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 (ß-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.

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.

Model-free phasor image analysis of quantitative myocardial T1 mapping.

Model-free phasor image analysis, well established in fluorescence lifetime imaging and only recently applied to qMRI [Formula: see text] data processing, is here adapted and validated for myocardial qMRI [Formula: see text] mapping. Contrarily to routine mono-exponential fitting procedures, phasor enables mapping the lifetime information from all image voxels to a single plot, without resorting to any regression fitting analysis, and describing multi-exponential qMRI decays without biases due to violated modelling assumptions. In this feasibility study, we test the performance of our recently developed full-harmonics phasor method for unravelling partial-volume effects, motion or pathological tissue alteration, respectively on a numerically-simulated dataset, a healthy subject scan, and two pilot patient datasets. Our results show that phasor analysis can be used, as alternative method to fitting analysis or other model-free approaches, to identify motion artifacts or partial-volume effects at the myocardium-blood interface as characteristic deviations, or delineations of scar and remote myocardial tissue in patient data.

Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization.

BACKGROUND: Patients with previous coronary artery bypass graft (CABG) surgery typically have complex coronary disease and remain at high risk of adverse events. Quantitative myocardial perfusion indices predict outcomes in native vessel disease, but their prognostic performance in patients with prior CABG is unknown. OBJECTIVES: In this study, we sought to evaluate whether global stress myocardial blood flow (MBF) and perfusion reserve (MPR) derived from perfusion mapping cardiac magnetic resonance (CMR) independently predict adverse outcomes in patients with prior CABG. METHODS: This was a retrospective analysis of consecutive patients with prior CABG referred for adenosine stress perfusion CMR. Perfusion mapping was performed in-line with automated quantification of MBF. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular events defined as nonfatal myocardial infarction and unplanned revascularization. Associations were evaluated with the use of Cox proportional hazards models after adjusting for comorbidities and CMR parameters. RESULTS: A total of 341 patients (median age 67 years, 86% male) were included. Over a median follow-up of 638 days (IQR: 367-976 days), 81 patients (24%) reached the primary outcome. Both stress MBF and MPR independently predicted outcomes after adjusting for known prognostic factors (regional ischemia, infarction). The adjusted hazard ratio (HR) for 1 mL/g/min of decrease in stress MBF was 2.56 (95% CI: 1.45-4.35) and for 1 unit of decrease in MPR was 1.61 (95% CI: 1.08-2.38). CONCLUSIONS: Global stress MBF and MPR derived from perfusion CMR independently predict adverse outcomes in patients with previous CABG. This effect is independent from the presence of regional ischemia on visual assessment and the extent of previous infarction.

Detailed Assessment of Low-Voltage Zones Localization by Cardiac MRI in Patients With Implantable Devices.

OBJECTIVES: The purpose of this study was to assess the performance and limitations of low-voltage zones (LVZ) localization by optimized late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) scar imaging in patients with cardiac implantable electronic devices (CIEDs). BACKGROUND: Scar evaluation by LGE-CMR can assist ventricular tachycardia (VT) ablation, but challenges with electroanatomical maps coregistration and presence of imaging artefacts from CIED limit accuracy. METHODS: A total of 10 patients underwent VT ablation and preprocedural LGE-CMR using wideband imaging. Scar was segmented from CMR pixel signal intensity maps using commercial software (ADAS-VT, Galgo Medical) with bespoke tools and compared with detailed electroanatomical maps (CARTO). Coregistration of EP and imaging-derived scar was performed using the aorta as a fiducial marker, and the impact of coregistration was determined by assessing intraobserver/interobserver variability and using computer simulations. Spatial smoothing was applied to assess correlation at different spatial resolutions and to reduce noise. RESULTS: Pixel signal intensity maps localized low-voltage zones (V <1.5 mV) with area under the receiver-operating characteristic curve: 0.82 (interquartile range [IQR]: 0.76-0.83), sensitivity 74% (IQR: 71%-77%), and specificity 78% (IQR: 73%-83%) and correlated with bipolar voltage (r = -0.57 [IQR: -0.68 to -0.42]) across patients. In simulations, small random shifts and rotations worsened LVZ localization in at least some cases. The use of the full aortic geometry ensured high reproducibility of LVZ localization (r >0.86 for area under the receiver-operating characteristic curve). Spatial smoothing improved localization of LVZ. Results for LVZ with V <0.5 mV were similar. CONCLUSIONS: In patients with CIEDs, novel wideband CMR sequences and personalized coregistration strategies can localize LVZ with good accuracy and may assist VT ablation procedures.

