Computational modeling of bicuspid aortopathy: Towards personalized risk strategies.

This paper describes current advances on the application of in-silico for the understanding of bicuspid aortopathy and future perspectives of this technology on routine clinical care. This includes the impact that artificial intelligence can provide to develop computer-based clinical decision support system and that wearable sensors can offer to remotely monitor high-risk bicuspid aortic valve (BAV) patients. First, we discussed the benefit of computational modeling by providing tangible examples of in-silico software products based on computational fluid-dynamic (CFD) and finite-element method (FEM) that are currently transforming the way we diagnose and treat cardiovascular diseases. Then, we presented recent findings on computational hemodynamic and structural mechanics of BAV to highlight the potentiality of patient-specific metrics (not-based on aortic size) to support the clinical-decision making process of BAV-associated aneurysms. Examples of BAV-related personalized healthcare solutions are illustrated.

Identification of circumferential regional heterogeneity of ascending thoracic aneurysmal aorta by biaxial mechanical testing.

Ascending thoracic aortic aneurysm (ATAA) in patients with bicuspid aortic valve (BAV) can present an asymmetrical aortic dilatation compared with patients with tricuspid aortic valve (TAV). This pattern of aneurysm dilatation led us to hypothesize that biomechanical differences likely induced by regional heterogeneity of material properties can underlie the observed asymmetric enlargement discrepancies between BAV ATAA and TAV ATAA. This study aimed to characterize the mechanical properties and associated aortic tissue stiffness changes along the circumferential direction of aortic rings collected from surgically-repaired patients with ATAA. Biaxial material testing was performed on tissue specimens extrapolated from all aortic quadrants (i.e. anterior, posterior, major and minor curvature of the aorta), and then the tissue stiffness was quantified at both physiological and supra-physiological stress levels (i.e. 142 kPa and 242 kPa, respectively). Tissue stiffness revealed that the major curvature of BAV ATAA is statistically less stiff than the anterior quadrant (276.6 ±â€¯137.1 kPa for BAV ATAA and 830.1 ±â€¯557.1 kPa for BAV ATAA, p = .024, at 142 kPa) and to that of major curvature of TAV ATAA (276.6 ±â€¯137.0 kPa for BAV ATAA and 733.2 ±â€¯391.1 kPa for TAV ATAA, p = .001, at 142 kPa), suggesting local weakening of bicuspid aortic wall. Multiphoton imaging revealed local changes on elastic fiber networks. The recovered material parameters for the Fung-type constitutive model are crucial for reliable stress predictions while the information on regional tissue stiffness changes are fundamental to develop risk stratification strategies not based on aortic size.

Patterns of ascending aortic dilatation and predictors of surgical replacement of the aorta: A comparison of bicuspid and tricuspid aortic valve patients over eight years of follow-up.

BACKGROUND: Predictors of thoracic aorta growth and early cardiac surgery in patients with bicuspid aortic valve are undefined. Our aim was to identify predictors of ascending aorta dilatation and cardiac surgery in patients with bicuspid aortic valve (BAV). METHODS: Forty-one patients with BAV were compared with 165 patients with tricuspid aortic valve (TAV). All patients had LV EF > 50%, normal LV dimensions, and similar degree of aortic root or ascending aorta dilatation at enrollment. Patients with more than mild aortic stenosis or regurgitation were excluded. A CT-scan was available on 76% of the population, and an echocardiogram was repeated every year for a median time of 4 years (range: 2 to 8 years). Patterns of aortic expansion in BAV and TAV groups were analyzed by a mixed-effects longitudinal linear model. In the time-to-event analysis, the primary end point was elective or emergent surgery for aorta replacement. RESULTS: BAV patients were younger, while the TAV group had greater LV wall thickness, arterial hypertension, and dyslipidemia than BAV patients. Growth rate was 0.46 ±â€¯0.04 mm/year, similar in BAV and TAV groups (p = 0.70). Predictors of cardiac surgery were aorta dimensions at baseline (HR 1.23, p = 0.01), severe aortic regurgitation developed during follow-up (HR 3.49, p 0.04), family history of aortic aneurysm (HR 4.16, p 1.73), and history of STEMI (HR 3.64, p < 0.001). CONCLUSIONS: Classic baseline risk factors were more commonly observed in TAV aortopathy compared with BAV aortopathy. However, it is reassuring that, though diagnosed with aneurysm on average 10 years earlier and in the absence of arterial hypertension, BAV patients had a relatively low growth rate, similar to patients with a tricuspid valve. Irrespective of aortic valve morphology, patients with a family history of aortic aneurysm, history of coronary artery disease, and those who developed severe aortic regurgitation at follow-up, had the highest chances of being referred for surgery.

