"Cardiac imaging"

KODEX-EPD for cardiac imaging during ablation of arrhythmias KODEX-EPD for cardiac imaging during ablation of arrhythmias Medtech innovation briefing Published: 11 May 2021 www.nice.org.uk/guidance/mib260 pathwaysSummary Summary • The technologytechnology described in this briefing is the KODEX-EPD system. It is used for cardiac imaging and navigation during ablation of cardiac arrhythmias for consumables. The technology The technology The KODEX-EPD system (Philips Medical Systems Nederland BV) is a non-fluoroscopic 3D cardiac imaging and navigation (mapping) system. It is an open-platform catheter-based cardiac electrophysiology system that works with any validated electrophysiology catheter and uses a novel dielectric energy source. This allows electrophysiologists to electrically image unique

Saudi Heart Association/National Heart Center/Saudi Arabian Cardiac Interventional Society/Saudi Society for Cardiac Surgeons/Saudi Cardiac Imaging Group 2023 TAVI Guidelines Saudi Arabia has seen a significant improvement in its healthcare system over the past four decades resulting in an increase in life-expectancy. Transcatheter aortic valve implantation (TAVI) has spread widely in Saudi

Noninvasive cardiac imaging Final Noninvasive Cardiac Imaging: findings and decision Page 1 of 4 Health Technology Clinical Committee FINAL Findings and Decision Topic: Noninvasive Cardiac Imaging Meeting date: November 5, 2021 Final adoption: March 18, 2022 Number and coverage topic: 20211105A – Noninvasive Cardiac Imaging for Coronary Artery Disease HTCC coverage determination : Noninvasive cardiac imaging is a covered benefit with conditions. HTCC reimbursement determination: Limitations of coverage: The following noninvasive cardiac imaging technologies are covered with conditions: • Stress echocardiography for: o Symptomatic adult patients (≥18 years of age) at intermediate or high risk of Coronary Artery Disease (CAD), or o Adult patients with known CAD who have new

How Machine Learning Might Help Improve Cardiac Imaging. In this Medical News interview, University of California, San Francisco, cardiologist Rima Arnaout, joins JAMA Editor in Chief Kirsten Bibbins-Domingo to discuss the transformative potential of AI on cardiac imaging.

Adverse cardiovascular events and cardiac imaging findings in patients on immune checkpoint inhibitors. There is an urgent need to better understand the diverse presentations, risk factors, and outcomes of immune checkpoint inhibitor (ICI)-associated cardiovascular toxicity. There remains a lack of consensus surrounding cardiovascular screening, risk stratification, and clinical decision-making /pericarditis was relatively uncommon, and the overall cardiovascular risks of dual ICI therapy appeared to be offset by a significant mortality benefit. The use of multimodal cardiac imaging can be helpful in stratifying risk and guiding preventative cardiovascular management in patients receiving ICIs.

Longitudinal cardiac imaging for assessment of myocardial injury in non-hospitalised community-dwelling individuals after COVID-19 infection: the Rotterdam Study. The aim of this study was to assess the presence of myocardial injury after COVID-19 infection and to evaluate the relation between persistent cardiac symptoms after COVID-19 and myocardial function in participants with known

Social media for cardiac imagers: a review. Cardiac imaging plays a pivotal role in the diagnosis and management of cardiovascular diseases. In the burgeoning landscape of digital technology and social media platforms, it becomes essential for cardiac imagers to know how to effectively increase the visibility and the impact of their activity. With the availability of social sites like X (formerly Twitter), Instagram and Facebook, cardiac imagers can now reach a wider audience and engage with peers, sharing their findings, insights, and discussions. The integration of persistent identifiers, such as Digital Object Identifiers (DOIs), facilitates traceability and citation of cardiac imaging publications across various digital platforms, further enhancing their discoverability. To maximize

Multimodality Cardiac Imaging and the Imaging Workforce in the United States: Diversity, Disparities, and Future Directions. Innovations in cardiac imaging have fundamentally advanced the understanding and treatment of cardiovascular disease. These advances in noninvasive cardiac imaging have also expanded the role of the cardiac imager and dramatically increased the demand for imagers who are cross-trained in multiple modalities. However, we hypothesize that there is significant variation in the availability of cardiac imaging expertise and a disparity in the adoption of advanced imaging technologies across the United States. To evaluate this, we have brought together the leaders of cardiovascular imaging societies, imaging trainees, as well as collaborated with national imaging

Challenges for augmenting intelligence in cardiac imaging. Artificial Intelligence (AI), through deep learning, has brought automation and predictive capabilities to cardiac imaging. However, despite considerable investment, tangible health-care cost reductions remain unproven. Although AI holds promise, there has been insufficient time for both methodological development and prospective clinical settings. Nevertheless, there is a strong push in industry and academia for AI solutions in medical imaging. This Series paper reviews key studies and identifies challenges that require a pragmatic change in the approach for using AI for cardiac imaging, whereby AI is viewed as augmented intelligence to complement, not replace, human judgement. The focus should shift from isolated measurements

