Xinpei Wang

Comparison of different threshold values r for approximate entropy: application to investigate the heart rate variability between heart failure and healthy control groups

Approximate entropy (ApEn) is widely accepted as a complexity measure of the heart rate variability (HRV) signal, but selecting the criteria for the threshold value r is controversial. This paper aims to verify whether Chons method of forecasting the r(max) is an appropriate one for the HRV signal. The standard limb lead ECG signals of 120 subjects were recorded for 10 min in a supine position. The subjects were divided into two groups: the heart failure (22 females and 38 males, median age 62.4 ± 12.6) and healthy control group (33 females and 27 males, median age 51.5 ± 16.9). Three types of ApEn were calculated: the ApEn(0.2) using the recommended constant r = 0.2, the ApEn(chon) using Chons method and the ApEn(max) using the true r(max). A Wilcoxon rank sum test showed that the ApEn(0.2) (p = 0.267) and the ApEn(max) (p = 0.813) had no statistical differences between the two groups, while the ApEn(chon) (p = 0.040) had. We generated a synthetic database to study the effect of two influential factors (the signal length N and the ratio of short- and long-term variability sd(1)/sd(2)) on the empirical formula in Chons method (Chon et al 2009 IEEE Eng. Med. Biol. Mag. 28 18-23). The results showed that the empirical formula proposed by Chon et al is a good method for analyzing the random signal, but not an appropriate tool for analyzing nonlinear signals, such as the logistic or HRV signals.

Clinical evaluation of dual-energy bone removal in CT angiography of the head and neck: comparison with conventional bone-subtraction CT angiography

AIM To evaluate the bone-subtraction effect of dual-energy bone removal in computed tomography angiography (CTA) of the head and neck in comparison with conventional bone-subtraction CTA. MATERIAL AND METHODS The study comprised 52 patients who were divided into two groups at random, and examined using dual-source CT for head and neck CTA. Dual-energy bone removal CTA and conventional bone-subtraction CTA were applied to each of the two groups, respectively. The bone subtraction was performed automatically in both methods. Vascular structures, as well as brain tissue remained visible. The subtracted images were further processed with maximum intensity projection (MIP) and volume-rendering technique (VRT) for image evaluation. Two experienced radiologists reviewed the resulting subtracted and non-subtracted volume data with respect to the delineation and detection of image quality and vascular pathology. RESULTS The means of the weighted CT dose index (CTDIvol) for bone-removal dual-energy CTA and conventional bone-subtraction CTA were 20.56+/-0.01 mGy and 25.57+/-0.56 mGy, respectively. There was a significant difference between them. The percentage of carotid and vertebral arteries and all other vessels that could be successfully assessed with these two methods were 87.8, 68, and 83%, and 93.5, 91.8, and 92.6%, respectively. There were no significant differences in the visualization of the carotid arteries; however, there were significant differences in the visualization of the vertebral arteries. CONCLUSION Compared with conventional bone-subtraction CTA, dual-energy bone-removal CTA had a lower radiation dose. It eliminated most bones in the head and neck successfully; however, the bone subtraction effect around the vertebral artery was unsatisfactory. Dual-energy bone-removal CTA provides a new method for detecting vascular diseases in routine clinical work.

Testing pattern synchronization in coupled systems through different entropy-based measures

Pattern synchronization (PS) can capture one aspect of the dynamic interactions between bivariate physiological systems. It can be tested by several entropy-based measures, e.g., cross sample entropy (X-SampEn), cross fuzzy entropy (X-FuzzyEn), multivariate multiscale entropy (MMSE), etc. A comprehensive comparison on their distinguishability is currently missing. Besides, they are highly dependent on several pre-defined parameters, the threshold value r in particular. Thus, their consistency also needs further elucidation. Based on the well-accepted assumption that a tight coupling necessarily leads to a high PS, we performed a couple of evaluations over several simulated coupled models in this study. All measures were compared to each other with respect to their consistency and distinguishability, which were quantified by two pre-defined criteria—degree of crossing (DoC) and degree of monotonicity (DoM). Results indicated that X-SampEn and X-FuzzyEn could only work well over coupled stochastic systems with meticulously selected r. It is thus not recommended to apply them to the intrinsic complex physiological systems. However, MMSE was suitable for both, indicating by relatively higher DoC and DoM values. Final analysis on the cardiorespiratory coupling validated our results.Pattern synchronization (PS) can capture one aspect of the dynamic interactions between bivariate physiological systems. It can be tested by several entropy-based measures, e.g., cross sample entropy (X-SampEn), cross fuzzy entropy (X-FuzzyEn), multivariate multiscale entropy (MMSE), etc. A comprehensive comparison on their distinguishability is currently missing. Besides, they are highly dependent on several pre-defined parameters, the threshold value r in particular. Thus, their consistency also needs further elucidation. Based on the well-accepted assumption that a tight coupling necessarily leads to a high PS, we performed a couple of evaluations over several simulated coupled models in this study. All measures were compared to each other with respect to their consistency and distinguishability, which were quantified by two pre-defined criteria—degree of crossing (DoC) and degree of monotonicity (DoM). Results indicated that X-SampEn and X-FuzzyEn could only work well over coupled stochastic systems with meticulously selected r. It is thus not recommended to apply them to the intrinsic complex physiological systems. However, MMSE was suitable for both, indicating by relatively higher DoC and DoM values. Final analysis on the cardiorespiratory coupling validated our results.

