An automated and time-efficient framework for simulation of coronary blood flow under steady and pulsatile conditions.

BACKGROUND AND OBJECTIVE: Invasive fractional flow reserve (FFR) measurement is the gold standard method for coronary artery disease (CAD) diagnosis. FFR-CT exploits computational fluid dynamics (CFD) for non-invasive evaluation of FFR, simulating coronary flow in virtual geometries reconstructed from computed tomography (CT), but suffers from cost-intensive computing process and uncertainties in the definition of patient specific boundary conditions (BCs). In this work, we investigated the use of time-averaged steady BCs, compared to pulsatile to reduce the computational time and deployed a self-adjusting method for the tuning of BCs to patient-specific clinical data. METHODS: 133 coronary arteries were reconstructed form CT images of patients suffering from CAD. For each vessel, invasive FFR was measured. After segmentation, the geometries were prepared for CFD simulation by clipping the outlets and discretizing into tetrahedral mesh. Steady BCs were defined in two steps: (i) rest BCs were extrapolated from clinical and image-derived data; (ii) hyperemic BCs were computed from resting conditions. Flow rate was iteratively adjusted during the simulation, until patient's aortic pressure was matched. Pulsatile BCs were defined exploiting the convergence values of steady BCs. After CFD simulation, lesion-specific hemodynamic indexes were computed and compared between group of patients for which surgery was indicated and not. The whole pipeline was implemented as a straightforward process, in which each single step is performed automatically. RESULTS: Steady and pulsatile FFR-CT yielded a strong correlation (r = 0.988, p < 0.001) and correlated with invasive FFR (r = 0.797, p < 0.001). The per-point difference between the pressure and FFR-CT field predicted by the two methods was below 1 % and 2 %, respectively. Both approaches exhibited a good diagnostic performance: accuracy was 0.860 and 0.864, the AUC was 0.923 and 0.912, for steady and pulsatile case, respectively. The computational time required by steady BCs CFD was approximatively 30-folds lower than pulsatile case. CONCLUSIONS: This work shows the feasibility of using steady BCs CFD for computing the FFR-CT in coronary arteries, as well as its computational and diagnostic performance within a fully automated pipeline.

Role of advanced CMR features in identifying a positive genotype of hypertrophic cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disease that affects approximately one in 500 people. Cardiac magnetic resonance (CMR) imaging has emerged as a powerful tool for the non-invasive assessment of HCM. CMR can accurately quantify the extent and distribution of hypertrophy, assess the presence and severity of myocardial fibrosis, and detect associated abnormalities. We will study basic and advanced features of CMR in 2 groups of HCM patients with negative and positive genotype, respectively. MATERIALS AND METHODS: The study population consisted in consecutive HCM patients referred to Centro Cardiologico Monzino who performed both CMR and genetic testing. Clinical CMR images were acquired at 1.5 T Discovery MR450 scanner (GE Healthcare, Milwaukee, Wisconsin)) using standardized protocols T1 mapping, T2 mapping and late gadolinium enhancement (LGE). Population was divided in 2 groups: group 1 with HCM patients with a negative genotype and group 2 with a positive genotype. RESULTS: The analytic population consisted of 110 patients: 75 in group 1 and 35 patients in group 2. At CMR evaluation, patients with a positive genotype had higher LV mass (136 vs. 116 g, p = 0.02), LV thickness (17.5 vs. 16.9 mm), right ventricle ejection fraction (63 % vs. 58 %, p = 0.002). Regarding the LGE patients with positive genotype have a higher absolute (33.8 vs 16.7 g, p = 0.0003) and relative LGE mass (31.6 % vs 14.6 %, p = 0.0007). On a segmental analysis all the septum (segments 2, 8, 9, and 14) had a significantly increased native T1 compared to others segments. ECV in the mid antero and infero-septum (segments 8 and 9) have lower values in positive genotype HCM. Interestingly the mean T2 was lower in positive genotype HCM as compared to negative genotype HCM (50,1 ms vs 52,4). CONCLUSIONS: Our paper identifies the mid septum (segments 8 and 9) as a key to diagnose a positive genotype HCM.

