT.

Results

The mean septal-lateral ratio of the G+LVH- patients was 1.22 (SD 0.22) and the mean septal-lateral ratio of the matched controls was 1.14 (SD 0.15) with a statistically significant mean difference of 0.08 (p=0.01). There was no significant difference between the MWT of the G+LVH- patients at 10.3mm (SD 2.2) and healthy volunteers at 10.1mm (SD 1.8) (p = 0.61).

Conclusion

G+LVH- patients have a 7% increase in their septal-lateral ratio compared with age-matched controls despite the lack of difference in the MWT. Using increased precision offered by AI, early features of HCM can be observed in patients without overt LVH.

CNNT DB-LGE: free-breathing dark blood late enhancement imaging using the convolutional neural network transformer speeds acquisition by 50%

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Supported in part by the Division of Intramural Research of the National Heart, Lung, and Blood Institute, National Institutes of Health (grants Z1A-HL006214-05 and Z1A-HL006242-02).

Background

Dark blood late gadolinium enhancement (DB-LGE) imaging shows superior delineation of myocardial infarction (MI), especially at the sub-endocardial boundary. Our previous study [1] developed a free-breathing DB-LGE with the single shot SSFP readout, phase sensitive inversion recovery (PSIR) reconstruction, and respiratory motion corrected averaging. To compensate the potential signal-to-noise ratio loss, our previous DB-LGE doubled the measurements, thereby increasing the acquisition time.

Purpose

In this study, we developed a deep learning image enhancement model using a novel neural network architecture called the convolutional neural network transformer (CNNT) to improve the image quality of DB-LGE and to reduce the acquisition time by decreasing the number of measurements.

Methods

A novel image enhancement model was developed using a novel network architecture called the Convolutional Neural Network Transformer (CNNT) proposed by us. This architecture is suitable for the 2D+Time CMR acquisition, by exploiting the temporal correlation between images over multiple averages.

The evaluation was first retrospectively conducted on a cohort of 12 patients acquired with the original protocol [1] using the full 16 measurements. For every subject, a complete short-axis stack (typically 12 slices) was acquired to cover the entire left ventricular. The imaging data was reconstructed in three ways. Original: using all acquired 16 measurements. This is our base-line protocol. Original 50%: using only the first 8 measurements. CNNT 50%: using only the first 8 averages, but performing the CNNT deep learning image enhancement before MOCO PSIR reconstruction. Two experienced imaging researchers (PK and MF, &gt;10 years of experience for both) scored all DB-LGE images for the overall quality, diagnostic confidence and delineation of MI/boundaries (5 = excellent, 4 = good, 3 = fair, 2 = poor, and 1 = non-diagnostic). The CNNT DB-LGE was deployed to the MR scanner using the Gadgetron InlineAI [2].

Results

Figure 1 gives examples of DB-LGE with three reconstruction methods. The CNNT image has higher SNR and well delineated MI. The Original images with the longest acquisition have good quality and the Original-50% acquired with 8 measurements are good quality but have reduced SNR. The mean scores for overall image quality, diagnostic confidence and MI delineation of two reviewers were 4.88±0.23, 4.88±0.23, 4.83±0.25 for CNNT and 4.96±0.14, 4.96±0.14, 4.67±0.39 for the original approach. No significant differences were found between the original and the CNNT (P&gt;0.15 for all).

Figure 2 shows an acute MI patient prospectively acquired with the 50% scan time reduction, with and without the CNNT enhancement. The resulting PSIR images well delineate the MVO due to the acute MI, with improved SNR.

Conclusion

A novel CNNT model was proposed and evaluated to speed up the free-breathing MOCO DB LGE by 50% without sacrificing image quality.

Improving the diagnostic accuracy of apical hypertrophic cardiomyopathy using machine learning

Funding Acknowledgements

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).

Introduction

The imaging criteria for diagnosis of apical hypertrophic cardiomyopathy (ApHCM) is a maximum wall thickness (MWT) ≥15mm. CMR enables detection of subtle phenotypic features (e.g. loss of apical tapering, cavity obliteration) and coupled with characteristic electrocardiogram changes, ApHCM can be diagnosed without overt hypertrophy. However, these patients are not captured by current diagnostic criteria.

Purpose

We sought to use a machine learning tool to quantify wall thickness and identify patients with ‘relative’ ApHCM that do not reach current diagnostic thresholds.