NT-ProBNP and hsTnI: A Multistate Survival Analysis in Outpatients with Reduced Left-Ventricular Ejection Fraction.

Heart failure (HF) with reduced ejection fraction (HFrEF) has a well-known epidemic relevance in western countries. It affects up to 1-2% of patients > 60 years and reaches a prevalence of 12% in octogenarian patients. The role of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitive troponin I (hsTnI) in risk stratifying HFrEF patients has been established; at present, evidence is exclusively based on one-time assessments, and the prognostic usefulness of serial biochemical assessments in this population still remains to be determined. We prospectively recruited 226 patients with chronic HFrEF, who were all referred to the Outpatient Clinic of our institution from November 2011 through September 2014. Recruited patients underwent full clinical evaluation with complete history taking and physical examination as well as ECG, biochemical assessment, and standard 2D and Doppler flow echocardiography at the first visit, and then again at each visit during the follow-up, repeated every 6 months. During the follow-up period, cardiovascular (CV) death, which occurred in 16 patients, was not statistically correlated with gender (p = 0.088) or age (p = 0.1636); however, baseline serum levels of NT-proBNP, which were 3 times higher in deceased patients, were significantly related to this clinical event (p = 0.001). We found that NT-proBNP represents a strong and independent predictor of CV outcome; serum levels of hsTnI, which are significantly related to an increased risk of hospitalization, cannot properly predict the relative risk of CV mortality. Our study validates, eventually, the multimarker strategy, which reflects the complexity of the HF pathophysiology.

Risk Factors Associated With Peripheral Neuropathy in Heart Failure Patients Candidates for Transplantation.

INTRODUCTION: Peripheral neuropathy can affect patients with heart failure, though its prevalence is unknown. After heart transplantation, it can influence the postoperative course and quality of life, but screening for neuromuscular disease is not routinely performed. OBJECTIVE: The aim of this study was to identify the factors associated with neuropathy in a population of patients with heart failure who are candidates for heart transplantation. STUDY DESIGN: Data regarding patients' clinical history, including recent hospitalizations, were collected. All patients underwent a complete neurological examination and a neurophysiological protocol including nerve conduction studies and concentric needle electromyography. RESULTS: Thirty-two patients were included in the study, and neuropathy was diagnosed in 10 (31.3%). Neuropathy was associated with the number of admissions ( P = .023; odds ratio [OR]: 1.96) and the total number of days of hospitalization in the year prior to inclusion in the study ( P = .010; OR: 1.03). The majority of hospitalizations occurred in the step-down unit (85%), with acute heart failure the leading cause of admission (42%). CONCLUSIONS: This study shows that neuropathy is frequent in patients with advanced heart failure and that hospitalization for cardiac care, also in the absence of intensive care, is a marker of high risk of neurologic damage. These data can help physicians in selecting and managing candidates for transplantation and can guide decisions on the best immunosuppressive regimen or rehabilitation strategy.

MicroRNA-30d and -483-3p for bi-ventricular remodelling and miR-126-3p for pulmonary hypertension in advanced heart failure.

