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Background Cardiovascular magnetic resonance (CMR) strain imaging is an established technique to quantify myocardial deformation. However, to what extent left ventricular (LV) systolic strain, and therefore LV mechanics, reflects classical hemodynamic parameters under various inotropic states is still not completely clear. Therefore, the aim of this study was to investigate the correlation of LV global strain parameters measured via CMR feature tracking (CMR-FT, based on conventional cine balanced steady state free precession (bSSFP) images) with hemodynamic parameters such as cardiac index (CI), cardiac power output (CPO) and end-systolic elastance (Ees) under various inotropic states. Methods  Ten anaesthetized, healthy Landrace swine were acutely instrumented closed-chest and transported to the CMR facility for measurements. After baseline measurements, two steps were performed: (1) dobutamine-stress (Dobutamine) and (2) verapamil-induced cardiovascular depression (Verapamil). During each protocol, CMR images were acquired in the short axisand apical 2Ch, 3Ch and 4Ch views. MEDIS software was utilized to analyze global longitudinal (GLS), global circumferential (GCS), and global radial strain (GRS). Results Dobutamine significantly increased heart rate, CI, CPO and Ees, while Verapamil decreased them. Absolute values of GLS, GCS and GRS accordingly increased during Dobutamine infusion, while GLS and GCS decreased during Verapamil. Linear regression analysis showed a moderate correlation between GLS, GCS and LV hemodynamic parameters, while GRS correlated poorly. Indexing global strain parameters for indirect measures of afterload, such as mean aortic pressure or wall stress, significantly improved these correlations, with GLS indexed for wall stress reflecting LV contractility as the clinically widespread LV ejection fraction. Conclusion GLS and GCS correlate accordingly with LV hemodynamics under various inotropic states in swine. Indexing strain parameters for indirect measures of afterload substantially improves this correlation, with GLS being as good as LV ejection fraction in reflecting LV contractility. CMR-FT-strain imaging may be a quick and promising tool to characterize LV hemodynamics in patients with varying degrees of LV dysfunction.

Heart failure (HF) patients represent one of the most prevalent as well as one of the most fragile population encountered in the cardiology and internal medicine departments nowadays. Estimated to account for around 26 million people worldwide, diagnosed patients present a poor prognosis and quality of life with a clinical history accompanied by repeated hospital admissions caused by an exacerbation of their chronic condition. The frequent hospitalizations and the extended hospital stays mean an extremely high economic burden for healthcare institutions. Meanwhile, the number of chronically diseased and elderly patients is continuously rising, and a lack of specialized physicians is evident. To cope with this health emergency, more efficient strategies for patient management, more accurate diagnostic tools, and more efficient preventive plans are needed. In recent years, telemonitoring has been introduced as the potential answer to solve such needs. Different methodologies and devices have been progressively investigated for effective home monitoring of cardiologic patients. Invasive hemodynamic devices, such as CardioMEMS™, have been demonstrated to be reducing hospitalizations and mortality, but their use is however restricted to limited cases. The role of external non-invasive devices for remote patient monitoring, instead, is yet to be clarified. In this review, we summarized the most relevant studies and devices that, by utilizing non-invasive telemonitoring, demonstrated whether beneficial effects in the management of HF patients were effective.

Due to an increasingly aging population, Alzheimer disease (AD) represents a crucial issue for the healthcare system because of its widespread prevalence and the burden of its care needs. Several hypotheses on AD pathogenesis have been proposed and current therapeutical strategies have shown limited effectiveness. In the last decade, more evidence has supported a role for neuroinflammation and immune system dysregulation in AD. It remains unclear whether astrocytes, microglia and immune cells influence disease onset, progression or both. Amyloid-β peptides that aggregate extracellularly in the typical neuritic plaques generate a constant inflammatory environment. This causes a prolonged activation of microglial and astroglial cells that potentiate neuronal damage and provoke the alteration of the blood brain barrier (BBB), damaging the permeability of blood vessels. Recent data support the role of the BBB as a link between neuroinflammation, the immune system and AD. Hence, a thorough investigation of the neuroinflammatory and immune system pathways that impact neurodegeneration and novel exciting findings such as microglia-derived microvesicles, inflammasomes and signalosomes will ultimately enhance our understanding of the pathological process. Eventually, we should proceed with caution in defining a causal or consequential role of neuroinflammation in AD, but rather focus on identifying its exact pathological contribution.