Detection of coronary artery anomalies by dual-source CT coronary angiography

AIM To retrospectively evaluate the clinical value of dual-source computed tomography (DSCT) coronary angiography in the diagnosis of coronary artery anomalies. MATERIALS AND METHODS A large cohort of 3625 consecutive patients, who underwent DSCT coronary angiography in our institute, was reviewed for coronary artery anomalies. All images were evaluated by two experienced readers using axial source images, multi-planar reformations (MPR), maximum intensity projections (MIP) and volume rendering (VR). Coronary artery anomalies were found in 36 patients (male 20, female 16, mean age 48 years, range 15-76 years). Of the 36 patients, 19 patients also underwent conventional coronary angiography (CCA). RESULTS The incidence of coronary artery anomalies was 0.99% (36/3625). Six different types of coronary artery anomalies were diagnosed by DSCT coronary angiography: (1) 11 anomalies of the right coronary artery; (2) five anomalies of the left coronary artery; (3) 10 anomalies of the left circumflex artery; (4) two single coronary artery; (5) one anomalous pulmonary origin of the coronary artery; (6) seven coronary artery fistula. Evaluation of the CCA resulted in a precise diagnosis in 53% (10/19) patients. CONCLUSION DSCT coronary angiography is a good diagnostic tool to examine coronary artery anomalies.

The role of ultrasonography and MRI in patients with non-traumatic nerve fascicle torsion of the upper extremity

AIM To evaluate the role of ultrasonography and magnetic resonance imaging (MRI) in the diagnosis of non-traumatic nerve fascicle torsion of the upper extremity. MATERIALS AND METHODS Eleven patients (unilateral upper extremity) who underwent surgical treatment for nerve fascicle torsion were included in the study. Ultrasonography and MRI showed the detailed anatomy of the region well enough to reveal nerve fascicle torsion. The characterization and classification (single-segmental or multi-segmental) based on ultrasonography and diffusion-weighted (DW) MRI findings were recorded. RESULTS The hourglass-shaped appearance was a characteristic feature of nerve fascicle torsion, Characterization and classification based on ultrasonography and MRI findings were consistent with intraoperative findings. CONCLUSION Ultrasonography and MRI may be valuable in the diagnosis of non-traumatic nerve fascicle torsion of the upper extremity.

Detection of the First and Second Heart Sound Using Heart Sound Energy

Detection of the primary sound components in heart sound signal is the first step in automated diagnosis of cardiac abnormality. Although most existing heart sound detection algorithms perform well in normal signals, they usually have no effect on signals with heart murmurs. In this paper, an algorithm based on energy is proposed for robust detection of the first and second heart sound. It improved preprocessing and energy formula in envelope-based algorithm to overcome the interference of noises, which include heart murmurs and background noises, and can detect the accurate boundaries of the first and second heart sounds by constructing time gates. The algorithm has been tested using normal and abnormal clinical data and compared with the normalized average Shannon energy algorithm. The results show that the algorithm has over 96 percent correct ratio. That is superior to the normalized average Shannon energy algorithm.

The value of low-dose prospective ECG-gated dual-source CT angiography in the diagnosis of coarctation of the aorta in infants and children

AIM To investigate the value of prospective electrocardiogram (ECG)-gated dual-source computed tomography (DSCT) in the diagnosis of coarctation of the aorta (CoA). MATERIALS AND METHODS Seventeen patients clinically suspected of having CoA underwent prospective ECG-gated DSCT angiography and transthoracic echocardiography (TTE). Surgery was performed in all patients. The diagnostic accuracy of DSCT angiography and TTE was compared with the surgical findings as the reference standard. Image quality was evaluated using a five-point scale. Effective radiation dose was calculated from the dose-length product (DLP). RESULTS CoA was diagnosed in 17 patients by DSCT angiography and in 16 patients by TTE. A total of 46 separate cardiovascular abnormalities were confirmed by surgical findings. The diagnostic accuracy of DSCT angiography and TTE was 96.32% and 97.06%, respectively. There was no significant difference in the diagnostic accuracy between DSCT angiography and TTE (χ(2) = 0, p > 0.05). The mean score of image quality was 4.2 ± 0.8. The mean effective dose was 0.69 ± 0.09 mSv. CONCLUSION Prospective ECG-gated DSCT with a low radiation dose is a valuable technique in the diagnosis of CoA in infants and children.

