Search Results (86)

Background/Objectives: Historically, echocardiographic imaging of the right heart has been challenging because its abnormal geometry is not conducive to reproducible anatomical and functional assessment. With the development of advanced echocardiographic techniques, it is now possible to complete an integrated assessment of the right heart that has fewer assumptions, resulting in increased accuracy and precision. Echocardiography continues to be the first-line imaging modality for diagnostic analysis and the management of acute and chronic right heart failure because of its portability, versatility, and affordability compared to cardiac computed tomography, magnetic resonance imaging, nuclear scintigraphy, and positron emission tomography. Virtually all echocardiographic parameters have been well-validated and have demonstrated prognostic significance. The goal of this narrative review of the echocardiographic parameters of the right heart chambers and hemodynamic alterations associated with right ventricular dysfunction is to present information that must be acquired during each examination to deliver a comprehensive assessment of the right heart and to discuss their clinical significance in right heart failure. Methods: Using a literature search in the PubMed database from 1985 to 2025 and the Cochrane database, which included but was not limited to terminology that are descriptive of right heart anatomy and function, disease states involving acute and chronic right heart failure and pulmonary hypertension, and the application of conventional and advanced echocardiographic modalities that strive to elucidate the pathophysiology of right heart failure, we reviewed randomized control trials, observational retrospective and prospective cohort studies, societal guidelines, and systematic review articles. Conclusions: In addition to the conventional 2-dimensional echocardiography and color, spectral, and tissue Doppler measurements, a contemporary echocardiographic assessment of a patient with suspected or proven right heart failure must include 3-dimensional echocardiographic-derived measurements, speckle-tracking echocardiography strain analysis, and hemodynamics parameters to not only characterize the right heart anatomy but to also determine the underlying pathophysiology of right heart failure. Complete and point-of-care echocardiography is available in virtually all clinical settings for routine care, but this imaging tool is particularly indispensable in the emergency department, intensive care units, and operating room, where it can provide an immediate assessment of right ventricular function and associated hemodynamic changes to assist with real-time management decisions. Full article

Background/Objectives: This study aimed to evaluate myocardial scar burden and distribution, as well as other nuclear imaging parameters, in predicting cardiac resynchronization therapy (CRT) responses and long-term outcomes in patients selected for CRT with ischemic HF etiology. Methods: Seventy-one patients were prospectively included. They all had NYHA class II/III despite optimal medical therapy, LVEF ≤ 35%, wide QRS complexes, and ischemic HF etiology. All were indicated for de novo CRT implantation and underwent a SPECT MPI viability test prior to CRT implantation. Two-dimensional echocardiography was performed one day before CRT implantation and 6 months after the intervention. The follow-up examination was conducted six months after the CRT implantation and, after 5 years, patients underwent a telephone follow-up to assess survival. Results: Most patients (85%) were male, with an average age of 66.26 ± 9.25 yrs. SPECT MPI revealed large myocardial scars (44.53 ± 20.94%) with high summed rest scores (SRSs) of 25.02 ± 11.29 and low EFs of 26.67 ± 7.71%. At the 6-month follow-up, after the CRT implantation, the NYHA class significantly changed and 35% of the patients were classified as CRT responders. The only difference between responders and non-responders was in the SRS and myocardial scar size (p < 0.001). A scar size of 19.5% was an optimal cutoff for the prediction of CRT response (AUC 0.853, Sn 85% and 1-sp 94%). Conclusions: SPECT MPI parameters are valuable in predicting responses and long-term survival in patients with CRT. Patients with myocardial scars of less than 19.5% may be suited to CRT and experience better cardiovascular survival. Full article

Cardiac amyloidosis (CA) results from the deposition of either immunoglobulin light chain (AL) or transthyretin (ATTR) amyloid fibrils in the myocardium, causing restrictive cardiomyopathy and, if left untreated, can lead to early death. Advancements in non-invasive diagnostic modalities have led to an increased recognition of the disease. Monoclonal gammopathy plays a pivotal role in the diagnostic algorithm for CA, particularly in differentiating AL from ATTR. This review highlights the importance of monoclonal protein detection through serum protein electrophoresis, immunofixation electrophoresis, and serum free light chain assays as initial screening tools. However, these tests alone are insufficient for a definitive diagnosis due to the complexities associated with coexisting monoclonal gammopathies and the potential for false negative and positive results. Advanced imaging modalities, such as echocardiography, cardiac magnetic resonance, and nuclear scintigraphy, along with tissue biopsy, are crucial for confirming CA and accurately determining the CA subtype. Full article