Validation of cardiac image-derived input functions for functional PET quantification. Functional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate quantification of fPET relies on measuring the arterial input function (AIF), traditionally achieved through invasive arterial blood sampling. While non-invasive image-derived

Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging. Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent heterogeneity of these diseases poses challenges, necessitating advanced prediction. Radiomics and artificial intelligence thus hold promise for significantly enhancing diagnostic and prognostic capabilities in cardiac imaging, paving the way for more personalized and effective patient care. This review explores the synergies between radiomics and artificial intelligence in cardiac imaging, following the radiomics workflow and introducing concepts from both domains. Potential

Multimodality Cardiac Imaging, Cardiac Symptoms, and Clinical Outcomes in Patients Who Recovered from Mild COVID-19. Background Many patients have persistent cardiac symptoms after mild COVID-19. However, studies assessing the relationship between symptoms and cardiac imaging are limited. Purpose To assess the relationship between multi-modality cardiac imaging parameters, symptoms, and clinical

Cardiac Imaging in Childhood Cancer Survivors: A State-of-the-Art Review. Childhood cancer survival has improved significantly in the past few decades, reaching rates of 80% or more at 5 years. However, with improved survival, early- and late-occurring complications of chemotherapy and radiotherapy exposure are becoming progressively more evident. Cardiovascular diseases represent the leading

Approach to Cardiac Masses Using Multimodal Cardiac Imaging. Incidental cardiac masses can pose diagnostic challenges given the numerous differentials, and difficulty in obtaining tissue confirmation without invasive procedures. With recent advancements in cardiac imaging technology, non-invasive efforts to diagnose the intracardiac lesions have become more surmountable. In this paper, we report a case of a patient incidentally found to have an intra-cardiac mass during routine evaluation. Transthoracic echocardiography demonstrated a small mass attached to the tricuspid valve, which was not visualized on follow up cardiac magnetic resonance imaging. Here, we review the currently available cardiac imaging modalities and discuss their values and limitations. From this, we also propose

Multi-modality cardiac image computing: A survey. Multi-modality cardiac imaging plays a key role in the management of patients with cardiovascular diseases. It allows a combination of complementary anatomical, morphological and functional information, increases diagnosis accuracy, and improves the efficacy of cardiovascular interventions and clinical outcomes. Fully-automated processing and quantitative analysis of multi-modality cardiac images could have a direct impact on clinical research and evidence-based patient management. However, these require overcoming significant challenges including inter-modality misalignment and finding optimal methods to integrate information from different modalities. This paper aims to provide a comprehensive review of multi-modality imaging in cardiology

Myocardial injury after major non-cardiac surgery evaluated with advanced cardiac imaging: a pilot study. Myocardial injury after non-cardiac surgery (MINS) is a frequent complication caused by cardiac and non-cardiac pathophysiological mechanisms, but often it is subclinical. MINS is associated with increased morbidity and mortality, justifying the need to its diagnose and the investigation

Three-dimensional echocardiography and strain cardiac imaging in women with pre-eclampsia with follow up to six months postpartum. Epidemiological studies have established that women with preeclampsia (PE) are at increased long-term cardiovascular risk. Mild cardiac functional changes have been documented during pregnancy in women with PE, but how these are modified from transition to postpartum

Explainable Artificial Intelligence and Cardiac Imaging: Toward More Interpretable Models. Artificial intelligence applications have shown success in different medical and health care domains, and cardiac imaging is no exception. However, some machine learning models, especially deep learning, are considered black box as they do not provide an explanation or rationale for model outcomes . Complexity and vagueness in these models necessitate a transition to explainable artificial intelligence (XAI) methods to ensure that model results are both transparent and understandable to end users. In cardiac imaging studies, there are a limited number of papers that use XAI methodologies. This article provides a comprehensive literature review of state-of-the-art works using XAI methods for cardiac

Competency-based cardiac imaging for patient-centred care. A statement of the European Society of Cardiology (ESC). Imaging plays an integral role in all aspects of managing heart disease and cardiac imaging is a core competency of cardiologists. The adequate delivery of cardiac imaging services requires expertise in both imaging methodology - with specific adaptations to imaging of the heart - as well as intricate knowledge of heart disease. The European Society of Cardiology (ESC) and the European Association of Cardiovascular Imaging (EACVI) of the ESC have developed and implemented a successful education and certification programme for all cardiac imaging modalities. This programme equips cardiologists to provide high quality competency-based cardiac imaging services ensuring

Competency-based cardiac imaging for patient-centred care. A statement of the European Society of Cardiology (ESC). Imaging plays an integral role in all aspects of managing heart disease and cardiac imaging is a core competency of cardiologists. The adequate delivery of cardiac imaging services requires expertise in both imaging methodology - with specific adaptations to imaging of the heart - as well as intricate knowledge of heart disease. The European Society of Cardiology (ESC) and the European Association of Cardiovascular Imaging (EACVI) of the ESC have developed and implemented a successful education and certification programme for all cardiac imaging modalities. This programme equips cardiologists to provide high quality competency-based cardiac imaging services ensuring