Imaging Cardiac Masses in Patients with Cancer.

BACKGROUND: Cardiac tumors are rare and the majority are from a primary source outside of the heart. Most are found, incidentally, with echocardiography but often additional cardiac imaging is needed to refine the differential diagnosis. For this purpose, cardiac magnetic resonance imaging (MRI) and to a lesser extent cardiac computed tomography (CT) or 18F-fluorodeoxyglucose positron-emission tomography/computed tomography (18F-FDG PET/CT) are useful imaging modalities to better characterize a cardiac tumor and determine the likelihood of a neoplastic versus non-neoplastic origin. Cardiac CT may be useful to evaluate the effect of treatment while using 18F-FDG PET/CT to evaluate cardiac masses is under-studied but may be useful in patients who are already having a scan performed for oncologic reasons. It is through understanding the clinical context of a newly discovered cardiac mass, knowledge of the typical locations of various cardiac tumor types, combined with imaging techniques that avoid ionizing radiation that yield the greatest confidence in the noninvasive diagnosis of a cardiac mass.

Point-of-Care Ultrasound.

PURPOSE OF THE REVIEW: Point-of-care ultrasound using small ultrasound devices has expanded beyond emergency and critical care medicine to many other subspecialties. Awareness of the strengths and limitations of the technology and knowledge of the appropriate settings and common indications for point-of-care ultrasound is important. RECENT FINDINGS: Point-of-care ultrasound is widely embraced as an extension of the physical exam and is employed in acute care and medical education settings. Echocardiography laboratories involved in education must individualize training to the intended scope of practice of the user. Advances in artificial intelligence may assist in image acquisition and interpretation by novice users. Point-of-care ultrasound is widely available in a variety of clinical settings. The field has advanced substantially in the past 2 decades and will likely continue to expand with advancement in technology, reduced cost, and improved opportunities to assist new users.

Risk factors for chemotherapy-related cardiac toxicity.

PURPOSE OF REVIEW: The purpose of this review is to discuss the clinical and treatment-related factors that increase the risk of cardiotoxicity with anthracyclines and human epidermal growth factor 2 receptor inhibitors. RECENT FINDINGS: Age and preexisting left ventricular dysfunction have been identified most consistently as being associated with the development of clinical heart failure or a worsening of left ventricular function with chemotherapy. Other cardiovascular conditions, including hypertension, diabetes, and coronary artery disease, are also associated with the risk of cardiotoxicity. There is growing evidence that Blacks are at a higher risk of developing cardiotoxicity than Whites, even after adjusting for known confounders. Pharmacogenomics is also emerging as a potential tool to help identify patients who are at higher risk for cardiotoxicity. Treatment-related risk factors include the dose of anthracycline or its formulation, whether the patient is receiving additional chemotherapeutic agents or radiation. SUMMARY: Several clinical and treatment-related risk factors are associated with cardiotoxicity. Further study is needed to determine whether optimization of modifiable risk factors prior to treatment can reduce the risk of cardiotoxicity.

Diagnosis and Management of Aortic Diseases.

This JAMA Clinical Guidelines Synopsis summarizes the 2022 American College of Cardiology/American Heart Association guidelines for diagnosis and management of aortic disease.

Integrated analyses of gene expression and genetic association studies in a founder population.

Genome-wide association studies (GWASs) have become a standard tool for dissecting genetic contributions to disease risk. However, these studies typically require extraordinarily large sample sizes to be adequately powered. Strategies that incorporate functional information alongside genetic associations have proved successful in increasing GWAS power. Following this paradigm, we present the results of 20 different genetic association studies for quantitative traits related to complex diseases, conducted in the Hutterites of South Dakota. To boost the power of these association studies, we collected RNA-sequencing data from lymphoblastoid cell lines for 431 Hutterite individuals. We then used Sherlock, a tool that integrates GWAS and expression quantitative trait locus (eQTL) data, to identify weak GWAS signals that are also supported by eQTL data. Using this approach, we found novel associations with quantitative phenotypes related to cardiovascular disease, including carotid intima-media thickness, left atrial volume index, monocyte count and serum YKL-40 levels.

An insidious and deadly complication of mechanical chest compressions in a patient on anticoagulation and the subtle echocardiographic findings that enabled timely diagnosis.

