Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study.

BACKGROUND: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. METHODS: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4-5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4-9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. FINDINGS: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9-63·9], p<0·001) or MACE (12·6 [8·5-18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17-8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93-5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. INTERPRETATION: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. FUNDING: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.

Retained Metabolic Flexibility of the Failing Human Heart.

BACKGROUND: The failing heart is traditionally described as metabolically inflexible and oxygen starved, causing energetic deficit and contractile dysfunction. Current metabolic modulator therapies aim to increase glucose oxidation to increase oxygen efficiency of adenosine triphosphate production, with mixed results. METHODS: To investigate metabolic flexibility and oxygen delivery in the failing heart, 20 patients with nonischemic heart failure with reduced ejection fraction (left ventricular ejection fraction 34.9±9.1) underwent separate infusions of insulin+glucose infusion (I+G) or Intralipid infusion. We used cardiovascular magnetic resonance to assess cardiac function and measured energetics using phosphorus-31 magnetic resonance spectroscopy. To investigate the effects of these infusions on cardiac substrate use, function, and myocardial oxygen uptake (MVo2), invasive arteriovenous sampling and pressure-volume loops were performed (n=9). RESULTS: At rest, we found that the heart had considerable metabolic flexibility. During I+G, cardiac glucose uptake and oxidation were predominant (70±14% total energy substrate for adenosine triphosphate production versus 17±16% for Intralipid; P=0.002); however, no change in cardiac function was seen relative to basal conditions. In contrast, during Intralipid infusion, cardiac long-chain fatty acid (LCFA) delivery, uptake, LCFA acylcarnitine production, and fatty acid oxidation were all increased (LCFA 73±17% of total substrate versus 19±26% total during I+G; P=0.009). Myocardial energetics were better with Intralipid compared with I+G (phosphocreatine/adenosine triphosphate 1.86±0.25 versus 2.01±0.33; P=0.02), and systolic and diastolic function were improved (LVEF 34.9±9.1 baseline, 33.7±8.2 I+G, 39.9±9.3 Intralipid; P<0.001). During increased cardiac workload, LCFA uptake and oxidation were again increased during both infusions. There was no evidence of systolic dysfunction or lactate efflux at 65% maximal heart rate, suggesting that a metabolic switch to fat did not cause clinically meaningful ischemic metabolism. CONCLUSIONS: Our findings show that even in nonischemic heart failure with reduced ejection fraction with severely impaired systolic function, significant cardiac metabolic flexibility is retained, including the ability to alter substrate use to match both arterial supply and changes in workload. Increasing LCFA uptake and oxidation is associated with improved myocardial energetics and contractility. Together, these findings challenge aspects of the rationale underlying existing metabolic therapies for heart failure and suggest that strategies promoting fatty acid oxidation may form the basis for future therapies.

Assessment of Cardiac Energy Metabolism, Function, and Physiology in Patients With Heart Failure Taking Empagliflozin: The Randomized, Controlled EMPA-VISION Trial.

BACKGROUND: Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have emerged as a paramount treatment for patients with heart failure (HF), irrespective of underlying reduced or preserved ejection fraction. However, a definite cardiac mechanism of action remains elusive. Derangements in myocardial energy metabolism are detectable in all HF phenotypes, and it was proposed that SGLT2i may improve energy production. The authors aimed to investigate whether treatment with empagliflozin leads to changes in myocardial energetics, serum metabolomics, and cardiorespiratory fitness. METHODS: EMPA-VISION (Assessment of Cardiac Energy Metabolism, Function and Physiology in Patients With Heart Failure Taking Empagliflozin) is a prospective, randomized, double-blind, placebo-controlled, mechanistic trial that enrolled 72 symptomatic patients with chronic HF with reduced ejection fraction (HFrEF; n=36; left ventricular ejection fraction ≤40%; New York Heart Association class ≥II; NT-proBNP [N-terminal pro-B-type natriuretic peptide] ≥125 pg/mL) and HF with preserved ejection fraction (HFpEF; n=36; left ventricular ejection fraction ≥50%; New York Heart Association class ≥II; NT-proBNP ≥125 pg/mL). Patients were stratified into respective cohorts (HFrEF versus HFpEF) and randomly assigned to empagliflozin (10 mg; n=35: 17 HFrEF and 18 HFpEF) or placebo (n=37: 19 HFrEF and 18 HFpEF) once daily for 12 weeks. The primary end point was a change in the cardiac phosphocreatine:ATP ratio (PCr/ATP) from baseline to week 12, determined by phosphorus magnetic resonance spectroscopy at rest and during peak dobutamine stress (65% of age-maximum heart rate). Mass spectrometry on a targeted set of 19 metabolites was performed at baseline and after treatment. Other exploratory end points were investigated. RESULTS: Empagliflozin treatment did not change cardiac energetics (ie, PCr/ATP) at rest in HFrEF (adjusted mean treatment difference [empagliflozin - placebo], -0.25 [95% CI, -0.58 to 0.09]; P=0.14) or HFpEF (adjusted mean treatment difference, -0.16 [95% CI, -0.60 to 0.29]; P=0.47]. Likewise, there were no changes in PCr/ATP during dobutamine stress in HFrEF (adjusted mean treatment difference, -0.13 [95% CI, -0.35 to 0.09]; P=0.23) or HFpEF (adjusted mean treatment difference, -0.22 [95% CI, -0.66 to 0.23]; P=0.32). No changes in serum metabolomics or levels of circulating ketone bodies were observed. CONCLUSIONS: In patients with either HFrEF or HFpEF, treatment with 10 mg of empagliflozin once daily for 12 weeks did not improve cardiac energetics or change circulating serum metabolites associated with energy metabolism when compared with placebo. Based on our results, it is unlikely that enhancing cardiac energy metabolism mediates the beneficial effects of SGLT2i in HF. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03332212.

