Coronary bypass surgery guided by computed tomography in a low-risk population.

BACKGROUND AND AIMS: In patients with three-vessel disease and/or left main disease, selecting revascularization strategy based on coronary computed tomography angiography (CCTA) has a high level of virtual agreement with treatment decisions based on invasive coronary angiography (ICA). METHODS: In this study, coronary artery bypass grafting (CABG) procedures were planned based on CCTA without knowledge of ICA. The CABG strategy was recommended by a central core laboratory assessing the anatomy and functionality of the coronary circulation. The primary feasibility endpoint was the percentage of operations performed without access to the ICA. The primary safety endpoint was graft patency on 30-day follow-up CCTA. Secondary endpoints included topographical adequacy of grafting, major adverse cardiac and cerebrovascular (MACCE), and major bleeding events at 30 days. The study was considered positive if the lower boundary of confidence intervals (CI) for feasibility was ≥75% (NCT04142021). RESULTS: The study enrolled 114 patients with a mean (standard deviation) anatomical SYNTAX score and Society of Thoracic Surgery score of 43.6 (15.3) and 0.81 (0.63), respectively. Unblinding ICA was required in one case yielding a feasibility of 99.1% (95% CI 95.2%-100%). The concordance and agreement in revascularization planning between the ICA- and CCTA-Heart Teams was 82.9% with a moderate kappa of 0.58 (95% CI 0.50-0.66) and between the CCTA-Heart Team and actual treatment was 83.7% with a substantial kappa of 0.61 (95% CI 0.53-0.68). The 30-day follow-up CCTA in 102 patients (91.9%) showed an anastomosis patency rate of 92.6%, whilst MACCE was 7.2% and major bleeding 2.7%. CONCLUSIONS: CABG guided by CCTA is feasible and has an acceptable safety profile in a selected population of complex coronary artery disease.

Atrial and ventricular strain using cardiovascular magnetic resonance in the prediction of outcomes of pericarditis patients: a pilot study.

OBJECTIVE: Our study aimed to explore with cardiovascular magnetic resonance (CMR) the impact of left atrial (LA) and left ventricular (LV) myocardial strain in patients with acute pericarditis and to investigate their possible prognostic significance in adverse outcomes. METHOD: This retrospective study performed CMR scans in 36 consecutive patients with acute pericarditis (24 males, age 52 [23-52]). The primary endpoint was the combination of recurrent pericarditis, constrictive pericarditis, and surgery for pericardial diseases defined as pericardial events. Atrial and ventricular strain function were performed on conventional cine SSFP sequences. RESULTS: After a median follow-up time of 16 months (interquartile range [13-24]), 12 patients with acute pericarditis reached the primary endpoint. In multivariable Cox regression analysis, LA reservoir and LA conduit strain parameters were all independent determinants of adverse pericardial diseases. Conversely, LV myocardial strain parameters did not remain an independent predictor of outcome. With receiving operating characteristics curve analysis, LA conduit and reservoir strain showed excellent predictive performance (area under the curve of 0.914 and 0.895, respectively) for outcome prediction at 12 months. CONCLUSION: LA reservoir and conduit mechanisms on CMR are independently associated with a higher risk of adverse pericardial events. Including atrial strain parameters in the management of acute pericarditis may improve risk stratification. CLINICAL RELEVANCE STATEMENT: Atrial strain could be a suitable non-invasive and non-contrast cardiovascular magnetic resonance parameter for predicting adverse pericardial complications in patients with acute pericarditis. KEY POINTS: • Myocardial strain is a well-validated CMR parameter for risk stratification in cardiovascular diseases. • LA reservoir and conduit functions are significantly associated with adverse pericardial events. • Atrial strain may serve as an additional non-contrast CMR parameter for stratifying patients with acute pericarditis.

Pre- and post-procedural cardiac imaging (computed tomography and magnetic resonance imaging) in electrophysiology: a clinical consensus statement of the European Heart Rhythm Association and European Association of Cardiovascular Imaging of the European Society of Cardiology.