Improving cardiovascular magnetic resonance access in low- and middle-income countries for cardiomyopathy assessment: rapid cardiovascular magnetic resonance.

AIMS: To evaluate the impact of a simplified, rapid cardiovascular magnetic resonance (CMR) protocol embedded in care and supported by a partner education programme on the management of cardiomyopathy (CMP) in low- and middle-income countries (LMICs). METHODS AND RESULTS: Rapid CMR focused particularly on CMP was implemented in 11 centres, 7 cities, 5 countries, and 3 continents linked to training courses for local professionals. Patients were followed up for 24 months to assess impact. The rate of subsequent adoption was tracked. Five CMR conferences were delivered (920 attendees-potential referrers, radiographers, reporting cardiologists, or radiologists) and five new centres starting CMR. Six hundred and one patients were scanned. Cardiovascular magnetic resonance indications were 24% non-contrast T2* scans [myocardial iron overload (MIO)] and 72% suspected/known cardiomyopathies (including ischaemic and viability). Ninety-eighty per cent of studies were of diagnostic quality. The average scan time was 22 ± 6 min (contrast) and 12 ± 4 min (non-contrast), a potential cost/throughput reduction of between 30 and 60%. Cardiovascular magnetic resonance findings impacted management in 62%, including a new diagnosis in 22% and MIO detected in 30% of non-contrast scans. Nine centres continued using rapid CMR 2 years later (typically 1-2 days per week, 30 min slots). CONCLUSIONS: Rapid CMR of diagnostic quality can be delivered using available technology in LMICs. When embedded in care and a training programme, costs are lower, care is improved, and services can be sustained over time.

Non-invasive characterization of pleural and pericardial effusions using T1 mapping by magnetic resonance imaging.

AIMS: Differentiating exudative from transudative effusions is clinically important and is currently performed via biochemical analysis of invasively obtained samples using Light's criteria. Diagnostic performance is however limited. Biochemical composition can be measured with T1 mapping using cardiovascular magnetic resonance (CMR) and hence may offer diagnostic utility for assessment of effusions. METHODS AND RESULTS: A phantom consisting of serially diluted human albumin solutions (25-200 g/L) was constructed and scanned at 1.5 T to derive the relationship between fluid T1 values and fluid albumin concentration. Native T1 values of pleural and pericardial effusions from 86 patients undergoing clinical CMR studies retrospectively analysed at four tertiary centres. Effusions were classified using Light's criteria where biochemical data was available (n = 55) or clinically in decompensated heart failure patients with presumed transudative effusions (n = 31). Fluid T1 and protein values were inversely correlated both in the phantom (r = -0.992) and clinical samples (r = -0.663, P < 0.0001). T1 values were lower in exudative compared to transudative pleural (3252 ± 207 ms vs. 3596 ± 213 ms, P < 0.0001) and pericardial (2749 ± 373 ms vs. 3337 ± 245 ms, P < 0.0001) effusions. The diagnostic accuracy of T1 mapping for detecting transudates was very good for pleural and excellent for pericardial effusions, respectively [area under the curve 0.88, (95% CI 0.764-0.996), P = 0.001, 79% sensitivity, 89% specificity, and 0.93, (95% CI 0.855-1.000), P < 0.0001, 95% sensitivity; 81% specificity]. CONCLUSION: Native T1 values of effusions measured using CMR correlate well with protein concentrations and may be helpful for discriminating between transudates and exudates. This may help focus the requirement for invasive diagnostic sampling, avoiding unnecessary intervention in patients with unequivocal transudative effusions.

Myocardial Perfusion Imaging After Severe COVID-19 Infection Demonstrates Regional Ischemia Rather Than Global Blood Flow Reduction.