STress computed tomogRaphy perfusion and stress cArdiac magnetic resonance for ThE manaGement of suspected or known coronarY artery disease: resources and outcomes impact.

BACKGROUND: The aim of this study is to describe resources and outcomes of coronary computed tomography angiography plus Stress CT perfusion (CCTA â€‹+ â€‹Stress-CTP) and stress cardiovascular magnetic resonance (Stress-CMR) in symptomatic patients with suspected or known CAD. METHODS: Six hundred and twenty-four consecutive symptomatic patients with intermediate to high-risk pretest likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA â€‹+ â€‹Stress-CTP or Stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients while 401 patients performed Stress-CMR. Patient follow-up was performed at 1 year after index test performance. Endpoints were all cardiac events, as a combined endpoint of revascularization, non-fatal MI and death, and hard cardiac events, as combined endpoint of non-fatal MI and death. RESULTS: Twenty-nine percent of patients who underwent CCTA â€‹+ â€‹Stress-CTP received revascularization, 7% of subjects assessed with Stress-CMR were treated invasively, and a low number of non-fatal MI and death was observed with both strategies (hard events in 0.4% of patients that had CCTA â€‹+ â€‹Stress-CTP as index test, and in 3% of patients evaluated with Stress-CMR). According to the predefined endpoints, CCTA â€‹+ â€‹Stress-CTP group showed high rate of all cardiac events and low rate of hard cardiac events, respectively. The cumulative costs were 1970 â€‹± â€‹2506 Euro and 733 â€‹± â€‹1418 Euro for the CCTA â€‹+ â€‹Stress-CTP group and Stress-CMR group, respectively. CONCLUSIONS: The use of CCTA â€‹+ â€‹Stress-CTP strategy was associated with high referral to revascularization but with a favourable trend in terms of hard cardiac events and diagnostic yield in identifying individuals at lower risk of adverse events despite the presence of CAD.

Cardiac magnetic resonance reveals concealed structural heart disease in patients with frequent premature ventricular contractions and normal echocardiography: A systematic review.

Premature ventricular contractions (PVCs) are a common form of arrhythmic events, often representing an idiopathic and benign condition without further therapeutic interventions. However, in certain circumstances PVCs may represent the epiphenomenon of a concealed structural heart disease (SHD). Surface 12­leads EKG and 24-h dynamic EKG are necessary to assess their main characteristics such as site of origin, frequency and complexity. Echocardiography represents the first-line imaging tool recommended to evaluate cardiac structures and function. Cardiac Magnetic Resonance (CMR) is recognized as a superior modality for detecting structural cardiac alterations, that might evade detection by conventional echocardiography. Moreover, in specific populations such as athletes, CMR may have a crucial role to exclude a concealed SHD and the risk of serious arrhythmic events during sport activity. Some clinical characteristics such as male sex, older age or family history of sudden cardiac death (SCD) or cardiomyopathy, and some electrocardiographic features of PVCs, in particular a right branch bundle block (RBBB) with superior/intermediate axis morphology, the reproducibility of VAs during exercise test (ET) or the evidence of complex ventricular arrhythmias, may warrant a CMR evaluation, due to the high probability of SHD. In this systematic review our objective was to provide an exhaustive overview on the role of CMR in detecting a concealed SHD in patients with high daily burden of PVCs and a normal echocardiographic evaluation, paving the way for a more extensive utilization of CMR in presence of certain high-risk clinical and/or EKG features identified during the diagnostic workup.

Modeling cardiac microcirculation for the simulation of coronary flow and 3D myocardial perfusion.