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.

NHS Health Check attendance is associated with reduced multiorgan disease risk: a matched cohort study in the UK Biobank.

BACKGROUND: The NHS Health Check is a preventive programme in the UK designed to screen for cardiovascular risk and to aid in primary disease prevention. Despite its widespread implementation, the effectiveness of the NHS Health Check for longer-term disease prevention is unclear. In this study, we measured the rate of new diagnoses in UK Biobank participants who underwent the NHS Health Check compared with those who did not. METHODS: Within the UK Biobank prospective study, 48,602 NHS Health Check recipients were identified from linked primary care records. These participants were then covariate-matched on an extensive range of socio-demographic, lifestyle, and medical factors with 48,602 participants without record of the check. Follow-up diagnoses were ascertained from health records over an average of 9 years (SD 2 years) including hypertension, diabetes, hypercholesterolaemia, stroke, dementia, myocardial infarction, atrial fibrillation, heart failure, fatty liver disease, alcoholic liver disease, liver cirrhosis, liver failure, acute kidney injury, chronic kidney disease (stage 3 +), cardiovascular mortality, and all-cause mortality. Time-varying survival modelling was used to compare adjusted outcome rates between the groups. RESULTS: In the immediate 2 years after the NHS Health Check, higher diagnosis rates were observed for hypertension, high cholesterol, and chronic kidney disease among health check recipients compared to their matched counterparts. However, in the longer term, NHS Health Check recipients had significantly lower risk across all multiorgan disease outcomes and reduced rates of cardiovascular and all-cause mortality. CONCLUSIONS: The NHS Health Check is linked to reduced incidence of disease across multiple organ systems, which may be attributed to risk modification through earlier detection and treatment of key risk factors such as hypertension and high cholesterol. This work adds important evidence to the growing body of research supporting the effectiveness of preventative interventions in reducing longer-term multimorbidity.

Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement.

BACKGROUND: Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan without contrast-associated problems. METHODS: Virtual native enhancement (VNE) is a novel technology that can produce virtual LGE-like images without the need for contrast. VNE combines cine imaging and native T1 maps to produce LGE-like images using artificial intelligence. VNE was developed for patients with previous myocardial infarction from 4271 data sets (912 patients); each data set comprises slice position-matched cine, T1 maps, and LGE images. After quality control, 3002 data sets (775 patients) were used for development and 291 data sets (68 patients) for testing. The VNE generator was trained using generative adversarial networks, using 2 adversarial discriminators to improve the image quality. The left ventricle was contoured semiautomatically. Myocardial scar volume was quantified using the full width at half maximum method. Scar transmurality was measured using the centerline chord method and visualized on bull's-eye plots. Lesion quantification by VNE and LGE was compared using linear regression, Pearson correlation (R), and intraclass correlation coefficients. Proof-of-principle histopathologic comparison of VNE in a porcine model of myocardial infarction also was performed. RESULTS: VNE provided significantly better image quality than LGE on blinded analysis by 5 independent operators on 291 data sets (all P<0.001). VNE correlated strongly with LGE in quantifying scar size (R, 0.89; intraclass correlation coefficient, 0.94) and transmurality (R, 0.84; intraclass correlation coefficient, 0.90) in 66 patients (277 test data sets). Two cardiovascular magnetic resonance experts reviewed all test image slices and reported an overall accuracy of 84% for VNE in detecting scars when compared with LGE, with specificity of 100% and sensitivity of 77%. VNE also showed excellent visuospatial agreement with histopathology in 2 cases of a porcine model of myocardial infarction. CONCLUSIONS: VNE demonstrated high agreement with LGE cardiovascular magnetic resonance for myocardial scar assessment in patients with previous myocardial infarction in visuospatial distribution and lesion quantification with superior image quality. VNE is a potentially transformative artificial intelligence-based technology with promise in reducing scan times and costs, increasing clinical throughput, and improving the accessibility of cardiovascular magnetic resonance in the near future.

