From physiological complexity to data interactions-A case study of recordings from exercise monitoring.

The popularity of nonlinear analysis has been growing simultaneously with the technology of effort monitoring. Therefore, considering the simple methods of physiological data collection and the approaches from the information domain, we proposed integrating univariate and bivariate analysis for the rest and effort comparison. Two sessions separated by an intensive training program were studied. Nine subjects participated in the first session (S1) and seven in the second session (S2). The protocol included baseline (BAS), exercise, and recovery phase. During all phases, electrocardiogram (ECG) was recorded. For the analysis, we selected corresponding data lengths of BAS and exercise usually lasting less than 5 min. We found the utility of the differences between original data and their surrogates for sample entropy Sdiff and Kullback-Leibler divergence KLDdiff. Sdiff of heart rate variability was negative in BAS and exercise but its sensitivity for phases discrimination was not satisfactory. We studied the bivariate analysis of RR intervals and corresponding QT peaks by Interlayer Mutual Information (IMI) and average edge overlap (AVO) markers. While the IMI parameter decreases in exercise conditions, AVO increased in effort compared to BAS. These findings conclude that researchers should consider a bivariate analysis of extracted RR intervals and corresponding QT datasets, when only ECG is recorded during tests.

Analytical Analysis of Factors Affecting the Accuracy of a Dual-Heat Flux Core Body Temperature Sensor.

Non-invasive core body temperature (CBT) measurements using temperature and heat-flux have become popular in health, sports, work safety, and general well-being applications. This research aimed to evaluate two commonly used sensor designs: those that combine heat flux and temperature sensors, and those with four temperature sensors. We used analytical methods, particularly uncertainty analysis calculus and Monte Carlo simulations, to analyse measurement accuracy, which depends on the accuracy of the temperature and flux sensors, mechanical construction parameters (such as heat transfer coefficient), ambient air temperature, and CBT values. The results show the relationship between the accuracy of each measurement method variant and various sensor parameters, indicating their suitability for different scenarios. All measurement variants showed unstable behaviour around the point where ambient temperature equals CBT. The ratio of the heat transfer coefficients of the dual-heat flux (DHF) sensor's channels impacts the CBT estimation uncertainty. An analysis of the individual components of uncertainty in CBT estimates reveals that the accuracy of temperature sensors significantly impacts the overall uncertainty of the CBT measurement. We also calculated the theoretical limits of measurement uncertainty, which varied depending on the method variant and could be as low as 0.05 °C.

Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography-Performance Study In Silico.

Although the two dimensional Speckle Tracking Echocardiography has gained a strong position among medical diagnostic techniques in cardiology, it still requires further developments to improve its repeatability and reliability. Few works have attempted to incorporate the left ventricle segmentation results in the process of displacements and strain estimation to improve its performance. We proposed the use of mask information as an additional penalty in the elastic image registration based displacements estimation. This approach was studied using a short axis view synthetic echocardiographic data, segmented using an active contour method. The obtained masks were distorted to a different degree, using different methods to assess the influence of the segmentation quality on the displacements and strain estimation process. The results of displacements and circumferential strain estimations show, that even though the method is dependent on the mask quality, the potential loss in accuracy due to the poor segmentation quality is much lower than the potential accuracy gain in cases where the segmentation performs well.

Evaluation of strain averaging area and strain estimation errors in a spheroidal left ventricular model using synthetic image data and speckle tracking.

