Diastology with Cardiac MRI: A Practical Guide.

Diastolic filling of the ventricle is a complex interplay of volume and pressure, contingent on active energy-dependent myocardial relaxation and myocardial stiffness. Abnormal diastolic function is the hallmark of the clinical entity of heart failure with preserved ejection fraction (HFpEF), which is now the dominant type of heart failure and is associated with significant morbidity and mortality. Although echocardiography is the current first-line imaging modality used in evaluation of diastolic function, cardiac MRI (CMR) is emerging as an important technique. The principal role of CMR is to categorize the cause of diastolic dysfunction (DD) and distinguish other entities that manifest similarly to HFpEF, particularly infiltrative and pericardial disorders. CMR also provides prognostic information and risk stratification based on late gadolinium enhancement and parametric mapping techniques. Advances in hardware, sequences, and postprocessing software now enable CMR to diagnose and grade DD accurately, a role traditionally assigned to echocardiography. Two-dimensional or four-dimensional velocity-encoded phase-contrast sequences can measure flow and velocities at the mitral inflow, mitral annulus, and pulmonary veins to provide diastolic functional metrics analogous to those at echocardiography. The commonly used cine steady-state free-precession sequence can provide clues to DD including left ventricular mass, left ventricular filling curves, and left atrial size and function. MR strain imaging provides information on myocardial mechanics that further aids in diagnosis and prognosis of diastolic function. Research sequences such as MR elastography and MR spectroscopy can help evaluate myocardial stiffness and metabolism, respectively, providing additional insights on diastolic function. The authors review the physiology of diastolic function, mechanics of diastolic heart failure, and CMR techniques in the evaluation of diastolic function. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

The Mechanism and Natural History of Mitral Regurgitation in Cardiac Sarcoidosis.

Cardiac sarcoidosis (CS) is an infl/ammatory cardiomyopathy that can present with mitral regurgitation (MR), but few studies describe the mechanisms and natural history of MR in CS. We queried an institutional registry of 512 patients with CS for moderate or greater MR at diagnosis. Baseline demographic and echocardiography (TTE) data were collected. MR was classified by Carpentier type. Positron emission tomography was analyzed for 2-deoxy-2-[fluorine-18] fluoro-d-glucose (FDG) avidity of anterolateral and posteromedial papillary muscles. Follow-up TTE and positron emission tomography imaging of patients treated with immunosuppression was analyzed for MR severity and FDG avidity changes. Fifty-four patients were identified. Mean left ventricular ejection fraction was 39.3%, effective regurgitant orifice 0.34 cm2, and MR regurgitant volume 46.3 ml. Carpentier type I was the most common MR mechanism (46.3%). Forty-one patients had follow-up TTE (median follow-up 1.7 years, interquartile range 2.6 years). Evaluating preprocedural follow-up TTE only, MR severity was significantly reduced, with 37% of patients showing reduction by at least 1 severity grade (p = 0.04). With postprocedural TTE included, 61% of patients showed alleviation of MR severity with mean decrease in grade - 0.98 (p <0.001). Sixty-eight percent of patients had anterolateral/posteromedial FDG avidity. Papillary muscle FDG avidity resolved in 80% of patients (n = 20, median follow-up 1.6 years, interquartile range 2.5 years). In conclusion, Carpentier type I functional MR is the most common MR mechanism in CS. MR severity and papillary muscle FDG avidity decrease after treatment, and MR resolution is further strengthened by procedural intervention in a minority of patients, suggesting an overall favorable natural history of MR in CS.

COVID-19 Misinformation Detection: Machine-Learned Solutions to the Infodemic.

