Comparative Analysis of the Complications of 5347 Endomyocardial Biopsies Applied to Patients After Heart Transplantation and With Cardiomyopathies: A Single-center Study

Introduction. Endomyocardial biopsy (EMB) plays an important role in allograft surveillance to screen an acute rejection episode after heart transplantation (HT), to diagnose an unknown cause of cardiomyopathies (CMP) or to reveal a cardiac tumor. However, the procedure is not risk free. Objective. The main objective of this research was to describe our experience with EMB during the last 33 years comparing surgical risk between FIT versus no-HT patients. Method. We analyzed retrospectively the data of 5347 EMBs performed from 1978 to 2011 (33 years). For surveillance of acute rejection episodes after HT we performed 3564 (66.7%), whereas 1777 (33.2%) for CMP diagnosis, and 6 (1.0%) for cardiac tumor identification. Results. The main complications due to EMB were divided into 2 groups to facilitate analysis: major complications associated with potential death risk, and minor complications. The variables that showed a significant difference in the HT group were as follows: tricuspid Injury (.0490) and coronary fistula (.0000). Among the no-HT cohort they were insufficient fragment (.0000), major complications (.0000) and total complications (.0000). Conclusions. EMB can be accomplished with a low risk of complications and high effectiveness to diagnose CMP and rejection after HT. However, the risk is great among patients with CMP due to their anatomic characteristics. Children also constitute a risk group for EMB due to their small size in addition to the heart disease. The risk of injury to the tricuspid valve was higher among the HT group.

ECM versus ICP for point registration

Iterative Closest Point (ICP) is a widely exploited method for point registration that is based on binary point-to-point assignments, whereas the Expectation Conditional Maximization (ECM) algorithm tries to solve the problem of point registration within the framework of maximum likelihood with point-to-cluster matching. In this paper, by fulfilling the implementation of both algorithms as well as conducting experiments in a scenario where dozens of model points must be registered with thousands of observation points on a pelvis model, we investigated and compared the performance (e.g. accuracy and robustness) of both ICP and ECM for point registration in cases without noise and with Gaussian white noise. The experiment results reveal that the ECM method is much less sensitive to initialization and is able to achieve more consistent estimations of the transformation parameters than the ICP algorithm, since the latter easily sinks into local minima and leads to quite different registration results with respect to different initializations. Both algorithms can reach the high registration accuracy at the same level, however, the ICP method usually requires an appropriate initialization to converge globally. In the presence of Gaussian white noise, it is observed in experiments that ECM is less efficient but more robust than ICP.

Strategies for routine biopsies in heart transplantation based on 8-year results with more than 13,000 biopsies

The endomyocardial biopsy (EMB) in heart transplant recipients has been considered the "gold standard" for diagnosis of graft rejection (REJ). The purpose of this retrospective study is to develop long-term strategies (frequency and postoperative duration of EMB) for REJ monitoring. Between 1985 and 1992, 346 patients (mean age 44.5 years, female patients = 14%) received 382 heart grafts. For graft surveillance EMBs were performed according to a fixed schedule depending on postoperative day and the results of previous biopsies. In the first year the average number (no.) of EMBs/patient was 20 with 19% positive for REJ in the first quarter, dropping to 7% REJ/EMB by the end of the first year. The percentage of REJ/EMB declined annually from 4.7% to 4.5%, 2.2% and less than 1% after the fifth year. Individual biopsy results in the first 3 postoperative months had little predictive value. Patients with fewer than two REJ (group 1), vs patients with two or more REJ in the first 6 postoperative months (group 2), were significantly less likely to reject in the second half of the first year (group 1: 0.29 +/- 0.6 REJ/patient; group 2:0.83 +/- 1.3 REJ/patient; P < 0.001) and third postoperative year (group 1:0.12 +/- 0.33 REJ/patients; group 2:0.46 +/- 0.93 REJ/patient; P < 0.05). In conclusion, routine EMBs in the first 3 postoperative months have only limited predictive value, however the number of routine EMBs can be drastically reduced later depending on the intermediate postoperative REJ pattern.

Functional polypyrrole coatings for wirelessly controlled magnetic microrobots

A wirelessly controlled magnetic microrobot has been proposed to diagnose and treat pathologies in the posterior segment of the human eye. The robot consists of a magnetic CoNi platform with a conformal coating of functional polymers. Electrodeposition has been the preferred method to fabricate and to functionalize the microrobot. Poly(pyrrole), a widely studied intrinsically conductive polymer has been investigated as a biocompatible coating to reduce biofouling, and as a coating that can release incorporated drugs on demand. The mechanism of redox cycling has been investigated to reduce the stiction of NIH 3T3 fibroblasts onto poly(pyrrole) surfaces. To demonstrate triggered drug release, Rhodamine B has been incorporated into the Ppy matrix as a model drug. Rapid Rhodamine B release is obtained when eddy current losses are induced by alternating magnetic fields on the CoNi substrates underneath these films.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

A Mobile Feedback System for Integrated E-health Platforms to improve Self-Care and Compliance of Diabetes Mellitus Patients

Exploiting the full potential of telemedical systems means using platform based solutions: data are recovered from biomedical sensors, hospital information systems, care-givers, as well as patients themselves, and are processed and redistributed in an either centralized or, more probably, decentralized way. The integration of all these different devices, and interfaces, as well as the automated analysis and representation of all the pieces of information are current key challenges in telemedicine. Mobile phone technology has just begun to offer great opportunities of using this diverse information for guiding, warning, and educating patients, thus increasing their autonomy and adherence to their prescriptions. However, most of these existing mobile solutions are not based on platform systems and therefore represent limited, isolated applications. This article depicts how telemedical systems, based on integrated health data platforms, can maximize prescription adherence in chronic patients through mobile feedback. The application described here has been developed in an EU-funded R&D project called METABO, dedicated to patients with type 1 or type 2 Diabetes Mellitus

Influence of delay time on regularity estimation for voice pathology detection

The employment of nonlinear analysis techniques for automatic voice pathology detection systems has gained popularity due to the ability of such techniques for dealing with the underlying nonlinear phenomena. On this respect, characterization using nonlinear analysis typically employs the classical Correlation Dimension and the largest Lyapunov Exponent, as well as some regularity quantifiers computing the system predictability. Mostly, regularity features highly depend on a correct choosing of some parameters. One of those, the delay time �, is usually fixed to be 1. Nonetheless, it has been stated that a unity � can not avoid linear correlation of the time series and hence, may not correctly capture system nonlinearities. Therefore, present work studies the influence of the � parameter on the estimation of regularity features. Three � estimations are considered: the baseline value 1; a � based on the Average Automutual Information criterion; and � chosen from the embedding window. Testing results obtained for pathological voice suggest that an improved accuracy might be obtained by using a � value different from 1, as it accounts for the underlying nonlinearities of the voice signal.