Artificial intelligence applied to coronary artery calcium scans (AI-CAC) significantly improves cardiovascular events prediction.

Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) applied to CAC scans can predict non-CHD events, including heart failure, atrial fibrillation, and stroke. We applied AI-enabled automated cardiac chambers volumetry and calcified plaque characterization to CAC scans (AI-CAC) of 5830 asymptomatic individuals (52.

AI-enabled Cardiac Chambers Volumetry and Calcified Plaque Characterization in Coronary Artery Calcium (CAC) Scans (AI-CAC) Significantly Improves on Agatston CAC Score for Predicting All Cardiovascular Events: The Multi-Ethnic Study of Atherosclerosis.

Background: Coronary artery calcium (CAC) scans contain valuable information beyond the Agatston Score which is currently reported for predicting coronary heart disease (CHD) only. We examined whether new artificial intelligence (AI) algorithms applied to CAC scans may provide significant improvement in prediction of all cardiovascular disease (CVD) events in addition to CHD, including heart failure, atrial fibrillation, stroke, resuscitated cardiac arrest, and all CVD-related deaths.

Methods: We applied AI-enabled automated cardiac chambers volumetry and automated calcified plaque characterization to CAC scans (AI-CAC) of 5830 individuals (52.

AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CAC) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis.

Introduction: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF).

AI-enabled left atrial volumetry in coronary artery calcium scans (AI-CAC) predicts atrial fibrillation as early as one year, improves CHARGE-AF, and outperforms NT-proBNP: The multi-ethnic study of atherosclerosis.

Background: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported.

Methods: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CAC) to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA).

AI-enabled Left Atrial Volumetry in Cardiac CT Scans Improves CHARGE-AF and Outperforms NT-ProBNP for Prediction of Atrial Fibrillation in Asymptomatic Individuals: Multi-Ethnic Study of Atherosclerosis.

Background: Coronary artery calcium (CAC) scans contain actionable information beyond CAC scores that is not currently reported.

Methods: We have applied artificial intelligence-enabled automated cardiac chambers volumetry to CAC scans (AI-CAC), taking on average 21 seconds per CAC scan, to 5535 asymptomatic individuals (52.2% women, ages 45-84) that were previously obtained for CAC scoring in the baseline examination (2000-2002) of the Multi-Ethnic Study of Atherosclerosis (MESA).

Validation of Opportunistic Artificial Intelligence-Based Bone Mineral Density Measurements in Coronary Artery Calcium Scans.

Background: Previously we reported a manual method of measuring thoracic vertebral bone mineral density (BMD) using quantitative CT in noncontrast cardiac CT scans used for coronary artery calcium (CAC) scoring. In this report, we present validation studies of an artificial intelligence-based automated BMD measurement (AutoBMD) that recently received FDA approval as an opportunistic add-on to CAC scans.

Methods: A deep learning model was trained to detect vertebral bodies.

Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent.

Rationale And Objectives: We previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans.

High Frequency of Microvascular Dysfunction in US Outpatient Clinics: A Sign of High Residual Risk? Data from 7,105 Patients.

Previous studies have linked peripheral microvascular dysfunction measured by arterial tonometry to high residual risk in on-statin patients. Digital thermal monitoring (DTM) of microvascular function is a new and simplified technique based on fingertip temperature measurements that has been correlated with the burden of atherosclerosis and its risk factors. Here, we report analyses of DTM data from two large US registries: Registry-I (6,084 cases) and Registry-II (1,021 cases) across 49 US outpatient clinics.

The association of nadir CD4-T cell count and endothelial dysfunction in a healthy HIV cohort without major cardiovascular risk factors.

Objectives: HIV-infected population may have increased risk of cardiovascular disease. The prevalence of traditional cardiovascular disease risk factors such as hypertension, diabetes and dyslipidemia in HIV-infected individuals has made it difficult to assess the direct effects of HIV and immune factors on endothelial dysfunction and associated increased risk of atherosclerosis. The purpose of this study was to investigate indicators of endothelial dysfunction in an HIV cohort without hypertension and diabetes.

Coronary artery calcium testing: A call for universal coverage.

Heart attacks kill more Americans than all cancers combined. Fatal heart attack victims have no symptoms until minutes before they die, hence early detection of high-risk asymptomatic individuals is needed. Even though heart attacks kill and cost more than cancers, as a nation we spend over 20 times more on screening for asymptomatic cancer than for asymptomatic atherosclerotic cardiovascular disease (ASCVD), the underlying cause of heart attacks.

Machine Learning Outperforms ACC / AHA CVD Risk Calculator in MESA.

Background Studies have demonstrated that the current US guidelines based on American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort Equations Risk Calculator may underestimate risk of atherosclerotic cardiovascular disease ( CVD ) in certain high-risk individuals, therefore missing opportunities for intensive therapy and preventing CVD events. Similarly, the guidelines may overestimate risk in low risk populations resulting in unnecessary statin therapy. We used Machine Learning ( ML ) to tackle this problem.