Heart failure (HF) is a complex clinical syndrome that results from any structural or functional impairment of ventricular filling or ejection of blood. The etiology of heart failure is multifactorial, encompassing ischemic heart disease, hypertension, valvular disorders, cardiomyopathies, and metabolic and infiltrative diseases. Despite advances in pharmacologic and device-based therapies, heart failure continues to carry a substantial burden of morbidity, mortality, and healthcare utilization. With the advancement and increased accessibility of cardiac imaging modalities, the diagnostic accuracy for identifying the underlying etiologies of nonischemic cardiomyopathy has significantly improved, allowing for more precise classification and tailored management strategies. This review aims to provide a comprehensive analysis of the current understanding of heart failure, encompassing epidemiology, etiological factors, with a specific focus on diagnostic imaging modalities including the role of echocardiography and strain imaging, cardiac magnetic resonance imaging (CMR), cardiac computed tomography (CT), and nuclear positron emission tomography (PET) imaging and recent advances in the diagnosis and management of heart failure. Full article

Early detection and the rise of targeted cancer treatment have led to increased overall survival and decreased mortality among cancer patients. As the cancer survivor population ages, there is an increased risk for cardiovascular disease due to pre-existing comorbidities, deconditioning during therapy, or the natural progression of aging. Furthermore, with emerging oncologic therapies, there is an increased recognition of their potential cardiovascular toxicities. Indeed, heart disease is the leading cause of death in cancer survivors, which may reflect upon both the success of novel oncologic therapies and their potential cardiovascular toxicities. This recognition has driven the development of cardio-oncology, a multi-disciplinary field that involves collaboration between hematologists, oncologists, and cardiologists to screen, prevent, and manage cardiovascular disease in cancer patients and cancer survivors. The field focuses on early cardiovascular detection and prevention for these patients before, during, and after their oncologic treatment. As oncologic therapies evolve and our knowledge of short- and long-term adverse cardiovascular effects grows, it is critical for physicians to identify those at risk for increased morbidity and mortality, while also balancing the importance of their oncologic treatment plan. Multimodality cardiac imaging is the crux of the diagnosis and surveillance of these patients within cardio-oncology, and includes echocardiography, nuclear, computed tomography (CT), and cardiac magnetic resonance (CMR). Cardiac imaging is essential to establish the baseline function and assess various cardiotoxicities, including left ventricular dysfunction, heart failure, atherosclerosis, vascular injury, and arrhythmias. This review will discuss common oncologic therapies and their cardiotoxic profiles, the cardiac multimodality imaging modalities used in cardio-oncology, and the various approaches for the diagnosis and surveillance of this population. Full article

Background: Granulomatous and amyloidogenic cardiomyopathies are infiltrative conditions that can be fatal if left untreated. Among these, cardiac amyloidosis and cardiac sarcoidosis are significant but often underdiagnosed causes of heart failure, each serving as cardiac manifestations of broader systemic diseases. Advancements in imaging techniques and the emergence of novel therapies—particularly for cardiac amyloidosis—have brought these conditions into sharper focus for both clinicians and researchers. Methods: We conducted a comprehensive review of the literature by searching databases including PubMed and Scopus for studies published since 1990 regarding clinical features, diagnostic techniques, and treatment strategies for cardiac amyloidosis and cardiac sarcoidosis. Studies were selected based on relevance to imaging methods, including echocardiography, cardiac magnetic resonance imaging (CMR), positron emission tomography (PET), and technetium-labeled nuclear scintigraphy, as well as treatment modalities for both conditions. Results: Imaging techniques, particularly CMR, technetium-labeled nuclear scan, and PET, were found to be crucial for the early identification and differentiation of cardiac amyloidosis and cardiac sarcoidosis. Distinct late gadolinium enhancement patterns were observed in CMR along with morphological differences, aiding in diagnosis. Technetium-labeled nuclear scintigraphy can definitively distinguish between subtypes of cardiac amyloidosis in the absence of paraproteinemia. Early diagnosis has been shown to significantly improve patient outcomes. Early treatment can reduce morbidity in both cardiomyopathies. Conclusions: Multimodality imaging can help in the early detection of cardiac amyloidosis and cardiac sarcoidosis. Treatment strategies differ substantially: cardiac amyloidosis is primarily managed with disease-modifying therapies for the transthyretin subtype and chemotherapy/stem cell transplant for the AL subtype, while cardiac sarcoidosis is treated with corticosteroids and immunosuppressive drugs to reduce inflammation. Early and accurate diagnosis through advanced imaging techniques is critical to improving outcomes for patients with these conditions. Full article