AIMS: MicroRNAs play a role in pathogenic mechanisms leading to heart failure. We measured a panel of 754 miRNAs in the myocardial tissue and in the serum of patients with heart failure with reduced ejection fraction due to dilatative idiopathic cardiomyopathy (DCM, N = 10) or ischaemic cardiomyopathy (N = 3), referred to left ventricular assist device implant. We aim to identify circulating miRNAs with high tissue co-expression, significantly associated to echocardiographic and haemodynamic measures. METHODS AND RESULTS: We have measured a panel of 754 miRNAs in the myocardial tissue [left ventricular (LV) apex] and in the serum obtained at the same time in a well selected study population of end-stage heart failure with reduced ejection fraction due to either DCM or ischaemic cardiomyopathy, referred to continuous flow left ventricular assist device implant. We observed moderate agreement for miR-30d, miR-126-3p, and miR-483-3p. MiR-30d was correlated to LV systolic as well as diastolic volumes (r = 0.78, P = 0.001 and r = 0.80, P = 0.005, respectively), while miR-126-3p was associated to mPAP and PCWP (r = -0.79, P = 0.007 and r = -0.80, P = 0.005, respectively). Finally, serum miR-483-3p had an association with right ventricular end diastolic diameter (r = -0.73, P = 0.02) and central venous pressure (CVP) (r - 0.68 p 0.03). CONCLUSIONS: In patients with DCM, few miRNAs are co-expressed in serum and tissue: They are related to LV remodelling (miR-30d), post-capillary pulmonary artery pressure (miR-126-3p), and right ventricular remodelling/filling pressures (miR-483-3p). Further studies are needed to confirm their role in diagnosis, prognosis or as therapeutic targets in heart failure with reduced ejection fraction.

On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) is a minimally invasive procedure used to treat patients with severe aortic valve stenosis. However, there is limited knowledge on the material properties of the aortic root in TAVI patients, and this can impact the credibility of computer simulations. This study aimed to develop a non-invasive inverse approach for estimating reliable material constituents for the aortic root and calcified valve leaflets in patients undergoing TAVI. METHODS: The identification of material parameters is based on the simultaneous minimization of two cost functions, which define the difference between model predictions and cardiac-gated CT measurements of the aortic wall and valve orifice area. Validation of the inverse analysis output was performed comparing the numerical predictions with actual CT shapes and post-TAVI measures of implanted device diameter. RESULTS: A good agreement of the peak systolic shape of the aortic wall was found between simulations and imaging, with similarity index in the range in the range of 83.7% to 91.5% for n.20 patients. Not any statistical difference was observed between predictions and CT measures of orifice area for the stenotic aortic valve. After TAVI simulations, the measurements of SAPIEN 3 Ultra (S3) device diameter were in agreement with those from post-TAVI angio-CT imaging. A sensitivity analysis demonstrated a modest impact on the S3 diameters when altering the elastic material property of the aortic wall in the range of inverse analysis solution. CONCLUSIONS: Overall, this study demonstrates the feasibility and potential benefits of using non-invasive imaging techniques and computational modeling to estimate material properties in patients undergoing TAVI.

Cognitive outcomes in patients treated with neuromuscular electrical stimulation after coronary artery bypass grafting.

Objective: Mechanisms of neurocognitive injury as post-operative sequelae of coronary artery bypass grafting (CABG) are not understood. The systemic inflammatory response to surgical stress causes skeletal muscle impairment, and this is also worsened by immobility. Since evidence supports a link between muscle vitality and neuroprotection, there is a need to understand the mechanisms by which promotion of muscle activity counteracts the deleterious effects of surgery on long-term cognition. Methods: We performed a clinical trial to test the hypothesis that adding neuromuscular electrical stimulation (NMES) to standard rehabilitation care in post-CABG patients promotes the maintenance of skeletal muscle strength and the expression of circulating neuroprotective myokines. Results: We did not find higher serum levels of neuroprotective myokines, except for interleukin-6, nor better long-term cognitive performance in our intervention group. However, a greater increase in functional connectivity at brain magnetic resonance was seen between seed regions within the default mode, frontoparietal, salience, and sensorimotor networks in the NMES group. Regardless of the treatment protocol, patients with a Klotho increase 3 months after hospital discharge compared to baseline Klotho values showed better scores in delayed memory tests. Significance: We confirm the potential neuroprotective effect of Klotho in a clinical setting and for the first time post-CABG.