Acute and Subacute Triggers of Cardiovascular Events.

Inability to predict short-term cardiovascular (CV) events and take immediate preemptive actions has long been the Achilles heel of cardiology. However, certain triggers of these events have come to light. Although these triggers are nonspecific and are part of normal life, studying their temporal relationship with the onset of CV events provides an opportunity to alert high-risk atherosclerotic patients who may be most vulnerable to such triggers, the "vulnerable patient".

Radiation exposure and coronary artery calcium scans in the society for heart attack prevention and eradication cohort.

Coronary artery calcium (CAC) scoring is used in asymptomatic patients to improve their clinically predicted risk for future cardiovascular events. Current CT protocols seek to reduce radiation exposure without diminishing image quality. Reported radiation exposure remains widely variable (0.

New Indices of Endothelial Function Measured by Digital Thermal Monitoring of Vascular Reactivity: Data from 6084 Patients Registry.

Endothelial function is viewed as a barometer of cardiovascular health and plays a central role in vascular reactivity. Several studies showed digital thermal monitoring (DTM) as a simple noninvasive method to measure vascular reactivity that is correlated with atherosclerosis risk factors and coronary artery disease. To further evaluate the relations between patient characteristics and DTM indices in a large patient registry.

Cardiovascular health informatics: risk screening and intervention.

Despite enormous efforts to prevent cardiovascular disease (CVD) in the past, it remains the leading cause of death in most countries worldwide. Around two-thirds of these deaths are due to acute events, which frequently occur suddenly and are often fatal before medical care can be given. New strategies for screening and early intervening CVD, in addition to the conventional methods, are therefore needed in order to provide personalized and pervasive healthcare.

Analysis of contrast-enhanced intravascular ultrasound images for the assessment of coronary plaque neoangiogenesis: another step closer to the identification of the vulnerable plaque.

Atherosclerotic cardiovascular disease (CVD), primarily manifested as heart attacks and strokes, remains the main cause of death in the developed countries and is rapidly increasing in the developing world. Early detection and aggressive treatment of hidden (asymptomatic) atherosclerotic plaques that cause heart attack or stroke are most needed. However, existing clinical tools are not sufficient to address this need.

Reproducibility and variability of digital thermal monitoring of vascular reactivity.

Background: Previous studies demonstrated that digital thermal monitoring (DTM) of vascular reactivity, a new test for vascular function assessment, is well correlated with Framingham Risk Score, coronary calcium score and CT angiography. This study evaluates the variability and reproducibility of DTM measurements. We hypothesized that DTM is reproducible, and its variability falls within the accepted range of clinical diagnostic tests.

Use of temperature alterations to characterize vascular reactivity.

Monitoring alterations in fingertip temperature during ischaemia and the subsequent hyperaemia provides a novel way of studying microvascular reactivity. The relations between parameters characterizing blood perfusion and the thermal response of fingertips were studied using experimental and theoretical approaches. During the experimental protocol, two brachial artery occlusion tests were conducted in 12 healthy volunteers, and fingertip temperature, heat flux and skin perfusion using laser Doppler flowmetry (LDF) were measured.

Sensitivity of digital thermal monitoring parameters to reactive hyperemia.

Both structural and functional evaluations of the endothelium exist in order to diagnose cardiovascular disease (CVD) in its asymptomatic stages. Vascular reactivity, a functional evaluation of the endothelium in response to factors such as occlusion, cold, and stress, in addition to plasma markers, is the most widely accepted test and has been found to be a better predictor of the health of the endothelium than structural assessment tools such as coronary calcium scores or carotid intima-media thickness. Among the vascular reactivity assessment techniques available, digital thermal monitoring (DTM) is a noninvasive technique that measures the recovery of fingertip temperature after 2-5 min of brachial occlusion.

Vascular function measured by fingertip thermal reactivity is impaired in patients with metabolic syndrome and diabetes mellitus.

Digital thermal monitoring (DTM) of vascular function has already been shown to correlate well with coronary artery calcium (CAC) score and coronary artery disease. To determine its utility in the metabolic syndrome (MS) and diabetes mellitus (DM), 233 asymptomatic patients with DM/MS but without coronary artery disease underwent DTM during and after 5 minutes of supra-systolic arm cuff inflation, as well as CAC. Post-cuff deflation adjusted temperature rebound (aTR) was lower in MS and DM compared with the normal group.

Digital thermal monitoring of vascular function: a novel tool to improve cardiovascular risk assessment.

Digital thermal monitoring (DTM) of vascular function during cuff-occlusive reactive hyperemia relies on the premise that changes in fingertip temperature during and after an ischemic stimulus reflect changes in blood flow. To determine its utility in individuals with and without known coronary heart disease (CHD), 133 consecutive individuals (age 54 +/- 10 years, 50% male, 19 with known CHD) underwent DTM during and after 2 minutes of supra-systolic arm cuff inflation. Fingertip temperatures of the occluded and non-occluded fingertips were measured simultaneously.