Methods

CMR images from 4118 healthy participants from the UK Biobank were segmented automatically with a clinically validated machine learning algorithm and wall thickness measured at all point in the myocardium by solving a solution to Laplace’s equation. MWT were pooled into 16 AHA segments and indexed to body surface area (BSA). The non-indexed and indexed segmental upper limit of normal was calculated as the mean + 3 standard deviations (the equivalent of 95% confidence interval after correcting for multiple [16] comparisons using the Bonferroni method).

Results

73 overt ApHCM subjects (MWT&gt;15mm) and 31 relative ApHCM subjects underwent CMR scanning. In healthy controls, the non-indexed (and indexed) upper limits were calculated for the apical-anterior 10.2mm (5.2 mm/m2), apical-septal 11.1mm (5.6 mm/m2), apical-inferior 10.5mm (5.3 mm/m2) and apical-lateral 10.1mm (5.2 mm/m2) segments. With a non-indexed cut-off, all (73 of 73) overt ApHCM and 84% (26 of 31) relative ApHCM were classified as having an abnormally thick apex. 3% (127 of 4118) of the healthy UK Biobank cohort were classified as abnormal, as expected. Using an indexed cut-off, all overt ApHCM and 87% (27/31) relative ApHCM were classified as abnormal, and 3% (123 of 4118) of the healthy UK Biobank cohort were misclassified.

Conclusion

We can successfully classify 87% of relative ApHCM patients from a normative reference range derived from a large cohort of healthy patients – a significant improvement on existing methods. We show that the specificity and sensitivity is increased when MWT is indexed to BSA. For practical clinical application, we recommend a cut-off of 10mm or an indexed cut-off of 5mm/m2 in any apical segment to diagnose apical LVH. Overt and relative apical HCM examplesHealthy controls AHA maps (non-indexed)

Speeding up cardiac MR segmentation with semi-supervision: applications in cine imaging

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): This material is based upon work supported by the Google Cloud Research Credits program with the award GCP19980904.

Background

Segmentation is an important postprocessing step in cardiac magnetic resonance (CMR) imaging that enables quantitative assessment of functional parameters. Deep learning can automate the segmentation process, producing accurate contours of cardiac structures while reducing the time required to analyze images and the interobserver variation compared to manual analysis. However, common approaches to training neural networks (NNs) require large amounts of labeled data, which is costly to generate and slows down the development of CMR segmentation NNs for new applications. Semi-supervision is an approach to alleviate this labeling burden by relying on abundant unlabeled data and a smaller amount of labeled data to train NNs.

Purpose

We propose a novel semi-supervised method to train CMR segmentation NNs. We use the proposed method to train NNs to segment the left ventricle in CMR cine images. Ultimately, we aim to show that semi-supervision can drastically reduce the amount of labeled data required to develop machine learning segmentation applications for CMR while maintaining high performance.

Methods

Our dataset consists of 1,208 short-axis cine CMR images and 1,244 long-axis cine CMR images. An expert annotator manually segmented the endocardium on the end-diastolic and end-systolic short-axis and long-axis images and the epicardium on the end-diastolic short-axis images. We split the dataset randomly by patient into 60% training, 20% validation, and 20% testing data. We train semi-supervised segmentation networks using a supervised cross-entropy loss to learn from the labeled training data and a cosine embedding loss in addition to a pseudo-labeling step to learn from the unlabeled training data. To evaluate how performance changes with different amounts of labeled training data, we vary the percent of training data that has labels from &lt;1%-100%. We evaluate the predicted segmentation masks using the Dice coefficient.

Results

Using only 100 labeled image slices, the semi-supervised segmentation NNs achieve a mean Dice coefficient within 1.10% of networks trained with fully labeled training sets, corresponding to &gt;85% reduction in required labeled training data (Table 1). The proposed semi-supervised method improves performance over naïve training by 6.21% for the most limited labeled data setting (i.e., 10 labeled image slices; Figure 1).

Conclusion

We have shown that NNs trained with limited labeled data achieve high performance on left ventricle segmentation in short-axis and long-axis CMR cines. The proposed approach is flexible and broadly applicable to different CMR segmentation tasks, enabling rapid development of segmentation networks for many cardiac structures and applications. Table 1Figure 1