Background: Acute myocardial damage is common in severe COVID-19. Post-mortem studies have implicated microvascular thrombosis, with cardiovascular magnetic resonance (CMR) demonstrating a high prevalence of myocardial infarction and myocarditis-like scar. The microcirculatory sequelae are incompletely characterized. Perfusion CMR can quantify the stress myocardial blood flow (MBF) and identify its association with infarction and myocarditis. Objectives: To determine the impact of the severe hospitalized COVID-19 on global and regional myocardial perfusion in recovered patients. Methods: A case-control study of previously hospitalized, troponin-positive COVID-19 patients was undertaken. The results were compared with a propensity-matched, pre-COVID chest pain cohort (referred for clinical CMR; angiography subsequently demonstrating unobstructed coronary arteries) and 27 healthy volunteers (HV). The analysis used visual assessment for the regional perfusion defects and AI-based segmentation to derive the global and regional stress and rest MBF. Results: Ninety recovered post-COVID patients {median age 64 [interquartile range (IQR) 54-71] years, 83% male, 44% requiring the intensive care unit (ICU)} underwent adenosine-stress perfusion CMR at a median of 61 (IQR 29-146) days post-discharge. The mean left ventricular ejection fraction (LVEF) was 67 ± 10%; 10 (11%) with impaired LVEF. Fifty patients (56%) had late gadolinium enhancement (LGE); 15 (17%) had infarct-pattern, 31 (34%) had non-ischemic, and 4 (4.4%) had mixed pattern LGE. Thirty-two patients (36%) had adenosine-induced regional perfusion defects, 26 out of 32 with at least one segment without prior infarction. The global stress MBF in post-COVID patients was similar to the age-, sex- and co-morbidities of the matched controls (2.53 ± 0.77 vs. 2.52 ± 0.79 ml/g/min, p = 0.10), though lower than HV (3.00 ± 0.76 ml/g/min, p< 0.01). Conclusions: After severe hospitalized COVID-19 infection, patients who attended clinical ischemia testing had little evidence of significant microvascular disease at 2 months post-discharge. The high prevalence of regional inducible ischemia and/or infarction (nearly 40%) may suggest that occult coronary disease is an important putative mechanism for troponin elevation in this cohort. This should be considered hypothesis-generating for future studies which combine ischemia and anatomical assessment.

Myocardial Perfusion Defects in Hypertrophic Cardiomyopathy Mutation Carriers.

Background Impaired myocardial blood flow (MBF) in the absence of epicardial coronary disease is a feature of hypertrophic cardiomyopathy (HCM). Although most evident in hypertrophied or scarred segments, reduced MBF can occur in apparently normal segments. We hypothesized that impaired MBF and myocardial perfusion reserve, quantified using perfusion mapping cardiac magnetic resonance, might occur in the absence of overt left ventricular hypertrophy (LVH) and late gadolinium enhancement, in mutation carriers without LVH criteria for HCM (genotype-positive, left ventricular hypertrophy-negative). Methods and Results A single center, case-control study investigated MBF and myocardial perfusion reserve (the ratio of MBF at stress:rest), along with other pre-phenotypic features of HCM. Individuals with genotype-positive, left ventricular hypertrophy-negative (n=50) with likely pathogenic/pathogenic variants and no evidence of LVH, and matched controls (n=28) underwent cardiac magnetic resonance. Cardiac magnetic resonance identified LVH-fulfilling criteria for HCM in 5 patients who were excluded. Individuals with genotype-positive, left ventricular hypertrophy-negative had longer indexed anterior mitral valve leaflet length (12.52±2.1 versus 11.55±1.6 mm/m2, P=0.03), lower left ventricular end-systolic volume (21.0±6.9 versus 26.7±6.2 mm/m2, P≤0.005) and higher left ventricular ejection fraction (71.9±5.5 versus 65.8±4.4%, P≤0.005). Maximum wall thickness was not significantly different (9.03±1.95 versus 8.37±1.2 mm, P=0.075), and no subject had significant late gadolinium enhancement (minor right ventricle‒insertion point late gadolinium enhancement only). Perfusion mapping demonstrated visual perfusion defects in 9 (20%) carriers versus 0 controls (P=0.011). These were almost all septal or near right ventricle insertion points. Globally, myocardial perfusion reserve was lower in carriers (2.77±0.83 versus 3.24±0.63, P=0.009), with a subendocardial:subepicardial myocardial perfusion reserve gradient (2.55±0.75 versus 3.2±0.65, P=<0.005; 3.01±0.96 versus 3.47±0.75, P=0.026) but equivalent MBF (2.75±0.82 versus 2.65±0.69 mL/g per min, P=0.826). Conclusions Regional and global impaired myocardial perfusion can occur in HCM mutation carriers, in the absence of significant hypertrophy or scarring.

