Heart Health Research Articles

The role of different nutrients in the prevention and treatment of cardiovascular diseases

Cardiovascular health is a hot topic around the world, and as the incidence of cardiovascular disease increases each year, people are increasingly focusing on the management of their heart health. Dietary and lifestyle changes as non-pharmacological treatments have been increasingly recognized as important in the prevention of cardiovascular disease and in reducing the risk of cardiovascular accidents. Awareness of different nutrients and their effects on cardiovascular health is important for establishing a good dietary pattern. This review summarizes the effects of the five major nutrients in the daily diet, namely carbohydrates, proteins, dietary fats, vitamins, and minerals, on cardiovascular health, and aims to provide a more comprehensive understanding of the effects of a healthy dietary pattern on cardiovascular health.

Unveiling the microbiota-metabolite-myocardium axis: a novel perspective on cardiovascular health

IntroductionCardiovascular diseases, including myocardial infarction, remain a leading cause of death globally. Emerging evidence suggests the gut microbiota plays a crucial role in cardiovascular health. This study aims to explore the impact of gut microbiota on myocardial infarction using a mouse model.MethodsThe research utilizes a multi-omics approach, including 16S rDNA sequencing and LC-MS-based metabolomics to analyze fecal and serum samples from mice modeled to mimic myocardial infarction. This methodology allows for a comprehensive analysis of microbial populations and their metabolic output.ResultsThe findings reveal a significant reduction in gut microbiota α-diversity in mice with induced myocardial infarction compared to healthy controls. Notably, there is an increase in populations of Fusobacteria and Clostridia. Metabolomic analysis indicates disruptions in amino acid and energy metabolism, suggesting a metabolic dysregulation linked to myocardial health.DiscussionThe study proposes a novel microbiota-metabolite-myocardium axis, where specific microbial metabolites may directly affect heart health. This connection points to the gut microbiota as a potential player in the pathogenesis of myocardial infarction and may open new therapeutic avenues targeting the gut microbiome to combat cardiovascular diseases.

Advancement in AI-Based Devices for Monitoring Heart Health in Patients with Cardiac Conditions

In the contemporary landscape of cardiac healthcare, the integration of Artificial Intelligence (AI) into monitoring devices represents a groundbreaking shift towards enhancing patient outcomes and streamlining the management of heart health. This review paper delves into the burgeoning domain of AI-based devices designed for the meticulous monitoring of heart patients, elucidating the methodologies behind their operation, the breadth of their applications, and the palpable impact they have had on both clinical practices and patient experiences. Through a meticulous selection and analysis of current studies, we uncover the transformative capabilities of AI technologies in detecting and predicting heart-related anomalies, offering a personalized approach to cardiac care. The findings underscore the paramount importance of AI in facilitating early intervention, reducing the incidence of heart-related morbacies, and ultimately, charting a course towards a more responsive and adaptive healthcare ecosystem. The significance of this review lies not only in its comprehensive synthesis of existing research but also in its exploration of future potentials, highlighting the ongoing evolution of AI as a pivotal ally in the quest for improved heart health monitoring. This paper aims to contribute to the academic and medical discourse surrounding AI applications in healthcare, offering insights that may guide future innovations and research directions. Keywords--- AI-driven Cardiac Monitoring, Wearable Health Technology, Remote Heart Health Monitoring, Smart Health Devices, Cardiovascular Disease Management, Machine Learning in, Cardiology, Digital Health Solutions, Real-time Heart Health Analytics, Sensor Technology in Cardiac Care, Patient-Centric Heart Monitoring, AI-based Cardiac Diagnostics, Continuous Heart Rate Monitoring, Mobile Health Applications, Personalized Cardiac Care, Telemedicine in Cardiology.

Use of Dietary Supplements Among People With Atherosclerotic Cardiovascular Disease in the United States: A Population-Based Analysis From NHANES.

