Imaging findings of cesarean delivery complications: cesarean scar disease and much more.

In the last years, there has been a significant increase in the number of cesarean deliveries and, with it, of the number of complications following the procedure. They can be divided into early and late ones. We will illustrate herein the most common complications following cesarean section to help radiologists to recognize them. To familiarize with these various pathologic conditions is crucial to alert referring clinicians for a prompt and appropriate maternal and fetal management. Special attention will be given to the cesarean scar defect (CSD), the most common but also the most unknown of such conditions. Although often asymptomatic, a severe CSD represents a predisposing factor for subsequent complications especially in future pregnancies.

Computationally inexpensive methods for intra-cardiac atrial bipolar electrogram compression.

AIM: This paper reports studies of mathematical algorithms for intra-cardiac atrial bipolar electrogram compression suitable with implementation on implantable devices. PATIENTS AND METHODS: Bipolar intra-cardiac electrograms (IEGMs) of high right atrium were obtained from 20 patients who underwent electrophysiological studies for arrhythmias. Four thousand seven hundred and eighty-two seconds of IEGM were collected and divided into three rhythm groups: sinus rhythm (SR), atrial fibrillation (AF) and atrial flutter (AFL). Since mathematical algorithms suitable for use with implantable devices demand low computational cost, we employed piecemeal linear approximation methods (ZOP--Zero Order Prediction and SAPA--Scan Along Polygonal Approximation), and beat detection method (Peak) both or which need small numbers of operations to perform electrogram compression. Compression ratio (CR) and percent root mean square difference (PRD) were used to compare the three methods, with statistical analyses performed using paired t-test. RESULTS AND CONCLUSION: The best performance was obtained using the Peak method which reaches an average CR of 10.6 in the case of SR group, 2.8 for AF, and 3.6 for AFL groups, respectively, while PRD lies below 2% for SR and AFL groups and 6% for the AF group. Results show that, for bipolar electrograms, the Peak method reaches statistically significant better performance (P<0.001) in all cases except for Peak vs SAPA applied to AF (P=0.2). The number of operations necessary to compress the data indicate that time consumption can be reduced to be suitable for real time compression in implantable devices. The Peak method, which was assumed to receive the instant of occurrence of each recognized beat, from the hardware of the device, requires fewer operations than ZOP and SAPA. Increasing the length of electrograms recorded in pacemakers will enhance the amount of information provided by the implantable device, allowing more detailed characterization of the intra-cardiac activity and leading to new perspectives in arrhythmia diagnosis and therapy.

Automatic atrial tachyarrhythmia detection from intracardiac electrograms.

BACKGROUND: Automatic atrial tachyarrhythmia recognition is crucial in order to allow a correct switching-mode function of dual-chamber pacemakers and to avoid inappropriate shocks of ventricular implantable cardioverter-defibrillators. In this paper we considered three algorithms suitable for implantable devices. The first was based on the atrial cycle length; the others analyze different morphologic characteristics of atrial signals. METHODS: Intracardiac bipolar electrogram recordings were obtained from the high right atrium during electrophysiological study. Twenty patients were considered, some of them presenting with different types of cardiac rhythm at different intervals of the study. Cardiac rhythms were divided into three groups: sinus rhythm consisting of 2,196 s obtained from 12 subjects, atrial fibrillation consisting of 771 s obtained from 7 subjects, and atrial flutter consisting of 1,793 s obtained from 7 subjects. The automatic detection was performed on each electrogram segment lasting 1 or 4 s. Atrial segments were separated into two subgroups: the first for the training of the algorithm and the second for testing and validation of results. We considered two types of statistical analysis: comparison between pairs of rhythm (paired classification), and classification among the three different groups (direct classification). RESULTS: The combination of the cycle length algorithm with a morphological method achieved the best performance for both statistical analyses. Paired classification resulted in the following: atrial fibrillation vs sinus rhythm was detected with no error; atrial flutter vs sinus rhythm with a total accuracy of 99.3% (sensitivity 99.4%, specificity 99.2%); atrial fibrillation vs atrial flutter with a total accuracy of 99.1% (sensitivity 98.5%, specificity 99.4%). The total accuracy achieved for the direct classification was 98.6% (average sensitivity 98.5%, specificity 98.8%). CONCLUSIONS: Our results support the association of algorithms for future enhancement of atrial tachyarrhythmia detection in dual-chamber devices, thanks to the limited computational effort.

Automatic estimation of the correlation dimension for the analysis of electrocardiograms.

The main purpose of the present work is the definition of a fully automatic procedure for correlation dimension (D(2)) estimation. In the first part, the procedure for the estimation of the correlation dimension (D(2)) is proposed and tested on various types of mathematical models: chaotic (Lorenz and Henon models), periodical (sinusoidal waves) and stochastic (Gaussian and uniform noise). In all cases, accurate D(2) estimates were obtained. The procedure can detect the presence of multiple scaling regions in the correlation integral function. The connection between the presence of multiple scaling regions and multiple dynamic activities cooperating in a system is investigated through the study of composite time series. In the second part of the paper, the proposed algorithm is applied to the study of cardiac electrical activity through the analysis of electrocardiographic signals (ECG) obtained from the commercially available MIT-BIH ECG arrhythmia database. Three groups of ECG signals have been considered: the ECGs of normal subjects and ECGs of subjects with atrial fibrillation and with premature ventricular contraction. D(2) estimates are computed on single ECG intervals (static analysis) of appropriate duration, striking a balance between stationarity requisites and accurate computation requirements. In addition, D(2) temporal variability is studied by analyzing consecutive intervals of ECG tracings (dynamic analysis). The procedure reveals the presence of multiple scaling regions in many ECG signals, and the D(2) temporal variability differs in the three ECG groups considered; it is greater in the case of atrial fibrillation than in normal sinus rhythms. This study points out the importance of considering both the static and dynamic D(2) analysis for a more complete study of the system under analysis. While the static analysis visualizes the underlying heart activity, dynamic D(2) analysis insights the time evolution of the underlying system.

Study of the Lyapunov exponents in heart rate variability signals.

Heart rate variability signals obtained from 24 h recordings are analyzed for normal and pathological subjects. This time series contains information about the autonomic nervous system action regulating the beat-to-beat heart rate. Nonlinear contributions to the long period variability have been assessed by the calculation of the entire spectrum of Lyapunov exponents, after the system trajectory reconstruction, starting from the original variability signal. The positivity of Lyapunov exponent values, obtained from an unknown process, can establish whether the structure generating it shows nonlinear chaotic characteristics. This is what happens for the cardiovascular signals. Moreover, the different values obtained for the Lyapunov exponents operate a classification among the considered pathophysiological cases.

Study of bound water of poly-adenine using high frequency dielectric measurements.

The high frequency dielectric constant of poly-adenine (poly-A) was measured between 1 MHz and 1 GHz. The purpose of these experiments was to investigate the state of water molecules that are bound to the charged groups of the poly-A molecule. Analysis of the data using the Maxwell's mixture equation revealed the dielectric constant of bound water higher than we expected. Using Onsager's internal field in Debye's equation, we calculated the dielectric constant of water in the vicinity of a charged ion. The result of this computation demonstrates that the dielectric constant of bound water is much smaller than the normal value only in the immediate proximity of charged ions (within 2 A). The dielectric constant increases rapidly to the normal value as the distance increases from 2 to 4 A. This observation indicates that charged sites of polyions have only short range interactions with the surrounding water molecules. However, this conclusion pertains only to rotary diffusion of bound water since dielectric measurement is unable to detect translational diffusion.