Use of quantitative cardiovascular magnetic resonance myocardial perfusion mapping for characterization of ischemia in patients with left internal mammary coronary artery bypass grafts.

BACKGROUND: Quantitative myocardial perfusion mapping using cardiovascular magnetic resonance (CMR) is validated for myocardial blood flow (MBF) estimation in native vessel coronary artery disease (CAD). Following coronary artery bypass graft (CABG) surgery, perfusion defects are often detected in territories supplied by the left internal mammary artery (LIMA) graft, but their interpretation and subsequent clinical management is variable. METHODS: We assessed myocardial perfusion using quantitative CMR perfusion mapping in 38 patients with prior CABG surgery, all with angiographically-proven patent LIMA grafts to the left anterior descending coronary artery (LAD) and no prior infarction in the LAD territory. Factors potentially determining MBF in the LIMA-LAD myocardial territory, including the impact of delayed contrast arrival through the LIMA graft were evaluated. RESULTS: Perfusion defects were reported on blinded visual analysis in the LIMA-LAD territory in 27 (71%) cases, despite LIMA graft patency and no LAD infarction. Native LAD chronic total occlusion (CTO) was a strong independent predictor of stress MBF (B = - 0.41, p = 0.014) and myocardial perfusion reserve (MPR) (B = - 0.56, p = 0.005), and was associated with reduced stress MBF in the basal (1.47 vs 2.07 ml/g/min; p = 0.002) but not the apical myocardial segments (1.52 vs 1.87 ml/g/min; p = 0.057). Extending the maximum arterial time delay incorporated in the quantitative perfusion algorithm, resulted only in a small increase (3.4%) of estimated stress MBF. CONCLUSIONS: Perfusion defects are frequently detected in LIMA-LAD subtended territories post CABG despite LIMA patency. Although delayed contrast arrival through LIMA grafts causes a small underestimation of MBF, perfusion defects are likely to reflect true reductions in myocardial blood flow, largely due to proximal native LAD disease.

Prospective Case-Control Study of Cardiovascular Abnormalities 6 Months Following Mild COVID-19 in Healthcare Workers.

OBJECTIVES: The purpose of this study was to detect cardiovascular changes after mild severe acute respiratory syndrome-coronavirus-2 infection. BACKGROUND: Concern exists that mild coronavirus disease 2019 may cause myocardial and vascular disease. METHODS: Participants were recruited from COVIDsortium, a 3-hospital prospective study of 731 health care workers who underwent first-wave weekly symptom, polymerase chain reaction, and serology assessment over 4 months, with seroconversion in 21.5% (n = 157). At 6 months post-infection, 74 seropositive and 75 age-, sex-, and ethnicity-matched seronegative control subjects were recruited for cardiovascular phenotyping (comprehensive phantom-calibrated cardiovascular magnetic resonance and blood biomarkers). Analysis was blinded, using objective artificial intelligence analytics where available. RESULTS: A total of 149 subjects (mean age 37 years, range 18 to 63 years, 58% women) were recruited. Seropositive infections had been mild with case definition, noncase definition, and asymptomatic disease in 45 (61%), 18 (24%), and 11 (15%), respectively, with 1 person hospitalized (for 2 days). Between seropositive and seronegative groups, there were no differences in cardiac structure (left ventricular volumes, mass, atrial area), function (ejection fraction, global longitudinal shortening, aortic distensibility), tissue characterization (T1, T2, extracellular volume fraction mapping, late gadolinium enhancement) or biomarkers (troponin, N-terminal pro-B-type natriuretic peptide). With abnormal defined by the 75 seronegatives (2 SDs from mean, e.g., ejection fraction <54%, septal T1 >1,072 ms, septal T2 >52.4 ms), individuals had abnormalities including reduced ejection fraction (n = 2, minimum 50%), T1 elevation (n = 6), T2 elevation (n = 9), late gadolinium enhancement (n = 13, median 1%, max 5% of myocardium), biomarker elevation (borderline troponin elevation in 4; all N-terminal pro-B-type natriuretic peptide normal). These were distributed equally between seropositive and seronegative individuals. CONCLUSIONS: Cardiovascular abnormalities are no more common in seropositive versus seronegative otherwise healthy, workforce representative individuals 6 months post-mild severe acute respiratory syndrome-coronavirus-2 infection.

