T2 Relaxation Times at Cardiac MRI in Healthy Adults: A Systematic Review and Meta-Analysis.

Background T2 mapping is an important cardiac MRI technique with applications in various conditions. However, a comprehensive evaluation of the T2 literature for normal values is lacking. Purpose To characterize the ranges of normal values and variability of myocardial T2 relaxation times using a systematic review and meta-analysis of the T2 literature. Materials and Methods PubMed and Cochrane Central were searched from June 2019 to January 2020 for myocardial T2 measurements in healthy adults. Studies quantifying T2 relaxation times conducted at 1.5 T or 3.0 T using gradient and spin-echo (GRASE) or T2-prepared balanced steady-state free precession sequences were included. Summary means were generated using a random-effects model. Subgroup analysis and meta-regression were performed to assess factors causing heterogeneity. Results Of the 2481 articles retrieved, 42 studies were included with 954 healthy adults (mean age, 42.4 years ± 10.5 [standard deviation]; 538 men). The pooled mean of T2 across studies was 52 msec at 1.5 T (95% confidence interval [CI]: 51 msec, 53 msec) and 46 msec at 3.0 T (95% CI: 44 msec, 48 msec) (P ≤ .001). I2 was 98% at 1.5 T and 3.0 T. Meta-regression at 1.5 T and 3.0 T identified vendor (ß at 1.5 T = -4 msec [with Philips as reference], P < .001; ß at 3.0 T = -5 msec, P = .02) and pulse sequence (ß at 1.5 T = -5 msec [with GRASE as reference], P < .001; ß at 3.0 T = -6 msec, P = .002) as significant covariates, but it did not identify any association with covariates of age (ß at 1.5 T = 0 msec per year, P = .70; ß at 3.0 T = 0 msec per year, P = .83) or sex (ß at 1.5 T = -1 msec, P = .88; ß at 3.0 T = 6 msec, P = .42). Conclusion The pooled mean of T2 relaxation times in healthy adults had marked heterogeneity across studies with field strength, vendor, and pulse sequence identified as covariates associated with T2. T2-prepared measurements were similar between vendors at each field strength. © RSNA, 2020 Online supplemental material is available for this article.

Native T1 and Extracellular Volume Measurements by Cardiac MRI in Healthy Adults: A Meta-Analysis.

Purpose To summarize the literature by performing a systematic review and pooled analysis of the data, to understand the extent of variability among studies of native T1 and extracellular volume (ECV) measurements, and to identify covariates that account for heterogeneity between studies. Materials and Methods PubMed, Web of Science, and Cochrane Central were searched for native T1 and ECV measurements of the left ventricle in health adult study participants. The search terms used were "T1 mapping heart," "Native T1 heart," and "ECV heart." Summary means were generated with random-effects modeling. Heterogeneity was assessed by using the inconsistency factor (I 2). Subgroup analyses and meta-regression analyses were conducted to identify etiologic causes of heterogeneity. Results This systematic review of native T1 included 120 articles, with 5541 participants (mean age, 50 years; 51.0% men [2826 of 5541]). The pooled mean of native T1 was 976 msec (95% confidence interval [CI]: 969 msec, 983 msec) at 1.5 T and 1159 msec (95% CI: 1143 msec, 1175 msec) at 3.0 T. I 2 was 99% at both field strengths. Eighty-one articles were included in the systematic review of ECV, with 3872 participants (mean age, 52 years; 50.0% men [1936 of 3872]). The pooled mean of ECV was 25.9% at field strength of 1.5 T (95% CI: 25.5%, 26.3%) and 3.0 T (95% CI: 25.4%, 26.5%). I 2 was 94% and 90% at 1.5 and 3.0 T, respectively. Conclusion The pooled means of extracellular volume and native T1 measurements in healthy adult participants are summarized in this analysis. There was significant heterogeneity found among studies, highlighting the importance of standardized cardiac MRI protocols and the derivation of institution specific reference ranges. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Dodd and Dewey in this issue.

Evolution of diastolic function algorithms: Implications for clinical practice.