Background: The volume of COVID-19-related misinformation has long exceeded the resources available to fact checkers to effectively mitigate its ill effects. Automated and web-based approaches can provide effective deterrents to online misinformation. Machine learning-based methods have achieved robust performance on text classification tasks, including potentially low-quality-news credibility assessment. Despite the progress of initial, rapid interventions, the enormity of COVID-19-related misinformation continues to overwhelm fact checkers. Therefore, improvement in automated and machine-learned methods for an infodemic response is urgently needed. Objective: The aim of this study was to achieve improvement in automated and machine-learned methods for an infodemic response. Methods: We evaluated three strategies for training a machine-learning model to determine the highest model performance: (1) COVID-19-related fact-checked data only, (2) general fact-checked data only, and (3) combined COVID-19 and general fact-checked data. We created two COVID-19-related misinformation data sets from fact-checked "false" content combined with programmatically retrieved "true" content. The first set contained ~7000 entries from July to August 2020, and the second contained ~31,000 entries from January 2020 to June 2022. We crowdsourced 31,441 votes to human label the first data set. Results: The models achieved an accuracy of 96.55% and 94.56% on the first and second external validation data set, respectively. Our best-performing model was developed using COVID-19-specific content. We were able to successfully develop combined models that outperformed human votes of misinformation. Specifically, when we blended our model predictions with human votes, the highest accuracy we achieved on the first external validation data set was 99.1%. When we considered outputs where the machine-learning model agreed with human votes, we achieved accuracies up to 98.59% on the first validation data set. This outperformed human votes alone with an accuracy of only 73%. Conclusions: External validation accuracies of 96.55% and 94.56% are evidence that machine learning can produce superior results for the difficult task of classifying the veracity of COVID-19 content. Pretrained language models performed best when fine-tuned on a topic-specific data set, while other models achieved their best accuracy when fine-tuned on a combination of topic-specific and general-topic data sets. Crucially, our study found that blended models, trained/fine-tuned on general-topic content with crowdsourced data, improved our models' accuracies up to 99.7%. The successful use of crowdsourced data can increase the accuracy of models in situations when expert-labeled data are scarce. The 98.59% accuracy on a "high-confidence" subsection comprised of machine-learned and human labels suggests that crowdsourced votes can optimize machine-learned labels to improve accuracy above human-only levels. These results support the utility of supervised machine learning to deter and combat future health-related disinformation.

Routine Laboratory Biomarkers As Prognostic Indicators of Cardiac Sarcoidosis Outcomes.

Background: Biomarkers to monitor disease activity and predict major adverse cardiac events (MACE) in CS have not been described previously. We aimed to identify biomarkers to predict MACE in cardiac sarcoidosis (CS). Methods: Patients (N=232) diagnosed with CS were retrospectively enrolled. Biomarkers including angiotensin-converting enzyme (ACE), N-terminal brain natriuretic peptide (NT-proBNP), troponin T, and creatinine levels were evaluated against a primary end point of left ventricular assist device implantation, heart transplantation, or death, and a secondary end point of cardiac hospitalization-free survival. Results: Troponin T (hazard ratio [HR], 1.06 per 0.01 ng/mL; P=.006), NT-proBNP (HR, 1.31 per 1,000 pg/mL; P<.001), and creatinine (HR, 4.02 per mg/dL; P=.01) were associated with the primary end point, even after adjusting for ejection fraction. NT-proBNP, B-type natriuretic peptide (BNP), creatinine, albumin, and calcium were associated with the secondary end point (P<.05). ACE levels were associated with presence of late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) imaging (mean difference, 14.7; P=.03); 1,25 dihydroxyvitamin D (1,25-OHVit-D) was associated with uptake on cardiac 18F-flurodeoxyglucose position emission tomography (FDG-PET, P=.03). Conclusions: Troponin T, NT-proBNP, and creatinine predict clinically significant outcomes in CS. ACE levels correlated with LGE on CMR, and 1,25-OHVit-D levels correlated with FDG-PET activity.

Natural History of Patients Diagnosed with Cardiac Sarcoidosis at Left Ventricular Assist Device Implantation or Cardiac Transplantation.

To our knowledge, natural history has not been reported for cardiac sarcoidosis (CS) diagnosed by pathologic evaluation of the apical core at left ventricular assist device (LVAD) implantation or cardiac transplantation. We retrospectively identified 232 consecutive patients meeting CS criteria. Of these patients, 54 were diagnosed by pathologic confirmation of CS, 10 after evaluation of the apical core (LVAD implant) or explanted heart (transplant). We compared clinical characteristics at initial evaluation and outcomes for these 10 patients with those of 10 patients with known CS before LVAD implant/transplant. In the study group, five patients (50%) had confirmed extracardiac sarcoidosis before LVAD implant/transplant; five had not been diagnosed with sarcoidosis. Mean (standard deviation) left ventricular ejection fraction at initial evaluation was 23% (16%), and left ventricular end-diastolic dimension was 61 (10) mm. Four patients died during follow-up; however, no survival difference was found for the 10 patients diagnosed incidentally and the group with a previous diagnosis or institutional LVAD/transplant cohorts. Patients diagnosed with CS on pathological examination of the apical core/explanted heart may have severe dilated cardiomyopathy as the initial presentation. Outcomes for patients with CS after advanced heart failure therapies may be comparable with those of non-CS patients.

Identification of a novel presumed cardiac sarcoidosis category for patients at high risk of disease.

