Video Kinematic Evaluation: new insights on the cardiac mechanical function

The cardiac mechanical function plays a critical role in governing and regulating its performance under both normal and pathological conditions. The left ventricle has historically received more attention in both congenital and acquired heart diseases and was considered as the mainstay of normal hemodynamics. However, over the past few decades, there has been increasing recognition of the pivotal role of the right ventricle in determining functional performance status and prognosis in multiple conditions. Nonetheless, the ventricles should not be considered separately as they share the septum, are encircled with common myocardial fibers and are surrounded by the pericardium. Thus, changes in the filling of one ventricle may alter the mechanical function of its counterpart. This ventricular interdependence remains even after the removal of the pericardium because of constrictive pericarditis or during open chest surgery. Interestingly, during open chest surgery, only the right ventricle mechanical activity is visually checked by the surgeon and cardiologist due to the absence of an intraoperative imaging technique able to evaluate its complex function. Noteworthy, most of the imaging techniques available to clinicians are established for the assessment of the left ventricle, with the ejection fraction being the most used parameter. However, this value is a measure of global systolic function which comes short in identifying regional myocardial impairment and the mechanical contraction. Therefore, new approaches are needed to deeply investigate the mechanics of both ventricles and correctly assess the cardiac mechanical performance. In this thesis, I studied the mechanical function of the left ventricle through different modalities of cardiac magnetic resonance and employed an innovative imaging technique for the assessment of the right ventricle mechanical function during open chest surgery

A Random Shuffle Method to Expand a Narrow Dataset and Overcome the Associated Challenges in a Clinical Study: A Heart Failure Cohort Example

Heart failure (HF) affects at least 26 million people worldwide, so predicting adverse events in HF patients represents a major target of clinical data science. However, achieving large sample sizes sometimes represents a challenge due to difficulties in patient recruiting and long follow-up times, increasing the problem of missing data. To overcome the issue of a narrow dataset cardinality (in a clinical dataset, the cardinality is the number of patients in that dataset), population-enhancing algorithms are therefore crucial. The aim of this study was to design a random shuffle method to enhance the cardinality of an HF dataset while it is statistically legitimate, without the need of specific hypotheses and regression models. The cardinality enhancement was validated against an established random repeated-measures method with regard to the correctness in predicting clinical conditions and endpoints. In particular, machine learning and regression models were employed to highlight the benefits of the enhanced datasets. The proposed random shuffle method was able to enhance the HF dataset cardinality (711 patients before dataset preprocessing) circa 10 times and circa 21 times when followed by a random repeated-measures approach. We believe that the random shuffle method could be used in the cardiovascular field and in other data science problems when missing data and the narrow dataset cardinality represent an issue

Bionic for Training: Smart Framework Design for Multisensor Mechatronic Platform Validation

: Home monitoring supports the continuous improvement of the therapy by sharing data with healthcare professionals. It is required when life-threatening events can still occur after hospital discharge such as neonatal apnea. However, multiple sources of external noise could affect data quality and/or increase the misdetection rate. In this study, we developed a mechatronic platform for sensor characterizations and a framework to manage data in the context of neonatal apnea. The platform can simulate the movement of the abdomen in different plausible newborn positions by merging data acquired simultaneously from three-axis accelerometers and infrared sensors. We simulated nine apnea conditions combining three different linear displacements and body postures in the presence of self-generated external noise, showing how it is possible to reduce errors near to zero in phenomena detection. Finally, the development of a smart 8Ws-based software and a customizable mobile application were proposed to facilitate data management and interpretation, classifying the alerts to guarantee the correct information sharing without specialized skills

Unlocking cardiac motion: assessing software and machine learning for single-cell and cardioid kinematic insights

The heart coordinates its functional parameters for optimal beat-to-beat mechanical activity. Reliable detection and quantification of these parameters still represent a hot topic in cardiovascular research. Nowadays, computer vision allows the development of open-source algorithms to measure cellular kinematics. However, the analysis software can vary based on analyzed specimens. In this study, we compared different software performances in in-silico model, in-vitro mouse adult ventricular cardiomyocytes and cardioids. We acquired in-vitro high-resolution videos during suprathreshold stimulation at 0.5-1-2 Hz, adapting the protocol for the cardioids. Moreover, we exposed the samples to inotropic and depolarizing substances. We analyzed in-silico and in-vitro videos by (i) MUSCLEMOTION, the gold standard among open-source software; (ii) CONTRACTIONWAVE, a recently developed tracking software; and (iii) ViKiE, an in-house customized video kinematic evaluation software. We enriched the study with three machine-learning algorithms to test the robustness of the motion-tracking approaches. Our results revealed that all software produced comparable estimations of cardiac mechanical parameters. For instance, in cardioids, beat duration measurements at 0.5 Hz were 1053.58 ms (MUSCLEMOTION), 1043.59 ms (CONTRACTIONWAVE), and 937.11 ms (ViKiE). ViKiE exhibited higher sensitivity in exposed samples due to its localized kinematic analysis, while MUSCLEMOTION and CONTRACTIONWAVE offered temporal correlation, combining global assessment with time-efficient analysis. Finally, machine learning reveals greater accuracy when trained with MUSCLEMOTION dataset in comparison with the other software (accuracy > 83%). In conclusion, our findings provide valuable insights for the accurate selection and integration of software tools into the kinematic analysis pipeline, tailored to the experimental protocol