Prognostic Value of Pulmonary Transit Time and Pulmonary Blood Volume Estimation Using Myocardial Perfusion CMR.

OBJECTIVES: The purpose of this study was to explore the prognostic significance of PTT and PBVi using an automated, inline method of estimation using CMR. BACKGROUND: Pulmonary transit time (PTT) and pulmonary blood volume index (PBVi) (the product of PTT and cardiac index), are quantitative biomarkers of cardiopulmonary status. The development of cardiovascular magnetic resonance (CMR) quantitative perfusion mapping permits their automated derivation, facilitating clinical adoption. METHODS: In this retrospective 2-center study of patients referred for clinical myocardial perfusion assessment using CMR, analysis of right and left ventricular cavity arterial input function curves from first pass perfusion was performed automatically (incorporating artificial intelligence techniques), allowing estimation of PTT and subsequent derivation of PBVi. Association with major adverse cardiovascular events (MACE) and all-cause mortality were evaluated using Cox proportional hazard models, after adjusting for comorbidities and CMR parameters. RESULTS: A total of 985 patients (67% men, median age 62 years [interquartile range (IQR): 52 to 71 years]) were included, with median left ventricular ejection fraction (LVEF) of 62% (IQR: 54% to 69%). PTT increased with age, male sex, atrial fibrillation, and left atrial area, and reduced with LVEF, heart rate, diabetes, and hypertension (model r2 = 0.57). Over a median follow-up period of 28.6 months (IQR: 22.6 to 35.7 months), MACE occurred in 61 (6.2%) patients. After adjusting for prognostic factors, both PTT and PBVi independently predicted MACE, but not all-cause mortality. There was no association between cardiac index and MACE. For every 1 × SD (2.39-s) increase in PTT, the adjusted hazard ratio for MACE was 1.43 (95% confidence interval [CI]: 1.10 to 1.85; p = 0.007). The adjusted hazard ratio for 1 × SD (118 ml/m2) increase in PBVi was 1.42 (95% CI: 1.13 to 1.78; p = 0.002). CONCLUSIONS: Pulmonary transit time (and its derived parameter pulmonary blood volume index), measured automatically without user interaction as part of CMR perfusion mapping, independently predicted adverse cardiovascular outcomes. These biomarkers may offer additional insights into cardiopulmonary function beyond conventional predictors including ejection fraction.

Noninvasive rapid cardiac magnetic resonance for the assessment of cardiomyopathies in low-middle income countries.

Introduction: Cardiac Magnetic Resonance (CMR) is a crucial diagnostic imaging test that redefines diagnosis and enables targeted therapies, but the access to CMR is limited in low-middle Income Countries (LMICs) even though cardiovascular disease is an emergent primary cause of mortality in LMICs. New abbreviated CMR protocols can be less expensive, faster, whilst maintaining accuracy, potentially leading to a higher utilization in LMICs.Areas covered: This article will review cardiovascular disease in LMICs and the current role of CMR in cardiac diagnosis and enable targeted therapy, discussing the main obstacles to prevent the adoption of CMR in LMICs. We will then review the potential utility of abbreviated, cost-effective CMR protocols to improve cardiac diagnosis and care, the clinical indications of the exam, current evidence and future directions.Expert opinion: Rapid CMR protocols, provided that they are utilized in potentially high yield cases, could reduce cost and increase effectiveness. The adoption of these protocols, their integration into care pathways, and prioritizing key treatable diagnoses can potentially improve patient care. Several LMIC countries are now pioneering these approaches and the application of rapid CMR protocols appears to have a bright future if delivered effectively.

Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.

BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT measurement and compared precision (reproducibility) with that of 11 international experts, using a dataset of patients with hypertrophic cardiomyopathy. METHODS: 60 adult patients with hypertrophic cardiomyopathy, including those carrying hypertrophic cardiomyopathy gene mutations, were recruited at three institutes in the UK from August, 2018, to September, 2019: Barts Heart Centre, University College London Hospital (The Heart Hospital), and Leeds Teaching Hospitals NHS Trust. Participants had two cardiovascular magnetic resonance scans (test and retest) on the same day, ensuring no biological variability, using four cardiac MRI scanner models represented across two manufacturers and two field strengths. End-diastolic short-axis MWT was measured in test and retest by 11 international experts (from nine centres in six countries) and an automated machine learning method, which was trained to segment endocardial and epicardial contours on an independent, multicentre, multidisease dataset of 1923 patients. Machine learning MWT measurement was done with a method based on solving Laplace's equation. To assess test-retest reproducibility, we estimated the absolute test-retest MWT difference (precision), the coefficient of variation (CoV) for duplicate measurements, and the number of patients reclassified between test and retest according to different thresholds (MWT >15 mm and >30 mm). We calculated the sample size required to detect a prespecified MWT change between pairs of scans for machine learning and each expert. FINDINGS: 1440 MWT measurements were analysed, corresponding to two scans from 60 participants by 12 observers (11 experts and machine learning). Experts differed in the MWT they measured, ranging from 14·9 mm (SD 4·2) to 19·0 mm (4·7; p<0·0001 for trend). Machine learning-measured mean MWT was 16·8 mm (4·1). Machine learning precision was superior, with a test-retest difference of 0·7 mm (0·6) compared with experts, who ranged from 1·1 mm (0·9) to 3·7 mm (2·0; p values for machine learning vs expert comparison ranging from <0·0001 to 0·0073) and a significantly lower CoV than for all experts (4·3% [95% CI 3·3-5·1] vs 5·7-12·1% across experts). On average, 38 (64%) patients were designated as having MWT greater than 15 mm by machine learning compared with 27 (45%) to 50 (83%) patients by experts; five (8%) patients were reclassified in test-retest by machine learning compared with four (7%) to 12 (20%) by experts. With a cutoff point of more than 30 mm for implantable cardioverter-defibrillator, three experts would have changed recommendations between tests a total of four times, but machine learning was consistent. Using machine learning, a clinical trial to detect a 2 mm MWT change would need 2·3 times (range 1·6-4·6) fewer patients. INTERPRETATION: In this preliminary study, machine learning MWT measurement in hypertrophic cardiomyopathy is superior to human experts with potential implications for diagnosis, risk stratification, and clinical trials. FUNDING: European Regional Development Fund and Barts Charity.

Measurement of T1 Mapping in Patients With Cardiac Devices: Off-Resonance Error Extends Beyond Visual Artifact but Can Be Quantified and Corrected.

Background: Measurement of myocardial T1 is increasingly incorporated into standard cardiovascular magnetic resonance (CMR) protocols, however accuracy may be reduced in patients with metallic cardiovascular implants. Measurement is feasible in segments free from visual artifact, but there may still be off-resonance induced error. Aim: To quantify off-resonance induced T1 error in patients with metallic cardiovascular implants, and validate a method for error correction for a conventional MOLLI pulse sequence. Methods: Twenty-four patients with cardiac implantable electronic devices (CIEDs: 46% permanent pacemakers, PPMs; 33% implantable loop recorders, ILRs; and 21% implantable cardioverter-defibrillators, ICDs); and 31 patients with aortic valve replacement (AVR) (45% metallic) were studied. Paired mid-myocardial short-axis MOLLI and single breath-hold off-resonance field maps were acquired at 1.5 T. T1 values were measured by AHA segment, and segments with visual artifact were excluded. T1 correction was applied using a published relationship between off-resonance and T1. The accuracy of the correction was assessed in 10 healthy volunteers by measuring T1 before and after external placement of an ICD generator next to the chest to generate off-resonance. Results: T1 values in healthy volunteers with an ICD were underestimated compared to without (967 ± 52 vs. 997 ± 26 ms respectively, p = 0.0001), but were similar after correction (p = 0.57, residual difference 2 ± 27 ms). Artifact was visible in 4 ± 12, 42 ± 31, and 53 ± 27% of AHA segments in patients with ILRs, PPMs, and ICDs, respectively. In segments without artifact, T1 was underestimated by 63 ms (interquartile range: 7-143) per patient. The greatest error for patients with ILRs, PPMs and ICDs were 79, 146, and 191 ms, respectively. The presence of an AVR did not generate T1 error. Conclusion: Even when there is no visual artifact, there is error in T1 in patients with CIEDs, but not AVRs. Off-resonance field map acquisition can detect error in measured T1, and a correction can be applied to quantify T1 MOLLI accurately.

