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The objective of the current study was to develop and evaluate a DEep learning‐based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)‐based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high‐resolution spiral real‐time cine imaging, including 2D balanced steady‐state free precession imaging at 1.5 T and gradient echo (GRE) imaging at 1.5 and 3 T. A 3D U‐Net–based image reconstruction network and 2D U‐Net–based image segmentation network were proposed and evaluated. Low‐rank plus sparse (L+S) served as the reference for the image reconstruction network and manual contouring of the left ventricle was the reference of the segmentation network. To assess the image reconstruction quality, structural similarity index, peak signal‐to‐noise ratio, normalized root‐mean‐square error, and blind grading by two experienced cardiologists (5: excellent; 1: poor) were performed. To assess the segmentation performance, quantification of the LVEF on GRE imaging at 3 T was compared with the quantification from manual contouring. Excellent performance was demonstrated by the proposed technique. In terms of image quality, there was no difference between L+S and the proposed DESIRE technique. For quantification analysis, the proposed DL method was not different to the manual segmentation method (p > 0.05) in terms of quantification of LVEF. The reconstruction time for DESIRE was ~32 s (including nonuniform fast Fourier transform [NUFFT]) per dynamic series (40 frames), while the reconstruction time of L+S with GPU acceleration was approximately 3 min. The DL segmentation takes less than 5 s. In conclusion, the proposed DL‐based image reconstruction and quantification techniques enabled 1‐min image reconstruction for the whole heart and quantification with automatic reconstruction and quantification of the left ventricle function for high‐resolution spiral real‐time cine imaging with excellent performance. [ABSTRACT FROM AUTHOR]

Artificial intelligence-enhanced electrocardiography (AI-ECG) can identify hypertrophic cardiomyopathy (HCM) on 12-lead ECGs and offers a novel way to monitor treatment response. Although the surgical or percutaneous reduction of the interventricular septum (SRT) represented initial HCM therapies, mavacamten offers an oral alternative. We aimed to assess the use of AI-ECG as a strategy to evaluate biologic responses to SRT and mavacamten. We applied an AI-ECG model for HCM detection to electrocardiography images from patients who underwent SRT across 3 sites: Yale New Haven Health System (YNHHS), Cleveland Clinic Foundation (CCF), and Atlantic Health System (AHS) and to electrocardiography images from patients receiving mavacamten at YNHHS. A total of 70 patients underwent SRT at YNHHS, 100 at CCF, and 145 at AHS. At YNHHS, there was no significant change in the AI-ECG HCM score before versus after SRT (before SRT: median 0.55 [interquartile range 0.24 to 0.77] vs after SRT: 0.59 [0.40 to 0.75]). The AI-ECG HCM scores also did not improve after SRT at CCF (0.61 [0.32 to 0.79] vs 0.69 [0.52 to 0.79]) and AHS (0.52 [0.35 to 0.69] vs 0.61 [0.49 to 0.70]). Of the 36 YNHHS patients on mavacamten therapy, the median AI-ECG score before starting mavacamten was 0.41 (0.22 to 0.77), which decreased significantly to 0.28 (0.11 to 0.50, p <0.001 by Wilcoxon signed-rank test) at the end of a median follow-up period of 237 days. In conclusion, we observed a lack of improvement in AI-based HCM score with SRT, in contrast to a significant decrease with mavacamten. Our approach suggests the potential role of AI-ECG for serial point-of-care monitoring of pathophysiologic improvement after medical therapy in HCM using ECG images., Competing Interests: Declaration of competing interest Mr. Sangha and Dr. Khera are the coinventors of US Provisional Patent Application No. 63/346,610, “Articles and methods for format-independent detection of hidden cardiovascular disease from printed electrocardiographic images using deep learning.” Dr. Khera receives support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (under awards R01AG089981, R01HL167858, and K23HL153775) and the Doris Duke Charitable Foundation (under award 2022060). He receives support from the Blavatnik Foundation through the Blavatnik fund for Innovation at Yale. He also receives research support, through Yale, from Bristol-Myers Squibb, Novo Nordisk, and BridgeBio. He is an Associate Editor at JAMA. In addition to 63/346,610, Dr. Khera is a coinventor of US Provisional Patent Applications 