OBJECTIVE: We undertook this study of echocardiographic classification of diastolic function by three different algorithms to determine: (1) how frequently each algorithm classified patients and (2) how well the results agreed with one another. BACKGROUND: Several algorithms exist to grade diastolic function (DF), the Mayo Clinic scheme of Redfield et al (Mayo 2003) and the 2 ASE guideline documents of 2009 and 2016 (ASE 2009 and ASE 2016). METHODS: A total of 200 consecutive echocardiograms were retrospectively analyzed; mean age of patients 60.3 ± 3.5 years, 45% male. Echocardiograms were performed using Intersocietal Accreditation Commission guidelines. Diastolic function was assessed by Mayo 2003 and ASE 2009 and 2016. Coexisting conditions affecting DF analysis, such as mitral annular calcification (MAC), were tabulated. Data were compared using a paired t-test. Concordance between algorithms was assessed using the Kappa statistic. RESULTS: A total of 117 of 200 studies (58.5%) were excluded for the presence of coexisting conditions (51.5%), poor image quality (2.5%), or incomplete data (4.5%). Thirty-three of the remaining 83 studies (40%) received the same grade of DF based on assessments made using the Mayo 2003 and ASE 2016 algorithms; the Kappa statistic was 0.20. 36 of the 83 studies (43%) received the same grade of DF based on assessments made using the ASE 2009 and ASE 2016 algorithms; the Kappa statistic was 0.25. CONCLUSION: Assessment of diastolic function via echocardiography cannot be reliably accomplished in approximately 50% of patients using current guidelines. Further, when studies are suitable for assessment, widely used guidelines yield discordant results.

Association between deep neural network-derived electrocardiographic-age and incident stroke.

Background: Stroke continues to be a leading cause of death and disability worldwide despite improvements in prevention and treatment. Traditional stroke risk calculators are biased and imprecise. Novel stroke predictors need to be identified. Recently, deep neural networks (DNNs) have been used to determine age from ECGs, otherwise known as the electrocardiographic-age (ECG-age), which predicts clinical outcomes. However, the relationship between ECG-age and stroke has not been well studied. We hypothesized that ECG-age is associated with incident stroke. Methods: In this study, UK Biobank participants with available ECGs (from 2014 or later). ECG-age was estimated using a deep neural network (DNN) applied to raw ECG waveforms. We calculated the Δage (ECG-age minus chronological age) and classified individuals as having normal, accelerated, or decelerated aging if Δage was within, higher, or lower than the mean absolute error of the model, respectively. Multivariable Cox proportional hazards regression models adjusted for age, sex, and clinical factors were used to assess the association between Δage and incident stroke. Results: The study population included 67,757 UK Biobank participants (mean age 65 ± 8 years; 48.3% male). Every 10-year increase in Δage was associated with a 22% increase in incident stroke [HR, 1.22 (95% CI, 1.00-1.49)] in the multivariable-adjusted model. Accelerated aging was associated with a 42% increase in incident stroke [HR, 1.42 (95% CI, 1.12-1.80)] compared to normal aging. In addition, Δage was associated with prevalent stroke [OR, 1.28 (95% CI, 1.11-1.49)]. Conclusions: DNN-estimated ECG-age was associated with incident and prevalent stroke in the UK Biobank. Further investigation is required to determine if ECG-age can be used as a reliable biomarker of stroke risk.

Insights Into the Standard Echocardiographic Views From Multimodality Imaging: Ventricles, Pericardium, Valves, and Atria.

The widespread use of cardiac computed tomography and cardiac magnetic resonance imaging in patients undergoing echocardiography presents an opportunity to correlate the images side by side. Accordingly, the aim of this report is to review aspects of the standard echocardiographic examination alongside similarly oriented images from the two tomographic imaging modalities. It is hoped that this exercise will enhance understanding of the structures depicted by echocardiography as they relate to other structures in the thorax. In addition to reviewing basic cardiac anatomy, the authors take advantage of these correlations with computed tomography and cardiac magnetic resonance imaging to better understand the issue of foreshortening, a common pitfall in transthoracic echocardiography. The authors also highlight an important role that three-dimensional echocardiography can potentially play in the future, especially as advances in image processing permit higher fidelity multiplanar reconstruction images.

False Atrial Fibrillation Alerts from Smartwatches are Associated with Decreased Perceived Physical Well-being and Confidence in Chronic Symptoms Management.