Background: Artificial intelligence (AI) and deep learning are increasingly applied in cardiovascular imaging. However, the “black box” nature of these models raises challenges for clinical trust and integration. Explainable Artificial Intelligence (XAI) seeks to address these concerns by providing insights into model decision-making. This systematic review synthesizes current research on the use of XAI methods in radiological cardiovascular imaging. Methods: A systematic literature search was conducted in PubMed, Scopus, and Web of Science to identify peer-reviewed original research articles published between January 2015 and March 2025. Studies were included if they applied XAI techniques—such as Gradient-Weighted Class Activation Mapping (Grad-CAM), Shapley Additive Explanations (SHAPs), Local Interpretable Model-Agnostic Explanations (LIMEs), or saliency maps—to cardiovascular imaging modalities, including cardiac computed tomography (CT), magnetic resonance imaging (MRI), echocardiography and other ultrasound examinations, and chest X-ray (CXR). Studies focusing on nuclear medicine, structured/tabular data without imaging, or lacking concrete explainability features were excluded. Screening and data extraction followed PRISMA guidelines. Results: A total of 28 studies met the inclusion criteria. Ultrasound examinations (n = 9) and CT (n = 9) were the most common imaging modalities, followed by MRI (n = 6) and chest X-rays (n = 4). Clinical applications included disease classification (e.g., coronary artery disease and valvular heart disease) and the detection of myocardial or congenital abnormalities. Grad-CAM was the most frequently employed XAI method, followed by SHAP. Most studies used saliency-based techniques to generate visual explanations of model predictions. Conclusions: XAI holds considerable promise for improving the transparency and clinical acceptance of deep learning models in cardiovascular imaging. However, the evaluation of XAI methods remains largely qualitative, and standardization is lacking. Future research should focus on the robust, quantitative assessment of explainability, prospective clinical validation, and the development of more advanced XAI techniques beyond saliency-based methods. Strengthening the interpretability of AI models will be crucial to ensuring their safe, ethical, and effective integration into cardiovascular care. Full article

Background and Objectives: Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a well-established technique for evaluating myocardial perfusion and function in patients with suspected or known coronary artery disease. While conventional dual-detector SPECT scanners have limitations in spatial resolution and photon detection sensitivity, recent advancements, including full-ring solid-state cadmium zinc telluride (CZT) detectors, offer enhanced image quality and improved diagnostic accuracy. This study aimed to compare the performance of Veriton-CT, a full-ring CZT SPECT system, with GE Discovery 530c, a dedicated cardiac fixed-angle gamma camera, in myocardial perfusion imaging and their correlation with coronary angiography findings. Materials and Methods: This was a prospective study that analyzed 21 patients who underwent MPI at the Department of Nuclear Medicine, Lithuanian University of Health Sciences, Kauno Klinikos. A one-day stress–rest protocol using 99mTc-Sestamibi was employed, with stress testing performed via bicycle ergometry or pharmacological induction. MPI was first conducted using GE Discovery 530c (GE Health Care, Boston, MA, USA), followed by imaging on Veriton-CT, which included low-dose CT for attenuation correction. The summed stress score (SSS), summed rest score (SRS), and summed difference score (SDS) were analyzed and compared between both imaging modalities. Coronary angiography results were retrospectively collected, and lesion-based analysis was performed to assess the correlation between imaging results and the presence of significant coronary artery stenosis (≥35% and ≥70% narrowing). Image quality and the certainty of distinguishing the inferior myocardial wall from extracardiac structures were also evaluated by two independent researchers with differing levels of experience. Results: Among the 14 patients included in the final analysis, Veriton-CT was more likely to classify MPI scans as normal (64.3%) compared to GE Discovery 530c (28.6%). Additionally, Veriton-CT provided a better assessment of the right coronary artery (RCA) basin, showing greater agreement with coronary angiography findings than GE Discovery 530c, although the difference was not statistically significant. No significant differences in lesion overlap were observed for the left anterior descending artery (LAD) or left circumflex artery (LCx) basins. Furthermore, the image quality assessment revealed slightly better delineation of extracardiac structures using Veriton-CT (Spectrum Dynamics Medical, Caesarea, Israel), particularly when evaluated by an experienced researcher. However, no significant difference was observed when assessed by a less experienced observer. Conclusions: Our findings suggest that Veriton-CT, with its full-ring CZT detector system, may offer advantages over fixed-angle gamma cameras in improving image quality and reducing attenuation artifacts in MPI. Although the difference in correlations with coronary angiography findings was not statistically significant, Veriton-CT showed a trend toward better agreement, particularly in the RCA basin. These results indicate that full-ring SPECT imaging could improve the diagnostic accuracy of non-invasive MPI, potentially reducing the need for unnecessary invasive angiography. Further studies with larger patient cohorts are required to confirm these findings and evaluate the clinical impact of full-ring SPECT technology in myocardial perfusion imaging. Full article