BACKGROUND: Histologic evidence is required for a definitive diagnosis of cardiac sarcoidosis (CS) by published guidelines; however, the sporadic nature of the disease may produce false negative biopsy results, causing CS to be underdiagnosed. We sought to establish a clinical category of CS absent histologic findings. METHODS: Patients evaluated for CS were stratified into 3 groups: probable CS and definite CS based on Heart Rhythm Society (HRS) criteria and presumed CS, ie, patients without any histologic evidence of sarcoidosis, but with unexplained high-grade atrioventricular block or ventricular arrhythmia and findings suggestive of CS on either cardiac magnetic resonance imaging or positron emission tomography. The primary end point was hospitalization-free and overall survival at 10 years. RESULTS: A total of 383 patients were included in the study: 59, definite CS; 223, probable CS; and 101, presumed CS (62, isolated CS and 39, systemic CS). Compared with patients meeting HRS criteria for CS, patients with presumed CS had lower odds of New York Heart Association class III or IV symptoms (odds ratio [OR], 0.44 [95% CI, 0.23-0.83]; P = .01) but greater odds of previous ventricular tachycardia (OR, 2.4 [95% CI, 1.4-4.0]; P = .001) or history of resuscitated sudden cardiac arrest (OR, 2.9 [95% CI, 1.0-8.6]; P = .05). Hospitalization-free and overall survival were similar among groups (P = .51 and P = .71, respectively). CONCLUSIONS: Clinical categorization of patients with presumed CS identified a high-risk cohort comparable to patients with histologic evidence of disease, although caution should be exercised in reaching this diagnosis without paying due diligence to the differential diagnosis.

Effect of Corticosteroid Therapy in Patients With Cardiac Sarcoidosis on Frequency of Venous Thromboembolism.

Sarcoidosis is a multisystem inflammatory condition with occasional cardiac involvement (CS), which may be associated with risk of venous thromboembolism (VTE). As data on VTE in CS are sparse and corticosteroid therapy has not been previously examined, we aim to determine the association between CS, corticosteroid treatment for CS, and VTE. Patients referred to our institution with concern for sarcoidosis and underwent a positron emission tomography (PET) scan were retrospectively assessed. Chi-squared and multivariate regression analyses were conducted to determine the association between a diagnosis of sarcoidosis, CS, corticosteroid use, and VTE events. Six hundred and forty nine patients were split into 3 categories: 235 with no sarcoidosis (NS), 91 with extra-cardiac sarcoidosis only (ECS), and 323 with CS (isolated CS and/or CS with extra cardiac sarcoid). Thirty nine CS, 7 ECS, and 9 NS patients developed PE while 44 CS, 3 ECS, and 18 NS patients developed DVT. On multivariate regression, neither CS nor ECS was an independent risk factor for VTE (p >0.05) but corticosteroid use was independently associated with VTE (HR 3.06, p = 0.007 for PE, HR 6.21, p <0.0001 for DVT). On logistic regression analysis, corticosteroid dose was found to be independently associated with both PE (p = 0.001) and DVT (p = 0.007). Optimal threshold for defining VTE risk with corticosteroid therapy was a prednisone-equivalent dose of 17.5 mg. In conclusion, contrary to previous studies, this current study found that neither sarcoidosis nor CS is an independent risk factor for VTE. Rather, corticosteroid therapy was associated with an increased risk of VTE.

CoVerifi: A COVID-19 news verification system.

There is an abundance of misinformation, disinformation, and "fake news" related to COVID-19, leading the director-general of the World Health Organization to term this an 'infodemic'. Given the high volume of COVID-19 content on the Internet, many find it difficult to evaluate veracity. Vulnerable and marginalized groups are being misinformed and subject to high levels of stress. Riots and panic buying have also taken place due to "fake news". However, individual research-led websites can make a major difference in terms of providing accurate information. For example, the Johns Hopkins Coronavirus Resource Center website has over 81 million entries linked to it on Google. With the outbreak of COVID-19 and the knowledge that deceptive news has the potential to measurably affect the beliefs of the public, new strategies are needed to prevent the spread of misinformation. This study seeks to make a timely intervention to the information landscape through a COVID-19 "fake news", misinformation, and disinformation website. In this article, we introduce CoVerifi, a web application which combines both the power of machine learning and the power of human feedback to assess the credibility of news. By allowing users the ability to "vote" on news content, the CoVerifi platform will allow us to release labelled data as open source, which will enable further research on preventing the spread of COVID-19-related misinformation. We discuss the development of CoVerifi and the potential utility of deploying the system at scale for combating the COVID-19 "infodemic".

Convolutional neural networks to automate the screening of malaria in low-resource countries.