Wrist-based wearables have been FDA approved for AF detection. However, the health behavior impact of false AF alerts from wearables on older patients at high risk for AF are not known. In this work, we analyzed data from the Pulsewatch (NCT03761394) study, which randomized patients (≥50 years) with history of stroke or transient ischemic attack to wear a patch monitor and a smartwatch linked to a smartphone running the Pulsewatch application vs to only the cardiac patch monitor over 14 days. At baseline and 14 days, participants completed validated instruments to assess for anxiety, patient activation, perceived mental and physical health, chronic symptom management self-efficacy, and medicine adherence. We employed linear regression to examine associations between false AF alerts with change in patient-reported outcomes. Receipt of false AF alerts was related to a dose-dependent decline in self-perceived physical health and levels of disease self-management. We developed a novel convolutional denoising autoencoder (CDA) to remove motion and noise artifacts in photoplethysmography (PPG) segments to optimize AF detection, which substantially reduced the number of false alerts. A promising approach to avoid negative impact of false alerts is to employ artificial intelligence driven algorithms to improve accuracy.

Accuracy, Usability, and Adherence of Smartwatches for Atrial Fibrillation Detection in Older Adults After Stroke: Randomized Controlled Trial.

BACKGROUND: Atrial fibrillation (AF) is a common cause of stroke, and timely diagnosis is critical for secondary prevention. Little is known about smartwatches for AF detection among stroke survivors. We aimed to examine accuracy, usability, and adherence to a smartwatch-based AF monitoring system designed by older stroke survivors and their caregivers. OBJECTIVE: This study aims to examine the feasibility of smartwatches for AF detection in older stroke survivors. METHODS: Pulsewatch is a randomized controlled trial (RCT) in which stroke survivors received either a smartwatch-smartphone dyad for AF detection (Pulsewatch system) plus an electrocardiogram patch or the patch alone for 14 days to assess the accuracy and usability of the system (phase 1). Participants were subsequently rerandomized to potentially 30 additional days of system use to examine adherence to watch wear (phase 2). Participants were aged 50 years or older, had survived an ischemic stroke, and had no major contraindications to oral anticoagulants. The accuracy for AF detection was determined by comparing it to cardiologist-overread electrocardiogram patch, and the usability was assessed with the System Usability Scale (SUS). Adherence was operationalized as daily watch wear time over the 30-day monitoring period. RESULTS: A total of 120 participants were enrolled (mean age 65 years; 50/120, 41% female; 106/120, 88% White). The Pulsewatch system demonstrated 92.9% (95% CI 85.3%-97.4%) accuracy for AF detection. Mean usability score was 65 out of 100, and on average, participants wore the watch for 21.2 (SD 8.3) of the 30 days. CONCLUSIONS: Our findings demonstrate that a smartwatch system designed by and for stroke survivors is a viable option for long-term arrhythmia detection among older adults at risk for AF, though it may benefit from strategies to enhance adherence to watch wear. TRIAL REGISTRATION: ClinicalTrials.gov NCT03761394; https://clinicaltrials.gov/study/NCT03761394. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.cvdhj.2021.07.002.

Effect of Transaortic Valve Intervention for Aortic Stenosis on Myocardial Mechanics.

Chronic afterload excess in aortic stenosis results in compensatory concentric hypertrophy which mitigates the increased systolic load. Surgical aortic valve replacement has been shown to decrease afterload and improve left ventricular (LV) ejection fraction (EF). The extent to which these changes take place in patients undergoing TAVI (transcatheter aortic valve intervention) may be different than what has been observed in the surgical aortic valve replacement patients who were generally younger with few co-morbidities. Accordingly, we analyzed indices of LV structure and ventricular mechanics pre- and 1-year after TAVI in 397 patients (mean age 81±9, 46% women) with severe symptomatic aortic stenosis, complete echocardiographic data was available in 156 patients and these patients compromised our study population. Our principal findings are: (1) LV remodeling occurs after TAVI; (2) afterload decreases significantly; (3) LV chamber and myocardial function, assessed by left ventricular ejection fraction and midwall fractional shortening, and stroke volume, respectively, remain unchanged or decrease. In conclusion, TAVI effects LV remodeling despite significant co-morbidities. Thus, TAVI reduces afterload and leads to LV remodeling. Surprisingly, however, systolic function does not improve. These data run counter to the paradigm that afterload reduction improves systolic function and suggest that the response to afterload reduction is complex in the TAVI population.

Circulating extracellular RNAs, myocardial remodeling, and heart failure in patients with acute coronary syndrome.