Imaging using cardiac computed tomography (CT) or magnetic resonance (MR) imaging has become an important option for anatomic and substrate delineation in complex atrial fibrillation (AF) and ventricular tachycardia (VT) ablation procedures. Computed tomography more common than MR has been used to detect procedure-associated complications such as oesophageal, cerebral, and vascular injury. This clinical consensus statement summarizes the current knowledge of CT and MR to facilitate electrophysiological procedures, the current value of real-time integration of imaging-derived anatomy, and substrate information during the procedure and the current role of CT and MR in diagnosing relevant procedure-related complications. Practical advice on potential advantages of one imaging modality over the other is discussed for patients with implanted cardiac rhythm devices as well as for planning, intraprocedural integration, and post-interventional management in AF and VT ablation patients. Establishing a team of electrophysiologists and cardiac imaging specialists working on specific details of imaging for complex ablation procedures is key. Cardiac magnetic resonance (CMR) can safely be performed in most patients with implanted active cardiac devices. Standard procedures for pre- and post-scanning management of the device and potential CMR-associated device malfunctions need to be in place. In VT patients, imaging-specifically MR-may help to determine scar location and mural distribution in patients with ischaemic and non-ischaemic cardiomyopathy beyond evaluating the underlying structural heart disease. Future directions in imaging may include the ability to register multiple imaging modalities and novel high-resolution modalities, but also refinements of imaging-guided ablation strategies are expected.

Aortic valve neocuspidization and bioprosthetic valves: Evaluating turbulence haemodynamics.

Aortic valve disease is often treated with bioprosthetic valves. An alternative treatment is aortic valve neocuspidization which is a relatively new reparative procedure whereby the three aortic cusps are replaced with patient pericardium or bovine tissues. Recent research indicates that aortic blood flow is disturbed, and turbulence effects have yet to be evaluated in either bioprosthetic or aortic valve neocuspidization valve types in patient-specific settings. The aim of this study is to better understand turbulence production in the aorta and evaluate its effects on laminar and turbulent wall shear stress. Four patients with aortic valve disease were treated with either bioprosthetic valves (n=2) or aortic valve neocuspidization valvular repair (n=2). Aortic geometries were segmented from magnetic resonance images (MRI), and 4D flow MRI was used to derive physiological inlet and outlet boundary conditions. Pulsatile large-eddy simulations were performed to capture the full range of laminar, transitional and turbulence characteristics in the aorta. Turbulence was produced in all aortas with highest levels occurring during systolic deceleration. In the ascending aorta, turbulence production is attributed to a combination of valvular skew, valvular eccentricity, and ascending aortic dilation. In the proximal descending thoracic aorta, turbulence production is dependent on the type of arch-descending aorta connection (e.g., a narrowing or sharp bend) which induces flow separation. Laminar and turbulent wall shear stresses are of similar magnitude throughout late systolic deceleration and diastole, although turbulent wall shear stress magnitudes exceed laminar wall shear stresses between 27.3% and 61.1% of the cardiac cycle. This emphasises the significance of including turbulent wall shear stress to improve our comprehension of progressive arterial wall diseases. The findings of this study recommend that aortic valve treatments should prioritise minimising valvular eccentricity and skew in order to mitigate turbulence generation.

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.

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.

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.

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-observer variability. Artificial intelligence (AI) is a field that permits automated task performance through the identification of high-level and complex data relationships. In this review, we review the rapidly growing role of AI in CMR, including image acquisition, sequence prescription, artifact detection, reconstruction, segmentation, and data reporting and analysis including quantification of volumes, function, myocardial infarction (MI) and scar detection, and prediction of outcomes. We conclude with a discussion of the emerging challenges to widespread adoption and solutions that will allow for successful, broader uptake of this powerful technology.

Clinical and cardiac CT characteristics of congenital coronary abnormalities occasionally detected in a middle-aged population: A long-term follow-up study.

