Publications by authors named "Amedeo Chiribiri"

Introduction: Atrial late gadolinium enhancement (Atrial-LGE) and electroanatomic voltage mapping (Atrial-EAVM) quantify the anatomical and functional extent of atrial cardiomyopathy. We aimed to explore the relationships between, and outcomes from, these modalities in patients with atrial fibrillation undergoing ablation.

Methods: Patients undergoing first-time ablation had disease severities quantified using both Atrial-LGE and Atrial-EAVM.

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The pathophysiology of myocardial injury following COVID-19 remains uncertain. COVID-HEART was a prospective, multicentre study utilising cardiovascular magnetic resonance (CMR) to characterise COVID-related myocardial injury. In this pre-specified analysis, the objectives were to examine (1) the frequency of myocardial ischaemia following COVID-19, and (2) the association between ischaemia and myocardial injury.

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With a prevalence of 2-3% in the general population, mitral valve prolapse (MVP) is the most common valvular heart disease. The clinical course is benign in the majority of patients, although severe mitral regurgitation, heart failure, and sudden cardiac death affect a non-negligible subset of patients. Imaging of MVP was confined to echocardiography until a few years ago when it became apparent that cardiovascular magnetic resonance (CMR) could offer comparative advantages for detecting and quantifying mitral valve abnormalities alongside tissue myocardial characterization.

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Background: The prognostic value of late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR) imaging is well-established. However, the direct relationship between image pixels and outcomes remains poorly understood. We hypothesised that leveraging artificial intelligence (AI) to analyse qualitative LGE images based on American Heart Association (AHA) guidelines could elucidate this relationship.

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Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing the blood supply of the myocardium. Currently, the majority of clinical perfusion scans are evaluated based on visual assessment by experienced clinicians. This makes the process subjective, and to this end, quantitative methods have been proposed to offer a more user-independent assessment of perfusion.

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Background: The diagnosis of myocarditis by cardiovascular magnetic resonance (CMR) requires the use of T2 and T1 weighted imaging, ideally incorporating parametric mapping. Current two-dimensional (2D) mapping sequences are acquired sequentially and involve multiple breath-holds resulting in prolonged scan times and anisotropic image resolution. We developed an isotropic free-breathing three-dimensional (3D) whole-heart sequence that allows simultaneous T1 and T2 mapping and validated it in patients with suspected myocarditis.

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Article Synopsis
  • The study examined the effects of myocardial injury in hospitalized COVID-19 survivors who had elevated troponin levels, using cardiac imaging and tracking health-related quality of life over 12 months.* -
  • Conducted in 25 UK centers, the research involved 342 participants, finding that while some cardiovascular events occurred, overall major adverse outcomes were low after 12 months.* -
  • Results showed slight improvements in heart function and quality of life after 6 months, with no evidence of ongoing myocardial inflammation or progression of heart injury.*
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Background: Human CD16 monocytes (hCD16 Ms) have proangiogenic properties. We assessed the feasibility, safety and efficacy of hCD16 Ms in a porcine model of myocardial infarction (MI).

Methods And Results: A total of 27 female Large White pigs underwent MI with reperfusion and cardiac magnetic resonance (CMR).

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Purpose: Myocardial T mapping techniques commonly acquire multiple images in one breathhold to calculate a single-slice T map. Recently, non-selective adiabatic pulses have been used for robust spin-lock preparation (T). The objective of this study was to develop a fast multi-slice myocardial T mapping approach.

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Quantification of myocardial scar from late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) images can be facilitated by automated artificial intelligence (AI)-based analysis. However, AI models are susceptible to domain shifts in which the model performance is degraded when applied to data with different characteristics than the original training data. In this study, CycleGAN models were trained to translate local hospital data to the appearance of a public LGE CMR dataset.

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Article Synopsis
  • The study aimed to assess the effectiveness of ECG in detecting cardiac issues in post-hospitalized COVID-19 patients through cardiac magnetic resonance (CMR) imaging.
  • Results showed that these patients had significantly more ECG abnormalities compared to healthy controls, yet both groups had similar levels of CMR abnormalities.
  • Adding additional analyses on repolarization improved ECG's ability to identify patients with CMR abnormalities and reduced the reliance on sex in the diagnostic process.
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Background: Simultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g.

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Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods This retrospective study included patients with MVP without hemodynamically significant mitral regurgitation or left ventricular (LV) dysfunction undergoing late gadolinium enhancement (LGE) cardiac MRI between October 2007 and June 2020 in 15 European tertiary centers. The study end point was a composite of sustained ventricular tachycardia, (aborted) sudden cardiac death, or unexplained syncope.

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Background: Despite recent guideline recommendations, quantitative perfusion (QP) estimates of myocardial blood flow from cardiac magnetic resonance (CMR) have only been sparsely validated. Furthermore, the additional diagnostic value of utilizing QP in addition to the traditional visual expert interpretation of stress-perfusion CMR remains unknown. The aim was to investigate the correlation between myocardial blood flow measurements estimated by CMR, positron emission tomography, and invasive coronary thermodilution.

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Background: Complete revascularization of coronary artery disease has been linked to improved outcomes in patients with preserved left ventricular (LV) function.

Objectives: This study sought to identify the impact of complete revascularization in patients with severe LV dysfunction.

Methods: Patients enrolled in the REVIVED-BCIS2 (Revascularization for Ischemic Ventricular Dysfunction) trial were eligible if baseline/procedural angiograms and viability studies were available for analysis by independent core laboratories.

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Objectives: Dark-blood late gadolinium enhancement (DB-LGE) cardiac magnetic resonance has been proposed as an alternative to standard white-blood LGE (WB-LGE) imaging protocols to enhance scar-to-blood contrast without compromising scar-to-myocardium contrast. In practice, both DB and WB contrasts may have clinical utility, but acquiring both has the drawback of additional acquisition time. The aim of this study was to develop and evaluate a deep learning method to generate synthetic WB-LGE images from DB-LGE, allowing the assessment of both contrasts without additional scan time.

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Aims: Hypertensive patients of African ancestry (Afr-a) have higher incidences of heart failure and worse clinical outcomes than hypertensive patients of European ancestry (Eu-a), yet the underlying mechanisms remain misunderstood. This study investigated right (RV) and left (LV) ventricular remodelling alongside myocardial tissue derangements between Afr-a and Eu-a hypertensives.

Methods And Results: 63 Afr-a and 47 Eu-a hypertensives underwent multi-parametric cardiovascular magnetic resonance.

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Article Synopsis
  • This study investigates how artificial intelligence, specifically hybrid neural networks (HNN), can predict mortality outcomes in patients with coronary artery disease (CAD) using stress perfusion cardiac magnetic resonance (SP-CMR) images and electronic health records (EHRs).
  • A retrospective analysis included 1,286 patients from 2011 to 2021, with results showing HNN outperformed traditional clinical models and pure image-based models in predicting all-cause mortality.
  • The findings suggest that mortality prediction can be achieved directly from imaging without the need for clinical knowledge and that combining image and clinical data enhances prediction accuracy.
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Dark-blood late gadolinium enhancement (LGE) has been shown to improve the visualization and quantification of areas of ischemic scar compared to standard bright-blood LGE. Recently, the performance of various semi-automated quantification methods has been evaluated for the assessment of infarct size using both dark-blood LGE and conventional bright-blood LGE with histopathology as a reference standard. However, the impact of this sequence on different quantification strategies in vivo remains uncertain.

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