Cardiac kinematic parameters computed from video of in situ beating heart

Mechanical function of the heart during open-chest cardiac surgery is exclusively monitored by echocardiographic techniques. However, little is known about local kinematics, particularly for the reperfused regions after ischemic events. We report a novel imaging modality, which extracts local and global kinematic parameters from videos of in situ beating hearts, displaying live video cardiograms of the contraction events. A custom algorithm tracked the movement of a video marker positioned ad hoc onto a selected area and analyzed, during the entire recording, the contraction trajectory, displacement, velocity, acceleration, kinetic energy and force. Moreover, global epicardial velocity and vorticity were analyzed by means of Particle Image Velocimetry tool. We validated our new technique by i) computational modeling of cardiac ischemia, ii) video recordings of ischemic/reperfused rat hearts, iii) videos of beating human hearts before and after coronary artery bypass graft, and iv) local Frank-Starling effect. In rats, we observed a decrement of kinematic parameters during acute ischemia and a significant increment in the same region after reperfusion. We detected similar behavior in operated patients. This modality adds important functional values on cardiac outcomes and supports the intervention in a contact-free and non-invasive mode. Moreover, it does not require particular operator-dependent skills

Synthetic recovery of impulse propagation in myocardial infarction via silicon carbide semiconductive nanowires

: Myocardial infarction causes 7.3 million deaths worldwide, mostly for fibrillation that electrically originates from the damaged areas of the left ventricle. Conventional cardiac bypass graft and percutaneous coronary interventions allow reperfusion of the downstream tissue but do not counteract the bioelectrical alteration originated from the infarct area. Genetic, cellular, and tissue engineering therapies are promising avenues but require days/months for permitting proper functional tissue regeneration. Here we engineered biocompatible silicon carbide semiconductive nanowires that synthetically couple, via membrane nanobridge formations, isolated beating cardiomyocytes over distance, restoring physiological cell-cell conductance, thereby permitting the synchronization of bioelectrical activity in otherwise uncoupled cells. Local in-situ multiple injections of nanowires in the left ventricular infarcted regions allow rapid reinstatement of impulse propagation across damaged areas and recover electrogram parameters and conduction velocity. Here we propose this nanomedical intervention as a strategy for reducing ventricular arrhythmia after acute myocardial infarction

Video analysis of ex vivo beating hearts during preservation on the TransMedics® organ care system

BackgroundReliable biomarkers for assessing the viability of the donor hearts undergoing ex vivo perfusion remain elusive. A unique feature of normothermic ex vivo perfusion on the TransMedics® Organ Care System (OCS™) is that the donor heart is maintained in a beating state throughout the preservation period. We applied a video algorithm for an in vivo assessment of cardiac kinematics, video kinematic evaluation (Vi.Ki.E.), to the donor hearts undergoing ex vivo perfusion on the OCS™ to assess the feasibility of applying this algorithm in this setting.MethodsHealthy donor porcine hearts (n = 6) were procured from Yucatan pigs and underwent 2 h of normothermic ex vivo perfusion on the OCS™ device. During the preservation period, serial high-resolution videos were captured at 30 frames per second. Using Vi.Ki.E., we assessed the force, energy, contractility, and trajectory parameters of each heart.ResultsThere were no significant changes in any of the measured parameters of the heart on the OCS™ device over time as judged by linear regression analysis. Importantly, there were no significant changes in contractility during the duration of the preservation period (time 0–30 min, 918 ± 430 px/s; time 31–60 min, 1,386 ± 603 px/s; time 61–90 min, 1,299 ± 617 px/s; time 91–120 min, 1,535 ± 728 px/s). Similarly, there were no significant changes in the force, energy, or trajectory parameters. Post-transplantation echocardiograms demonstrated robust contractility of each allograft.ConclusionVi.Ki.E. assessment of the donor hearts undergoing ex vivo perfusion is feasible on the TransMedics OCS™, and we observed that the donor hearts maintain steady kinematic measurements throughout the duration

Anxiety and depression in keratotic oral lichen planus: a multicentric study from the SIPMO

Objectives: Oral lichen planus with exclusive keratotic reticular, papular, and/or plaque-like lesions (K-OLP) is a clinical pattern of OLP that may be associated with a complex symptomatology and psychological alteration. The aim of the study was to evaluate the prevalence of anxiety (A) and depression (D) in patients with K-OLP, analyzing the potential predictors which can affect mental health status. Methods: Three hundred K-OLP patients versus 300 healthy controls (HC) were recruited in 15 Italian universities. The Numeric Rating Scale (NRS), Total Pain Rating Index (T-PRI), and Hamilton Rating Scales for Depression and for Anxiety (HAM-D and HAM-A) were administered. Results: The K-OLP patients showed statistically higher scores in the NRS, T-PRI, HAM-D, and HAM-A compared with the HC (p-value < 0.001**). A and D were found in 158 (52.7%) and 148 (49.3%) K-OLP patients. Strong linear correlations were identified between HAM-A, HAM-D, NRS, T-PRI, and employment status and between HAM-D, HAM-A, NRS, T-PRI, employment status, and female gender. Multivariate logistic regression revealed that HAM-D and HAM-A showed the greatest increase in the R2 value for A and D in the K-OLP patients, respectively (DR2 = 55.5% p-value < 0.001**; DR2 = 56.5% p-value < 0.001**). Conclusions: The prevalence of A and D is higher in the K-OLP patients compared with the HC, also found in K-OLP subjects without pain, suggesting that the processing of pain may be in a certain way independent of the processing of mood. Clinical relevance: Mood disorders and pain assessment should be carefully performed in relation to K-OLP to obtain a complete analysis of the patients

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London