INTRODUCTION: Congenital coronary artery anomalies (CCAA) represent one of the most challenging conditions as their clinical presentation may range from sudden cardiac death to a complete subclinical form. The aim of the present study was to evaluate the diagnostic and prognostic role of cardiac CT (CCT) evaluation in patients with CCAA, focusing on anomalies of origin. MATERIAL AND METHODS: The present is a retrospective analysis of a prospective clinical registry including a consecutive cohort of patients who underwent clinically indicated CCT from January 2007 to October 2015 for suspected but unknown coronary artery disease (CAD) and were diagnosed for having a congenital coronary abnormality compared to a control group matched for age, sex and segment stenosis score (SSS). Dedicated analysis of all CCT was performed for the present study and only coronary anomalies of origin were considered and included in the study. Two different composite end-points were identified for the present analysis: major cardiovascular events (MACE) and all-cause of death. RESULTS: Among the 81 patients with CCAAs enrolled the most frequent anomaly was left main artery absence, which was identified in 41 individuals (50.6%). Forty-five subjects (55.5%) have an anomalous origin of the coronary artery from a different sinus of Valsalva and 45 subjects had also an anomalous course with the retro-aortic being the most common (32%). Eleven participants (13.6%) displayed also an intramural segment, while 10 (10.3%) had a slit-like ostial morphology. At multivariate analysis CT identification of ARCA, anomalous inter-arterial course and abnormal ostial morphology were significantly associated with MACE even when adjusted for age and SSS, without any differences in all-cause mortality between the two groups (6.2% vs 2.4% p â€‹= â€‹0.2478). CONCLUSION: The result of the present study is that CCT can be successfully used to define the anatomy and features of CAA. It suggested that in middle-aged patients, the identification of high risk characteristics at CT may have a prognostic value in term of cardiovascular events occurrence at follow-up even if the rate of events strictly linked to CCAA is low.

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.

Improvement of myocardial contractility with leadless endocardial single-lead atrial sensing ventricular pacing in patients with prolonged PQ interval.

Aim: Micra AV represents a leadless endocardial pacing system able to detect atrial contractions providing atrioventricular synchrony. A reduction of myocardial contractility may be detected in case of first-degree atrioventricular block (AVB). Materials & methods: In six patients with first-degree AVB (PQ interval ≥220 msec) was evaluated the left ventricle global longitudinal strain (LV GLS) by speckle tracking (ST) echocardiography during single-lead atrial sensing ventricular pacing (VDD) stimulation as compared with spontaneous rhythm (SR), 24-48 h after Micra AV implantation. Results: A statistically significant difference between the two modalities was observed (LV GLS during SR: -14.7% [interquartile range (IQR) 5.5], LV GLS during VDD pacing: -16.1% [IQR 5.2]; p value = 0.041). Conclusion: Our preliminary results suggest an improvement of myocardial contractility with VDD pacing as compared with SR.

What is this article about? The Micra AV is an electronic device placed in the heart chambers capable to supply the electrical activity of the heart. A reduction of cardiac contractility may be observed in patients with electrical disorders of the heart. What were the results? In six patients affected by electrical cardiac disorders, we observed an improvement of cardiac contractility using Micra AV as compared with the spontaneous electrical activity of the heart. What do the results of the study mean? The results of this study suggest that in patients carrying this electronic device should be preferred a specific modality of activation of the device as compared with the spontaneous electrical activity of the heart in order to improve the contractility of the cardiac walls.

Enhancing cardiovascular risk stratification: Radiomics of coronary plaque and perivascular adipose tissue - Current insights and future perspectives.

Radiomics, the quantitative extraction and mining of features from radiological images, has recently emerged as a promising source of non-invasive image-based cardiovascular biomarkers, potentially revolutionizing diagnostics and risk assessment. This review explores its application within coronary plaques and pericoronary adipose tissue, particularly focusing on plaque characterization and cardiac events prediction. By shedding light on the current state-of-the-art, achievements, and prospective avenues, this review contributes to a deeper understanding of the evolving landscape of radiomics in the context of coronary arteries. Finally, open challenges and existing gaps are emphasized to underscore the need for future efforts aimed at ensuring the robustness and reliability of radiomics studies, facilitating their clinical translation.