Liver disease is a significant risk factor for cardiovascular outcomes - A UK Biobank study.

BACKGROUND & AIMS: Chronic liver disease (CLD) is associated with increased cardiovascular disease (CVD) risk. We investigated whether early signs of liver disease (measured by iron-corrected T1-mapping [cT1]) were associated with an increased risk of major CVD events. METHODS: Liver disease activity (cT1) and fat (proton density fat fraction [PDFF]) were measured using LiverMultiScan® between January 2016 and February 2020 in the UK Biobank imaging sub-study. Using multivariable Cox regression, we explored associations between liver cT1 (MRI) and primary CVD (coronary artery disease, atrial fibrillation [AF], embolism/vascular events, heart failure [HF] and stroke), and CVD hospitalisation and all-cause mortality. Liver blood biomarkers, general metabolism biomarkers, and demographics were also included. Subgroup analysis was conducted in those without metabolic syndrome (defined as at least three of: a large waist, high triglycerides, low high-density lipoprotein cholesterol, increased systolic blood pressure, or elevated haemoglobin A1c). RESULTS: A total of 33,616 participants (mean age 65 years, mean BMI 26 kg/m2, mean haemoglobin A1c 35 mmol/mol) had complete MRI liver data with linked clinical outcomes (median time to major CVD event onset: 1.4 years [range: 0.002-5.1]; follow-up: 2.5 years [range: 1.1-5.2]). Liver disease activity (cT1), but not liver fat (PDFF), was associated with higher risk of any major CVD event (hazard ratio 1.14; 95% CI 1.03-1.26; p = 0.008), AF (1.30; 1.12-1.51; p <0.001); HF (1.30; 1.09-1.56; p= 0.004); CVD hospitalisation (1.27; 1.18-1.37; p <0.001) and all-cause mortality (1.19; 1.02-1.38; p = 0.026). FIB-4 index was associated with HF (1.06; 1.01-1.10; p = 0.007). Risk of CVD hospitalisation was independently associated with cT1 in individuals without metabolic syndrome (1.26; 1.13-1.4; p <0.001). CONCLUSION: Liver disease activity, by cT1, was independently associated with a higher risk of incident CVD and all-cause mortality, independent of pre-existing metabolic syndrome, liver fibrosis or fat. IMPACT AND IMPLICATIONS: Chronic liver disease (CLD) is associated with a twofold greater incidence of cardiovascular disease. Our work shows that early liver disease on iron-corrected T1 mapping was associated with a higher risk of major cardiovascular disease (14%), cardiovascular disease hospitalisation (27%) and all-cause mortality (19%). These findings highlight the prognostic relevance of a comprehensive evaluation of liver health in populations at risk of CVD and/or CLD, even in the absence of clinical manifestations or metabolic syndrome, when there is an opportunity to modify/address risk factors and prevent disease progression. As such, they are relevant to patients, carers, clinicians, and policymakers.

Angiotensin receptor blockers and ß blockers in Marfan syndrome: an individual patient data meta-analysis of randomised trials.