63/177,117, 63/428,569, and 63/484,426. Dr. Khera and Dr. Oikonomou are cofounders of Evidence2Health, a precision health platform to improve evidence-based cardiovascular care. Dr. Oikonomou is a coinventor of the US Patent Applications 63/508,315 & 63/177,117 and has served as a consultant to Caristo Diagnostics Ltd (all outside the current work). Dr. Krumholz works under contract with the Centers for Medicare & Medicaid Services to support quality measurement programs, was a recipient of a research grant from Johnson & Johnson, through Yale University, to support clinical trial data sharing; was a recipient of a research agreement, through Yale University, from the Shenzhen Center for Health Information for work to advance intelligent disease prevention and health promotion; collaborates with the National Center for Cardiovascular Diseases in Beijing; receives payment from the Arnold & Porter Law Firm for work related to the Sanofi clopidogrel litigation, from the Martin Baughman Law Firm for work related to the Cook Celect IVC filter litigation, and from the Siegfried and Jensen Law Firm for work related to Vioxx litigation; chairs a Cardiac Scientific Advisory Board for UnitedHealth; was a member of the IBM Watson Health Life Sciences Board; is a member of the Advisory Board for Element Science, the Advisory Board for Facebook, and the Physician Advisory Board for Aetna; and is the co-founder of Hugo Health, a personal health information platform; and co-founder of Refactor Health, a health care AI-augmented data management company. Mr. Sangha, Dr. Krumholz and Dr. Khera are cofounders of Ensight-AI, Inc., a Yale-backed startup focusing on cardiovascular diagnostics. Dr. Desai acknowledges the Haslam family–endowed chair in cardiovascular medicine and receives philanthropic support from the Holekamp and Stinson family. The remaining authors have no competing interests to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Patients with heart failure, a preserved ejection fraction (HFpEF), and obesity have significant disability and suffer frequent exacerbations of heart failure. We hypothesized that tirzepatide, a long-acting agonist of glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptors, would improve a comprehensive suite of clinical endpoints, including measures of health status, functional capacity, quality of life, exercise tolerance, patient well-being, and medication burden in these patients., Methods: 731 patients in class II-IV heart failure, ejection fraction ≥50%, and body mass index ≥30 kg/m 2 were randomized(double-blind) to tirzepatide(titrated up to 15mg subcutaneously weekly)(n=364) or placebo(n=367), added to background therapy for a median of 104 weeks (Q1=66, Q3=126 weeks)., Primary Endpoints: tirzepatide reduced the combined risk of cardiovascular death or worsening heart failure and improved Kansas City Cardiomyopathy Questionnaire Clinical Summary Score(KCCQ-CSS). The current expanded analysis included sensitivity analyses of the primary endpoints, 6-minute walk distance(6MWD), EQ-5D-5L health state index, Patient Global Impression of Severity Overall Health(PGIS), NYHA class, use of heart failure medications, and a hierarchical composite based on all-cause death, worsening heart failure, and 52-week changes in KCCQ-CSS and 6MWD., Results: Patients were aged 65.2±10.7, 53.8%(n=393) were female; BMI 38.2±6.7kg/m 2 , KCCQ-CSS 53.5±18.5, 6MWD 302.8±81.7meters, and 53%(n=388) had a worsening heart failure event in the prior 12 months. Compared with placebo, tirzepatide produced a consistent beneficial effect across all composites of death and worsening heart failure events, analyzed as time-to-first-event (hazard ratios 0.41-0.67). At 52 weeks, tirzepatide increased KCCQ-CSS 6.9 points (95%CI, 3.3, 10.6, P<0.001), 6MWD 18.3 meters (95%CI, 9.9, 26.7, P<0.001) and EQ-5D-5L 0.06 (95%CI, 0.03, 0.09, P<0.001). The tirzepatide group shifted to a more favorable PGIS (proportional odds ratio 1.99 (95%CI, 1.44, 2.76) and NYHA class (proportional odds ratio 2.26 (95%CI, 1.54, 3.31), both P<0.001 and required less heart failure medications (P=0.015). The broad spectrum of effects was reflected in benefits on the hierarchical composite (win ratio 1.63, 95%CI, 1.17, 2.28;P=0.004)., Conclusions: Tirzepatide produced a comprehensive, meaningful improvement in heart failure across multiple complementary domains; enhanced health status, quality of life, functional capacity, exercise tolerance and well-being; and reduced symptoms and medication burden in patients with HFpEF and obesity.