The role of computational methods in cardiovascular medicine: a narrative review.

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data with physical knowledge of the processes underlying the heart function. These models have been increasingly employed in clinical practice to understand pathological mechanisms and their progression, design medical devices, support clinicians in improving therapies. Hinging upon a long-year experience in cardiovascular modeling, we have recently constructed a computational multi-physics and multi-scale integrated model of the heart for the investigation of its physiological function, the analysis of pathological conditions, and to support clinicians in both diagnosis and treatment planning. This narrative review aims to systematically discuss the role that such model had in addressing specific clinical questions, and how further impact of computational models on clinical practice are envisaged. Methods: We developed computational models of the physical processes encompassed by the heart function (electrophysiology, electrical activation, force generation, mechanics, blood flow dynamics, valve dynamics, myocardial perfusion) and of their inherently strong coupling. To solve the equations of such models, we devised advanced numerical methods, implemented in a flexible and highly efficient software library. We also developed computational procedures for clinical data post-processing-like the reconstruction of the heart geometry and motion from diagnostic images-and for their integration into computational models. Key Content and Findings: Our integrated computational model of the heart function provides non-invasive measures of indicators characterizing the heart function and dysfunctions, and sheds light on its underlying processes and their coupling. Moreover, thanks to the close collaboration with several clinical partners, we addressed specific clinical questions on pathological conditions, such as arrhythmias, ventricular dyssynchrony, hypertrophic cardiomyopathy, degeneration of prosthetic valves, and the way coronavirus disease 2019 (COVID-19) infection may affect the cardiac function. In multiple cases, we were also able to provide quantitative indications for treatment. Conclusions: Computational models provide a quantitative and detailed tool to support clinicians in patient care, which can enhance the assessment of cardiac diseases, the prediction of the development of pathological conditions, and the planning of treatments and follow-up tests.

Atrial and Ventricular Strain Imaging Using CMR in the Prediction of Ventricular Arrhythmia in Patients with Myocarditis.

(1) Objective: Myocarditis can be associated with ventricular arrhythmia (VA), individual non-invasive risk stratification through cardiovascular magnetic resonance (CMR) is of great clinical significance. Our study aimed to explore whether left atrial (LA) and left ventricle (LV) myocardial strain serve as independent predictors of VA in patients with myocarditis. (2) Methods: This retrospective study evaluated CMR scans in 141 consecutive patients diagnosed with myocarditis based on the updated Lake Louise criteria (29 females, mean age 41 ± 20). The primary endpoint was VA; this encompassed ventricular fibrillation, sustained ventricular tachycardia, nonsustained ventricular tachycardia, and frequent premature ventricular complexes. LA and LV strain function were performed on conventional cine SSFP sequences. (3) Results: After a median follow-up time of 23 months (interquartile range (18-30)), 17 patients with acute myocarditis reached the primary endpoint. In the multivariable Cox regression analysis, LA reservoir (hazard ratio [HR] and 95% confidence interval [CI]: 0.93 [0.87-0.99], p = 0.02), LA booster (0.87 95% CI [0.76-0.99], p = 0.04), LV global longitudinal (1.26 95% CI [1.02-1.55], p = 0.03), circumferential (1.37 95% CI [1.08-1.73], p = 0.008), and radial strain (0.89 95% CI [0.80-0.98], p = 0.01) were all independent determinants of VA. Patients with LV global circumferential strain > -13.3% exhibited worse event-free survival compared to those with values ≤ -13.3% (p < 0.0001). (4) Conclusions: LA and LV strain mechanism on CMR are independently associated with VA events in patients with myocarditis, independent to LV ejection fraction, and late gadolinium enhancement location. Incorporating myocardial strain parameters into the management of myocarditis may improve risk stratification.

CAD-RADS scoring of coronary CT angiography with Multi-Axis Vision Transformer: A clinically-inspired deep learning pipeline.