BACKGROUND: Angiotensin receptor blockers (ARBs) and ß blockers are widely used in the treatment of Marfan syndrome to try to reduce the rate of progressive aortic root enlargement characteristic of this condition, but their separate and joint effects are uncertain. We aimed to determine these effects in a collaborative individual patient data meta-analysis of randomised trials of these treatments. METHODS: In this meta-analysis, we identified relevant trials of patients with Marfan syndrome by systematically searching MEDLINE, Embase, and CENTRAL from database inception to Nov 2, 2021. Trials were eligible if they involved a randomised comparison of an ARB versus control or an ARB versus ß blocker. We used individual patient data from patients with no prior aortic surgery to estimate the effects of: ARB versus control (placebo or open control); ARB versus ß blocker; and indirectly, ß blocker versus control. The primary endpoint was the annual rate of change of body surface area-adjusted aortic root dimension Z score, measured at the sinuses of Valsalva. FINDINGS: We identified ten potentially eligible trials including 1836 patients from our search, from which seven trials and 1442 patients were eligible for inclusion in our main analyses. Four trials involving 676 eligible participants compared ARB with control. During a median follow-up of 3 years, allocation to ARB approximately halved the annual rate of change in the aortic root Z score (mean annual increase 0·07 [SE 0·02] ARB vs 0·13 [SE 0·02] control; absolute difference -0·07 [95% CI -0·12 to -0·01]; p=0·012). Prespecified secondary subgroup analyses showed that the effects of ARB were particularly large in those with pathogenic variants in fibrillin-1, compared with those without such variants (heterogeneity p=0·0050), and there was no evidence to suggest that the effect of ARB varied with ß-blocker use (heterogeneity p=0·54). Three trials involving 766 eligible participants compared ARBs with ß blockers. During a median follow-up of 3 years, the annual change in the aortic root Z score was similar in the two groups (annual increase -0·08 [SE 0·03] in ARB groups vs -0·11 [SE 0·02] in ß-blocker groups; absolute difference 0·03 [95% CI -0·05 to 0·10]; p=0·48). Thus, indirectly, the difference in the annual change in the aortic root Z score between ß blockers and control was -0·09 (95% CI -0·18 to 0·00; p=0·042). INTERPRETATION: In people with Marfan syndrome and no previous aortic surgery, ARBs reduced the rate of increase of the aortic root Z score by about one half, including among those taking a ß blocker. The effects of ß blockers were similar to those of ARBs. Assuming additivity, combination therapy with both ARBs and ß blockers from the time of diagnosis would provide even greater reductions in the rate of aortic enlargement than either treatment alone, which, if maintained over a number of years, would be expected to lead to a delay in the need for aortic surgery. FUNDING: Marfan Foundation, the Oxford British Heart Foundation Centre for Research Excellence, and the UK Medical Research Council.

Detection and alterations of acetylcarnitine (AC) in human liver by 1 H MRS at 3T after supplementation with l-carnitine.

PURPOSE: Acetylcarnitine can be assessed in vivo using proton MRS (1 H-MRS) with long TEs and this has been previously applied successfully in muscle. The aim of this study was to evaluate a 1 H-MRS technique for liver acetylcarnitine quantification in healthy humans before and after l-carnitine supplementation. METHOD: Baseline acetylcarnitine levels were quantified using a STEAM sequence with prolonged TE in 15 healthy adults. Using STEAM with four different TEs was evaluated in phantoms. To assess reproducibility of the measurements, five of the participants had repeated 1 H-MRS without receiving l-carnitine supplementation. To determine if liver acetylcarnitine could be changed after l-carnitine supplementation, acetylcarnitine was quantified 2 h after intravenous l-carnitine supplementation (50 mg/kg body weight) in the other 10 participants. Hepatic lipids were also quantified from the 1 H-MRS spectra. RESULTS: There was good separation between the acetylcarnitine and fat in the phantoms using TE = 100 ms. Hepatic acetylcarnitine levels were reproducible (coefficient of reproducibility = 0.049%) and there was a significant (p < 0.001) increase in the relative abundance after a single supplementation of l-carnitine. Hepatic allylic, methyl, and methylene peaks were not altered by l-carnitine supplementation in healthy volunteers. CONCLUSION: Our results demonstrate that our 1 H-MRS technique could be used to measure acetylcarnitine in the liver and detect changes following intravenous supplementation in healthy adults despite the presence of lipids. Our techniques should be explored further in the study of fatty liver disease, where acetylcarnitine is suggested to be altered due to hepatic inflexibilities.

Image-Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers.

BACKGROUND: Biological heart age estimation can provide insights into cardiac aging. However, existing studies do not consider differential aging across cardiac regions. PURPOSE: To estimate biological age of the left ventricle (LV), right ventricle (RV), myocardium, left atrium, and right atrium using magnetic resonance imaging radiomics phenotypes and to investigate determinants of aging by cardiac region. STUDY TYPE: Cross-sectional. POPULATION: A total of 18,117 healthy UK Biobank participants including 8338 men (mean age = 64.2 ± 7.5) and 9779 women (mean age = 63.0 ± 7.4). FIELD STRENGTH/SEQUENCE: A 1.5 T/balanced steady-state free precession. ASSESSMENT: An automated algorithm was used to segment the five cardiac regions, from which radiomic features were extracted. Bayesian ridge regression was used to estimate biological age of each cardiac region with radiomics features as predictors and chronological age as the output. The "age gap" was the difference between biological and chronological age. Linear regression was used to calculate associations of age gap from each cardiac region with socioeconomic, lifestyle, body composition, blood pressure and arterial stiffness, blood biomarkers, mental well-being, multiorgan health, and sex hormone exposures (n = 49). STATISTICAL TEST: Multiple testing correction with false discovery method (threshold = 5%). RESULTS: The largest model error was with RV and the smallest with LV age (mean absolute error in men: 5.26 vs. 4.96 years). There were 172 statistically significant age gap associations. Greater visceral adiposity was the strongest correlate of larger age gaps, for example, myocardial age gap in women (Beta = 0.85, P = 1.69 × 10-26 ). Poor mental health associated with large age gaps, for example, "disinterested" episodes and myocardial age gap in men (Beta = 0.25, P = 0.001), as did a history of dental problems (eg LV in men Beta = 0.19, P = 0.02). Higher bone mineral density was the strongest associate of smaller age gaps, for example, myocardial age gap in men (Beta = -1.52, P = 7.44 × 10-6 ). DATA CONCLUSION: This work demonstrates image-based heart age estimation as a novel method for understanding cardiac aging. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 1.