Accurate modeling of blood dynamics in the coronary microcirculation is a crucial step toward the clinical application of in silico methods for the diagnosis of coronary artery disease. In this work, we present a new mathematical model of microcirculatory hemodynamics accounting for microvasculature compliance and cardiac contraction; we also present its application to a full simulation of hyperemic coronary blood flow and 3D myocardial perfusion in real clinical cases. Microvasculature hemodynamics is modeled with a compliant multi-compartment Darcy formulation, with the new compliance terms depending on the local intramyocardial pressure generated by cardiac contraction. Nonlinear analytical relationships for vessels distensibility are included based on experimental data, and all the parameters of the model are reformulated based on histologically relevant quantities, allowing a deeper model personalization. Phasic flow patterns of high arterial inflow in diastole and venous outflow in systole are obtained, with flow waveforms morphology and pressure distribution along the microcirculation reproduced in accordance with experimental and in vivo measures. Phasic diameter change for arterioles and capillaries is also obtained with relevant differences depending on the depth location. Coronary blood dynamics exhibits a disturbed flow at the systolic onset, while the obtained 3D perfusion maps reproduce the systolic impediment effect and show relevant regional and transmural heterogeneities in myocardial blood flow (MBF). The proposed model successfully reproduces microvasculature hemodynamics over the whole heartbeat and along the entire intramural vessels. Quantification of phasic flow patterns, diameter changes, regional and transmural heterogeneities in MBF represent key steps ahead in the direction of the predictive simulation of cardiac perfusion.

Beyond Stress Ischemia: Unveiling the Multifaceted Nature of Coronary Vulnerable Plaques Using Cardiac Computed Tomography.

Historically, cardiovascular prevention has been predominantly focused on stress-induced ischemia, but recent trials have challenged this paradigm, highlighting the emerging role of vulnerable, non-flow-limiting coronary plaques, leading to a shift towards integrating plaque morphology with functional data into risk prediction models. Coronary computed tomography angiography (CCTA) represents a high-resolution, low-risk, and largely available non-invasive modality for the precise delineation of plaque composition, morphology, and inflammatory activity, further enhancing our ability to stratify high-risk plaque and predict adverse cardiovascular outcomes. Coronary artery calcium (CAC) scoring, derived from CCTA, has emerged as a promising tool for predicting future cardiovascular events in asymptomatic individuals, demonstrating incremental prognostic value beyond traditional cardiovascular risk factors in terms of myocardial infarction, stroke, and all-cause mortality. Additionally, CCTA-derived information on adverse plaque characteristics, geometric characteristics, and hemodynamic forces provides valuable insights into plaque vulnerability and seems promising in guiding revascularization strategies. Additionally, non-invasive assessments of epicardial and pericoronary adipose tissue (PCAT) further refine risk stratification, adding prognostic significance to coronary artery disease (CAD), correlating with plaque development, vulnerability, and rupture. Moreover, CT imaging not only aids in risk stratification but is now emerging as a screening tool able to monitor CAD progression and treatment efficacy over time. Thus, the integration of CAC scoring and PCAT evaluation into risk stratification algorithms, as well as the identification of high-risk plaque morphology and adverse geometric and hemodynamic characteristics, holds promising results for guiding personalized preventive interventions, helping physicians in identifying high-risk individuals earlier, tailoring lifestyle and pharmacological interventions, and improving clinical outcomes in their patients.

PROGnostic RolE of strain measurements in stress cardiac MRI in predicting major adverse cardiac events.

OBJECTIVES: We aimed to investigate the role of feature-tracking (FT) strain in long-term risk stratification of patients with known or suspected coronary artery disease (CAD) who underwent stress cardiac MRI with dipyridamole; to determine if contrast-free stress cardiac MRI with strain measurements could provide comparable prognostic value to myocardial perfusion. MATERIALS AND METHODS: This retrospective study included consecutive patients with stable symptoms suggesting possible cardiac ischemia who underwent stress cardiac MRI with dipyridamole. The mean follow-up period was 5.8 years ±1.2 [SD]. FT cardiac MRI analysis was performed for each patient to obtain 2D global peak circumferential strain (GCS). The primary outcome measure was major adverse cardiac events (MACE), defined as nonfatal myocardial infarction and cardiac death. RESULTS: A total of 729 patients (mean age, 63 years ±10 [SD]; 616 males) were included. MACE occurred in 70 (9.6%) patients. The presence of late gadolinium enhancement (LGE) ([HR] 2.74, [95% CI: 1.53, 4.88]; P < .001) and stress GCS (HR, 1.06 [95% CI: 1.01, 1.12]; P = .016) were independently associated with MACE. A model based on contrast-free assessment of LVEF and stress GCS showed similar performance for predicting MACE than LVEF and perfusion (P = .056). CONCLUSIONS: In patients with known or suspected CAD undergoing stress cardiac MRI with dipyridamole, GCS and LGE presence were independent predictors of MACE. Contrast-free stress cardiac MRI with stress GCS measurement offered prognostic value akin to myocardial perfusion assessment. CLINICAL RELEVANCE STATEMENT: Stress global circumferential strain represented an additional method to predict major adverse cardiac events in patients undergoing stress cardiac MRI, even without the use of contrast agents. This would be of particular significance in patients with severe renal impairment.