BACKGROUND: In majority of studies on speckle tracking echocardiography (STE) the strain estimates are averaged over large areas of the left ventricle. This may impair the diagnostic capability of the STE in the case of e.g. local changes of the cardiac contractility. This work attempts to evaluate, how far one can reduce the averaging area, without sacrificing the estimation accuracy that could be important from the clinical point of view. METHODS: Synthetic radio frequency (RF) data of a spheroidal left ventricular (LV) model were generated using FIELD II package and meshes obtained from finite element method (FEM) simulation. The apical two chamber (A2C) view and the mid parasternal short axis view (pSAXM) were simulated. The sector encompassed the entire cross-section (full view) of the LV model or its part (partial view). The wall segments obtained according to the American Heart Association (AHA17) were divided into subsegments of area decreasing down to 3 mm2. Longitudinal, circumferential and radial strain estimates, obtained using a hierarchical block-matching method, were averaged over these subsegments. Estimation accuracy was assessed using several error measures, making most use of the prediction of the maximal relative error of the strain estimate obtained using the FEM derived reference. Three limits of this predicted maximal error were studied, namely 16.7%, 33% and 66%. The smallest averaging area resulting in the strain estimation error below one of these limits was considered the smallest allowable averaging area (SAAA) of the strain estimation. RESULTS: In all AHA17 segments, using the A2C projection, the SAAA ensuring maximal longitudinal strain estimates error below 33% was below 3 mm2, except for the segment no 17 where it was above 278 mm2. The SAAA ensuring maximal circumferential strain estimates error below 33% depended on the AHA17 segment position within the imaging sector and view type and ranged from below 3-287 mm2. The SAAA ensuring maximal radial strain estimates error below 33% obtained in the pSAXM projection was not less than 287 mm2. The SAAA values obtained using other maximal error limits differ from SAAA values observed for the 33% error limit only in limited number of cases. SAAA decreased when using maximal error limit equal to 66% in these cases. The use of the partial view (narrow sector) resulted in a decrease of the SAAA. CONCLUSIONS: The SAAA varies strongly between strain components. In a vast part of the LV model wall in the A2C view the longitudinal strain could be estimated using SAAA below 3 mm2, which is smaller than the averaging area currently used in clinic, thus with a higher resolution. The SAAA of the circumferential strain estimation strongly depends on the position of the region of interest and the parameters of the acquisition. The SAAA of the radial strain estimation takes the highest values. The use of a narrow sector could increase diagnostic capabilities of 2D STE.

Quantitative Assessment of the Effect of the Out-of-Plane Movement of the Homogenous Ellipsoidal Model of the Left Ventricle on the Deformation Measures Estimated Using 2-D Speckle Tracking-An In-Silico Study.

Effect of the out-of-plane (OOP) movement amplitude on estimates of global displacements (radial, circumferential) and strains (radial , circumferential ) was studied in an ellipsoidal model of the left ventricle using finite-element modeling (FEM), synthetic ultrasonic data, and short-axis view. This effect was assessed using median of the absolute relative error (RE) of the global parameters. FEM provided node displacements for synthetic ultrasonic data and reference data generation. Displacements were estimated using block-matching (BM) and B-spline (BS) methods. FEM-derived data analysis, free from errors resulting from speckle tracking, indicated that the tissue motion introduced REs of global strain estimates below 4.5%. The effect of the OOP motion amplitude on strain estimates was strain specific and depended on the displacement estimation method. In the case of , the increase of the OOP amplitude resulted in quasi-linear increase of the RE from approximately 10% to 15%. The modulus of the end-systolic (ES) errors of the estimates almost linearly increased with increasing OOP amplitude approximately from 10% to 16%. REs of the estimate were close to 80% and 40%, respectively, in the case of the BM and BS methods, and increased with increasing OOP amplitude. The modulus of the ES errors of the estimates in the case of the BS method was about -40% and showed low sensitivity to the OOP amplitude; in the BM case, these errors varied approximately from -70% to -58% for OOP amplitude from 0 to 15 mm.

Effect of Transmural Extent of the Simulated Infarction in a Left Ventricular Model on Displacement and Strain Distribution Estimated from Synthetic Ultrasonic Data.

The identification of a sub-endocardial infarction is of major interest in cardiology. This study evaluates the sensitivity of selected measures to the thickness of such an infarction. Synthetic ultrasonic data (long-axis view) of left ventricular models with inclusions were generated using Field II and meshes obtained from finite-element simulations, which also provided the reference for the estimates obtained from ultrasonic data. The displacements, the first and second component of the principal strain (ε1 and ε2), and several measures derived from these quantities were estimated. All estimates, except for the poorly estimated ε2, exhibited sensitivity to the presence and transmurality of the inclusion. The most sensitive was the gradient of the averaged transmural profiles of ε1, and ε1 averaged over the area corresponding to the transmural inclusion. The inflection point of the ε1 profile shifted toward the outer wall with increasing thickness of the non-transmural inclusion.