Non-invasive Ischaemia Testing in Patients With Prior Coronary Artery Bypass Graft Surgery: Technical Challenges, Limitations, and Future Directions.

Coronary artery bypass graft (CABG) surgery effectively relieves symptoms and improves outcomes. However, patients undergoing CABG surgery typically have advanced coronary atherosclerotic disease and remain at high risk for symptom recurrence and adverse events. Functional non-invasive testing for ischaemia is commonly used as a gatekeeper for invasive coronary and graft angiography, and for guiding subsequent revascularisation decisions. However, performing and interpreting non-invasive ischaemia testing in patients post CABG is challenging, irrespective of the imaging modality used. Multiple factors including advanced multi-vessel native vessel disease, variability in coronary hemodynamics post-surgery, differences in graft lengths and vasomotor properties, and complex myocardial scar morphology are only some of the pathophysiological mechanisms that complicate ischaemia evaluation in this patient population. Systematic assessment of the impact of these challenges in relation to each imaging modality may help optimize diagnostic test selection by incorporating clinical information and individual patient characteristics. At the same time, recent technological advances in cardiac imaging including improvements in image quality, wider availability of quantitative techniques for measuring myocardial blood flow and the introduction of artificial intelligence-based approaches for image analysis offer the opportunity to re-evaluate the value of ischaemia testing, providing new insights into the pathophysiological processes that determine outcomes in this patient population.

The myocardial phenotype of Fabry disease pre-hypertrophy and pre-detectable storage.

AIMS: Cardiac involvement in Fabry disease (FD) occurs prior to left ventricular hypertrophy (LVH) and is characterized by low myocardial native T1 with sphingolipid storage reflected by cardiovascular magnetic resonance (CMR) and electrocardiogram (ECG) changes. We hypothesize that a pre-storage myocardial phenotype might occur even earlier, prior to T1 lowering. METHODS AND RESULTS: FD patients and age-, sex-, and heart rate-matched healthy controls underwent same-day ECG with advanced analysis and multiparametric CMR [cines, global longitudinal strain (GLS), T1 and T2 mapping, stress perfusion (myocardial blood flow, MBF), and late gadolinium enhancement (LGE)]. One hundred and fourteen Fabry patients (46 ± 13 years, 61% female) and 76 controls (49 ± 15 years, 50% female) were included. In pre-LVH FD (n = 72, 63%), a low T1 (n = 32/72, 44%) was associated with a constellation of ECG and functional abnormalities compared to normal T1 FD patients and controls. However, pre-LVH FD with normal T1 (n = 40/72, 56%) also had abnormalities compared to controls: reduced GLS (-18 ± 2 vs. -20 ± 2%, P < 0.001), microvascular changes (lower MBF 2.5 ± 0.7 vs. 3.0 ± 0.8 mL/g/min, P = 0.028), subtle T2 elevation (50 ± 4 vs. 48 ± 2 ms, P = 0.027), and limited LGE (%LGE 0.3 ± 1.1 vs. 0%, P = 0.004). ECG abnormalities included shorter P-wave duration (88 ± 12 vs. 94 ± 15 ms, P = 0.010) and T-wave peak time (Tonset - Tpeak; 104 ± 28 vs. 115 ± 20 ms, P = 0.015), resulting in a more symmetric T wave with lower T-wave time ratio (Tonset - Tpeak)/(Tpeak - Tend) (1.5 ± 0.4 vs. 1.8 ± 0.4, P < 0.001) compared to controls. CONCLUSION: FD has a measurable myocardial phenotype pre-LVH and pre-detectable myocyte storage with microvascular dysfunction, subtly impaired GLS and altered atrial depolarization and ventricular repolarization intervals.