Rationale and design of the CV-PREVITAL study: an Italian multiple cohort randomised controlled trial investigating innovative digital strategies in primary cardiovascular prevention.

INTRODUCTION: Prevention of cardiovascular disease (CVD) is of key importance in reducing morbidity, disability and mortality worldwide. Observational studies suggest that digital health interventions can be an effective strategy to reduce cardiovascular (CV) risk. However, evidence from large randomised clinical trials is lacking. METHODS AND ANALYSIS: The CV-PREVITAL study is a multicentre, prospective, randomised, controlled, open-label interventional trial designed to compare the effectiveness of an educational and motivational mobile health (mHealth) intervention versus usual care in reducing CV risk. The intervention aims at improving diet, physical activity, sleep quality, psycho-behavioural aspects, as well as promoting smoking cessation and adherence to pharmacological treatment for CV risk factors. The trial aims to enrol approximately 80 000 subjects without overt CVDs referring to general practitioners' offices, community pharmacies or clinics of Scientific Institute for Research, Hospitalization and Health Care (Italian acronym IRCCS) affiliated with the Italian Cardiology Network. All participants are evaluated at baseline and after 12 months to assess the effectiveness of the intervention on short-term endpoints, namely improvement in CV risk score and reduction of major CV risk factors. Beyond the funded life of the study, a long-term (7 years) follow-up is also planned to assess the effectiveness of the intervention on the incidence of major adverse CV events. A series of ancillary studies designed to evaluate the effect of the mHealth intervention on additional risk biomarkers are also performed. ETHICS AND DISSEMINATION: This study received ethics approval from the ethics committee of the coordinating centre (Monzino Cardiology Center; R1256/20-CCM 1319) and from all other relevant IRBs and ethics committees. Findings are disseminated through scientific meetings and peer-reviewed journals and via social media. Partners are informed about the study's course and findings through regular meetings. TRIAL REGISTRATION NUMBER: NCT05339841.

Transcatheter Heart Valve Implantation in Bicuspid Patients with Self-Expanding Device.

Bicuspid aortic valve (BAV) patients are conventionally not treated by transcathether aortic valve implantation (TAVI) because of anatomic constraint with unfavorable outcome. Patient-specific numerical simulation of TAVI in BAV may predict important clinical insights to assess the conformability of the transcathether heart valves (THV) implanted on the aortic root of members of this challenging patient population. We aimed to develop a computational approach and virtually simulate TAVI in a group of n.6 stenotic BAV patients using the self-expanding Evolut Pro THV. Specifically, the structural mechanics were evaluated by a finite-element model to estimate the deformed THV configuration in the oval bicuspid anatomy. Then, a fluid-solid interaction analysis based on the smoothed-particle hydrodynamics (SPH) technique was adopted to quantify the blood-flow patterns as well as the regions at high risk of paravalvular leakage (PVL). Simulations demonstrated a slight asymmetric and elliptical expansion of the THV stent frame in the BAV anatomy. The contact pressure between the luminal aortic root surface and the THV stent frame was determined to quantify the device anchoring force at the level of the aortic annulus and mid-ascending aorta. At late diastole, PVL was found in the gap between the aortic wall and THV stent frame. Though the modeling framework was not validated by clinical data, this study could be considered a further step towards the use of numerical simulations for the assessment of TAVI in BAV, aiming at understanding patients not suitable for device implantation on an anatomic basis.

[Quality of life and psychological distress in a cohort of patients with left ventricular assist device]. / Qualità della vita e disagio psicologico in un gruppo di pazienti con dispositivo di assistenza ventricolare sinistra.