Hypertrophic cardiomyopathy (HCM) is the most common genetically inherited cardiac condition, characterized by clinical heterogeneity and a significantly increased risk of adverse cardiovascular outcomes, including sudden cardiac death. Current diagnostic methods primarily use echocardiography, often supplemented by cardiovascular magnetic resonance imaging (MRI), to assess the clinical profile of the disorder. Effective risk stratification protocols are essential for managing patients with HCM. These models rely on patient histories, imaging findings, and genetic information to evaluate the prognosis. Important factors in risk assessment include severe left ventricular hypertrophy (>30 mm), late gadolinium enhancement (>15%), or the presence of an apical aneurysm. However, these imaging techniques may lack sensitivity when it comes to detecting ischemia or microvascular dysfunction. Nuclear imaging methods, such as single-photon emission computed tomography (SPECT) and positron emission tomography (PET), offer a more comprehensive analysis of HCM. They provide valuable insights into the complex physiological mechanisms underlying the disease and facilitate early detection of functional abnormalities. This is particularly important for identifying high-risk phenotypes and understanding associated risk factors that may increase morbidity or mortality. This narrative review focuses on the role of nuclear imaging in the context of hypertrophic cardiomyopathy. Full article

Cardiovascular disease (CVD) is a leading cause of death, accounting for over 30% of annual global fatalities. Ischemic heart disease, in turn, is a frontrunner of worldwide CVD mortality. With the burden of coronary disease rapidly growing, understanding the nuances of cardiac imaging and risk prognostication becomes paramount. Myocardial perfusion imaging (MPI) is a frequently utilized and well established testing modality due to its significant clinical impact in disease diagnosis and risk assessment. Recently, nuclear cardiology has witnessed major advancements, driven by innovations in novel imaging technologies and improved understanding of cardiovascular pathophysiology. Applications of artificial intelligence (AI) to MPI have enhanced diagnostic accuracy, risk stratification, and therapeutic decision-making in patients with coronary artery disease (CAD). AI techniques such as machine learning (ML) and deep learning (DL) neural networks offer new interpretations of immense data fields, acquired through cardiovascular imaging modalities such as nuclear medicine (NM). Recently, AI algorithms have been employed to enhance image reconstruction, reduce noise, and assist in the interpretation of complex datasets. The rise of AI in nuclear medicine (AI-NM) has proven itself groundbreaking in the efficiency of image acquisition, post-processing time, diagnostic ability, consistency, and even in risk-stratification and outcome prognostication. To that end, this narrative review will explore these latest advances in AI in nuclear medicine and its rapid transformation of the cardiac diagnostics landscape. This paper will examine the evolution of AI-NM, review novel AI techniques and applications in nuclear cardiac imaging, summarize recent AI-NM clinical trials, and explore the technical and clinical challenges in its implementation of artificial intelligence. Full article

Cardiovascular diseases and cancer are the leading causes of morbidity and mortality in modern society. Expanding cancer therapies that have improved prognosis may also be associated with cardiotoxicity, and extended life span after survivorship is associated with the increasing prevalence of cardiovascular disease. As such, the field of cardio-oncology has been rapidly expanding, with an aim to identify cardiotoxicity and cardiac disease early in a patient who is receiving treatment for cancer or is in survivorship. Artificial intelligence is revolutionizing modern medicine with its ability to identify cardiac disease early. This article comprehensively reviews applications of artificial intelligence specifically applied to electrocardiograms, echocardiography, cardiac magnetic resonance imaging, and nuclear imaging to predict cardiac toxicity in the setting of cancer therapies, with a view to reduce early complications and cardiac side effects from cancer therapies such as chemotherapy, radiation therapy, or immunotherapy. Full article