Good-quality chest compressions improve outcomes in cardiac arrest. While manual chest compressions are suboptimal in this regard, the LUCAS device has been shown to improve the effectiveness of chest compressions during cardiopulmonary resuscitation (CPR). The complication rate associated with mechanical CPR, however, has not been adequately studied. Limited evidence suggests no difference in internal injury between manual and mechanical CPR. We report the case of a patient on anticoagulation who developed a mediastinal hematoma post mechanical CPR and on whom subtle findings on initial echocardiography could have alerted the clinician to this complication early during the clinical course. This case further suggests that there may be special populations of patients in whom we may need to be more vigilant in the use of mechanical CPR.

Cardio-Oncology Training: A Proposal From the International Cardioncology Society and Canadian Cardiac Oncology Network for a New Multidisciplinary Specialty.

There is an increasing awareness and clinical interest in cardiac safety during cancer therapy as well as in optimally addressing cardiac issues in cancer survivors. Although there is an emerging expertise in this area, known as cardio-oncology, there is a lack of organization in the essential components of contemporary training. This proposal, an international consensus statement organized by the International Cardioncology Society and the Canadian Cardiac Oncology Network, attempts to marshal the important ongoing efforts for training the next generation of cardio-oncologists. The necessary elements are outlined, including the expectations for exposure necessary to develop adequate training. There should also be a commitment to local, regional, and international education and research in cardio-oncology as a requirement for advancement in the field.

Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers.

BACKGROUND: Although regional wall motion abnormality (RWMA) detection is foundational to transthoracic echocardiography, current methods are prone to interobserver variability. We aimed to develop a deep learning (DL) model for RWMA assessment and compare it to expert and novice readers. METHODS: We used 15,746 transthoracic echocardiography studies-including 25,529 apical videos-which were split into training, validation, and test datasets. A convolutional neural network was trained and validated using apical 2-, 3-, and 4-chamber videos to predict the presence of RWMA in 7 regions defined by coronary perfusion territories, using the ground truth derived from clinical transthoracic echocardiography reports. Within the test cohort, DL model accuracy was compared to 6 expert and 3 novice readers using F1 score evaluation, with the ground truth of RWMA defined by expert readers. Significance between the DL model and novices was assessed using the permutation test. RESULTS: Within the test cohort, the DL model accurately identified any RWMA with an area under the curve of 0.96 (0.92-0.98). The mean F1 scores of the experts and the DL model were numerically similar for 6 of 7 regions: anterior (86 vs 84), anterolateral (80 vs 74), inferolateral (83 vs 87), inferoseptal (86 vs 86), apical (88 vs 87), inferior (79 vs 81), and any RWMA (90 vs 94), respectively, while in the anteroseptal region, the F1 score of the DL model was lower than the experts (75 vs 89). Using F1 scores, the DL model outperformed both novices 1 (P = .002) and 2 (P = .02) for the detection of any RWMA. CONCLUSIONS: Deep learning provides accurate detection of RWMA, which was comparable to experts and outperformed a majority of novices. Deep learning may improve the efficiency of RWMA assessment and serve as a teaching tool for novices.

Advancing the care of individuals with cancer through innovation & technology: Proceedings from the cardiology oncology innovation summit 2020 and 2021.

As cancer therapies increase in effectiveness and patients' life expectancies improve, balancing oncologic efficacy while reducing acute and long-term cardiovascular toxicities has become of paramount importance. To address this pressing need, the Cardiology Oncology Innovation Network (COIN) was formed to bring together domain experts with the overarching goal of collaboratively investigating, applying, and educating widely on various forms of innovation to improve the quality of life and cardiovascular healthcare of patients undergoing and surviving cancer therapies. The COIN mission pillars of innovation, collaboration, and education have been implemented with cross-collaboration among academic institutions, private and public establishments, and industry and technology companies. In this report, we summarize proceedings from the first two annual COIN summits (inaugural in 2020 and subsequent in 2021) including educational sessions on technological innovations for establishing best practices and aligning resources. Herein, we highlight emerging areas for innovation and defining unmet needs to further improve the outcome for cancer patients and survivors of all ages. Additionally, we provide actionable suggestions for advancing innovation, collaboration, and education in cardio-oncology in the digital era.