BACKGROUND: Left ventricular assist devices (LVAD) are the most common mechanical circulatory support for patients with advanced heart failure, and can be used either as a temporary or permanent therapy. Normally, LVAD carriers show psychological distress related to the difficulties in adapting to their new clinical condition. METHODS: This retrospective study aimed to analyze the quality of life of 21 patients after LVAD implantation and follow-up in a dedicated psychology outpatient clinic. The Short Form Health Survey (SF-36) was used to assess the quality of life, and the Hospital Anxiety and Depression Scale (HADS) to measure anxiety and depression levels. These constructs were examined according to the time of implant and their age, with correlational analyses. RESULTS: Outcomes seem to affect the quality of life of our population when compared with regulatory data, in terms of both physical health and mental health. Patient age was inversely related to the mental health index (Pearson's correlation coefficient -0.48, p<0.05) and two subscales, i.e. "vitality" (Pearson's correlation coefficient -0.60, p<0.05) and "mental health" (Pearson's correlation coefficient -0.44, p<0.05). The most critical areas included physical pain and social limitations. The overall incidence of anxiety and depression was within normal limits according to the HADS test: LVAD patients supported for less than 1 year showed a lower incidence of anxiety compared with LVAD carriers supported for more than 1 year, while the incidence of depression was higher compared with LVAD carriers supported for more than 1 year. CONCLUSIONS: LVAD negatively impact physical and mental health, 'especially in older people; the scores obtained at SF-36, both for the physical health index and the mental health index, show lower average values than the regulatory standard. In addition, the depression levels vary based on the time elapsed from the date of implantation confirming the need for continuous monitoring of patients during treatment to prevent an increase of this index over the years. This patient subset requires continuing support and careful psychological monitoring, from preliminary assessment to LVAD implant, and later over the entire therapeutic process.

Patient-Specific Analysis of Ascending Thoracic Aortic Aneurysm with the Living Heart Human Model.

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs.

Deep learning approach for the segmentation of aneurysmal ascending aorta.

Diagnosis of ascending thoracic aortic aneurysm (ATAA) is based on the measurement of the maximum aortic diameter, but size is not a good predictor of the risk of adverse events. There is growing interest in the development of novel image-derived risk strategies to improve patient risk management towards a highly individualized level. In this study, the feasibility and efficacy of deep learning for the automatic segmentation of ATAAs was investigated using UNet, ENet, and ERFNet techniques. Specifically, CT angiography done on 72 patients with ATAAs and different valve morphology (i.e., tricuspid aortic valve, TAV, and bicuspid aortic valve, BAV) were semi-automatically segmented with Mimics software (Materialize NV, Leuven, Belgium), and then used for training of the tested deep learning models. The segmentation performance in terms of accuracy and time inference were compared using several parameters. All deep learning models reported a dice score higher than 88%, suggesting a good agreement between predicted and manual ATAA segmentation. We found that the ENet and UNet are more accurate than ERFNet, with the ENet much faster than UNet. This study demonstrated that deep learning models can rapidly segment and quantify the 3D geometry of ATAAs with high accuracy, thereby facilitating the expansion into clinical workflow of personalized approach to the management of patients with ATAAs.

Simulation of left ventricular outflow tract (LVOT) obstruction in transcatheter mitral valve-in-ring replacement.

Left ventricular outflow tract (LVOT) obstruction is a feared complication of transcatheter mitral valve replacement (TMVR). This procedure leads to an elongation of LVOT in the left ventricle (namely, the neoLVOT), ultimately portending hemodynamic impairment and death. This study sought to understand the biomechanical implications of LVOT obstruction in two patients who underwent TMVR as an "off-label" application of the Edwards SAPIEN 3 (S3) Ultra transcatheter heart valve (THV). A computational framework of TMVR was developed to assess the neoLVOT area and quantify the sub-aortic flow structure. We observed that the annuloplasty ring serves as the key anchor zone of S3 Ultra THV. A good agreement was found between the numerically-predicted and CT-imaging measurements of neoLVOT area, with differences less than 10% in both patients. The pressure drop across the neoLVOT did not determine hemodynamic impairment in both patients. Quantification of structural and hemodynamic variables by computational modeling may facilitate more accurate predictions of the LVOT obstruction in TMVR, particularly for patients which are considered to have a borderline risk of obstruction.