Background: Artificial intelligence (AI) in echocardiography represents a transformative advancement in cardiology, addressing longstanding challenges in cardiac diagnostics. Echocardiography has traditionally been limited by operator-dependent variability and subjective interpretation, which impact diagnostic reliability. This study evaluates the role of AI, particularly machine learning (ML), in enhancing the accuracy and consistency of echocardiographic image analysis and its potential to complement clinical expertise. Methods: A comprehensive review of existing literature was conducted to analyze the integration of AI into echocardiography. Key AI functionalities, such as image acquisition, standard view classification, cardiac chamber segmentation, structural quantification, and functional assessment, were assessed. Comparisons with traditional imaging modalities like computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI) were also explored. Results: AI algorithms demonstrated expert-level accuracy in diagnosing conditions such as cardiomyopathies while reducing operator variability and enhancing diagnostic consistency. The application of ML was particularly effective in automating image analysis and minimizing human error, addressing the limitations of subjective operator expertise. Conclusions: The integration of AI into echocardiography marks a pivotal shift in cardiovascular diagnostics, offering enhanced accuracy, consistency, and reliability. By addressing operator variability and improving diagnostic performance, AI has the potential to elevate patient care and herald a new era in cardiology. Full article

Marfan syndrome (MFS) is a genetic disorder affecting connective tissue, often leading to cardiovascular complications such as aortic aneurysms and mitral valve prolapse. Cardiovascular multimodality imaging plays a crucial role in the diagnosis, monitoring, and management of MFS patients. This review explores the advancements in echocardiography, cardiovascular magnetic resonance (CMR), cardiac computed tomography (CCT), and nuclear medicine techniques in MFS. Echocardiography remains the first-line tool, essential for assessing aortic root, mitral valve abnormalities, and cardiac function. CMR provides detailed anatomical and functional assessments without radiation exposure, making it ideal for long-term follow-up. CT offers high-resolution imaging of the aorta, crucial for surgical planning, despite its ionizing radiation. Emerging nuclear medicine techniques, though less common, show promise in evaluating myocardial involvement and inflammatory conditions. This review underscores the importance of a comprehensive imaging approach to improve outcomes and guide interventions in MFS patients. It also introduces novel aspects of multimodality approaches, emphasizing their impact on early detection and management of cardiovascular complications in MFS. Full article

Iodine-123 metaiodobenzylguanidine (I-123 MIBG) is a crucial radiopharmaceutical widely used in nuclear medicine for its diagnostic capabilities in both cardiology and oncology. This review aims to present a comprehensive evaluation of the clinical applications of I-123 MIBG, focusing on its use in diagnosing and managing various diseases. In cardiology, I-123 MIBG has proven invaluable in assessing cardiac sympathetic innervation, particularly in patients with heart failure, where it provides prognostic information that guides treatment strategies. In oncology, I-123 MIBG is primarily utilized for imaging neuroendocrine tumors, such as neuroblastoma and pheochromocytoma, where it offers high specificity and sensitivity in the detection of adrenergic tissue. Additionally, its role in neurology, specifically in differentiating between Parkinson’s disease, dementia, and Lewy body dementia, has become increasingly significant due to its ability to identify postganglionic sympathetic dysfunction. Despite its established clinical utility, the use of I-123 MIBG is not without limitations, including variability in imaging protocols and interpretation challenges. This review will explore these issues and discuss emerging alternatives, while also highlighting areas where I-123 MIBG continues to be a gold standard. By synthesizing the current research, this article aims to provide a clear understanding of the strengths, limitations, and prospects of I-123 MIBG in clinical practice. Full article

Cardiac amyloidosis (CA) is a cardiac storage disease caused by the progressive extracellular deposition of misfolded proteins in the myocardium. Despite the increasing interest in this pathology, it remains an underdiagnosed condition. Non-invasive diagnostic techniques play a central role in the suspicion and detection of CA, also thanks to the continuous scientific and technological advances in these tools. The 12-lead electrocardiography is an inexpensive and reproducible test with a diagnostic accuracy that, in some cases, exceeds that of imaging techniques, as recent studies have shown. Echocardiography is the first-line imaging modality, although none of its parameters are pathognomonic. According to the 2023 ESC Guidelines, a left ventricular wall thickness ≥ 12 mm is mandatory for the suspicion of CA, making this technique crucial. Cardiac magnetic resonance provides high-resolution images associated with tissue characterization. The use of contrast and non-contrast sequences enhances the diagnostic power of this imaging modality. Nuclear imaging techniques, including bone scintigraphy and positron emission tomography, allow the detection of amyloid deposition in the heart, and their role is also central in assessing the prognosis and response to therapy. The role of computed tomography was recently evaluated by several studies, above in population affected by aortic stenosis undergoing transcatheter aortic valve replacement, with promising results. Finally, machine learning and artificial intelligence-derived algorithms are gaining ground in this scenario and provide the basis for future research. Understanding the new insights into non-invasive diagnostic techniques is critical to better diagnose and manage patients with CA and improve their survival. Full article