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1 H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters. PURPOSE: Develop a generalizable CNN for lung segmentation in 1 H-MRI, robust to pathology, acquisition protocol, vendor, and center. STUDY TYPE: Retrospective. POPULATION: A total of 809 1 H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6-85); 42% females) and 31 healthy participants (median age (range): 34 (23-76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1 H-MRI. ASSESSMENT: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. STATISTICAL TESTS: Kruskal-Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland-Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant. RESULTS: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880-0.987), Average HD of 1.63 mm (0.65-5.45) and XOR of 0.079 (0.025-0.240) on the testing set and a DSC of 0.973 (0.866-0.987), Average HD of 1.11 mm (0.47-8.13) and XOR of 0.054 (0.026-0.255) on external validation data. DATA CONCLUSION: The 3D CNN generated accurate 1 H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Radiomics of pericardial fat: a new frontier in heart failure discrimination and prediction.

OBJECTIVES: To use pericardial adipose tissue (PAT) radiomics phenotyping to differentiate existing and predict future heart failure (HF) cases in the UK Biobank. METHODS: PAT segmentations were derived from cardiovascular magnetic resonance (CMR) studies using an automated quality-controlled model to define the region-of-interest for radiomics analysis. Prevalent (present at time of imaging) and incident (first occurrence after imaging) HF were ascertained using health record linkage. We created balanced cohorts of non-HF individuals for comparison. PyRadiomics was utilised to extract 104 radiomics features, of which 28 were chosen after excluding highly correlated ones (0.8). These features, plus sex and age, served as predictors in binary classification models trained separately to detect (1) prevalent and (2) incident HF. We tested seven modeling methods using tenfold nested cross-validation and examined feature importance with explainability methods. RESULTS: We studied 1204 participants in total, 297 participants with prevalent (60 ± 7 years, 21% female) and 305 with incident (61 ± 6 years, 32% female) HF, and an equal number of non-HF comparators. We achieved good discriminative performance for both prevalent (voting classifier; AUC: 0.76; F1 score: 0.70) and incident (light gradient boosting machine: AUC: 0.74; F1 score: 0.68) HF. Our radiomics models showed marginally better performance compared to PAT area alone. Increased PAT size (maximum 2D diameter in a given column or slice) and texture heterogeneity (sum entropy) were important features for prevalent and incident HF classification models. CONCLUSIONS: The amount and character of PAT discriminate individuals with prevalent HF and predict incidence of future HF. CLINICAL RELEVANCE STATEMENT: This study presents an innovative application of pericardial adipose tissue (PAT) radiomics phenotyping as a predictive tool for heart failure (HF), a major public health concern. By leveraging advanced machine learning methods, the research uncovers that the quantity and characteristics of PAT can be used to identify existing cases of HF and predict future occurrences. The enhanced performance of these radiomics models over PAT area alone supports the potential for better personalised care through earlier detection and prevention of HF. KEY POINTS: •PAT radiomics applied to CMR was used for the first time to derive binary machine learning classifiers to develop models for discrimination of prevalence and prediction of incident heart failure. •Models using PAT area provided acceptable discrimination between cases of prevalent or incident heart failure and comparator groups. •An increased PAT volume (increased diameter using shape features) and greater texture heterogeneity captured by radiomics texture features (increased sum entropy) can be used as an additional classifier marker for heart failure.

Prediction of incident cardiovascular events using machine learning and CMR radiomics.