Global Cardio Oncology Registry (G-COR): Registry Design, Primary Objectives, and Future Perspectives of a Multicenter Global Initiative.

BACKGROUND: Global collaboration in cardio-oncology is needed to understand the prevalence of cancer therapy-related cardiovascular toxicity in different risk groups, practice settings, and geographic locations. There are limited data on the socioeconomic and racial/ethnic disparities that may impact access to care and outcomes. To address these gaps, we established the Global Cardio-Oncology Registry, a multinational, multicenter prospective registry. METHODS: We assembled cardiologists and oncologists from academic and community settings to collaborate in the first Global Cardio-Oncology Registry. Subsequently, a survey for site resources, demographics, and intention to participate was conducted. We designed an online data platform to facilitate this global initiative. RESULTS: A total of 119 sites responded to an online questionnaire on their practices and main goals of the registry: 49 US sites from 23 states and 70 international sites from 5 continents indicated a willingness to participate in the Global Cardio-Oncology Registry. Sites were more commonly led by cardiologists (85/119; 72%) and were more often university/teaching (81/119; 68%) than community based (38/119; 32%). The average number of cardio-oncology patients treated per month was 80 per site. The top 3 Global Cardio-Oncology Registry priorities in cardio-oncology care were breast cancer, hematologic malignancies, and patients treated with immune checkpoint inhibitors. Executive and scientific committees and specific committees were established. A pilot phase for breast cancer using Research Electronic Data Capture Cloud platform recently started patient enrollment. CONCLUSIONS: We present the structure for a global collaboration. Information derived from the Global Cardio-Oncology Registry will help understand the risk factors impacting cancer therapy-related cardiovascular toxicity in different geographic locations and therefore contribute to reduce access gaps in cardio-oncology care. Risk calculators will be prospectively derived and validated.

COVID-19 severity and cardiovascular outcomes in SARS-CoV-2-infected patients with cancer and cardiovascular disease.

Background: Data regarding outcomes among patients with cancer and co-morbid cardiovascular disease (CVD)/cardiovascular risk factors (CVRF) after SARS-CoV-2 infection are limited. Objectives: To compare Coronavirus disease 2019 (COVID-19) related complications among cancer patients with and without co-morbid CVD/CVRF. Methods: Retrospective cohort study of patients with cancer and laboratory-confirmed SARS-CoV-2, reported to the COVID-19 and Cancer Consortium (CCC19) registry from 03/17/2020 to 12/31/2021. CVD/CVRF was defined as established CVD or no established CVD, male ≥ 55 or female ≥ 60 years, and one additional CVRF. The primary endpoint was an ordinal COVID-19 severity outcome including need for hospitalization, supplemental oxygen, intensive care unit (ICU), mechanical ventilation, ICU or mechanical ventilation plus vasopressors, and death. Secondary endpoints included incident adverse CV events. Ordinal logistic regression models estimated associations of CVD/CVRF with COVID-19 severity. Effect modification by recent cancer therapy was evaluated. Results: Among 10,876 SARS-CoV-2 infected patients with cancer (median age 65 [IQR 54-74] years, 53% female, 52% White), 6253 patients (57%) had co-morbid CVD/CVRF. Co-morbid CVD/CVRF was associated with higher COVID-19 severity (adjusted OR: 1.25 [95% CI 1.11-1.40]). Adverse CV events were significantly higher in patients with CVD/CVRF (all p<0.001). CVD/CVRF was associated with worse COVID-19 severity in patients who had not received recent cancer therapy, but not in those undergoing active cancer therapy (OR 1.51 [95% CI 1.31-1.74] vs. OR 1.04 [95% CI 0.90-1.20], pinteraction <0.001). Conclusions: Co-morbid CVD/CVRF is associated with higher COVID-19 severity among patients with cancer, particularly those not receiving active cancer therapy. While infrequent, COVID-19 related CV complications were higher in patients with comorbid CVD/CVRF. (COVID-19 and Cancer Consortium Registry [CCC19]; NCT04354701).

Early detection of chemotherapy-related left ventricular dysfunction.