The Role of Multimodality Imaging (CT & MR) as a Guide to the Management of Chronic Coronary Syndromes.

Chronic coronary syndrome (CCS) is one of the leading cardiovascular causes of morbidity, mortality, and use of medical resources. After the introduction by international guidelines of the same level of recommendation to non-invasive imaging techniques in CCS evaluation, a large debate arose about the dilemma of choosing anatomical (with coronary computed tomography angiography (CCTA)) or functional imaging (with stress echocardiography (SE), cardiovascular magnetic resonance (CMR), or nuclear imaging techniques) as a first diagnostic evaluation. The determinant role of the atherosclerotic burden in defining cardiovascular risk and prognosis more than myocardial inducible ischemia has progressively increased the use of a first anatomical evaluation with CCTA in a wide range of pre-test probability in CCS patients. Functional testing holds importance, both because the role of revascularization in symptomatic patients with proven ischemia is well defined and because functional imaging, particularly with stress cardiac magnetic resonance (s-CMR), gives further prognostic information regarding LV function, detection of myocardial viability, and tissue characterization. Emerging techniques such as stress computed tomography perfusion (s-CTP) and fractional flow reserve derived from CT (FFRCT), combining anatomical and functional evaluation, appear capable of addressing the need for a single non-invasive examination, especially in patients with high risk or previous revascularization. Furthermore, CCTA in peri-procedural planning is promising to acquire greater importance in the non-invasive planning and guiding of complex coronary revascularization procedures, both by defining the correct strategy of interventional procedure and by improving patient selection. This review explores the different roles of non-invasive imaging techniques in managing CCS patients, also providing insights into preoperative planning for percutaneous or surgical myocardial revascularization.

The Role of Magnetic Resonance Imaging in Cardiomyopathies in the Light of New Guidelines: A Focus on Tissue Mapping.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Case report: acute myocarditis in two patients with coronary artery disease presenting with chest pain-thinking outside the box.

Background: In a subset of patients, acute myocarditis (AM) may mimic acute myocardial infarction, with a similar clinical presentation characterized by chest pain, electrocardiogram (ECG) changes consistent with acute coronary syndromes (ACS), and serum markers increment. Case summary: We present two cases of infarct-like myocarditis in patients with known coronary artery disease (CAD), in which the discrepancy between transthoracic echocardiogram findings, ECG, and angiography prompted us to look beyond the simplest diagnosis. In these cases, making a prompt and correct diagnosis is pivotal to address adequate therapy and establish a correct prognosis. Discussion: The right diagnosis can avoid unnecessary coronary revascularizations and subsequent antiplatelet therapy that may be associated with an increased haemorrhagic risk. Moreover, it allows setting up guideline-directed therapy for myocarditis, proper follow-up, as well as recommending abstention from physical activity.

DEep LearnIng-based QuaNtification of epicardial adipose tissue predicts MACE in patients undergoing stress CMR.