OBJECTIVES: Evaluation of the feasibility of using cardiovascular magnetic resonance (CMR) radiomics in the prediction of incident atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), and stroke using machine learning techniques. METHODS: We identified participants from the UK Biobank who experienced incident AF, HF, MI, or stroke during the continuous longitudinal follow-up. The CMR indices and the vascular risk factors (VRFs) as well as the CMR images were obtained for each participant. Three-segmented regions of interest (ROIs) were computed: right ventricle cavity, left ventricle (LV) cavity, and LV myocardium in end-systole and end-diastole phases. Radiomics features were extracted from the 3D volumes of the ROIs. Seven integrative models were built for each incident cardiovascular disease (CVD) as an outcome. Each model was built with VRF, CMR indices, and radiomics features and a combination of them. Support vector machine was used for classification. To assess the model performance, the accuracy, sensitivity, specificity, and AUC were reported. RESULTS: AF prediction model using the VRF+CMR+Rad model (accuracy: 0.71, AUC 0.76) obtained the best result. However, the AUC was similar to the VRF+Rad model. HF showed the most significant improvement with the inclusion of CMR metrics (VRF+CMR+Rad: 0.79, AUC 0.84). Moreover, adding only the radiomics features to the VRF reached an almost similarly good performance (VRF+Rad: accuracy 0.77, AUC 0.83). Prediction models looking into incident MI and stroke reached slightly smaller improvement. CONCLUSIONS: Radiomics features may provide incremental predictive value over VRF and CMR indices in the prediction of incident CVDs. KEY POINTS: • Prediction of incident atrial fibrillation, heart failure, stroke, and myocardial infarction using machine learning techniques. • CMR radiomics, vascular risk factors, and standard CMR indices will be considered in the machine learning models. • The experiments show that radiomics features can provide incremental predictive value over VRF and CMR indices in the prediction of incident cardiovascular diseases.

Synergistic effect on cardiac energetics by targeting the creatine kinase system: in vivo application of high-resolution 31P-CMRS in the mouse.

BACKGROUND: Phosphorus cardiovascular magnetic resonance spectroscopy (31P-CMRS) has emerged as an important tool for the preclinical assessment of myocardial energetics in vivo. However, the high rate and diminutive size of the mouse heart is a challenge, resulting in low resolution and poor signal-to-noise. Here we describe a refined high-resolution 31P-CMRS technique and apply it to a novel double transgenic mouse (dTg) with elevated myocardial creatine and creatine kinase (CK) activity. We hypothesised a synergistic effect to augment energetic status, evidenced by an increase in the ratio of phosphocreatine-to-adenosine-triphosphate (PCr/ATP). METHODS AND RESULTS: Single transgenic Creatine Transporter overexpressing (CrT-OE, n = 7) and dTg mice (CrT-OE and CK, n = 6) mice were anaesthetised with isoflurane to acquire 31P-CMRS measurements of the left ventricle (LV) utilising a two-dimensional (2D), threefold under-sampled density-weighted chemical shift imaging (2D-CSI) sequence, which provided high-resolution data with nominal voxel size of 8.5 µl within 70 min. (1H-) cine-CMR data for cardiac function assessment were obtained in the same imaging session. Under a separate examination, mice received invasive haemodynamic assessment, after which tissue was collected for biochemical analysis. Myocardial creatine levels were elevated in all mouse hearts, but only dTg exhibited significantly elevated CK activity, resulting in a 51% higher PCr/ATP ratio in heart (3.01 ± 0.96 vs. 2.04 ± 0.57-mean ± SD; dTg vs. CrT-OE), that was absent from adjacent skeletal muscle. No significant differences were observed for any parameters of LV structure and function, confirming that augmentation of CK activity does not have unforeseen consequences for the heart. CONCLUSIONS: We have developed an improved 31P-CMRS methodology for the in vivo assessment of energetics in the murine heart which enabled high-resolution imaging within acceptable scan times. Mice over-expressing both creatine and CK in the heart exhibited a synergistic elevation in PCr/ATP that can now be tested for therapeutic potential in models of chronic heart failure.

Myocardial Metabolism in Heart Failure.

PURPOSE OF REVIEW: Myocardial metabolism is intricately linked to cardiac function. Perturbations of cardiac energy metabolism result in an energy-starved heart and the development of contractile dysfunction. In this review, we discuss alterations in myocardial energy supply, transcriptional changes in response to different energy demands, and mitochondrial function in the development of heart failure. RECENT FINDINGS: Recent studies on substrate modulation through modifying energy substrate supply have shown cardioprotective properties. In addition, large cardiovascular outcome trials of anti-diabetic agents have demonstrated prognostic benefit, suggesting the importance of myocardial metabolism in cardiac function. Understanding molecular and transcriptional controls of cardiac metabolism promises new research avenues for metabolic treatment targets. Future studies assessing the impact of substrate modulation on cardiac energetic status and function will better inform development of metabolic therapies.

Long COVID: post-acute sequelae of COVID-19 with a cardiovascular focus.