Modern advances in cancer treatment have resulted in improved survival. As a result, effects of cancer therapy on other organ systems such as the heart are more likely to become clinically relevant. One such possibility is chemotherapy-related left ventricular dysfunction. Although in clinical practice cardiotoxicity is evaluated by symptoms and left ventricular ejection fraction, these occur relatively late in the disease process after the heart's compensatory mechanisms have been expended. Ideally, left ventricular dysfunction would be identified early so that cancer patients and their physicians can make informed decisions about their therapeutic options and institute careful surveillance and early initiation of cardioprotective medication where appropriate. This review discusses the role of echocardiography to detect subclinical left ventricular dysfunction in cancer patients exposed to chemotherapy with potential cardiotoxicity, particularly anthracyclines and trastuzumab.

Novel imaging paradigms for characterization of cardiovascular toxicities associated with cancer therapy.

Since the 1970s, there have been many paradigm shifts in the detection of cardiotoxicity associated with cancer treatment. These have included movement away from late sequelae of cancer treatment such as heart failure or decline in ejection fraction toward earlier detection of subclinical toxicity using echocardiographically derived global longitudinal strain and high sensitivity troponin assays. In addition to this, cardiac MRI has had an expanding role in detecting cardiotoxicity due to its reproducibility in left ventricular ejection fraction measurements and tissue characterization. This article summarizes the strengths and weaknesses of these imaging techniques in characterizing cardiotoxicity in patients receiving cancer therapy.

Interconnected Clinical and Social Risk Factors in Breast Cancer and Heart Failure.

Breast cancer and heart failure share several known clinical cardiovascular risk factors, including age, obesity, glucose dysregulation, cholesterol dysregulation, hypertension, atrial fibrillation and inflammation. However, to fully comprehend the complex interplay between risk of breast cancer and heart failure, factors attributed to both biological and social determinants of health must be explored in risk-assessment. There are several social factors that impede implementation of prevention strategies and treatment for breast cancer and heart failure prevention, including socioeconomic status, neighborhood disadvantage, food insecurity, access to healthcare, and social isolation. A comprehensive approach to prevention of both breast cancer and heart failure must include assessment for both traditional clinical risk factors and social determinants of health in patients to address root causes of lifestyle and modifiable risk factors. In this review, we examine clinical and social determinants of health in breast cancer and heart failure that are necessary to consider in the design and implementation of effective prevention strategies that altogether reduce the risk of both chronic diseases.

Utility of transillumination and transparency renderings in 3D transthoracic imaging.

Transillumination (TI) is a new 3D rendering tool that uses a freely movable virtual light source to enhance depth, contours, and image detail. The TI model was recently modified to allow the operator adjust the degree of transparency of both cardiac and extra-cardiac structures. While the addition of transparency was shown to significantly improve quality in 3D transesophageal imaging, this has not yet been shown for transthoracic (TTE) imaging. We prospectively studied 35 patients who underwent clinically indicated TTE with standard 3D acquisition, as well as TI with and without transparency. Six experienced echocardiographers were shown images of all three display types in random order. Each image was scored independently using a Likert Scale while assessing each of the following aspects: ability to identify anatomy or pathology, depth perception, degree of anatomic detail, and border delineation. All experts perceived an incremental value of the transparency mode, compared to TI without transparency and standard 3D rendering, in terms of ability to identify anatomy or pathology (4.15 ± 0.97 vs. 3.88 ± 0.99 vs. 2.52 ± 1.41, p < 0.01), depth perception (4.33 ± 0.78 vs. 3.88 ± 0.82 vs. 2.29 ± 1.07, p < 0.01), degree of anatomic detail (4.08 ± 1.0 vs. 3.89 ± 0.79 vs. 2.31 ± 1.08, p < 0.01), and border delineation (4.44 ± 0.80 vs. 3.90 ± 0.78 vs. 2.42 ± 1.13, p < 0.01). Compared to standard 3D and TI renderings of TTE images, the addition of transparency significantly improves both image quality and diagnostic confidence.

Advances in Multimodality Imaging in Cardio-Oncology: JACC State-of-the-Art Review.