Statistical Shape Analysis of Ascending Thoracic Aortic Aneurysm: Correlation between Shape and Biomechanical Descriptors.

An ascending thoracic aortic aneurysm (ATAA) is a heterogeneous disease showing different patterns of aortic dilatation and valve morphologies, each with distinct clinical course. This study aimed to explore the aortic morphology and the associations between shape and function in a population of ATAA, while further assessing novel risk models of aortic surgery not based on aortic size. Shape variability of n = 106 patients with ATAA and different valve morphologies (i.e., bicuspid versus tricuspid aortic valve) was estimated by statistical shape analysis (SSA) to compute a mean aortic shape and its deformation. Once the computational atlas was built, principal component analysis (PCA) allowed to reduce the complex ATAA anatomy to a few shape modes, which were correlated to shear stress and aortic strain, as determined by computational analysis. Findings demonstrated that shape modes are associated to specific morphological features of aneurysmal aorta as the vessel tortuosity and local bulging of the ATAA. A predictive model, built with principal shape modes of the ATAA wall, achieved better performance in stratifying surgically operated ATAAs versus monitored ATAAs, with respect to a baseline model using the maximum aortic diameter. Using current imaging resources, this study demonstrated the potential of SSA to investigate the association between shape and function in ATAAs, with the goal of developing a personalized approach for the treatment of the severity of aneurysmal aorta.

Echocardiography to estimate high filling pressure in patients with heart failure and reduced ejection fraction.

AIMS: Echocardiographic assessment of left ventricular filling pressures is performed using a multi-parametric algorithm. Unselected sample of patients with heart failure with reduced ejection fraction (HFrEF) patients may demonstrate an indeterminate status of diastolic indices making interpretation challenging. We sought to test improvement in the diagnostic accuracy of standard and strain echocardiography of the left ventricle and left atrium (LA) to estimate a pulmonary capillary wedge pressure (PCWP) > 15 mmHg in patients with HFrEF. METHODS AND RESULTS: Out of 82 consecutive patients, 78 patients were included in the final analysis and right heat catheterization, and echocardiogram was performed simultaneously. According to the univariable analysis, E wave velocity, the ratio between E-wave/A-wave (E/A, area under the curve [AUC] = 0.81, respectively), isovolumic relaxation time (AUC = 0.83), pulmonary vein D wave (AUC = 0.84), pulmonary vein S/D Ratio (AUC = 0.85), early pulmonary regurgitation velocity (AUC = 0.80), and accelerationa time at right ventricular out-flow tract (RVOT AT, AUC = 0.84) identified with the highest accuracy PCWP > 15 mmHg. They were all tested in multivariate analysis, and they were not independently correlated with PCWP. Tricuspid regurgitation (TR) velocity was measurement with the highest predictive value in identifying PCWP > 15 mmHg (AUC = 0.89), compared with other established parameters such as the ratio between e-wave velocity divided by mitral annular e' velocity (E/e'), deceleration time, or LA indexed volume (LAVi), which all reached a lower accuracy level (AUC = 0.75; 0.78; 0.76). Among strain measures, global longitudinal strain in four chamber view (GLS 4ch), the ratio between e-wave velocity divided by mitral annular e' strain rate (E/e'sr), and LA longitudinal strain at the reservoir phase were helpful in estimating elevated PCWP (AUC = 0.77; 0.76; 0.75). According to multivariable analysis, the following two models had the greatest accuracy in detecting PCWP > 15 mmHg: (i) TR velocity, LAVi, and E wave velocity (receiver operating characteristic [ROC]-AUC = 0.98), (ii) AT RVOT, LAVi and GLS 4ch (ROC-AUC = 0.96). Neither E/A (ROC-AUC = 0.81) nor E/e' (ROC-AUC = 0.75) was an independent predictor when included in the model. The two MODELS were applicable to the entire population and demonstrated better agreement with the invasive reference (91% and 88%) than the guidelines algorithm (77%) regardless of the type of rhythm. CONCLUSIONS: Our suggested echocardiographic approach could be used to potentially reduce the frequency of "doubtful" classification and increase the accuracy in predicting elevated left ventricular filling pressure leading to a decrease in the number of invasive assessment made by right heart catheterization.