BACKGROUND AND AIMS: This study investigated the additional prognostic value of epicardial adipose tissue (EAT) volume for major adverse cardiovascular events (MACE) in patients undergoing stress cardiac magnetic resonance (CMR) imaging. METHODS: 730 consecutive patients [mean age: 63 ± 10 years; 616 men] who underwent stress CMR for known or suspected coronary artery disease were randomly divided into derivation (n = 365) and validation (n = 365) cohorts. MACE was defined as non-fatal myocardial infarction and cardiac deaths. A deep learning algorithm was developed and trained to quantify EAT volume from CMR. EAT volume was adjusted for height (EAT volume index). A composite CMR-based risk score by Cox analysis of the risk of MACE was created. RESULTS: In the derivation cohort, 32 patients (8.7 %) developed MACE during a follow-up of 2103 days. Left ventricular ejection fraction (LVEF) < 35 % (HR 4.407 [95 % CI 1.903-10.202]; p<0.001), stress perfusion defect (HR 3.550 [95 % CI 1.765-7.138]; p<0.001), late gadolinium enhancement (LGE) (HR 4.428 [95%CI 1.822-10.759]; p = 0.001) and EAT volume index (HR 1.082 [95 % CI 1.045-1.120]; p<0.001) were independent predictors of MACE. In a multivariate Cox regression analysis, adding EAT volume index to a composite risk score including LVEF, stress perfusion defect and LGE provided additional value in MACE prediction, with a net reclassification improvement of 0.683 (95%CI, 0.336-1.03; p<0.001). The combined evaluation of risk score and EAT volume index showed a higher Harrel C statistic as compared to risk score (0.85 vs. 0.76; p<0.001) and EAT volume index alone (0.85 vs.0.74; p<0.001). These findings were confirmed in the validation cohort. CONCLUSIONS: In patients with clinically indicated stress CMR, fully automated EAT volume measured by deep learning can provide additional prognostic information on top of standard clinical and imaging parameters.

Cardiac Magnetic Resonance to Predict Cardiac Mass Malignancy: The CMR Mass Score.

BACKGROUND: Multimodality imaging is currently suggested for the noninvasive diagnosis of cardiac masses. The identification of cardiac masses' malignant nature is essential to guide proper treatment. We aimed to develop a cardiac magnetic resonance (CMR)-derived model including mass localization, morphology, and tissue characterization to predict malignancy (with histology as gold standard), to compare its accuracy versus the diagnostic echocardiographic mass score, and to evaluate its prognostic ability. METHODS: Observational cohort study of 167 consecutive patients undergoing comprehensive echocardiogram and CMR within 1-month time interval for suspected cardiac mass. A definitive diagnosis was achieved by histological examination or, in the case of cardiac thrombi, by histology or radiological resolution after adequate anticoagulation treatment. Logistic regression was performed to assess CMR-derived independent predictors of malignancy, which were included in a predictive model to derive the CMR mass score. Kaplan-Meier curves and Cox regression were used to investigate the prognostic ability of predictors. RESULTS: In CMR, mass morphological features (non-left localization, sessile, polylobate, inhomogeneity, infiltration, and pericardial effusion) and mass tissue characterization features (first-pass perfusion and heterogeneity enhancement) were independent predictors of malignancy. The CMR mass score (range, 0-8 and cutoff, ≥5), including sessile appearance, polylobate shape, infiltration, pericardial effusion, first-pass contrast perfusion, and heterogeneity enhancement, showed excellent accuracy in predicting malignancy (areas under the curve, 0.976 [95% CI, 0.96-0.99]), significantly higher than diagnostic echocardiographic mass score (areas under the curve, 0.932; P=0.040). The agreement between the diagnostic echocardiographic mass and CMR mass scores was good (κ=0.66). A CMR mass score of ≥5 predicted a higher risk of all-cause death (P<0.001; hazard ratio, 5.70) at follow-up. CONCLUSIONS: A CMR-derived model, including mass morphology and tissue characterization, showed excellent accuracy, superior to echocardiography, in predicting cardiac masses malignancy, with prognostic implications.

Predictors of adverse cardiac events of coronary myocardial bridging diagnosed with computed tomography angiography.

