Evaluation of a content-based image retrieval system for radiologists in high-resolution CT of interstitial lung diseases.

Background: This retrospective study aims to evaluate the impact of a content-based image retrieval (CBIR) application on diagnostic accuracy and confidence in interstitial lung disease (ILD) assessment using high-resolution computed tomography CT (HRCT).

Methods: Twenty-eight patients with verified pattern-based ILD diagnoses were split into two equal datasets (1 and 2). The images were assessed by two radiology residents (3rd and 5th year) and one expert radiologist in four sessions.

State of the art of CT myocardial perfusion.

Coronary computed tomography angiography (CCTA) is a powerful tool to rule out coronary artery disease (CAD). In the last decade, myocardial perfusion CT (CTP) technique has been developed for the evaluation of myocardial ischemia, thereby increasing positive predictive value for diagnosis of obstructive CAD. A diagnostic strategy combining CCTA and perfusion acquisitions provides both anatomical coronary evaluation and functional evaluation of the stenosis, increasing the specificity and the positive predictive value of cardiac CT.

Clinical parameters of death and heart failure hospitalization in biventricular systolic dysfunction assessed via cardiac magnetic resonance.

Aims: While factors associated with adverse events are well elucidated in setting of isolated left ventricular dysfunction, clinical and imaging-based prognosticators of adverse outcomes are lacking in context of biventricular dysfunction. The purpose of this study was to establish role of clinical variables in prognosis of biventricular heart failure (HF), as assessed by cardiac magnetic resonance imaging.

Methods: Study cohort consisted of 840 patients enrolled in DERIVATE registry with coexisting CMR-derived right ventricular (RV) and left ventricular (LV) dysfunction, as defined by RV and LV ejection fractions ≤45 % and ≤ 50 %, respectively.

Coronary Artery Calcium for Risk Stratification Among Persons With Very High HDL Cholesterol.

Background: Compared to normal high-density lipoprotein (HDL) cholesterol values, very high HDL cholesterol is associated with a higher incidence of mortality and atherosclerotic cardiovascular disease (ASCVD). As such, clinical risk stratification among persons with very high HDL cholesterol is challenging.

Objectives: Among persons with very high HDL cholesterol, the purpose was to determine the prevalence of coronary artery calcium (CAC) and compare the association between traditional risk factors vs CAC for all-cause mortality and ASCVD.

Confidence-Aware Severity Assessment of Lung Disease from Chest X-Rays Using Deep Neural Network on a Multi-Reader Dataset.

In this study, we present a method based on Monte Carlo Dropout (MCD) as Bayesian neural network (BNN) approximation for confidence-aware severity classification of lung diseases in COVID-19 patients using chest X-rays (CXRs). Trained and tested on 1208 CXRs from Hospital 1 in the USA, the model categorizes severity into four levels (i.e.

Special Report on the Consensus QIBA Profile for Objective Analytical Validation of Non-calcified and High-risk Plaque and Other Biomarkers using Computed Tomography Angiography.

Rationale And Objectives: Evidence is building in support of the clinical utility of atherosclerotic plaque imaging by computed tomography angiography (CTA). There is increasing organized activity to embrace non-calcified plaque (NCP) as a formally defined biomarker for clinical trials, and high-risk plaque (HRP) for clinical care, as the most relevant measures for the field to advance and worthy of community efforts to validate. Yet the ability to assess the quantitative performance of any given specific solution to make these measurements or classifications is not available.

Clinical Validation of a Deep Learning Algorithm for Automated Coronary Artery Disease Detection and Classification Using a Heterogeneous Multivendor Coronary Computed Tomography Angiography Data Set.

Purpose: We sought to clinically validate a fully automated deep learning (DL) algorithm for coronary artery disease (CAD) detection and classification in a heterogeneous multivendor cardiac computed tomography angiography data set.

Materials And Methods: In this single-centre retrospective study, we included patients who underwent cardiac computed tomography angiography scans between 2010 and 2020 with scanners from 4 vendors (Siemens Healthineers, Philips, General Electrics, and Canon). Coronary Artery Disease-Reporting and Data System (CAD-RADS) classification was performed by a DL algorithm and by an expert reader (reader 1, R1), the gold standard.

Epicardial adipose tissue attenuation on computed tomography in women with coronary microvascular dysfunction: A pilot, hypothesis generating study.

Background: Patients with myocardial ischemia without obstructive coronary artery disease often have coronary microvascular dysfunction (CMD) and associated increased risk of cardiovascular (CV) events and anginal hospitalizations. Epicardial adipose tissue (EAT) covers much of the myocardium and coronary arteries and when dysfunctional, secretes proinflammatory cytokines and is associated with CV events. While oxidative stress and systemic inflammation are associated with CMD, the relationship between EAT and CMD in women is not well known.

ACR Appropriateness Criteria® Preprocedural Planning for Left Atrial Procedures in Atrial Fibrillation.