Dietary supplement use is prevalent in the general US population, but little is known regarding the driving reasons for their use among those with atherosclerotic cardiovascular disease (ASCVD). Data from the National Health and Nutrition Examination Survey (NHANES) from 2017 to March 2020 were used to identify adults with ASCVD. Supplement use was assessed by interviewers using label review, and surveys captured self-reported reasons for use. Demographic, clinical, medication, and laboratory characteristics were compared between supplement users and nonusers. Among individuals with ASCVD in the National Health and Nutrition Examination Survey (n=965; mean age, 65 years; 56.1% men; 73.7% White individuals), 73.1% reported taking ≥1 dietary supplements, most commonly multivitamins (35.4%), vitamin D (30.8%), and fish oil (19.8%). Of those taking supplements, 47.3% report taking them under the advisement of a health professional. Nearly one fifth (17.9%) reported taking at least 1 supplement for "heart health," most commonly fish oil (11.1%), followed by CoQ10 (4.2%) and resveratrol (1.5%). Supplement users were older (68 versus 62 years; P=0.003), included more women (45.8% versus 37.7%; P=0.17), were less likely to smoke (11.0% versus 36.4%; P<0.001), had higher levels of education (P=0.005) and income (P<0.001), and higher use of statins (69.4% versus 55.8%; P=0.046). Supplement use is common in people with ASCVD. Among the top 3 supplements, a substantial minority were being taken under the direction of health professionals. Supplement users often report taking supplements "for heart health," despite a lack of randomized trial evidence for benefit in ASCVD, indicating a need for more patient and clinician education regarding health benefits of dietary supplements in ASCVD.

More People, More Active, More Often for Heart Health - Taking Action on Physical Activity.

Physical inactivity is a leading contributor to increased cardiovascular morbidity and mortality. Almost 500 million new cases of preventable noncommunicable diseases (NCDs) will occur globally between 2020 and 2030 due to physical inactivity, costing just over US$300 billion, or around US$ 27 billion annually (WHO 2022). Active adults can achieve a reduction of up to 35% in risk of death from cardiovascular disease. Physical activity also helps in moderating cardiovascular disease risk factors such as high blood pressure, unhealthy weight and type 2 diabetes. For people with cardiovascular disease, hypertension, type 2 diabetes and many cancers, physical activity is an established and evidence-based part of treatment and management. For children and young people, physical activity affords important health benefits. Physical activity can also achieve important cross-sector goals. Increased walking and cycling can reduce journeys by vehicles, air pollution, and traffic congestion and contribute to increased safety and liveability in cities.

Mitigation of Cisplatin-Induced Cardiotoxicity by Isorhamnetin: Mechanistic Insights into Oxidative Stress, Inflammation, and Apoptosis Modulation

The flavonoid compound Isorhamnetin (IRMN) is known for its considerable pharmacological properties, which include antioxidant and anti-inflammatory effects, as well as significant protective actions on heart health. However, the potential of IRMN to guard against heart damage caused by cisplatin (CP), a common chemotherapeutic agent, and the specific mechanisms involved, remain unexplored areas. This research was designed to investigate how IRMN counters CP-induced heart toxicity. In our study, mice were orally given IRMN at 50 or 150mg/kg/day for a week, followed by CP injections (5mg/kg/day) on the third and sixth days. The animals were euthanized under sodium pentobarbital anesthesia (50mg/kg, intraperitoneally) on the eighth day to collect blood and heart tissues for further examination. Our findings reveal that IRMN administration significantly reduced the heart damage and the elevation of heart injury markers such as cardiac troponin I, creatine kinase, and lactate dehydrogenase induced by CP. IRMN also effectively lowered oxidative stress markers, including reactive oxygen species and malondialdehyde, while boosting ATP production and antioxidants like superoxide dismutase, catalase, and glutathione. The compound’s capability to diminish the levels of pro-inflammatory cytokines like tumor necrosis factor-alpha and interleukin-6, alongside modulating apoptosis-regulating proteins (enhancing Bcl-2 while suppressing Bax and Caspase-3 expression), further underscores its cardioprotective effect. Notably, IRMN modulated the p62–Keap1–Nrf2 signaling pathway, suggesting a mechanism through which it exerts its protective effects against CP-induced cardiac injury. These insights underscore the potential of IRMN as an effective adjunct in cancer therapy, offering a strategy to mitigate the cardiotoxic side effects of cisplatin.