Malaria is an infectious disease caused by Plasmodium parasites, transmitted through mosquito bites. Symptoms include fever, headache, and vomiting, and in severe cases, seizures and coma. The World Health Organization reports that there were 228 million cases and 405,000 deaths in 2018, with Africa representing 93% of total cases and 94% of total deaths. Rapid diagnosis and subsequent treatment are the most effective means to mitigate the progression into serious symptoms. However, many fatal cases have been attributed to poor access to healthcare resources for malaria screenings. In these low-resource settings, the use of light microscopy on a thin blood smear with Giemsa stain is used to examine the severity of infection, requiring tedious and manual counting by a trained technician. To address the malaria endemic in Africa and its coexisting socioeconomic constraints, we propose an automated, mobile phone-based screening process that takes advantage of already existing resources. Through the use of convolutional neural networks (CNNs), we utilize a SSD multibox object detection architecture that rapidly processes thin blood smears acquired via light microscopy to isolate images of individual red blood cells with 90.4% average precision. Then we implement a FSRCNN model that upscales 32 × 32 low-resolution images to 128 × 128 high-resolution images with a PSNR of 30.2, compared to a baseline PSNR of 24.2 through traditional bicubic interpolation. Lastly, we utilize a modified VGG16 CNN that classifies red blood cells as either infected or uninfected with an accuracy of 96.5% in a balanced class dataset. These sequential models create a streamlined screening platform, giving the healthcare provider the number of malaria-infected red blood cells in a given sample. Our deep learning platform is efficient enough to operate exclusively on low-tier smartphone hardware, eliminating the need for high-speed internet connection.

Elevated serum uric acid is associated with peripheral endothelial dysfunction in women.

BACKGROUND AND AIMS: Both elevated serum uric acid (SUA) and peripheral endothelial dysfunction (PED) are associated independently with cardiovascular disease (CVD). However, the association between SUA and PED is yet to be established. We hypothesized that high normal range of SUA is associated with PED. METHODS: We performed a retrospective cross-sectional analysis of patients who were referred to Mayo Clinic between 2006 and 2014 for routine cardiovascular evaluation and who underwent evaluation of Reactive Hyperemia Peripheral Arterial Tonometry (index <2 consistent with PED). A high UA was defined as ≥5 mg/dL, in keeping with previous studies evaluating the link between SUA and CVD outcomes. RESULTS: One hundred forty patients were included (mean age 50.7 ±â€¯12.9 years, 86 (61.4%) female). Twenty four patients (17.1%) had pre-existing CVD (8 (9.3%) in females). Thirty patients (21.6%) had a Framingham score > 10% (8 (9.4%) in females). Fifty eight (41.4%) had PED and 77 (55.0%) had an elevated SUA. SUA levels were higher in patients with PED compared to those without (5.5 ±â€¯1.4 vs 4.8 ±â€¯1.2 mg/dL; p = 0.004). In an univariate analysis, elevated SUA levels were associated with PED (Odds Ratio (OR): 2.7; 95% confidence interval [CI] 1.33-5.48; p = 0.005). In a multivariate analysis adjusting for age, sex, presence of obstructive CVD and Framingham score>10, elevated SUA levels were associated with PED (OR 2.45; 95% CI 1.08-5.52; p = 0.031). After stratifying by sex, this association persisted in females only. CONCLUSIONS: High normal SUA levels are associated with PED in women who are otherwise at low risk for CVD. Thus, SUA is a promising circulating biomarker that could be used to assist in risk stratification in female patients with chest pain and/or those undergoing evaluation of CVD risk.

Coronary microvascular dysfunction is associated with poor glycemic control amongst female diabetics with chest pain and non-obstructive coronary artery disease.

