Improved delivery of rate-adaptive pacing using an impedance-derived contractility sensor in high-intensity exercise: A case report.

Effective rate-adaptive pacing may be difficult in the presence of atrial fibrillation (AF), and is important during high-intensity exercise. This case presents a 74-year-old elite cyclist with AF and a biventricular pacemaker after atrioventricular (AV) node ablation. He reported sudden breathlessness due to heart rate drops, caused by breaching the artefact threshold on the minute-ventilation sensor. He was exchanged to a generator with an impedance-derived contractility sensor (closed-loop stimulation), resulting in resolution of symptoms, and no further rate drops. This is the first description of the utility of closed-loop stimulation in high-intensity exercise.

Evidence to support magnetic resonance conditional labelling of all pacemaker and defibrillator leads in patients with cardiac implantable electronic devices.

AIMS: Many cardiac pacemakers and defibrillators are not approved by regulators for magnetic resonance imaging (MRI). Even following generator exchange to an approved magnetic resonance (MR)-conditional model, many systems remain classified 'non-MR conditional' due to the leads. This classification makes patient access to MRI challenging, but there is no evidence of increased clinical risk. We compared the effect of MRI on non-MR conditional and MR-conditional pacemaker and defibrillator leads. METHODS AND RESULTS: Patients undergoing clinical 1.5T MRI with pacemakers and defibrillators in three centres over 5 years were included. Magnetic resonance imaging protocols were similar for MR-conditional and non-MR conditional systems. Devices were interrogated pre- and immediately post-scan, and at follow-up, and adverse clinical events recorded. Lead parameter changes peri-scan were stratified by MR-conditional labelling. A total of 1148 MRI examinations were performed in 970 patients (54% non-MR conditional systems, 39% defibrillators, 15% pacing-dependent) with 2268 leads. There were no lead-related adverse clinical events, and no clinically significant immediate or late lead parameter changes following MRI in either MR-conditional or non-MR conditional leads. Small reductions in atrial and right ventricular sensed amplitudes and impedances were similar between groups, with no difference in the proportion of leads with parameter changes greater than pre-defined thresholds (7.1%, 95% confidence interval: 6.1-8.3). CONCLUSIONS: There was no increased risk of MRI in patients with non-MR conditional pacemaker or defibrillator leads when following recommended protocols. Standardizing MR conditions for all leads would significantly improve access to MRI by enabling patients to be scanned in non-specialist centres, with no discernible incremental risk.

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.

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.

Quantitative cardiac MRI.

Cardiac MRI has become an indispensable imaging modality in the investigation of patients with suspected heart disease. It has emerged as the gold standard test for cardiac function, volumes, and mass and allows noninvasive tissue characterization and the assessment of myocardial perfusion. Quantitative MRI already has a key role in the development and incorporation of machine learning in clinical imaging, potentially offering major improvements in both workflow efficiency and diagnostic accuracy. As the clinical applications of a wide range of quantitative cardiac MRI techniques are being explored and validated, we are expanding our capabilities for earlier detection, monitoring, and risk stratification of disease, potentially guiding personalized management decisions in various cardiac disease models. In this article we review established and emerging quantitative techniques, their clinical applications, highlight novel advances, and appraise their clinical diagnostic potential. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:693-711.

Quantitative myocardial perfusion in coronary artery disease: A perfusion mapping study.

BACKGROUND: Cardiac MR stress perfusion remains a qualitative technique in clinical practice due to technical and postprocessing challenges. However, automated inline perfusion mapping now permits myocardial blood flow (MBF, ml/g/min) quantification on-the-fly without user input. PURPOSE: To investigate the diagnostic performance of this novel technique in detecting occlusive coronary artery disease (CAD) in patients scheduled to undergo coronary angiography. STUDY TYPE: Prospective, observational. SUBJECTS: Fifty patients with suspected CAD and 24 healthy volunteers. FIELD STRENGTH: 1.5T. SEQUENCE: "Dual" sequence multislice 2D saturation recovery. ASSESSMENT: All patients underwent cardiac MR with perfusion mapping and invasive coronary angiography; the healthy volunteers had MR with perfusion mapping alone. STATISTICAL TESTS: Comparison between numerical variables was performed using an independent t-test. Receiver operator characteristic (ROC) curves were generated for transmyocardial, endocardial stress MBF, and myocardial perfusion reserve (MPR, the stress:rest MBF ratio) to diagnose severe (>70%) stenoses as measured by 3D quantitative coronary angiography (QCA). ROC curves were compared by the method of DeLong et al. RESULTS: Compared with volunteers, patients had lower stress MBF and MPR even in vessels with <50% stenosis (2.00 vs. 3.08 ml/g/min, respectively). As stenosis severity increased (<50%, 50-70%, >70%), MBF and MPR decreased. To diagnose occlusive (>70%) CAD, endocardial and transmyocardial stress MBF were superior to MPR (area under the curve 0.92 [95% CI 0.86-0.97] vs. 0.90 [95% CI 0.84-0.95] and 0.80 [95% CI 0.72-0.87], respectively). An endocardial threshold of 1.31 ml/g/min provided a per-coronary artery sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 90%, 82%, 50%, and 98%, with a per-patient diagnostic performance of 100%, 66%, 57%, and 100%, respectively. DATA CONCLUSION: Perfusion mapping can diagnose occlusive CAD with high accuracy and, in particular, high sensitivity and NPV make it a potential "rule-out" test. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:756-762.