The population of patients with cancer is rapidly expanding, and the diagnosis and monitoring of cardiovascular complications greatly rely on imaging. Numerous advances in the field of cardio-oncology and imaging have occurred in recent years. This review presents updated and practical approaches for multimodality cardiovascular imaging in the cardio-oncology patient and provides recommendations for imaging to detect the myriad of adverse cardiovascular effects associated with antineoplastic therapy, such as cardiomyopathy, atherosclerosis, vascular toxicity, myocarditis, valve disease, and cardiac masses. Uniquely, we address the role of cardiovascular imaging in patients with pre-existing cardiomyopathy, pregnant patients, long-term survivors, and populations with limited resources. We also address future avenues of investigation and opportunities for artificial intelligence applications in cardio-oncology imaging. This review provides a uniform practical approach to cardiovascular imaging for patients with cancer.

Echocardiographic predictors of new-onset atrial arrhythmias in patients undergoing hematopoietic stem cell transplantation.

BACKGROUND: Atrial arrhythmias following hematopoietic stem cell transplantation (HSCT) have been associated with increased length of stay, need for intensive care, and increased mortality within one-year post-transplant. We sought to identify echocardiographic parameters that may predict the development of new atrial arrhythmias post-HSCT. METHODS: We performed a retrospective chart review of 753 consecutive patients who underwent HSCT at the University of Chicago from January 2015 through December 2019. Patients with baseline echocardiogram within 6 months prior to transplantation were included. Those with prior transplants, history of atrial arrhythmias, or unavailable echocardiographic images were excluded, resulting in 187 patients included for final analysis. Baseline clinical and demographic variables, as well as echocardiographic parameters, were compared between patients who developed new atrial arrhythmias post-HSCT versus those who did not. RESULTS: Of the 187 patients included for analysis, 25 (13%) developed new atrial arrhythmias, with 13 of these occurring within 30 days of transplantation. Despite no significant difference in left atrial (LA) end-systolic volume between those with and without new arrhythmia following HSCT (OR 1.04; 95% CI 0.91-1.09, p = 0.233), univariable analysis demonstrated that patients who developed atrial arrhythmias had reduced LA function, as reflected by lower LA emptying fraction (OR 0.94; 95% CI 0.91-0.98, p = 0.003) and lower LA reservoir strain (OR 0.95; 95% CI 0.92-0.99, p = 0.009). CONCLUSIONS: Echocardiographic indices of LA function, namely LA emptying fraction and LA reservoir strain, can identify patients at risk for developing new atrial arrhythmias post-HSCT, prior to the development of morphologic changes in the LA.

Can echocardiographic assessment of diastolic function be automated?

Echocardiographic evaluation of left ventricular diastolic function relies on a multi-pronged algorithm, which incorporates Doppler-based and volumetric parameters. Integration of clinical data in diastolic assessment is recommended, though not clearly outlined. We sought to develop an automated tool for diastolic function, compare its performance to human-generated diagnoses and identify the common sources of error. Our software tool is based on the 2016 diastolic guidelines algorithm, which uses 8 parameters as input, with 10 conditions as the logic and 5 possible outputs as final diagnoses. Initially, we prospectively studied 563 patients whose diastolic function was independently evaluated by an expert echocardiographer and by the automated tool. Incongruent cases were further analyzed, after which features of myocardial disease were integrated into a refined version of the software that was tested in an independent cohort of 1106 patients. In the initial analysis, 202/563 grades (36%) were incongruent between the automated and human reads, with the highest rate of discordance for mild and indeterminate categories. In 17% of cases, human diagnoses differed from that dictated by the algorithm due to integration of clinical factors. Follow-up analysis using the refined automated tool did not improve the discordance rate (440/1106; 40%). There was more discordance in cases of: age > 40 years, impaired mitral inflow patterns (E/A < 0.8) and reduced mitral e' values. Further analysis revealed differences in how readers interpreted the interaction between these factors and diastolic function, which could not be incorporated into the automated tool. In conclusion, although assessment of diastolic function relies on an algorithm that can be automated, this algorithm does not include clear guidance on how to incorporate age, or age-related changes in Doppler-based parameters, often resulting in discordant diagnoses. Standardized interpretation of these factors is needed to improve the reproducibility of diastolic function grading by human readers and the accuracy of the automated classification.

Comparison of clinical and echocardiographic features of first and second waves of COVID-19 at a large, tertiary medical center serving a predominantly African American patient population.