AIMS: Myocardial bridging (MB) is a frequent congenital anomaly of the epicardial coronary arteries commonly considered a benign condition. However, in some cases a complex interplay between anatomical, clinical and physiology factors may lead to adverse events, including sudden cardiac death. Coronary CT angiography (CCTA) emerged as the gold standard noninvasive imaging technique for the evaluation of MB. Aim of the study was to evaluate MB prevalence and anatomical features in a large population of patients who underwent CCTA for suspected CAD and to identify potential anatomical and clinical predictors of adverse cardiac events at long-term follow-up. METHODS AND RESULTS: Two-hundred and six patients (mean age 60.3 ± 11.8 years, 128 male) with MB diagnosed at CCTA were considered. A long MB was defined as ≥25 mm of overlying myocardium, whereas a deep MB as ≥2 mm of overlying myocardium. The study endpoint was the sum of the following adverse events: cardiac death, bridge-related acute coronary syndrome, hospitalization for angina or bridge-related ventricular arrhythmias and MB surgical treatment. Of the 206 patients enrolled in the study, 9 were lost to follow-up, whereas 197 (95.6%) had complete follow-up (mean 7.01 ± 3.0 years) and formed the analytic population. Nineteen bridge-related events occurred in 18 patients (acute coronary syndrome in 7, MB surgical treatment in 2 and hospitalization for bridge-related events in 10). Typical angina at the time of diagnosis and long MB resulted as significant independent predictors of adverse outcome. CONCLUSIONS: Typical angina and MB length ≥ 25 mm were independent predictors of cardiac events.

Personalized Pressure Conditions and Calibration for a Predictive Computational Model of Coronary and Myocardial Blood Flow.

Predictive modeling of hyperemic coronary and myocardial blood flow (MBF) greatly supports diagnosis and prognostic stratification of patients suffering from coronary artery disease (CAD). In this work, we propose a novel strategy, using only readily available clinical data, to build personalized inlet conditions for coronary and MBF models and to achieve an effective calibration for their predictive application to real clinical cases. Experimental data are used to build personalized pressure waveforms at the aortic root, representative of the hyperemic state and adapted to surrogate the systolic contraction, to be used in computational fluid-dynamics analyses. Model calibration to simulate hyperemic flow is performed in a "blinded" way, not requiring any additional exam. Coronary and myocardial flow simulations are performed in eight patients with different clinical conditions to predict FFR and MBF. Realistic pressure waveforms are recovered for all the patients. Consistent pressure distribution, blood velocities in the large arteries, and distribution of MBF in the healthy myocardium are obtained. FFR results show great accuracy with a per-vessel sensitivity and specificity of 100% according to clinical threshold values. Mean MBF shows good agreement with values from stress-CTP, with lower values in patients with diagnosed perfusion defects. The proposed methodology allows us to quantitatively predict FFR and MBF, by the exclusive use of standard measures easily obtainable in a clinical context. This represents a fundamental step to avoid catheter-based exams and stress tests in CAD diagnosis.

A fully automated deep learning approach for coronary artery segmentation and comprehensive characterization.

Coronary computed tomography angiography (CCTA) allows detailed assessment of early markers associated with coronary artery disease (CAD), such as coronary artery calcium (CAC) and tortuosity (CorT). However, their analysis can be time-demanding and biased. We present a fully automated pipeline that performs (i) coronary artery segmentation and (ii) CAC and CorT objective analysis. Our method exploits supervised learning for the segmentation of the lumen, and then, CAC and CorT are automatically quantified. 281 manually annotated CCTA images were used to train a two-stage U-Net-based architecture. The first stage employed a 2.5D U-Net trained on axial, coronal, and sagittal slices for preliminary segmentation, while the second stage utilized a multichannel 3D U-Net for refinement. Then, a geometric post-processing was implemented: vessel centerlines were extracted, and tortuosity score was quantified as the count of branches with three or more bends with change in direction forming an angle >45°. CAC scoring relied on image attenuation. CAC was detected by setting a patient specific threshold, then a region growing algorithm was applied for refinement. The application of the complete pipeline required <5 min per patient. The model trained for coronary segmentation yielded a Dice score of 0.896 and a mean surface distance of 1.027 mm compared to the reference ground truth. Tracts that presented stenosis were correctly segmented. The vessel tortuosity significantly increased locally, moving from proximal, to distal regions (p < 0.001). Calcium volume score exhibited an opposite trend (p < 0.001), with larger plaques in the proximal regions. Volume score was lower in patients with a higher tortuosity score (p < 0.001). Our results suggest a linked negative correlation between tortuosity and calcific plaque formation. We implemented a fast and objective tool, suitable for population studies, that can help clinician in the quantification of CAC and various coronary morphological parameters, which is helpful for CAD risk assessment.