Advanced Imaging Modalities to Monitor for Cardiotoxicity.

OPINION STATEMENT: Early detection and treatment of cardiotoxicity from cancer therapies is key to preventing a rise in adverse cardiovascular outcomes in cancer patients. Over-diagnosis of cardiotoxicity in this context is however equally hazardous, leading to patients receiving suboptimal cancer treatment, thereby impacting cancer outcomes. Accurate screening therefore depends on the widespread availability of sensitive and reproducible biomarkers of cardiotoxicity, which can clearly discriminate early disease. Blood biomarkers are limited in cardiovascular disease and clinicians generally still use generic screening with ejection fraction, based on historical local expertise and resources. Recently, however, there has been growing recognition that simple measurement of left ventricular ejection fraction using 2D echocardiography may not be optimal for screening: diagnostic accuracy, reproducibility and feasibility are limited. Modern cancer therapies affect many myocardial pathways: inflammatory, fibrotic, metabolic, vascular and myocyte function, meaning that multiple biomarkers may be needed to track myocardial cardiotoxicity. Advanced imaging modalities including cardiovascular magnetic resonance (CMR), computed tomography (CT) and positron emission tomography (PET) add improved sensitivity and insights into the underlying pathophysiology, as well as the ability to screen for other cardiotoxicities including coronary artery, valve and pericardial diseases resulting from cancer treatment. Delivering screening for cardiotoxicity using advanced imaging modalities will however require a significant change in current clinical pathways, with incorporation of machine learning algorithms into imaging analysis fundamental to improving efficiency and precision. In the future, we should aspire to personalized rather than generic screening, based on a patient's individual risk factors and the pathophysiological mechanisms of the cancer treatment they are receiving. We should aspire that progress in cardiooncology is able to track progress in oncology, and to ensure that the current 'one size fits all' approach to screening be obsolete in the very near future.

Diagnostic performance of T1 and T2 mapping to detect intramyocardial hemorrhage in reperfused ST-segment elevation myocardial infarction (STEMI) patients.

PURPOSE: To investigate the performance of T1 and T2 mapping to detect intramyocardial hemorrhage (IMH) in ST-segment elevation myocardial infarction (STEMI) patients treated by primary percutaneous coronary intervention (PPCI). MATERIALS AND METHODS: Fifty STEMI patients were prospectively recruited between August 2013 and July 2014 following informed consent. Forty-eight patients completed a 1.5T cardiac magnetic resonance imaging (MRI) with native T1 , T2 , and T2* maps at 4 ± 2 days. Receiver operating characteristic (ROC) analyses were performed to assess the performance of T1 and T2 to detect IMH. RESULTS: The mean age was 59 ± 13 years old and 88% (24/48) were male. In all, 39 patients had interpretable T2* maps and 26/39 (67%) of the patients had IMH ( T2* <20 msec on T2* maps). Both T1 and T2 values of the hypointense core within the area-at-risk (AAR) performed equally well to detect IMH (T1 maps AUC 0.86 [95% confidence interval [CI] 0.72-0.99] versus T2 maps AUC 0.86 [95% CI 0.74-0.99]; P = 0.94). Using the binary assessment of presence or absence of a hypointense core on the maps, the diagnostic performance of T1 and T2 remained equally good (T1 AUC 0.87 [95% CI 0.73-1.00] versus T2 AUC 0.85 [95% CI 0.71-0.99]; P = 0.90) with good sensitivity and specificity (T1 : 88% and 85% and T2 : 85% and 85%, respectively). CONCLUSION: The presence of a hypointense core on the T1 and T2 maps can detect IMH equally well and with good sensitivity and specificity in reperfused STEMI patients and could be used as an alternative when T2* images are not acquired or are not interpretable. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:877-886.