EXERCISE PRESCRIPTION TO SUPPORT THE MANAGEMENT OF OSTEOPOROSIS: AN EXPERT STATEMENT FOR EXERCISE PHYSIOLOGISTS

INTRODUCTION &amp; AIMS Low bone density, which includes osteopenia and osteoporosis, leads to roughly 183,000 fractures annually in Australia, with associated direct costs of $2.59B. Osteoporosis is underdiagnosed. Exercise is effective therapy but is underutilised due to a lack of knowledge and unfounded concerns about risk of injury. The aim of the newly developed Exercise Prescription for the Prevention of Osteoporosis Fracture National Statement is to provide clear, actionable, evidence-based exercise advice to improve the bone health of people living with osteopenia and osteoporosis. The project was led and supported by Healthy Bones Australia with funding awarded by the Australian Government Department of Health, Public Health and Chronic Disease Program Osteoporosis – Education and Prevention. METHODS An expert working group (scientists, AEP, physiotherapist, endocrinologist and orthopaedic resident) and advisory committee (practising AEPs and physiotherapists) reviewed current evidence and existing guidelines to formulate recommendations for a national statement in the Australian context. A National Exercise Roundtable was convened, including consumers and stakeholders across multiple disciplines, to adapt the recommendations for clinical practice and consumer acceptability. RESULTS The final statement is presented as an evidence-based document, and a 2-page user summary. The Statement outlines the general principles of osteogenic loading and falls prevention, then presents a comprehensive exercise prescription based on those principles, along with special considerations for comorbid conditions. Level A consensus was achieved on five summary statements. CONCLUSION Bone health is an essential part of general health. While exercise prescription for other chronic diseases, such as, heart health and diabetes, is quite well established, there is a care gap for bone which we have addressed. Our National Statement, informed by high level evidence and expert insight, delivers best practice for prescribing exercise for osteoporosis to achieve best patient outcomes. We will present the document to the intended end users – exercise physiologists.

Consumption of Olive Oil and Diet Quality and Risk of Dementia-Related Death

Age-standardized dementia mortality rates are on the rise. Whether long-term consumption of olive oil and diet quality are associated with dementia-related death is unknown. To examine the association of olive oil intake with the subsequent risk of dementia-related death and assess the joint association with diet quality and substitution for other fats. This prospective cohort study examined data from the Nurses' Health Study (NHS; 1990-2018) and Health Professionals Follow-Up Study (HPFS; 1990-2018). The population included women from the NHS and men from the HPFS who were free of cardiovascular disease and cancer at baseline. Data were analyzed from May 2022 to July 2023. Olive oil intake was assessed every 4 years using a food frequency questionnaire and categorized as (1) never or less than once per month, (2) greater than 0 to less than or equal to 4.5 g/d, (3) greater than 4.5 g/d to less than or equal to 7 g/d, and (4) greater than 7 g/d. Diet quality was based on the Alternative Healthy Eating Index and Mediterranean Diet score. Dementia death was ascertained from death records. Multivariable Cox proportional hazards regressions were used to estimate hazard ratios (HRs) and 95% CIs adjusted for confounders including genetic, sociodemographic, and lifestyle factors. Of 92 383 participants, 60 582 (65.6%) were women and the mean (SD) age was 56.4 (8.0) years. During 28 years of follow-up (2 183 095 person-years), 4751 dementia-related deaths occurred. Individuals who were homozygous for the apolipoprotein ε4 (APOE ε4) allele were 5 to 9 times more likely to die with dementia. Consuming at least 7 g/d of olive oil was associated with a 28% lower risk of dementia-related death (adjusted pooled HR, 0.72 [95% CI, 0.64-0.81]) compared with never or rarely consuming olive oil (P for trend < .001); results were consistent after further adjustment for APOE ε4. No interaction by diet quality scores was found. In modeled substitution analyses, replacing 5 g/d of margarine and mayonnaise with the equivalent amount of olive oil was associated with an 8% (95% CI, 4%-12%) to 14% (95% CI, 7%-20%) lower risk of dementia mortality. Substitutions for other vegetable oils or butter were not significant. In US adults, higher olive oil intake was associated with a lower risk of dementia-related mortality, irrespective of diet quality. Beyond heart health, the findings extend the current dietary recommendations of choosing olive oil and other vegetable oils for cognitive-related health.

Development and validation of a novel sleep health score in the sleep heart health study