This document summarizes the relevant literature for the selection of preprocedural imaging in three clinical scenarios in patients needing endovascular treatment or cardioversion of atrial fibrillation. These clinical scenarios include preprocedural imaging prior to radiofrequency ablation; prior to left atrial appendage occlusion; and prior to cardioversion. The appropriateness of imaging modalities as they apply to each clinical scenario is rated as usually appropriate, may be appropriate, and usually not appropriate to assist the selection of the most appropriate imaging modality in the corresponding clinical scenarios.

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived technological advances but became one of the cornerstones of contemporary cardiovascular imaging. Its simplicity and quantitative nature established it as one of the most robust approaches for atherosclerotic cardiovascular disease risk stratification in primary prevention and a powerful tool to guide therapeutic choices. Groundbreaking advances in computational models and computer power translated into a surge of artificial intelligence (AI)-based approaches directly or indirectly linked to CACS analysis.

Intra- and inter-reader reproducibility in quantitative coronary plaque analysis on coronary computed tomography angiography.

Purpose: Coronary artery plaque burden, low attenuation non-calcified plaque (LAP), and pericoronary adipose tissue (PCAT) on coronary CT angiography (CCTA), have been linked to future cardiac events. The purpose of this study was to evaluate intra- and inter reader reproducibility in the quantification of coronary plaque burden and its characteristics using an artificial intelligence-enhanced semi-automated software.

Materials And Methods: A total of 10 women and 6 men, aged 52 (IQR 49-58) underwent CCTA using a Siemens Somatom Force, Somatom Definition AS and Somatom Definition Flash scanners.

The Role of Artificial Intelligence in Cardiac Imaging.

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

Left Main Coronary Artery Calcium and Diabetes Confer Very-High-Risk Equivalence in Coronary Artery Calcium >1,000.

Background: Although a coronary artery calcium (CAC) of ≥1,000 is a subclinical atherosclerosis threshold to consider combination lipid-lowering therapy, differentiating very high from high atherosclerotic cardiovascular disease (ASCVD) risk in this patient population is not well-defined.

Objectives: Among persons with a CAC of ≥1,000, the authors sought to identify risk factors equating with very high-risk ASCVD mortality rates.

Methods: The authors studied 2,246 asymptomatic patients with a CAC of ≥1,000 from the CAC Consortium without a prior ASCVD event.

Fusion Modeling: Combining Clinical and Imaging Data to Advance Cardiac Care.

In addition to the traditional clinical risk factors, an increasing amount of imaging biomarkers have shown value for cardiovascular risk prediction. Clinical and imaging data are captured from a variety of data sources during multiple patient encounters and are often analyzed independently. Initial studies showed that fusion of both clinical and imaging features results in superior prognostic performance compared with traditional scores.

Thoracic Aortic Calcium Density and Area in Long-Term Atherosclerotic Cardiovascular Disease Risk Among Men Versus Women.

Background: The development of thoracic aortic calcium (TAC) temporally precedes coronary artery calcium more often in women versus men. Whether TAC density and area confer sex-specific differences in atherosclerotic cardiovascular disease (ASCVD) risk is unknown.

Methods: We studied 5317 primary prevention patients who underwent coronary artery calcium scoring on noncontrast cardiac gated computed tomography with TAC >0.

Relationships of pericoronary and epicardial fat measurements in male and female patients with and without coronary artery disease.

Introduction: Although pericoronary adipose tissue (PCAT) is a component of the epicardial adipose tissue (EAT) depot, they may have different associations to coronary artery disease (CAD). We explored relationships between pericoronary adipose tissue mean attenuation (PCAT) and EAT measurements in coronary CT angiography (CCTA) in patients with and without CAD.

Material And Methods: CCTA scans of 185 non-CAD and 81 CAD patients (86.

Dual-Energy Computed Tomography in Cardiac Imaging.

Dual-energy computed tomography (DECT) acquires images using two energy spectra and offers a variation of reconstruction techniques for improved cardiac imaging. Virtual monoenergetic images decrease artifacts improving coronary plaque and stent visualization. Further, contrast attenuation is increased allowing significant reduction of contrast dose.

Transient left bundle branch block associated with very high coronary artery calcium: a case report.

Coronary artery calcium (CAC) is the measure of subclinical coronary artery atherosclerosis most strongly associated with atherosclerotic cardiovascular disease (ASCVD) risk. However, CAC is rarely reported in the inpatient setting to guide chest pain management. We present a case of very high CAC in a 64-year-old woman with hypertension, type 2 diabetes, and hyperlipidemia presenting with dyspnea.

A Pilot Study of Neurobiological Mechanisms of Stress and Cardiovascular Risk.

Objective: Coronary heart disease is a leading cause of death and disability. Although psychological stress has been identified as an important potential contributor, mechanisms by which stress increases risk of heart disease and mortality are not fully understood. The purpose of this study was to assess mechanisms by which stress acts through the brain and heart to confer increased CHD risk.