Detailed Evaluation of Five 3D Speckle Tracking Algorithms Using Synthetic Echocardiographic Recordings.

A plethora of techniques for cardiac deformation imaging with 3D ultrasound, typically referred to as 3D speckle tracking techniques, are available from academia and industry. Although the benefits of single methods over alternative ones have been reported in separate publications, the intrinsic differences in the data and definitions used makes it hard to compare the relative performance of different solutions. To address this issue, we have recently proposed a framework to simulate realistic 3D echocardiographic recordings and used it to generate a common set of ground-truth data for 3D speckle tracking algorithms, which was made available online. The aim of this study was therefore to use the newly developed database to contrast non-commercial speckle tracking solutions from research groups with leading expertise in the field. The five techniques involved cover the most representative families of existing approaches, namely block-matching, radio-frequency tracking, optical flow and elastic image registration. The techniques were contrasted in terms of tracking and strain accuracy. The feasibility of the obtained strain measurements to diagnose pathology was also tested for ischemia and dyssynchrony.

Acoustic radiation force impulse imaging of kidneys - a phantom study.

AIM OF THE STUDY: Since there have been only few works reporting the diagnosis of kidneys using Acoustic Radiation Force Impulse technique and those works do not provide consistent results of shear wave velocity measurements in renal tissue, we have decided to use kidney phantoms with known properties to examine the reliability of the method itself in a controlled setup similar to kidneys examination. MATERIALS AND METHODS: Four gelatin-based phantoms imitating different clinical situations were manufactured - two with thick and two with thin renal cortex, each type at a depth similar to a normal-weight or overweight patient. For each phantom, a series of interest points was chosen and for each point 20 Shear Wave Velocity measurements were taken using the build-in Virtual Touch Tissue Quantification™ tool in a Siemens Acuson S2000 ultrasound scanner equipped with a 6C1 HD Transducer (Siemens Mountainview, USA). RESULTS: Mean Shear Wave Velocity values obtained for all the examined points ranged from 2.445 to 3.941 m/s, with standard deviation exceeding 0.1 in only one case out of 29 points, but differing significantly between all points. CONCLUSIONS: The obtained results indicate that the method is highly reliable as long as the measurement volume contains a uniform tissue region. If the measurement window covers a region with different properties even partially, the obtained results are affected. The variance of measured values on the other hand is not affected by the said non-uniformity of material under examination. Furthermore, the variance of measured values does not show a clear dependency on the depth at which the shear wave velocities are measured.

Regional cardiac motion and strain estimation in three-dimensional echocardiography: a validation study in thick-walled univentricular phantoms.

Automatic quantification of regional left ventricular deformation in volumetric ultrasound data remains challenging. Many methods have been proposed to extract myocardial motion, including techniques using block matching, phase-based correlation, differential optical flow methods, and image registration. Our lab previously presented an approach based on elastic registration of subsequent volumes using a B-spline representation of the underlying transformation field. Encouraging results were obtained for the assessment of global left ventricular function, but a thorough validation on a regional level was still lacking. For this purpose, univentricular thick-walled cardiac phantoms were deformed in an experimental setup to locally assess strain accuracy against sonomicrometry as a reference method and to assess whether regions containing stiff inclusions could be detected. Our method showed good correlations against sonomicrometry: r(2) was 0.96, 0.92, and 0.84 for the radial (ε(RR)), longitudinal (ε(LL)), and circumferential (ε(CC)) strain, respectively. Absolute strain errors and strain drift were low for ε(LL) (absolute mean error: 2.42%, drift: -1.05%) and ε(CC) (error: 1.79%, drift: -1.33%) and slightly higher for ε(RR) (error: 3.37%, drift: 3.05%). The discriminative power of our methodology was adequate to resolve full transmural inclusions down to 17 mm in diameter, although the inclusion-to-surrounding tissue stiffness ratio was required to be at least 5:2 (absolute difference of 39.42 kPa). When the inclusion-to-surrounding tissue stiffness ratio was lowered to approximately 2:1 (absolute difference of 22.63 kPa), only larger inclusions down to 27 mm in diameter could still be identified. Radial strain was found not to be reliable in identifying dysfunctional regions.