BackgroundThere is a lack of consensus in evaluating multidimensional sleep health, especially concerning its implication for mortality. A validated multidimensional sleep health score is the foundation of effective interventions. MethodsWe obtained data from 5706 participants in the Sleep Heart Health Study. First, random forest-recursive feature elimination algorithm was used to select potential predictive variables. Second, a sleep composite score was developed based on the regression coefficients from a Cox proportional hazards model evaluating the associations between selected sleep-related variables and mortality. Last, we validated the score by constructing Cox proportional hazards models to assess its association with mortality. ResultsThe mean age of participants was 63.2 years old, and 47.6% (2715/5706) were male. Six sleep variables, including average oxygen saturation (%), spindle density (C3), sleep efficiency (%), spindle density (C4), percentage of fast spindles (%) and percentage of rapid eye movement (%) were selected to construct this multidimensional sleep health score. The average sleep composite score in participants was 6.8 of 22 (lower is better). Participants with a one-point increase in sleep composite score had an 10% higher risk of death (hazard ratio = 1.10, 95% confidence interval: 1.08–1.12). ConclusionsThis study constructed and validated a novel multidimensional sleep health score to better predict death based on sleep, with significant associations between sleep composite score and all-cause mortality. Integrating questionnaire information and sleep microstructures, our sleep composite score is more appropriately applied for mortality risk stratification.

A Facile Green Synthesis of Photoluminescent Carbon Dots using Pumpkin seeds for Ultra-Sensitive Cu2+ and Fe3+ ions Detection in Living Cells

A facile and efficient green synthesis of photoluminescent carbon dots (CDs) was achieved using pumpkin seeds (PS) through the hydrothermal-carbonization method. Pumpkin seeds, well-known for their nutrient-rich composition, offer potential health benefits, including heightened fertility, enhanced heart health, and improved blood sugar regulation. The as-synthesized PS-CDs characterization through UV–vis, photoluminescence (PL), FTIR, XRD, and HR(TEM) analysis. The PL PS-CDs exhibited an excitation-dependent behavior, with the peak shifting from 410 nm to 475 nm under excitation wavelengths ranging from 270 nm to 400 nm. Notably, the synthesized PS-CDs displayed outstanding advantages, such as a high fluorescent quantum yield of 12.7% with bright blue emissions when exposed to UV light at 365 nm. High-resolution TEM images revealed an average size of approximately 4.0 ± 0.2 nm for the synthesized PS-CDs, ranging from 2 to 7 nm with interlayer distance of 0.21 nm. PL spectra of PS-CDs solution, with an excitation wavelength of 338 nm and emission wavelength of 420 nm, were examined in the presence of various metal ions (50 μM). The fluorescence lifetime of the PS-CDs showed an exponential curve, with an average lifetime (τav) of 8.47 ns for Cu2+ and 3.61 ns for Fe3+ ions, respectively, which is strongly indicates that quenching occurs through a static mechanism. The PS-CDs exhibited high sensitivity and selectivity towards Cu2+ and Fe3+ ions, with a linear relationship observed up to a concentration of 50 μM and detection limits of 0.43 and 0.11 μM (S/N=3), respectively. Moreover, the low-toxicity and strongly fluorescent PS-CDs were successfully applied for cell imaging. The practical utility of the developed sensor was determined through the analysis of Cu2+ and Fe3+ ions in spiked water samples, highlighting its considerable analytical and bioanalytical applications.

The emergence and clinical significance of artificial intelligence–enhanced electrocardiography

The integration of artificial intelligence (AI) with electrocardiography (ECG), a technology known as AI-ECG, represents a transformative leap in the field of cardiovascular medicine. This innovative approach has significantly advanced the capabilities of ECG, traditionally used for diagnosing heart diseases. AI-ECG excels in detecting subtle changes and interconnected patterns in cardiac waveforms, offering a level of precision and sensitivity that was previously unattainable with conventional methods. The scope of AI-ECG extends beyond the realm of heart diseases. It has shown remarkable potential in predicting and identifying the impacts of noncardiac conditions on heart health, thereby broadening the diagnostic capabilities of ECG. This is especially valuable given the complex nature of cardiovascular diseases and their interactions with other health conditions. Despite its groundbreaking potential, AI-ECG faces several challenges. One of the primary concerns is the "black box" nature of AI algorithms, which can make the decision-making process opaque and difficult to interpret. This poses a challenge in medical settings where understanding the rationale behind a diagnosis is crucial. Additionally, the effectiveness of AI-ECG is dependent on the quality and diversity of the datasets used to train the algorithms. Limited or biased datasets can lead to inaccuracies and diminish the reliability of the technology. However, the benefits of AI-ECG are significant. It enables faster, more accurate diagnoses and has the potential to greatly enhance the efficiency of cardiovascular care. As research and technology continue to evolve, AI-ECG is poised to become an indispensable tool in the diagnosis and management of heart diseases.