Defining left ventricular remodeling following acute ST-segment elevation myocardial infarction using cardiovascular magnetic resonance.

BACKGROUND: The assessment of post-myocardial infarction (MI) left ventricular (LV) remodeling by cardiovascular magnetic resonance (CMR) currently uses criteria defined by echocardiography. Our aim was to provide CMR criteria for assessing LV remodeling following acute MI. METHODS: Firstly, 40 reperfused ST-segment elevation myocardial infarction (STEMI) patients with paired acute (4 ± 2 days) and follow-up (5 ± 2 months) CMR scans were analyzed by 2 independent reviewers and the minimal detectable changes (MDCs) for percentage change in LV end-diastolic volume (%ΔLVEDV), LV end-systolic volume (%ΔLVESV), and LV ejection fraction (%ΔLVEF) between the acute and follow-up scans were determined. Secondly, in 146 reperfused STEMI patients, receiver operator characteristic curve analyses for predicting LVEF <50% at follow-up (as a surrogate for clinical poor clinical outcome) were undertaken to obtain cut-off values for %ΔLVEDV and %ΔLVESV. RESULTS: The MDCs for %ΔLVEDV, %ΔLVESV, and %ΔLVEF were similar at 12%, 12%, 13%, respectively. The cut-off values for predicting LVEF < 50% at follow-up were 11% for %ΔLVEDV on receiver operating characteristic curve analysis (area under the curve (AUC) 0.75, 95% CI 0.6 to 0.83, sensitivity 72% specificity 70%), and 5% for %ΔLVESV (AUC 0.83, 95% CI 0.77 to 0.90, sensitivity and specificity 78%). Using cut-off MDC values (higher than the clinically important cut-off values) of 12% for both %ΔLVEDV and %ΔLVESV, 4 main patterns of LV remodeling were identified in our cohort: reverse LV remodeling (LVEF predominantly improved); no LV remodeling (LVEF predominantly unchanged); adverse LV remodeling with compensation (LVEF predominantly improved); and adverse LV remodeling (LVEF unchanged or worsened). CONCLUSIONS: The MDCs for %ΔLVEDV and %ΔLVESV between the acute and follow-up CMR scans of 12% each may be used to define adverse or reverse LV remodeling post-STEMI. The MDC for %ΔLVEF of 13%, relative to baseline, provides the minimal effect size required for investigating treatments aimed at improving LVEF following acute STEMI.

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).

[11C]metomidate PET-CT versus adrenal vein sampling for diagnosing surgically curable primary aldosteronism: a prospective, within-patient trial.

Primary aldosteronism (PA) due to a unilateral aldosterone-producing adenoma is a common cause of hypertension. This can be cured, or greatly improved, by adrenal surgery. However, the invasive nature of the standard pre-surgical investigation contributes to fewer than 1% of patients with PA being offered the chance of a cure. The primary objective of our prospective study of 143 patients with PA ( NCT02945904 ) was to compare the accuracy of a non-invasive test, [11C]metomidate positron emission tomography computed tomography (MTO) scanning, with adrenal vein sampling (AVS) in predicting the biochemical remission of PA and the resolution of hypertension after surgery. A total of 128 patients reached 6- to 9-month follow-up, with 78 (61%) treated surgically and 50 (39%) managed medically. Of the 78 patients receiving surgery, 77 achieved one or more PA surgical outcome criterion for success. The accuracies of MTO at predicting biochemical and clinical success following adrenalectomy were, respectively, 72.7 and 65.4%. For AVS, the accuracies were 63.6 and 61.5%. MTO was not significantly superior, but the differences of 9.1% (95% confidence interval = -6.5 to 24.1%) and 3.8% (95% confidence interval = -11.9 to 9.4) lay within the pre-specified -17% margin for non-inferiority (P = 0.00055 and P = 0.0077, respectively). Of 24 serious adverse events, none was considered related to either investigation and 22 were fully resolved. MTO enables non-invasive diagnosis of unilateral PA.

Echocardiographic and Cardiac Magnetic Resonance Imaging-Derived Strains in Relation to Late Gadolinium Enhancement in Hypertrophic Cardiomyopathy.