Automatic detection of atrial fibrillation using R-R interval signal

This paper presents a method to automatically detect atrial fibrillation (AF) based on the scatter plot of R-R interval signal. R-R intervals of AF are absolutely irregular, which are different from those of normal ECG. Scatter plot of R-R interval signal is illustrated here and characteristic indexes are extracted from the plot, i.e. VAI, VLI, SD1, and SD2. Algorithm test using AF Termination Challenge Database and clinical ECG data shows that these four indexes have high sensitivity and specificity to classify AF from normal ECG. Then a conjoint analysis method to combine these four indexes is proposed to detect AF with more high sensitivity and specificity.

Cross-Sample Entropy and Cross-Fuzzy Entropy for Testing Pattern Synchrony: How Results Vary with Different Threshold Value r

Cross-sample entropy (X-SampEn) and crossfuzzy entropy (X-FuzzyEn) are widely accepted as pattern synchrony or similarity measures to quantify interactions between different physiological subsystems. However, X-SampEn is highly parameter-dependent, especially on the threshold value r. As to X-FuzzyEn, which is said to be less dependent on parameter selection, crossing-over each other still could not be avoid in many situations, especially when low-frequency trend is contained. This study aims to show how results vary with different r so as to give it proper values to obtain a more unequivocal result. The influence of low-frequency trend was mainly concerned in this study. Logistic map time-series added by low-frequency sinusoids with different amplitudes were test under different r. The results showed that for both X-SampEn and X-FuzzyEn, the recommended range of r might not work well in many situations. Select r which is smaller than that at the crossing-over point might make sense. The crossing-over point moves to left with the increase of low-frequency trend, besides, X-FuzzyEn might not work well because r is too small where crossing-over occurs. Since non-stationary trend does exist for most physiological signals, special attention should be paid when using X-SampEn and X-FuzzyEn for testing pattern synchrony and it may be advisable for researchers to apply de-trend algorithms prior to the application of X-SampEn and X-FuzzyEn.

Measuring Electromechanical Coupling in Patients with Coronary Artery Disease and Healthy Subjects

Coronary artery disease (CAD) is the most common cause of death globally. To detect CAD noninvasively at an early stage before clinical symptoms occur is still nowadays challenging. Analysis of the variation of heartbeat interval (RRI) opens a new avenue for evaluating the functional change of cardiovascular system which is accepted to occur at the subclinical stage of CAD. In addition, systolic time interval (STI) and diastolic time interval (DTI) also show potential. There may be coupling in these electromechanical time series due to their physiological connection. However, to the best of our knowledge no publication has systematically investigated how can the coupling be measured and how it changes in CAD patients. In this study, we enrolled 39 CAD patients and 36 healthy subjects and for each subject the electrocardiogram (ECG) and photoplethysmography (PPG) signals were recorded simultaneously for 5 min. The RRI series, STI series, and DTI series were constructed, respectively. We used linear cross correlation (CC), coherence function (CF), as well as nonlinear mutual information (MI), cross conditional entropy (XCE), cross sample entropy (XSampEn), and cross fuzzy entropy (XFuzzyEn) to analyse the bivariate RRI-DTI coupling, RRI-STI coupling, and STI-DTI coupling, respectively. Our results suggest that the linear CC and CF generally have no significant difference between the two groups for all three types of bivariate coupling. The MI only shows weak change in RRI-DTI coupling. By comparison, the three entropy-based coupling measurements show significantly decreased coupling in CAD patients except XSampEn for RRI-DTI coupling (less significant) and XCE for STI-DTI and RRI-STI coupling (not significant). Additionally, the XFuzzyEn performs best as it was still significant if we further applied the Bonferroni correction in our statistical analysis. Our study indicates that the intrinsic electromechanical coupling is most probably nonlinear and can better be measured by nonlinear entropy-based measurements especially the XFuzzyEn. Besides, CAD patients are accompanied by a loss of electromechanical coupling. Our results suggest that cardiac electromechanical coupling may potentially serve as a noninvasive diagnostic tool for CAD.