Correction to: AI-Driven cardiac wellness: Predictive modeling for elderly heart health optimization

Correction to: AI-Driven cardiac wellness: Predictive modeling for elderly heart health optimization

TPTM-HANN-GA: A Novel Hyperparameter Optimization Framework Integrating the Taguchi Method, an Artificial Neural Network, and a Genetic Algorithm for the Precise Prediction of Cardiovascular Disease Risk

The timely and precise prediction of cardiovascular disease (CVD) risk is essential for effective prevention and intervention. This study proposes a novel framework that integrates the two-phase Taguchi method (TPTM), the hyperparameter artificial neural network (HANN), and a genetic algorithm (GA) called TPTM-HANN-GA. This framework efficiently optimizes hyperparameters for an artificial neural network (ANN) model during the training stage, significantly enhancing prediction accuracy for cardiovascular disease (CVD) risk. The proposed TPTM-HANN-GA framework requires far fewer experiments than a traditional grid search, making it highly suitable for application in resource-constrained, low-power computers, and edge artificial intelligence (edge AI) devices. Furthermore, the proposed TPTM-HANN-GA framework successfully identified the optimal configurations for the ANN model’s hyperparameters, resulting in a hidden layer of 4 nodes, a tan h activation function, an SGD optimizer, a learning rate of 0.23425849, a momentum rate of 0.75462782, and seven hidden nodes. This optimized ANN model achieves 74.25% accuracy in predicting the risk of cardiovascular disease, which exceeds the existing state-of-the-art GA-ANN and TSTO-ANN models. The proposed TPTM-HANN-GA framework enables personalized CVD prediction to be efficiently conducted on low-power computers and edge-AI devices, achieving the goal of point-of-care testing (POCT) and empowering individuals to manage their heart health effectively.

Classification Method of ECG Signals Based on RANet.

Electrocardiograms (ECG) are an important source of information on human heart health and are widely used to detect different types of arrhythmias. With the advancement of deep learning, end-to-end ECG classification models based on neural networks have been developed. However, deeper network layers lead to gradient vanishing. Moreover, different channels and periods of an ECG signal hold varying significance for identifying different types of ECG abnormalities. To solve these two problems, an ECG classification method based on a residual attention neural network is proposed in this paper. The residual network (ResNet) is used to solve the gradient vanishing problem. Moreover, it has fewer model parameters, and its structure is simpler. An attention mechanism is added to focus on key information, integrate channel features, and improve voting methods to alleviate the problem of data imbalance. Experiments and verifications are conducted using the PhysioNet/CinC Challenge 2017 dataset. The average F1 value is 0.817, which is 0.064 higher than that for the ResNet model. Compared with the mainstream methods, the performance is excellent.

Current Models for Congenital Heart Center Structure and Health System Integration.

Current Models for Congenital Heart Center Structure and Health System Integration.

0533 Sleep Spindle Features in Obstructive Sleep Apnea: Results from the Sleep Heart Health Study

0533 Sleep Spindle Features in Obstructive Sleep Apnea: Results from the Sleep Heart Health Study

Decolonizing Impact Through the Culture-Centered Approach to Health Communication: Mobilizing Communities to Transform the Structural Determinants of Health

ABSTRACT In this issue, we outline the central tenets of the culture-centered approach to health communication. What does the culture-centered approach address when suggesting the co-creation of voice infrastructures? What is the theory’s methodological emphasis for mobilizing and transforming structures that shape health inequalities for communities at the margins? Drawing on examples of culture-centered interventions in over fifty communities spread across 17 countries and three continents, a large number of them housed under the umbrella of the Center for Culture-centered Approach to Research and Evaluation (CARE) at Massey University in Aotearoa, New Zealand, we articulate the communicative processes (referring to actionable sources and targets of communicative action) that shape the building of voice infrastructures mobilizing toward structural transformation. For instance, African American communities organizing under the framework of the culture-centered approach, documented in Dutta, Collins, and colleagues study in 2019, discuss the building of voice infrastructures where community members participate in co-creating heart health information based on comparative effectiveness research, building an African American media ecosystem disseminating the information alongside community-led initiatives growing healthy food, community-led youth activities, and activism addressing the racist structural drivers that adversely impact African American heart health. In this essay, we describe the impact of culture-centered interventions reflected in the voice infrastructures within communities that witness and articulate the oppressions that threaten human health at the margins and in the transformations of these structures that organize various facets of life and livelihood at the global margins linked to health.

Diurnal expression of Dgat2 induced by time-restricted feeding maintains cardiac health in the Drosophila model of circadian disruption.