We compared speckle tracking echocardiography (STE) and feature tracking cardiovascular magnetic resonance (FT-CMR) in patients with hypertrophic cardiomyopathy (HC) with a varying extent of fibrosis as defined by late gadolinium enhancement to look at the level of agreement between methods and their ability to relate those to myocardial fibrosis. At 2 reference centers, 79 patients with HC and 16 volunteers (the control group) underwent STE and CMR with late gadolinium enhancement and FT-CMR. Patients were classified into 3 categories: no detectable, limited, and extensive fibrosis. Global longitudinal strain (GLS) and global radial strain (GRS) were derived using FT-CMR and STE. STE-derived GRS was decreased in all HC categories compared with the control group (p <0.001), whereas FT-CMR GRS was reduced only in patients with HC with fibrosis (p <0.05). Reduced STE-derived GLS was associated with extensive fibrosis (p <0.05) and a value less than -15.2% identified those with extensive fibrosis (sensitivity 79%, specificity 92%, area under the curve 0.863, 95% confidence interval [CI] 0.76 to 0.97, p <0.001). Inter-modality agreement was moderate for STE versus CMR-GLS (overall population intra-class correlation coefficient = 0.615, 95% CI 0.42 to 0.75, p <0.001; patients with HC 0.63, 0.42 to 0.76, p <0.001) and GRS (overall population intra-class correlation coefficient = 0.601, 95% CI 0.397 to 0.735, p <0.001). A low level of agreement for GRS was seen between methods in patients with HC. In conclusion, strain indexes measured using echocardiography and CMR are reduced in patients with HC compared with the control group and correlate well with the burden of myocardial fibrosis. Reduced STE-GLS can identify patients with extensive fibrosis, but whether there is an added value for risk stratification for sudden cardiac death remains to be determined.

Immune boosting by B.1.1.529 (Omicron) depends on previous SARS-CoV-2 exposure.

The Omicron, or Pango lineage B.1.1.529, variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) carries multiple spike mutations with high transmissibility and partial neutralizing antibody (nAb) escape. Vaccinated individuals show protection against severe disease, often attributed to primed cellular immunity. We investigated T and B cell immunity against B.1.1.529 in triple BioNTech BNT162b2 messenger RNA-vaccinated health care workers (HCWs) with different SARS-CoV-2 infection histories. B and T cell immunity against previous variants of concern was enhanced in triple-vaccinated individuals, but the magnitude of T and B cell responses against B.1.1.529 spike protein was reduced. Immune imprinting by infection with the earlier B.1.1.7 (Alpha) variant resulted in less durable binding antibody against B.1.1.529. Previously infection-naïve HCWs who became infected during the B.1.1.529 wave showed enhanced immunity against earlier variants but reduced nAb potency and T cell responses against B.1.1.529 itself. Previous Wuhan Hu-1 infection abrogated T cell recognition and any enhanced cross-reactive neutralizing immunity on infection with B.1.1.529.

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.

Age matters: differences in exercise-induced cardiovascular remodelling in young and middle aged healthy sedentary individuals.

AIMS: Remodelling of the cardiovascular system (including heart and vasculature) is a dynamic process influenced by multiple physiological and pathological factors. We sought to understand whether remodelling in response to a stimulus, exercise training, altered with healthy ageing. METHODS: A total of 237 untrained healthy male and female subjects volunteering for their first time marathon were recruited. At baseline and after 6 months of unsupervised training, race completers underwent tests including 1.5T cardiac magnetic resonance, brachial and non-invasive central blood pressure assessment. For analysis, runners were divided by age into under or over 35 years (U35, O35). RESULTS: Injury and completion rates were similar among the groups; 138 runners (U35: n = 71, women 49%; O35: n = 67, women 51%) completed the race. On average, U35 were faster by 37 minutes (12%). Training induced a small increase in left ventricular mass in both groups (3 g/m2, P < 0.001), but U35 also increased ventricular cavity sizes (left ventricular end-diastolic volume (EDV)i +3%; left ventricular end-systolic volume (ESV)i +8%; right ventricular end-diastolic volume (EDV)i +4%; right ventricular end-systolic volume (ESV)i +5%; P < 0.01 for all). Systemic aortic compliance fell in the whole sample by 7% (P = 0.020) and, especially in O35, also systemic vascular resistance (-4% in the whole sample, P = 0.04) and blood pressure (systolic/diastolic, whole sample: brachial -4/-3 mmHg, central -4/-2 mmHg, all P < 0.001; O35: brachial -6/-3 mmHg, central -6/-4 mmHg, all P < 0.001). CONCLUSION: Medium-term, unsupervised physical training in healthy sedentary individuals induces measurable remodelling of both heart and vasculature. This amount is age dependent, with predominant cardiac remodelling when younger and predominantly vascular remodelling when older.

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.

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.

Training for a First-Time Marathon Reverses Age-Related Aortic Stiffening.