Background: Obesity increases the risk of heart failure with preserved ejection fraction. Tirzepatide, a long-acting agonist of glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptors, causes considerable weight loss, but data are lacking with respect to its effects on cardiovascular outcomes., Methods: In this international, double-blind, randomized, placebo-controlled trial, we randomly assigned, in a 1:1 ratio, 731 patients with heart failure, an ejection fraction of at least 50%, and a body-mass index (the weight in kilograms divided by the square of the height in meters) of at least 30 to receive tirzepatide (up to 15 mg subcutaneously once per week) or placebo for at least 52 weeks. The two primary end points were a composite of adjudicated death from cardiovascular causes or a worsening heart-failure event (assessed in a time-to-first-event analysis) and the change from baseline to 52 weeks in the Kansas City Cardiomyopathy Questionnaire clinical summary score (KCCQ-CSS; scores range from 0 to 100, with higher scores indicating better quality of life)., Results: A total of 364 patients were assigned to the tirzepatide group and 367 to the placebo group; the median duration of follow-up was 104 weeks. Adjudicated death from cardiovascular causes or a worsening heart-failure event occurred in 36 patients (9.9%) in the tirzepatide group and in 56 patients (15.3%) in the placebo group (hazard ratio, 0.62; 95% confidence interval [CI], 0.41 to 0.95; P = 0.026). Worsening heart-failure events occurred in 29 patients (8.0%) in the tirzepatide group and in 52 patients (14.2%) in the placebo group (hazard ratio, 0.54; 95% CI, 0.34 to 0.85), and adjudicated death from cardiovascular causes occurred in 8 patients (2.2%) and 5 patients (1.4%), respectively (hazard ratio, 1.58; 95% CI, 0.52 to 4.83). At 52 weeks, the mean (±SD) change in the KCCQ-CSS was 19.5±1.2 in the tirzepatide group as compared with 12.7±1.3 in the placebo group (between-group difference, 6.9; 95% CI, 3.3 to 10.6; P<0.001). Adverse events (mainly gastrointestinal) leading to discontinuation of the trial drug occurred in 23 patients (6.3%) in the tirzepatide group and in 5 patients (1.4%) in the placebo group., Conclusions: Treatment with tirzepatide led to a lower risk of a composite of death from cardiovascular causes or worsening heart failure than placebo and improved health status in patients with heart failure with preserved ejection fraction and obesity. (Funded by Eli Lilly; SUMMIT ClinicalTrials.gov number, NCT04847557.)., (Copyright © 2024 Massachusetts Medical Society.)

Background: Obesity is a known risk factor for heart failure with preserved ejection fraction (HFpEF) and is considered a distinct phenotype with more concentric remodeling. Epicardial adipose tissue (EAT) is also increased in obesity-related HFpEF and is associated with adverse events., Objective: The Cardiac Magnetic Resonance (CMR) Substudy of the SUMMIT trial was aimed to examine the effects of tirzepatide on cardiac structure and function with the underlying hypothesis that it would reduce left ventricular (LV) mass and EAT in obesity-related HFpEF., Methods: One hundred seventy-five patients with obesity-related HFpEF from the parent study of tirzepatide (2.5mg SQ weekly, increasing to a maximum of 15mg weekly) or matching placebo underwent CMR at baseline, which consisted of multiplanar cine imaging. One hundred six patients completed the CMR and had adequate image quality for analysis of LV and LA structure and function and paracardiac (epicardial plus pericardial) adipose tissue at both baseline and 52 weeks. The prespecified primary endpoint of this substudy was between-group changes in LV mass., Results: LV mass decreased by 11 g (95% C.I. -19 to -4) in the treated group (n = 50) when corrected for placebo (n =56) (p=0.004). Paracardiac adipose tissue decreased in the treated group by 45 ml (95% C.I. -69 to -22) when corrected for placebo (p<0.001). The change in LV mass in the treated group correlated with changes in body weight (p<0.02) and, tended to correlate with changes in waist circumference and blood pressure (p=0.06 for both). The LV mass change also correlated with changes in LV end diastolic volume and LA end diastolic and end systolic volumes (p<0.03 for all)., Conclusion: The