Emerging as a new epidemic, long COVID or post-acute sequelae of coronavirus disease 2019 (COVID-19), a condition characterized by the persistence of COVID-19 symptoms beyond 3 months, is anticipated to substantially alter the lives of millions of people globally. Cardiopulmonary symptoms including chest pain, shortness of breath, fatigue, and autonomic manifestations such as postural orthostatic tachycardia are common and associated with significant disability, heightened anxiety, and public awareness. A range of cardiovascular (CV) abnormalities has been reported among patients beyond the acute phase and include myocardial inflammation, myocardial infarction, right ventricular dysfunction, and arrhythmias. Pathophysiological mechanisms for delayed complications are still poorly understood, with a dissociation seen between ongoing symptoms and objective measures of cardiopulmonary health. COVID-19 is anticipated to alter the long-term trajectory of many chronic cardiac diseases which are abundant in those at risk of severe disease. In this review, we discuss the definition of long COVID and its epidemiology, with an emphasis on cardiopulmonary symptoms. We further review the pathophysiological mechanisms underlying acute and chronic CV injury, the range of post-acute CV sequelae, and impact of COVID-19 on multiorgan health. We propose a possible model for referral of post-COVID-19 patients to cardiac services and discuss future directions including research priorities and clinical trials that are currently underway to evaluate the efficacy of treatment strategies for long COVID and associated CV sequelae.

Acute vasodilator response testing in the adult Fontan circulation using non-invasive 4D Flow MRI: a proof-of-principle study.

BACKGROUND: Pulmonary vasodilator therapy in Fontan patients can improve exercise tolerance. We aimed to assess the potential for non-invasive testing of acute vasodilator response using four-dimensional (D) flow MRI during oxygen inhalation. MATERIALS AND METHODS: Six patients with well-functioning Fontan circulations were prospectively recruited and underwent cardiac MRI. Ventricular anatomical imaging and 4D Flow MRI were acquired at baseline and during inhalation of oxygen. Data were compared with six age-matched healthy volunteers with 4D Flow MRI scans acquired at baseline. RESULTS: All six patients tolerated the MRI scan well. The dominant ventricle had a left ventricular morphology in all cases. On 4D Flow MRI assessment, two patients (Patients 2 and 6) showed improved cardiac filling with improved preload during oxygen administration, increased mitral inflow, increased maximum E-wave kinetic energy, and decreased systolic peak kinetic energy. Patient 1 showed improved preload only. Patient 5 showed no change, and patient 3 had equivocal results. Patient 4, however, showed a decrease in preload and cardiac filling/function with oxygen. DISCUSSION: Using oxygen as a pulmonary vasodilator to assess increased pulmonary venous return as a marker for positive acute vasodilator response would provide pre-treatment assessment in a more physiological state - the awake patient. This proof-of-concept study showed that it is well tolerated and has shown changes in some stable patients with a Fontan circulation.

Diagnostic accuracy of non-invasive tests for advanced fibrosis in patients with NAFLD: an individual patient data meta-analysis.

OBJECTIVE: Liver biopsy is still needed for fibrosis staging in many patients with non-alcoholic fatty liver disease. The aims of this study were to evaluate the individual diagnostic performance of liver stiffness measurement by vibration controlled transient elastography (LSM-VCTE), Fibrosis-4 Index (FIB-4) and NAFLD (non-alcoholic fatty liver disease) Fibrosis Score (NFS) and to derive diagnostic strategies that could reduce the need for liver biopsies. DESIGN: Individual patient data meta-analysis of studies evaluating LSM-VCTE against liver histology was conducted. FIB-4 and NFS were computed where possible. Sensitivity, specificity and area under the receiver operating curve (AUROC) were calculated. Biomarkers were assessed individually and in sequential combinations. RESULTS: Data were included from 37 primary studies (n=5735; 45% women; median age: 54 years; median body mass index: 30 kg/m2; 33% had type 2 diabetes; 30% had advanced fibrosis). AUROCs of individual LSM-VCTE, FIB-4 and NFS for advanced fibrosis were 0.85, 0.76 and 0.73. Sequential combination of FIB-4 cut-offs (<1.3; ≥2.67) followed by LSM-VCTE cut-offs (<8.0; ≥10.0 kPa) to rule-in or rule-out advanced fibrosis had sensitivity and specificity (95% CI) of 66% (63-68) and 86% (84-87) with 33% needing a biopsy to establish a final diagnosis. FIB-4 cut-offs (<1.3; ≥3.48) followed by LSM cut-offs (<8.0; ≥20.0 kPa) to rule out advanced fibrosis or rule in cirrhosis had a sensitivity of 38% (37-39) and specificity of 90% (89-91) with 19% needing biopsy. CONCLUSION: Sequential combinations of markers with a lower cut-off to rule-out advanced fibrosis and a higher cut-off to rule-in cirrhosis can reduce the need for liver biopsies.

Energetic Basis for Exercise-Induced Pulmonary Congestion in Heart Failure With Preserved Ejection Fraction.