Shear Stress and Aortic Strain Associations With Biomarkers of Ascending Thoracic Aortic Aneurysm.

BACKGROUND: This study aims to investigate the association of wall shear stress (WSS) and aortic strain with circulating biomarkers including matrix metalloproteinases (MMP), tissue inhibitors of metalloproteinase (TIMP), and exosomal level of microRNA (miRNA) in ascending aortic aneurysms of patients with bicuspid or tricuspid aortic valve. METHODS: A total of 76 variables from 125 patients with ascending aortic aneurysms were collected from (1) blood plasma to measure plasma levels of miRNAs and protein activity; (2) computational flow analysis to estimate peak systolic WSS and time-average WSS (TAWSS); and (3) imaging analysis of computed tomography angiography to determine aortic wall strain. Principal component analysis followed by logistic regression allowed the development of a predictive model of aortic surgery by combining biomechanical descriptors and biomarkers. RESULTS: The protein activity of MMP-1, TIMP-1, and MMP-2 was positively correlated to the systolic WSS and TAWSS observed in the proximal ascending aorta (eg, R = 0.52, P < .001, for MMP-1 with TAWSS) where local maxima of WSS were found. For bicuspid patients, aortic wall strain was associated with miR-26a (R = 0.55, P = .041) and miR-320a (R = 0.69, P < .001), which shows a significant difference between bicuspid and tricuspid patients. Receiver-operating characteristics curves revealed that the combination of WSS, MMP-1, TIMP-1, and MMP-12 is predictive of aortic surgery (area under the curve 0.898). CONCLUSIONS: Increased flow-based and structural descriptors of ascending aortic aneurysms are associated with high levels of circulating biomarkers, implicating adverse vascular remodeling in the dilated aorta by mechanotransduction. A combination of shear stress and circulating biomarkers has the potential to improve the decision-making process for ascending aortic aneurysms to a highly individualized level.

Simulation study of transcatheter heart valve implantation in patients with stenotic bicuspid aortic valve.

Bicuspid aortic valve (BAV) anatomy has routinely been considered an exclusion in the setting of transcatheter aortic valve implantation (TAVI) because of the large dimension of the aortic annulus having a more calcified, bulky, and irregular shape. The study aims to develop a patient-specific computational framework to virtually simulate TAVI in stenotic BAV patients using the Edwards SAPIEN 3 valve (S3) and its improved version SAPIEN 3 Ultra and quantify stent frame deformity as well as the severity of paravalvular leakage (PVL). Specifically, the aortic root anatomy of n.9 BAV patients who underwent TAVI was reconstructed from pre-operative CT imaging. Crimping and deployment of S3 frame were performed and then followed by fluid-solid interaction analysis to simulate valve leaflet dynamics throughout the entire cardiac cycle. Modeling revealed that the S3 stent frame expanded well on BAV anatomy with an elliptical shape at the aortic annulus. Comparison of predicted S3 deformity as assessed by eccentricity and expansion indices demonstrated a good agreement with the measurement obtained from CT imaging. Blood particle flow analysis demonstrated a backward blood jet during diastole, whereas the predicted PVL flows corresponded well with those determined by transesophageal echocardiography. This study represents a further step towards the use of personalized simulations to virtually plan TAVI, aiming at improving not only the efficacy of the implantation but also the exploration of "off-label" applications as the TAVI in the setting of BAV patients. Graphical abstract Computational frameworks of TAVI in patients with stenotic bicuspid aortic valve.