4D-flow MRI is a promising technique for assessing vessel hemodynamics. However, its utilization is currently limited by the lack of reference values, particularly for pulmonary vessels. In this work, we have analysed flow and velocity in the pulmonary trunk (PT), left and right pulmonary arteries (LPA and RPA, respectively) in Landrace pigs at both rest and stress through the software MEVISFlow. Nine healthy Landrace pigs were acutely instrumented closed-chest and transported to the CMR facility for evaluation. After rest measurements, dobutamine was administered to achieve a 25% increase in heart rate compared to rest. 4D-flow MRI images have been analysed through MEVISFlow by two independent observers. Inter- and intra-observer reproducibility was quantified using intraclass correlation coefficient. A significant difference between rest and stress regarding flow and velocity in all the pulmonary vessels was observed. Mean flow increased 55% in PT, 75% in LPA and 40% in RPA. Mean peak velocity increased 55% in PT, 75% in LPA and 66% in RPA. A good-to-excellent reproducibility was observed in rest and stress for flow measurements in all three arteries. An excellent reproducibility for velocity was found in PT at rest and stress, a good one for LPA and RPA at rest, while poor reproducibility was found at stress. The current study showed that pulmonary flow and velocity assessed through 4D-flow MRI follow the physiological alterations during cardiac cycle and after stress induced by dobutamine. A clinical translation to assess pulmonary diseases with 4D-flow MRI under stress conditions needs investigation.

Cardiovascular magnetic resonance feature tracking (CMR-FT) is a novel technique for non-invasive assessment of myocardial motion and deformation. Although CMR-FT is standardized in humans, literature on comparative analysis from animal models is scarce. In this study, we measured the reproducibility of global strain under various inotropic states and the sample size needed to test its relative changes in pigs. Ten anesthetized healthy Landrace pigs were investigated. After baseline (BL), two further steps were performed: (I) dobutamine-induced hyper-contractility (Dob) and (II) verapamil-induced hypocontractility (Ver). Global longitudinal (GLS), circumferential (GCS) and radial strain (GRS) were assessed. This study shows a good to excellent inter- and intra-observer reproducibility of CMR-FT in pigs under various inotropic states. The highest inter-observer reproducibility was observed for GLS at both BL (ICC 0.88) and Ver (ICC 0.79). According to the sample size calculation for GLS, a small number of animals could be used for future trials.

Right ventricular biopsy represents the gold standard for the assessment of myocardial fibrosis and collagen content. This invasive technique, however, is accompanied by perioperative complications and poor reproducibility. Extracellular volume (ECV) measured through cardiovascular magnetic resonance (CMR) has emerged as a valid surrogate method to assess fibrosis non-invasively. Nonetheless, ECV provides an overestimation of collagen concentration since it also considers interstitial space. Our study aims to investigate the feasibility of estimating total collagen volume (TCV) through CMR by comparing it with the TCV measured at histology. Seven healthy Landrace pigs were acutely instrumented closed-chest and transported to the MRI facility for measurements. For each protocol, CMR imaging at 3T was acquired. MEDIS software was used to analyze T1 mapping and ECV for both the left ventricular myocardium (LVmyo) and left ventricular septum (LVseptum). ECV was then used to estimate TCVCMR at LVmyo and LVseptum following previously published formulas. Tissues were prepared following an established protocol and stained with picrosirius red to analyze the TCVhisto in LVmyo and LVseptum. TCV measured at LVmyo and LVseptum with both histology (8 ± 5 ml and 7 ± 3 ml, respectively) and T1-Mapping (9 ± 5 ml and 8 ± 6 ml, respectively) did not show any regional differences. TCVhisto and TCVCMR showed a good level of data agreement by Bland–Altman analysis. Estimation of TCV through CMR may be a promising way to non-invasively assess myocardial collagen content and may be useful to track disease progression or treatment response.

