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Objectives: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. Methods: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. Results: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7–4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69–12.48) for the number of plaques with spotty calcification, 3.73 (1.46–9.52) for the number of plaques with low attenuation component, 2.71 (1.62–4.50) for 25–49% stenosis severity, 1.47 (1.17–1.84) for the number of bifurcation plaques, and 1.21 (1.02–1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676–0.788) and 0.668 (0.583–0.752) in the derivation and validation cohorts, respectively. Conclusions: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. Clinical relevance statement: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-u

Purpose: Takotsubo cardiomyopathy (TTC) is a transient but severe acute myocardial dysfunction with a wide range of outcomes from favorable to life-threatening. The current risk stratification scores of TTC patients do not include cardiac magnetic resonance (CMR) parameters. To date, it is still unknown whether and how clinical, trans-thoracic echocardiography (TTE), and CMR data can be integrated to improve risk stratification. Methods: EVOLUTION (Exploring the eVolution in prognOstic capabiLity of mUlti-sequence cardiac magneTIc resOnance in patieNts affected by Takotsubo cardiomyopathy) is a multicenter, international registry of TTC patients who will undergo a clinical, TTE, and CMR evaluation. Clinical data including demographics, risk factors, comorbidities, laboratory values, ECG, and results from TTE and CMR analysis will be collected, and each patient will be followed-up for in-hospital and long-term outcomes. Clinical outcome measures during hospitalization will include cardiovascular death, pulmonary edema, arrhythmias, stroke, or transient ischemic attack. Clinical long-term outcome measures will include cardiovascular death, pulmonary edema, heart failure, arrhythmias, sudden cardiac death, and major adverse cardiac and cerebrovascular events defined as a composite endpoint of death from any cause, myocardial infarction, recurrence of TTC, transient ischemic attack, and stroke. We will develop a comprehensive clinical and imaging score that predicts TTC outcomes and test the value of machine learning models, incorporating clinical and imaging parameters to predict prognosis. Conclusions: The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.

Background: Cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) is a key diagnostic tool in the differential diagnosis between non-ischemic cause of cardiac chest pain. Some patients are not eligible for a gadolinium contrast-enhanced CMR; in this scenario, the diagnosis remains challenging without invasive examination. Our purpose was to derive a machine learning model integrating some non-contrast CMR parameters and demographic factors to identify Takotsubo cardiomyopathy (TTC) in subjects with cardiac chest pain. Material and methods: Three groups of patients were retrospectively studied: TTC, acute myocarditis, and healthy controls. Global and regional left ventricular longitudinal, circumferential, and radial strain (RS) analysis included were assessed. Reservoir, conduit, and booster bi-atrial functions were evaluated by tissue-tracking. Parametric mapping values were also assessed in all the patients. Five different tree-based ensemble learning algorithms were tested concerning their ability in recognizing TTC in a fully cross-validated framework. Results: The CMR-based machine learning (ML) ensemble model, by using the Extremely Randomized Trees algorithm with Elastic Net feature selection, showed a sensitivity of 92% (95% CI 78–100), specificity of 86% (95% CI 80–92) and area under the ROC of 0.94 (95% CI 0.90–0.99) in diagnosing TTC. Among non-contrast CMR parameters, the Shapley additive explanations analysis revealed that left atrial (LA) strain and strain rate were the top imaging markers in identifying TTC patients. Conclusions: Our study demonstrated that using a tree-based ensemble learning algorithm on non-contrast CMR parameters and demographic factors enables the identification of subjects with TTC with good diagnostic accuracy. Translational outlook: Our results suggest that non-contrast CMR features can be implemented in a ML model to accurately identify TTC subjects. This model could be a valuable tool for aiding in the diag

Age is a non-modifiable cardiovascular risk factor, which leads to development and progression of chronic conditions, such as coronary artery disease, by promoting atherosclerosis. Aging is responsible for morphological structure changes of the coronary arteries and specific atherosclerotic plaque features, which can be studied with non-invasive coronary imaging techniques, particularly coronary CT angiography. The aim of this review is to evaluate current knowledge on this technique applied to the elderly population, and to describe CAD manifestation and plaque features of coronary atherosclerosis in this particular set of patients. We also discuss the clinical implication of frailty assessment and customization of diagnostic strategies in order to shift the approach from disease-centered to patient-centered care.

Cardiovascular diseases (CVDs), particularly ischemic heart disease (IHD) and stroke, present epidemiologically in a different way among sexes. The reasons of these sex-based differences should be delved into sex-specific cardiovascular (CV) risk factors and different mechanisms of atherosclerotic progression. Imaging techniques of both carotid and coronary atherosclerotic plaques represent a tool to demonstrate sex-related features which might be used to further and better assess CV risk of male and female population. The aim of this review is to evaluate current knowledge on sex-specific qualitative and quantitative plaque features of coronary and carotid atherosclerosis. We also discuss the clinical implication of a sex-based plaque phenotype, evaluated with non-invasive imaging techniques, such as CT-angiography and MRI-angiography, to stratify CV risk.