The Prognostic Significance of Quantitative Myocardial Perfusion: An Artificial Intelligence-Based Approach Using Perfusion Mapping.

BACKGROUND: Myocardial perfusion reflects the macro- and microvascular coronary circulation. Recent quantitation developments using cardiovascular magnetic resonance perfusion permit automated measurement clinically. We explored the prognostic significance of stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR, the ratio of stress to rest MBF). METHODS: A 2-center study of patients with both suspected and known coronary artery disease referred clinically for perfusion assessment. Image analysis was performed automatically using a novel artificial intelligence approach deriving global and regional stress and rest MBF and MPR. Cox proportional hazard models adjusting for comorbidities and cardiovascular magnetic resonance parameters sought associations of stress MBF and MPR with death and major adverse cardiovascular events (MACE), including myocardial infarction, stroke, heart failure hospitalization, late (>90 day) revascularization, and death. RESULTS: A total of 1049 patients were included with a median follow-up of 605 (interquartile range, 464-814) days. There were 42 (4.0%) deaths and 188 MACE in 174 (16.6%) patients. Stress MBF and MPR were independently associated with both death and MACE. For each 1 mL·g-1·min-1 decrease in stress MBF, the adjusted hazard ratios for death and MACE were 1.93 (95% CI, 1.08-3.48, P=0.028) and 2.14 (95% CI, 1.58-2.90, P<0.0001), respectively, even after adjusting for age and comorbidity. For each 1 U decrease in MPR, the adjusted hazard ratios for death and MACE were 2.45 (95% CI, 1.42-4.24, P=0.001) and 1.74 (95% CI, 1.36-2.22, P<0.0001), respectively. In patients without regional perfusion defects on clinical read and no known macrovascular coronary artery disease (n=783), MPR remained independently associated with death and MACE, with stress MBF remaining associated with MACE only. CONCLUSIONS: In patients with known or suspected coronary artery disease, reduced MBF and MPR measured automatically inline using artificial intelligence quantification of cardiovascular magnetic resonance perfusion mapping provides a strong, independent predictor of adverse cardiovascular outcomes.

Healthcare Workers Bioresource: Study outline and baseline characteristics of a prospective healthcare worker cohort to study immune protection and pathogenesis in COVID-19.

Background: Most biomedical research has focused on sampling COVID-19 patients presenting to hospital with advanced disease, with less focus on the asymptomatic or paucisymptomatic. We established a bioresource with serial sampling of health care workers (HCWs) designed to obtain samples before and during mainly mild disease, with follow-up sampling to evaluate the quality and duration of immune memory. Methods: We conducted a prospective study on HCWs from three hospital sites in London, initially at a single centre (recruited just prior to first peak community transmission in London), but then extended to multiple sites 3 weeks later (recruitment still ongoing, target n=1,000). Asymptomatic participants attending work complete a health questionnaire, and provide a nasal swab (for SARS-CoV-2 RNA by RT-PCR tests) and blood samples (mononuclear cells, serum, plasma, RNA and DNA are biobanked) at 16 weekly study visits, and at 6 and 12 months. Results: Preliminary baseline results for the first 731 HCWs (400 single-centre, 331 multicentre extension) are presented. Mean age was 38±11 years; 67% are female, 31% nurses, 20% doctors, and 19% work in intensive care units. COVID-19-associated risk factors were: 37% black, Asian or minority ethnicities; 18% smokers; 13% obesity; 11% asthma; 7% hypertension and 2% diabetes mellitus. At baseline, 41% reported symptoms in the preceding 2 weeks. Preliminary test results from the initial cohort (n=400) are available: PCR at baseline for SARS-CoV-2 was positive in 28 of 396 (7.1%, 95% CI 4.9-10.0%) and 15 of 385 (3.9%, 2.4-6.3%) had circulating IgG antibodies. Conclusions: This COVID-19 bioresource established just before the peak of infections in the UK will provide longitudinal assessments of incident infection and immune responses in HCWs through the natural time course of disease and convalescence. The samples and data from this bioresource are available to academic collaborators by application  https://covid-consortium.com/application-for-samples/.