CMR Mapping: The 4th-Era Revolution in Cardiac Imaging.

Cardiac magnetic resonance (CMR) imaging has witnessed substantial progress with the advent of parametric mapping techniques, most notably T1 and T2 mapping. These advanced techniques provide valuable insights into a wide range of cardiac conditions, including ischemic heart disease, cardiomyopathies, inflammatory cardiomyopathies, heart valve disease, and athlete's heart. Mapping could be the first sign of myocardial injury and oftentimes precedes symptoms, changes in ejection fraction, and irreversible myocardial remodeling. The ability of parametric mapping to offer a quantitative assessment of myocardial tissue properties addresses the limitations of conventional CMR methods, which often rely on qualitative or semiquantitative data. However, challenges persist, especially in terms of standardization and reference value establishment, hindering the wider clinical adoption of parametric mapping. Future developments should prioritize the standardization of techniques to enhance their clinical applicability, ultimately optimizing patient care pathways and outcomes. In this review, we endeavor to provide insights into the potential contributions of CMR mapping techniques in enhancing the diagnostic processes across a range of cardiac conditions.

Assessment and management of heart failure in patients with chronic kidney disease.

Heart failure (HF) and chronic kidney disease (CKD) are two pathological conditions with a high prevalence in the general population. When they coexist in the same patient, a strict interplay between them is observed, such that patients affected require a clinical multidisciplinary and personalized management. The diagnosis of HF and CKD relies on signs and symptoms of the patient but several additional tools, such as blood-based biomarkers and imaging techniques, are needed to clarify and discriminate the main characteristics of these diseases. Improved survival due to new recommended drugs in HF has increasingly challenged physicians to manage patients with multiple diseases, especially in case of CKD. However, the safe administration of these drugs in patients with HF and CKD is often challenging. Knowing up to which values ​​of creatinine or renal clearance each drug can be administered is fundamental. With this review we sought to give an insight on this sizable and complex topic, in order to get clearer ideas and a more precise reference about the diagnostic assessment and therapeutic management of HF and CKD.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

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-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

A comparison of intracardiac echocardiography and transesophageal echocardiography for guiding device closure of ostium secundum atrial septal defect: A 15-year experience.

BACKGROUND AND AIM: Our aim was to evaluate the fluoroscopy time (FT), procedure time (PT) safety and efficacy when using intracardiac echocardiography (ICE) in comparison to transesophageal echocardiography (TEE) guidance for transcatheter closure of Ostium Secundum Atrial Septal Defect (OS-ASD). METHOD: Ninety patients (n = 90) diagnosed with OS-ASD underwent transcatheter closure between March 2006 and October 2021. Fifty-seven patients were treated under ICE guidance, while 33 patients were treated under TEE guidance. RESULTS: Mean age was 43 ± 15 years and 42 ± 10 years in the ICE and TEE groups, respectively. The majority of patients had a centrally placed defect. Median FT was 8.40 min versus 11.70 min (p < .001) in the ICE group compared to the TEE group, respectively. Median PT was 43 min versus 94 min (p < .001) in the ICE group compared to the TEE group, respectively. Both ICE and TEE provided high quality images. All interventions were completed successfully, except for one patient in the ICE group who experienced a device migration, the development of atrial tachycardia in one patient and atrial fibrillation in two patients in the ICE group which spontaneously cardioverted. There were no other complications. CONCLUSION: This study on a consistent cohort of patients with OS-ASD undergoing percutaneous closure suggests that use of ICE is safe and efficacious. Compared to TEE, ICE demonstrated significantly shorter FT and PT, decreasing the entire duration of the procedure and x-ray exposure. No relevant differences were observed in terms of success rate and complications.