COVID-19 is strongly influenced by age and comorbidities. Acute kidney injury (AKI) is a frequent finding in COVID-19 patients and seems to be associated to mortality and severity. On the other hand, the role of kidney dysfunction in COVID-19 is still debated. We performed a retrospective study in a cohort of 174 hospitalized COVID-19 patients in Italy from March 3rd to May 21st 2020, to investigate the role of kidney dysfunction on COVID-19 severity and mortality. Moreover, we examined in depth the relationship between kidney function, age, and progression of COVID-19, also using different equations to estimate the glomerular filtration rate (GFR). We performed logistic regressions, while a predictive analysis was made through a machine learning approach. AKI and death occurred respectively in 10.2% and 19.5%, in our population. The major risk factors for mortality in our cohort were age [adjusted HR, 6.2; 95% confidence interval (CI) 1.8–21.4] and AKI [3.36 (1.44–7.87)], while, in these relationships, GFR at baseline mitigated the role of age. The occurrence of AKI was influenced by baseline kidney function, D-dimer, procalcitonin and hypertension. Our predictive analysis for AKI and mortality reached an accuracy of ≥ 94% and ≥ 91%, respectively. Our study scales down the role of kidney function impairment on hospital admission , especially in elderly patients. BIS-1 formula demonstrated a worse performance to predict the outcomes in COVID-19 patients when compared with MDRD and CKD-EPI.

Patients referred to the cath-lab are an increasingly elderly population. Thermodilution (TD, gold standard) and the estimated Fick method (eFM) are interchangeably used in the clinical routine to measure cardiac output (CO). However, their correlation in an elderly cohort of cardiac patients has not been tested so far. A single, clinically-indicated right heart catheterization was performed on each patient with CO estimated by eFM and TD in 155 consecutive patients (75.1±6.8 years, 57.7% male) between April 2015 and August 2017. Whole Body Oxygen Consumption (VO2) was assumed by applying the formulas of LaFarge (LaF), Dehmer (De) and Bergstra (Be). CO was indexed to body surface area (Cardiac Index, CI). CI-TD showed an overall moderate correlation to CI-eFM as assessed by LaF, De or Be (r2 = 0.53, r2 = 0.54, r2 = 0.57, all p < .001, respectively) with large limits of agreement (-0.64 to 1.09, -1.07 to 0.77, -1.38 to 0.53 l/m2/min, respectively). The mean difference of CI between methods was 0.22, -0.15 and -0.42 (all p<0.001 for difference to TD), respectively. A rate of error ≥20% occurred with the equations by LaF, De or Be in 40.6%, 26.5% and 36.1% of patients, respectively. A CI <2.2 l/m2min was present in 42.6% of patients according to TD and in 60.0%, 31.0% and in 16.1% of patients according to eFM by the formulas of LaF, De or Be. Although CI-eFM shows an overall reasonable correlation with CI-TD, the predictive value in a single patient is low. CI-eFM cannot replace CI-TD in elderly patients.

Pressure–volume (PV) analysis is the most comprehensive way to describe cardiac function, giving insights into cardiac mechanics and energetics. However, PV analysis still remains a highly invasive and time-consuming method, preventing it from integration into clinical practice. Most of the echocardiographic parameters currently used in the clinical routine to characterize left ventricular (LV) systolic function, such as LV ejection fraction and LV global longitudinal strain, do not take the pressure developed within the LV into account and therefore fall too short in describing LV function as a hydraulic pump. Recently, LV pressure-strain analysis has been introduced as a new technique to assess myocardial work in a non-invasive fashion. This new method showed new insights in comparison to invasive measurements and was validated in different cardiac pathologies, e.g., for the detection of coronary artery disease, cardiac resynchronization therapy (CRT)-response prediction, and different forms of heart failure. Non-invasively assessed myocardial work may play a major role in guiding therapies and estimating prognosis. However, its incremental prognostic validity in comparison to common echocardiographic parameters remains unclear. This review aims to provide an overview of pressure-strain analysis, including its current application in the clinical arena, as well as potential fields of exploitation.

Heart failure (HF) is defined as the inability of the heart to meet body oxygen demand requiring an elevation in left ventricular filling pressures (LVP) to compensate. LVP increase can be assessed in the cardiac catheterization laboratory, but this procedure is invasive and time-consuming to the extent that physicians rather rely on non-invasive diagnostic tools. In this work, we assess the feasibility to develop a novel machine-learning (ML) approach to predict clinically relevant LVP indices. Synchronized invasive (pressure–volume tracings) and non-invasive signals (ECG, pulse oximetry, and cardiac sounds) were collected from anesthetized, closed-chest Göttingen minipigs. Animals were either healthy or had HF with reduced ejection fraction and circa 500 heartbeats were included in the analysis for each animal. The ML algorithm showed excellent prediction of LVP indices estimating, for instance, the end-diastolic pressure with a R 2 of 0.955. This novel ML algorithm could assist clinicians in the care of HF patients. Graphical Abstract