CMR substudy of the SUMMIT trial demonstrated that tirzepatide therapy in obesity-related HFpEF led to reduced LV mass and paracardiac adipose tissue as compared to placebo and the change in LV mass paralleled weight loss. These physiologic changes may contribute to the reduction in heart failure events seen in the main SUMMIT trial., (Copyright © 2024 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Introduction: Guidelines recommend prospective ECG-triggered mid-diastolic coronary computed tomographic angiography (CCTA) acquisition after achieving optimal heart rate (HR) control in order to optimize scan image quality. With dual-source CCTA, prospective end-systolic acquisition has been shown to be less prone to motion artifacts at higher heart rates and may improve scan and CT laboratory efficiency by allowing CCTA without routine pre-scan beta-blocker (BB) administration., Methods: We implemented an institutional process change in CCTA performance effective January 2023, comprising a transition from prospective ECG-triggered mid-diastolic acquisitions individually supervised by a physician at the scanner to an algorithmic approach predominately utilizing prospective end-systolic acquisition (200-400 ​ms after R peak), employing an automated dose selection algorithm, without BB administration. All scans were performed on a third-generation 192-slice dual-source scanner. We reviewed 300 consecutive CCTAs done pre- and post-process change in Jan 2022 (phase 0), Jan 2023 (phase 1), and in May 2023 (phase 2) after implementation of a process improvement involving more selective utilization of automated tube potential/current algorithms (CARE kV) to optimize image quality. Coronary segmental image quality was assessed by two experienced CCTA readers by consensus using an 18-segment SCCT model on a 5-point Likert scale (1 ​= ​non-interpretable; 2 ​= ​poor; 3 ​= ​acceptable; 4 ​= ​good; 5 ​= ​excellent). Measures of radiation dose, medication administration, and time required for patient scanning were compared. Logistic regression was used to determine factors associated with patient-level reduction in image quality (IQ) and with repeat scans., Results: Post-process change, there was a significant reduction in the median overall patient appointment [phase 0: 95 (75-125) min vs. phase 1: 68 (52-88) min and phase 2: 72 (59-90) min; P ​< ​0.001] and scan times [phase 0: 13 (10-16) min vs. phase 1: 8 (6-13) min and phase 2: 9 (7-13) min; P ​< ​0.001]. Median IQ score in both post-process change phases was 4 (4-5) compared to a median score of 5 (4-5) pre-process change (P for comparison <0.001). The majority of segments post-process change had "good" IQ (Phase 1 segmental IQ scores: 5 ​= ​36.7 ​%, 4 ​= ​46.8 ​%, 3 ​= ​13 ​%, 2 ​= ​2.6 ​%, 1 ​= ​0.9 ​%; Phase 2 segmental IQ scores: 5 ​= ​26 ​%, 4 ​= ​49.7 ​%, 3 ​= ​16.3 ​%, 2 ​= ​6.1 ​%, 1 ​= ​1.9 ​%), whereas pre-process change, the majority of segments had "excellent" IQ (Phase 0 segmental IQ scores: 5 ​= ​56 ​%, 4 ​= ​34.3 ​%, 3 ​= ​7.5 ​%, 2 ​= ​1.8 ​%, 1 ​= ​0.4 ​%) There was no significant increase in non-interpretable scans at the patient level. The 22 ​% re-scan rate in phase 1 (vs. 6 ​% in phase 0, P ​= ​.002) improved to 15 ​% in phase 2. While patient related factors of body mass index [adjusted OR obese 2.64, 95 ​% CI 1.12-6.51, P ​= ​0.03; aOR morbidly obese 6.94, 95 ​% CI 2.21-23.52, P ​= ​0.001] and average HR [aOR (per 10 bpm increase) 1.51, 95 ​% CI 1.21-1.9, P ​< ​0.001] were associated with the scoring of any segment as ​≤ ​3 ​at the patient level in a fully adjusted model, the improved phase 2 of the process change was not [aOR 1.61, 95 ​% CI 0.78-3.32]., Conclusion: Implementation of an institutional process change utilizing prospective ECG-triggered dual-source end-systolic acquisition avoided the use of beta-blockers, significantly reduced patient appointment and scan times with acceptable diagnostic performance., Competing Interests: Declaration of competing interest Dr Patel has received research support from G.E. Healthcare, Siemens Healthineers, CircleCVI, and Neosoft. Dr. Kramer and Dr. Villines have has received royalties from Walters Kluwer for authorship of educational content (UpToDate.com) related to cardiac CT topics. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.)