BACKGROUND: Aging increases aortic stiffness, contributing to cardiovascular risk even in healthy individuals. Aortic stiffness is reduced through supervised training programs, but these are not easily generalizable. OBJECTIVES: The purpose of this study was to determine whether real-world exercise training for a first-time marathon can reverse age-related aortic stiffening. METHODS: Untrained healthy individuals underwent 6 months of training for the London Marathon. Assessment pre-training and 2 weeks post-marathon included central (aortic) blood pressure and aortic stiffness using cardiovascular magnetic resonance distensibility. Biological "aortic age" was calculated from the baseline chronological age-stiffness relationship. Change in stiffness was assessed at the ascending (Ao-A) and descending aorta at the pulmonary artery bifurcation (Ao-P) and diaphragm (Ao-D). Data are mean changes (95% confidence intervals [CIs]). RESULTS: A total of 138 first-time marathon completers (age 21 to 69 years, 49% male) were assessed, with an estimated training schedule of 6 to 13 miles/week. At baseline, a decade of chronological aging correlated with a decrease in Ao-A, Ao-P, and Ao-D distensibility by 2.3, 1.9, and 3.1 × 10-3 mm Hg-1, respectively (p < 0.05 for all). Training decreased systolic and diastolic central (aortic) blood pressure by 4 mm Hg (95% CI: 2.8 to 5.5 mm Hg) and 3 mm Hg (95% CI: 1.6 to 3.5 mm Hg). Descending aortic distensibility increased (Ao-P: 9%; p = 0.009; Ao-D: 16%; p = 0.002), while remaining unchanged in the Ao-A. These translated to a reduction in "aortic age" by 3.9 years (95% CI: 1.1 to 7.6 years) and 4.0 years (95% CI: 1.7 to 8.0 years) (Ao-P and Ao-D, respectively). Benefit was greater in older, male participants with slower running times (p < 0.05 for all). CONCLUSIONS: Training for and completing a marathon even at relatively low exercise intensity reduces central blood pressure and aortic stiffness-equivalent to a ∼4-year reduction in vascular age. Greater rejuvenation was observed in older, slower individuals.

Repeatability of Cardiac Magnetic Resonance Radiomics: A Multi-Centre Multi-Vendor Test-Retest Study.

Aims: To evaluate the repeatability of cardiac magnetic resonance (CMR) radiomics features on test-retest scanning using a multi-centre multi-vendor dataset with a varied case-mix. Methods and Results: The sample included 54 test-retest studies from the VOLUMES resource (thevolumesresource.com). Images were segmented according to a pre-defined protocol to select three regions of interest (ROI) in end-diastole and end-systole: right ventricle, left ventricle (LV), and LV myocardium. We extracted radiomics shape features from all three ROIs and, additionally, first-order and texture features from the LV myocardium. Overall, 280 features were derived per study. For each feature, we calculated intra-class correlation coefficient (ICC), within-subject coefficient of variation, and mean relative difference. We ranked robustness of features according to mean ICC stratified by feature category, ROI, and cardiac phase, demonstrating a wide range of repeatability. There were features with good and excellent repeatability (ICC ≥ 0.75) within all feature categories and ROIs. A high proportion of first-order and texture features had excellent repeatability (ICC ≥ 0.90), however, these categories also contained features with the poorest repeatability (ICC < 0.50). Conclusion: CMR radiomic features have a wide range of repeatability. This paper is intended as a reference for future researchers to guide selection of the most robust features for clinical CMR radiomics models. Further work in larger and richer datasets is needed to further define the technical performance and clinical utility of CMR radiomics.

Recreational marathon running does not cause exercise-induced left ventricular hypertrabeculation.

BACKGROUND: Marathon running in novices represents a natural experiment of short-term cardiovascular remodeling in response to running training. We examine whether this stimulus can produce exercise-induced left ventricular (LV) trabeculation. METHODS: Sixty-eight novice marathon runners aged 29.5 ± 3.2 years had indices of LV trabeculation measured by echocardiography and cardiac magnetic resonance imaging 6 months before and 2 weeks after the 2016 London Marathon race, in a prospective longitudinal study. RESULTS: After 17 weeks unsupervised marathon training, indices of LV trabeculation were essentially unchanged. Despite satisfactory inter-observer agreement in most methods of trabeculation measurement, criteria defining abnormally hypertrabeculated cases were discordant with each other. LV hypertrabeculation was a frequent finding in young, healthy individuals with no subject demonstrating clear evidence of a cardiomyopathy. CONCLUSION: Training for a first marathon does not induce LV trabeculation. It remains unclear whether prolonged, high-dose exercise can create de novo trabeculation or expose concealed trabeculation. Applying cut off values from published LV noncompaction cardiomyopathy criteria to young, healthy individuals risks over-diagnosis.