BACKGROUND: Patients with type 2 diabetes mellitus are at an increased risk of adverse cardiovascular events compared to those without diabetes. The timing, relative to disease onset, and degree of glycemic control that reduces the risk of adverse cardiovascular events remains uncertain. Coronary microvascular dysfunction is prevalent in patients with type 2 diabetes mellitus and is linked to adverse cardiovascular events. We assessed the association between endothelial-dependent and endothelial-independent coronary microvascular dysfunction and glycemic control in patients presenting with chest pain and nonobstructive coronary disease at angiography. METHODS: Patients presenting with chest pain and found to have non-obstructive CAD (stenosis < 40%) at angiography underwent an invasive assessment of endothelial-independent and endothelial -dependent microvascular function. Endothelial-independent microvascular function was assessed by comparing the coronary flow velocity, measured using a Doppler guidewire, in response to intracoronary infusion of adenosine to calculate the coronary flow reserve ratio in response to adenosine (CFRAdn Ratio). A CFRAdn Ratio ≤ 2.5 was considered abnormal. Endothelial-dependent microvascular function was assessed by measuring the percent change in coronary blood flow in response to intracoronary infusions of acetylcholine (%ΔCBFAch), and microvascular endothelial dysfunction defined as a %ΔCBFAch of ≤ 50%. Patients were classified by normal versus abnormal CFRAdn Ratio and %ΔCBFAch. Measurements of HbA1c and fasting serum glucose were obtained prior to catheterization and compared between groups. RESULTS: Between 1993 and 2012, 1469 patients (mean age 50.4 years, 35% male) underwent coronary angiography and invasive testing for coronary microvascular dysfunction, of which 129 (8.8%) had type 2 diabetes. Fifty-one (39.5%) had an abnormal %ΔCBFAch and 49 (38.0%) had an abnormal CFRAdn Ratio. Conventional cardiovascular risk factors and cardiovascular or diabetic medication use did not vary significantly between groups. Females with an abnormal CFRAdn Ratio or abnormal %ΔCBFAch had a significantly higher HbA1c compared to patients with a normal CFRAdn Ratio or %ΔCBFAch respectively: HbA1c % (standard deviation) 7.4 (2.1) vs. 6.5 (1.1), p = 0.035 and 7.3 (1.9) vs. 6.4 (1.2), p = 0.022, respectively. Female patients with an abnormal CFRAdn Ratio had significantly higher fasting serum glucose concentrations compared to those with a normal CFRAdn Ratio: fasting serum glucose mg/dL (standard deviation) 144.4 (55.6) vs. 121.9 (28.1), p = 0.035. This was not observed in men. Amongst female diabetics, a higher HbA1c was significantly associated with any coronary microvascular dysfunction both in a univariate and multivariate analysis: odds ratio (95% confidence interval) 1.69 (1.01-2.86) p = 0.049; and a fasting serum glucose > 140 mg/dL was significantly associated with an abnormal CFRAdn Ratio, 4.28 (1.43-12.81). CONCLUSION: Poor glycemic control is associated with coronary microvascular dysfunction amongst female diabetics presenting with chest pain and non-obstructive CAD. These findings highlight the importance of sex specific risk stratification models and treatment strategies when managing cardiovascular risk amongst diabetics. Further studies are required to identify additional risk prevention tools and therapies targeting microvascular dysfunction as an integrated index of cardiovascular risk.

HDAC inhibitors potentiate the activity of the BCR/ABL kinase inhibitor KW-2449 in imatinib-sensitive or -resistant BCR/ABL+ leukemia cells in vitro and in vivo.

PURPOSE: The purpose of this study was to determine whether histone deacetylase (HDAC) inhibitors (HDACI) such as vorinostat or entinostat (SNDX-275) could increase the lethality of the dual Bcr/Abl-Aurora kinase inhibitor KW-2449 in various Bcr/Abl(+) human leukemia cells, including those resistant to imatinib mesylate (IM). EXPERIMENTAL DESIGN: Bcr/Abl(+) chronic myelogenous leukemia (CML) and acute lymphoblastic leukemia (ALL) cells, including those resistant to IM (T315I, E255K), were exposed to KW-2449 in the presence or absence of vorinostat or SNDX-275, after which apoptosis and effects on signaling pathways were examined. In vivo studies combining HDACIs and KW2449 were carried out by using a systemic IM-resistant ALL xenograft model. RESULTS: Coadministration of HDACIs synergistically increased KW-2449 lethality in vitro in multiple CML and Ph(+) ALL cell types including human IM resistant cells (e.g., BV-173/E255K and Adult/T315I). Combined treatment resulted in inactivation of Bcr/Abl and downstream targets (e.g., STAT5 and CRKL), as well as increased reactive oxygen species (ROS) generation and DNA damage (γH2A.X). The latter events and cell death were significantly attenuated by free radical scavengers (TBAP). Increased lethality was also observed in primary CD34(+) cells from patients with CML, but not in normal CD34(+) cells. Finally, minimally active vorinostat or SNDX275 doses markedly increased KW2449 antitumor effects and significantly prolonged the survival of murine xenografts bearing IM-resistant ALL cells (BV173/E255K). CONCLUSIONS: HDACIs increase KW-2449 lethality in Bcr/Abl(+) cells in association with inhibition of Bcr/Abl, generation of ROS, and induction of DNA damage. This strategy preferentially targets primary Bcr/Abl(+) hematopoietic cells and exhibits enhanced in vivo activity. Combining KW-2449 with HDACIs warrants attention in IM-resistant Bcr/Abl(+) leukemias.