As clinicians have gained experience in treating patients with the novel SARS-CoV-2 (COVID-19) virus, mortality rates for patients with acute COVID-19 infection have decreased. The Centers for Disease Control (CDC) has identified the African American population as having increased risk of COVID-19 associated mortality, however little is known about echocardiographic markers associated with increased mortality in this patient population. We aimed to compare the clinical and echocardiographic features of a predominantly African American patient cohort hospitalized with acute COVID-19 infection during the first (March-June 2020) and second (September-December 2020) waves of the COVID-19 pandemic, and to investigate which parameters are most strongly associated with composite all-cause mortality. We performed consecutive transthoracic echocardiograms (TTEs) on 105 patients admitted with acute COVID-19 infection during the first wave and 129 patients admitted during the second wave. TTE parameters including left ventricular ejection fraction (LVEF), left ventricular global longitudinal strain (LVGLS), right ventricular global longitudinal strain (RVGLS), right ventricular free-wall strain (RVFWS), and right ventricular basal diameter (RVBD) were compared between the two groups. Clinical and demographic characteristics including underlying co-morbidities, biomarkers, in-hospital treatment regimens, and outcomes were collected and analyzed. Univariable and multivariable analyses were performed to determine variables associated with all-cause mortality. There were no significant differences between the two waves in terms of age, gender, BMI, or race. Overall all-cause mortality was 35.2% for the first wave compared to 14.7% for the second wave (p < 0.001). Previous medical conditions were similar between the two waves with the exception of underlying lung disease (41.9% vs. 29.5%, p = 0.047). Echocardiographic parameters were significantly more abnormal in the first wave compared to the second: LVGLS (- 17.1 ± 5.0 vs. - 18.9 ± 4.8, p = 0.02), RVGLS (- 15.7 ± 5.9% vs. - 19.0 ± 5.9%, p < 0.001), RVFWS (- 19.5 ± 6.8% vs. - 23.2 ± 6.9%, p = 0.001), and RVBD (4.5 ± 0.8 vs. 3.9 ± 0.7 cm, p < 0.001). Stepwise multivariable logistic analysis showed mechanical ventilation, RVFWS, and RVGLS to be independently associated with mortality. In a predominantly African American patient population on the south side of Chicago, the clinical and echocardiographic features of patients hospitalized with acute COVID-19 infection demonstrated marked improvement from the first to the second wave of the pandemic, with a significant decrease in all-cause mortality. Possible explanations include implementation of evidence-based therapies, changes in echocardiographic practices, and behavioral changes in our patient population. Mechanical ventilation and right-sided strain-based markers were independently associated with mortality.

Cardiac Magnetic Resonance Predicting Outcomes Among Patients at Risk for Cardiac AL Amyloidosis.

Introduction: Patients with systemic AL amyloidosis (AL) should be evaluated for cardiac amyloidosis (CA), as prognosis is strongly related to cardiac involvement. We assessed the characteristics of patients referred to cardiac magnetic resonance (CMR) with suspected CA from a cancer center and determine predictors of mortality/heart failure hospitalizations (HFH). Methods: Forty-four consecutive patients referred for CMR with suspected CA were retrospectively included. Variables collected included cardiac biomarkers, in addition to echocardiographic and CMR variables. Survival analyses were performed to determine which variables were more predictive of mortality and HFH. Results: Of the 44 patients included, 55% were females. 73% of patients were diagnosed with CA by CMR; 56% of them had an established diagnosis of AL. Patients with CA by CMR had higher native T1, higher extracellular volume (ECV) fraction, higher T2, less negative GLS by Echo, and higher troponin I and B-type natriuretic peptide (BNP). Kaplan-Meier survival analysis revealed that the following were predictive of mortality: an ECV ≥ 0.50 (p = 0.0098), CMR LVEF < 50% (p = 0.0010), T2/ECV ≤ 100 (p = 0.0001), and troponin I > 0.03 (p = 0.0025). In a stepwise conditional Cox logistic regression model, the only variable predictive of a composite of mortality and HFH was ECV (HR: 1.17, 95% CI = 1.02-1.34 p = 0.030). Conclusion: ECV seems to be an important biomarker that could be a predictor of outcomes in cardiac AL amyloidosis. In combination, CMR and serum cardiac biomarkers might help to establish prognosis in patients with CA.