Circadian disruption is associated with an increased risk of cardiometabolic disorders and cardiac diseases. Time-restricted feeding/eating (TRF/TRE), restricting food intake within a consistent window of the day, has shown improvements in heart function from flies and mice to humans. However, whether and how TRF still conveys cardiac benefits in the context of circadian disruption remains unclear. Here, we demonstrate that TRF sustains cardiac performance, myofibrillar organization, and regulates cardiac lipid accumulation in Drosophila when the circadian rhythm is disrupted by constant light. TRF induces oscillations in the expression of genes associated with triglyceride metabolism. In particular, TRF induces diurnal expression of diacylglycerol O-acyltransferase 2 (Dgat2), peaking during the feeding period. Heart-specific manipulation of Dgat2 modulates cardiac function and lipid droplet accumulation. Strikingly, heart-specific overexpression of human Dgat2 at ZT 0-10 significantly improves cardiac performance in flies exposed to constant light. We have demonstrated that TRF effectively attenuates cardiac decline induced by circadian disruption. Moreover, our data suggests that diurnal expression of Dgat2 induced by TRF is beneficial for heart health under circadian disruption. Overall, our findings have underscored the relevance of TRF in preserving heart health under circadian disruptions and provided potential targets, such as Dgat2, and strategies for therapeutic interventions in mitigating cardiac aging, metabolic disorders, and cardiac diseases in humans.

Prevalence of Cardiovascular Disease and Risk Factors Among Former National Football League Players

BackgroundCardiovascular disease (CVD) is the leading cause of death worldwide, but prevalence estimates in former professional athletes are limited. ObjectivesHUDDLE (Heart Health: Understanding and Diagnosing Disease by Leveraging Echocardiograms) aimed to raise awareness and estimate the prevalence of CVD and associated risk factors among members of the National Football League (NFL) Alumni Association and their families through education and screening events. MethodsHUDDLE was a multicity, cross-sectional study of NFL alumni and family members aged 50 years and older. Subjects reported their health history and participated in CVD education and screening (blood pressure, electrocardiogram, and transthoracic echocardiogram [TTE] assessments). Phone follow-up by investigators occurred 30 days postscreening to review results and recommendations. This analysis focuses on former NFL athletes. ResultsOf 498 participants screened, 57.2% (N = 285) were former NFL players, the majority of whom were African American (67.6%). The prevalence of hypertension among NFL alumni was estimated to be 89.8%, though only 37.5% reported a history of hypertension. Of 285 evaluable participants, 61.8% had structural cardiac abnormalities by TTE. Multivariable analysis showed that hypertension was a significant predictor of clinically relevant structural abnormalities on TTE. ConclusionsHUDDLE identified a large discrepancy between participant self-awareness and actual prevalence of CVD and risk factors, highlighting a significant opportunity for population health interventions. Structural cardiac abnormalities were observed in most participants and were independently predicted by hypertension, affirming the role of TTE for CVD screening in this population aged older than 50 years. (Heart Health: Understanding and Diagnosing Disease by Leveraging Echocardiograms [HUDDLE]; NCT05009589)

Radiology: Cardiothoracic Imaging Highlights 2023.

Radiology: Cardiothoracic Imaging publishes novel research and technical developments in cardiac, thoracic, and vascular imaging. The journal published many innovative studies during 2023 and achieved an impact factor for the first time since its inaugural issue in 2019, with an impact factor of 7.0. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2022 and October 2023. The review encompasses various aspects of coronary CT, photon-counting detector CT, PET/MRI, cardiac MRI, congenital heart disease, vascular imaging, thoracic imaging, artificial intelligence, and health services research. Key highlights include the potential for photon-counting detector CT to reduce contrast media volumes, utility of combined PET/MRI in the evaluation of cardiac sarcoidosis, the prognostic value of left atrial late gadolinium enhancement at MRI in predicting incident atrial fibrillation, the utility of an artificial intelligence tool to optimize detection of incidental pulmonary embolism, and standardization of medical terminology for cardiac CT. Ongoing research and future directions include evaluation of novel PET tracers for assessment of myocardial fibrosis, deployment of AI tools in clinical cardiovascular imaging workflows, and growing awareness of the need to improve environmental sustainability in imaging. Keywords: Coronary CT, Photon-counting Detector CT, PET/MRI, Cardiac MRI, Congenital Heart Disease, Vascular Imaging, Thoracic Imaging, Artificial Intelligence, Health Services Research © RSNA, 2024.