Usefulness of regional right ventricular and right atrial strain for prediction of early and late right ventricular failure following a left ventricular assist device implant: A machine learning approach.

BACKGROUND: Identifying candidates for left ventricular assist device surgery at risk of right ventricular failure remains difficult. The aim was to identify the most accurate predictors of right ventricular failure among clinical, biological, and imaging markers, assessed by agreement of different supervised machine learning algorithms. METHODS: Seventy-four patients, referred to HeartWare left ventricular assist device since 2010 in two Italian centers, were recruited. Biomarkers, right ventricular standard, and strain echocardiography, as well as cath-lab measures, were compared among patients who did not develop right ventricular failure (N = 56), those with acute-right ventricular failure (N = 8, 11%) or chronic-right ventricular failure (N = 10, 14%). Logistic regression, penalized logistic regression, linear support vector machines, and naïve Bayes algorithms with leave-one-out validation were used to evaluate the efficiency of any combination of three collected variables in an "all-subsets" approach. RESULTS: Michigan risk score combined with central venous pressure assessed invasively and apical longitudinal systolic strain of the right ventricular-free wall were the most significant predictors of acute-right ventricular failure (maximum receiver operating characteristic-area under the curve = 0.95, 95% confidence interval = 0.91-1.00, by the naïve Bayes), while the right ventricular-free wall systolic strain of the middle segment, right atrial strain (QRS-synced), and tricuspid annular plane systolic excursion were the most significant predictors of Chronic-RVF (receiver operating characteristic-area under the curve = 0.97, 95% confidence interval = 0.91-1.00, according to naïve Bayes). CONCLUSION: Apical right ventricular strain as well as right atrial strain provides complementary information, both critical to predict acute-right ventricular failure and chronic-right ventricular failure, respectively.

Assessment of "grading" with Ki-67 and c-kit immunohistochemical expressions may be a helpful tool in management of patients with flat epithelial atypia (FEA) and columnar cell lesions (CCLs) on core breast biopsy.

It is essential to reach a better understanding of "flat epithelial atypia/columnar cell lesions" (FEA/CCLs) in breast core biopsies. Our aim was to explore their biological nature, in order to predict the likelihood of an upgrade to carcinoma. "Cytological grading" has been specially focused, in view of its possible utility in the choice of management. One hundred thirty of a total of 900 cases core needle (CN)/vacuum-assisted biopsies (VABs), with diagnoses of "hyperplasia" and "atypia" were retrospectively re-evaluated. Pathological findings of further excision biopsies (FEBs) performed in 40/75 patients with follow-up were compared with the previous diagnoses. In all cases, both Ki-67 and c-kit immunoreactivities were explored and compared with both normal breast tissues and subsequently documented cancers, with special reference to the hyperplastic FEA/CCLs, with "mild" atypia (FEA/CCHAm). Sixteen cases were re-diagnosed as "usual ductal hyperplasia" (UDH), 60 as "columnar cell hyperplasia" (CCH), and 54 as FEA/CCHA, 30 of which FEA/CCHAm and 24 FEA/CCHAh (with high atypia). Significantly, the Ki-67 index proved to be on the increase and c-kit expression on the decrease in FEA/CCHA lesions, mainly in the FEA/CCHAh group and in the subsequently observed cancers, compared with either benign tissues or the FEA/CCH cases. It was also significant that most of the carcinomas were found in FEBs within the FEA/CCHAh group. In this study cytological grading, together with Ki-67 and c-kit indices, proved to be helpful in FEA/CCLs evaluation. With regard to FEA/CCHAm lesions, an adequate surveillance appears to be a more appropriate management tool than FEB, as a result of their biological nature and behavior.