BACKGROUND AND OBJECTIVE: The standard non-invasive imaging technique used to assess the severity and extent of Coronary Artery Disease (CAD) is Coronary Computed Tomography Angiography (CCTA). However, manual grading of each patient's CCTA according to the CAD-Reporting and Data System (CAD-RADS) scoring is time-consuming and operator-dependent, especially in borderline cases. This work proposes a fully automated, and visually explainable, deep learning pipeline to be used as a decision support system for the CAD screening procedure. The pipeline performs two classification tasks: firstly, identifying patients who require further clinical investigations and secondly, classifying patients into subgroups based on the degree of stenosis, according to commonly used CAD-RADS thresholds. METHODS: The pipeline pre-processes multiplanar projections of the coronary arteries, extracted from the original CCTAs, and classifies them using a fine-tuned Multi-Axis Vision Transformer architecture. With the aim of emulating the current clinical practice, the model is trained to assign a per-patient score by stacking the bi-dimensional longitudinal cross-sections of the three main coronary arteries along channel dimension. Furthermore, it generates visually interpretable maps to assess the reliability of the predictions. RESULTS: When run on a database of 1873 three-channel images of 253 patients collected at the Monzino Cardiology Center in Milan, the pipeline obtained an AUC of 0.87 and 0.93 for the two classification tasks, respectively. CONCLUSION: According to our knowledge, this is the first model trained to assign CAD-RADS scores learning solely from patient scores and not requiring finer imaging annotation steps that are not part of the clinical routine.

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.

Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario.

Carotid artery stenosis is a major cause of morbidity and mortality. The journey to understanding carotid disease has developed over time and radiology has a pivotal role in diagnosis, risk stratification and therapeutic management. This paper reviews the history of diagnostic imaging in carotid disease, its evolution towards its current applications in the clinical and research fields, and the potential of new technologies to aid clinicians in identifying the disease and tailoring medical and surgical treatment.

Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.

This work proposes a convolutional neural network (CNN) that utilizes different combinations of parametric images computed from cine cardiac magnetic resonance (CMR) images, to classify each slice for possible myocardial scar tissue presence. The CNN performance comparison in respect to expert interpretation of CMR with late gadolinium enhancement (LGE) images, used as ground truth (GT), was conducted on 206 patients (158 scar, 48 control) from Centro Cardiologico Monzino (Milan, Italy) at both slice- and patient-levels. Left ventricle dynamic features were extracted in non-enhanced cine images using parametric images based on both Fourier and monogenic signal analyses. The CNN, fed with cine images and Fourier-based parametric images, achieved an area under the ROC curve of 0.86 (accuracy 0.79, F1 0.81, sensitivity 0.9, specificity 0.65, and negative (NPV) and positive (PPV) predictive values 0.83 and 0.77, respectively), for individual slice classification. Remarkably, it exhibited 1.0 prediction accuracy (F1 0.98, sensitivity 1.0, specificity 0.9, NPV 1.0, and PPV 0.97) in patient classification as a control or pathologic. The proposed approach represents a first step towards scar detection in contrast-free CMR images. Patient-level results suggest its preliminary potential as a screening tool to guide decisions regarding LGE-CMR prescription, particularly in cases where indication is uncertain.

The Postoperative Paradoxical Septum (POPS): A Comprehensive Review on Physio-Pathological Mechanisms.

The interventricular septum (IVS) is a core myocardial structure involved in biventricular coupling and performance. Physiologically, during systole, it moves symmetrically toward the center of the left ventricle (LV) and opposite during diastole. Several pathological conditions produce a reversal or paradoxical septal motion, such as after uncomplicated cardiac surgery (CS). The postoperative paradoxical septum (POPS) was observed in a high rate of cases, representing a unicum in the panorama of paradoxical septa as it does not induce significant ventricular morpho-functional alterations nor negative clinical impact. Although it was previously considered a postoperative event, evidence suggests that it might also appear during surgery and gradually resolve over time. The mechanism behind this phenomenon is still debated. In this article, we will provide a comprehensive review of the various theories generated over the past fifty years to explain its pathological basis. Finally, we will attempt to give a heuristic interpretation of the biventricular postoperative motion pattern based on the switch of the ventricular anchor points.

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.