BACKGROUND: Transient pulmonary congestion during exercise is emerging as an important determinant of reduced exercise capacity in heart failure with preserved ejection fraction (HFpEF). We sought to determine whether an abnormal cardiac energetic state underpins this process. METHODS: We recruited patients across the spectrum of diastolic dysfunction and HFpEF (controls, n=11; type 2 diabetes, n=9; HFpEF, n=14; and severe diastolic dysfunction attributable to cardiac amyloidosis, n=9). Cardiac energetics were measured using phosphorus spectroscopy to define the myocardial phosphocreatine to ATP ratio. Cardiac function was assessed by cardiovascular magnetic resonance cine imaging and echocardiography and lung water using magnetic resonance proton density mapping. Studies were performed at rest and during submaximal exercise using a magnetic resonance imaging ergometer. RESULTS: Paralleling the stepwise decline in diastolic function across the groups (E/e' ratio; P<0.001) was an increase in NT-proBNP (N-terminal pro-brain natriuretic peptide; P<0.001) and a reduction in phosphocreatine/ATP ratio (control, 2.15 [2.09, 2.29]; type 2 diabetes, 1.71 [1.61, 1.91]; HFpEF, 1.66 [1.44, 1.89]; cardiac amyloidosis, 1.30 [1.16, 1.53]; P<0.001). During 20-W exercise, lower left ventricular diastolic filling rates (r=0.58; P<0.001), lower left ventricular diastolic reserve (r=0.55; P<0.001), left atrial dilatation (r=-0.52; P<0.001), lower right ventricular contractile reserve (right ventricular ejection fraction change, r=0.57; P<0.001), and right atrial dilation (r=-0.71; P<0.001) were all linked to lower phosphocreatine/ATP ratio. Along with these changes, pulmonary proton density mapping revealed transient pulmonary congestion in patients with HFpEF (+4.4% [0.5, 6.4]; P=0.002) and cardiac amyloidosis (+6.4% [3.3, 10.0]; P=0.004), which was not seen in healthy controls (-0.1% [-1.9, 2.1]; P=0.89) or type 2 diabetes without HFpEF (+0.8% [-1.7, 1.9]; P=0.82). The development of exercise-induced pulmonary congestion was associated with lower phosphocreatine/ATP ratio (r=-0.43; P=0.004). CONCLUSIONS: A gradient of myocardial energetic deficit exists across the spectrum of HFpEF. Even at low workload, this energetic deficit is related to markedly abnormal exercise responses in all 4 cardiac chambers, which is associated with detectable pulmonary congestion. The findings support an energetic basis for transient pulmonary congestion in HFpEF.

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to develop a contrast agent-free technology to replace LGE for faster and cheaper CMR scans. METHODS: A CMR virtual native enhancement (VNE) imaging technology was developed using artificial intelligence. The deep learning model for generating VNE uses multiple streams of convolutional neural networks to exploit and enhance the existing signals in native T1 maps (pixel-wise maps of tissue T1 relaxation times) and cine imaging of cardiac structure and function, presenting them as LGE-equivalent images. The VNE generator was trained using generative adversarial networks. This technology was first developed on CMR datasets from the multicenter Hypertrophic Cardiomyopathy Registry, using hypertrophic cardiomyopathy as an exemplar. The datasets were randomized into 2 independent groups for deep learning training and testing. The test data of VNE and LGE were scored and contoured by experienced human operators to assess image quality, visuospatial agreement, and myocardial lesion burden quantification. Image quality was compared using a nonparametric Wilcoxon test. Intra- and interobserver agreement was analyzed using intraclass correlation coefficients (ICC). Lesion quantification by VNE and LGE were compared using linear regression and ICC. RESULTS: A total of 1348 hypertrophic cardiomyopathy patients provided 4093 triplets of matched T1 maps, cines, and LGE datasets. After randomization and data quality control, 2695 datasets were used for VNE method development and 345 were used for independent testing. VNE had significantly better image quality than LGE, as assessed by 4 operators (n=345 datasets; P<0.001 [Wilcoxon test]). VNE revealed lesions characteristic of hypertrophic cardiomyopathy in high visuospatial agreement with LGE. In 121 patients (n=326 datasets), VNE correlated with LGE in detecting and quantifying both hyperintensity myocardial lesions (r=0.77-0.79; ICC=0.77-0.87; P<0.001) and intermediate-intensity lesions (r=0.70-0.76; ICC=0.82-0.85; P<0.001). The native CMR images (cine plus T1 map) required for VNE can be acquired within 15 minutes and producing a VNE image takes less than 1 second. CONCLUSIONS: VNE is a new CMR technology that resembles conventional LGE but without the need for contrast administration. VNE achieved high agreement with LGE in the distribution and quantification of lesions, with significantly better image quality.