BACKGROUND: Given high on-treatment mortality in heart failure (HF), identifying molecular pathways that underlie adverse cardiac remodeling may offer novel biomarkers and therapeutic avenues. Circulating extracellular RNAs (ex-RNAs) regulate important biological processes and are emerging as biomarkers of disease, but less is known about their role in the acute setting, particularly in the setting of HF. METHODS: We examined the ex-RNA profiles of 296 acute coronary syndrome (ACS) survivors enrolled in the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education Cohort. We measured 374 ex-RNAs selected a priori, based on previous findings from a large population study. We employed a two-step, mechanism-driven approach to identify ex-RNAs associated with echocardiographic phenotypes (left ventricular [LV] ejection fraction, LV mass, LV end-diastolic volume, left atrial [LA] dimension, and LA volume index) then tested relations of these ex-RNAs with prevalent HF (N=31, 10.5%). We performed further bioinformatics analysis of microRNA (miRNAs) predicted targets' genes ontology categories and molecular pathways. RESULTS: We identified 44 ex-RNAs associated with at least one echocardiographic phenotype associated with HF. Of these 44 exRNAs, miR-29-3p, miR-584-5p, and miR-1247-5p were also associated with prevalent HF. The three microRNAs were implicated in the regulation p53 and transforming growth factor-ß signaling pathways and predicted to be involved in cardiac fibrosis and cell death; miRNA predicted targets were enriched in gene ontology categories including several involving the extracellular matrix and cellular differentiation. CONCLUSIONS: Among ACS survivors, we observed that miR-29-3p, miR-584-5p, and miR-1247-5p were associated with both echocardiographic markers of cardiac remodeling and prevalent HF. RELEVANCE FOR PATIENTS: miR-29c-3p, miR-584-5p, and miR-1247-5p were associated with echocardiographic phenotypes and prevalent HF and are potential biomarkers for adverse cardiac remodeling in HF.

Computed Tomography Fractional Flow Reserve to Guide Coronary Angiography and Intervention.

Computed tomography angiography (CTA) has played a significant role in evaluation of coronary artery disease in the last decade and has demonstrated high sensitivity and negative predictive values. However, the positive predictive value as compared with invasive fractional flow reserve (FFR) is limited. CT-FFR has emerged as a disruptive noninvasive technology with higher specificity and diagnostic accuracy for detection of hemodynamically significant coronary lesions as compared with invasive FFR than conventional coronary CTA. CT-FFR has been shown to be cost-effective as a gate-keeper to invasive coronary angiography and has the potential to limit unnecessary invasive angiography studies.

C-GRApH: A Validated Scoring System for Early Stratification of Neurologic Outcome After Out-of-Hospital Cardiac Arrest Treated With Targeted Temperature Management.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) results in significant morbidity and mortality, primarily from neurologic injury. Predicting neurologic outcome early post-OHCA remains difficult in patients receiving targeted temperature management. METHODS AND RESULTS: Retrospective analysis was performed on consecutive OHCA patients receiving targeted temperature management (32-34°C) for 24 hours at a tertiary-care center from 2008 to 2012 (development cohort, n=122). The primary outcome was favorable neurologic outcome at hospital discharge, defined as cerebral performance category 1 to 2 (poor 3-5). Patient demographics, pre-OHCA diagnoses, and initial laboratory studies post-resuscitation were compared between favorable and poor neurologic outcomes with multivariable logistic regression used to develop a simple scoring system (C-GRApH). The C-GRApH score ranges 0 to 5 using equally weighted variables: (C): coronary artery disease, known pre-OHCA; (G): glucose ≥200 mg/dL; (R): rhythm of arrest not ventricular tachycardia/fibrillation; (A): age >45; (pH): arterial pH ≤7.0. A validation cohort (n=344) included subsequent patients from the initial site (n=72) and an external quaternary-care health system (n=272) from 2012 to 2014. The c-statistic for predicting neurologic outcome was 0.82 (0.74-0.90, P<0.001) in the development cohort and 0.81 (0.76-0.87, P<0.001) in the validation cohort. When subdivided by C-GRApH score, similar rates of favorable neurologic outcome were seen in both cohorts, 70% each for low (0-1, n=60), 22% versus 19% for medium (2-3, n=307), and 0% versus 2% for high (4-5, n=99) C-GRApH scores in the development and validation cohorts, respectively. CONCLUSIONS: C-GRApH stratifies neurologic outcomes following OHCA in patients receiving targeted temperature management (32-34°C) using objective data available at hospital presentation, identifying patient subsets with disproportionally favorable (C-GRApH ≤1) and poor (C-GRApH ≥4) prognoses.