MRI characterization of hemodynamic patterns of human fetuses with cyanotic congenital heart disease.

OBJECTIVES: To characterize, using magnetic resonance imaging (MRI), the distribution of blood flow and oxygen transport in human fetuses with subtypes of congenital heart disease (CHD) that present with neonatal cyanosis. METHODS: Blood flow was measured in the major vessels of 152 late-gestation human fetuses with CHD and 40 gestational-age-matched normal fetuses, using cine phase-contrast MRI. Oxygen saturation (SaO2 ) was measured in the major vessels of 57 fetuses with CHD and 40 controls. RESULTS: Compared with controls, we found lower combined ventricular output in fetuses with single-ventricle physiology, with the lowest being observed in fetuses with severe forms of Ebstein's anomaly. Obstructive lesions of the left or right heart were associated with increased flow across the contralateral side. Pulmonary blood flow was reduced in fetuses with Ebstein's anomaly, while those with Ebstein's anomaly and tricuspid atresia had reduced umbilical flow. Flow in the superior vena cava was elevated in fetuses with transposition of the great arteries, normal in fetuses with hypoplastic left heart, tetralogy of Fallot or tricuspid atresia and reduced in fetuses with Ebstein's anomaly. Umbilical vein SaO2 was reduced in fetuses with hypoplastic left heart or tetralogy of Fallot. Ascending aorta and superior vena cava SaO2 were reduced in nearly all CHD subtypes. CONCLUSIONS: Fetuses with cyanotic CHD exhibit profound changes in the distribution of blood flow and oxygen transport, which result in changes in cerebral, pulmonary and placental blood flow and oxygenation. These alterations of fetal circulatory physiology may influence the neonatal course and help account for abnormalities of prenatal growth and development that have been described in newborns with cyanotic CHD. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Design of tree structured matched wavelet for HRV signals of menstrual cycle.

An algorithm is presented for designing a new class of wavelets matched to the Heart Rate Variability (HRV) signals of the menstrual cycle. The proposed wavelets are used to find HRV variations between phases of menstrual cycle. The method finds the signal matching characteristics by minimising the shape feature error using Least Mean Square method. The proposed filter banks are used for the decomposition of the HRV signal. For reconstructing the original signal, the tree structure method is used. In this approach, decomposed sub-bands are selected based upon their energy in each sub-band. Thus, instead of using all sub-bands for reconstruction, sub-bands having high energy content are used for the reconstruction of signal. Thus, a lower number of sub-bands are required for reconstruction of the original signal which shows the effectiveness of newly created filter coefficients. Results show that proposed wavelets are able to differentiate HRV variations between phases of the menstrual cycle accurately than standard wavelets.

An alternative approach to approximate entropy threshold value (r) selection: application to heart rate variability and systolic blood pressure variability under postural challenge.

This study presents an alternative approach to approximate entropy (ApEn) threshold value (r) selection. There are two limitations of traditional ApEn algorithm: (1) the occurrence of undefined conditional probability (CPu) where no template match is found and (2) use of a crisp tolerance (radius) threshold 'r'. To overcome these limitations, CPu is substituted with optimum bias setting ɛ opt which is found by varying ɛ from (1/N - m) to 1 in the increments of 0.05, where N is the length of the series and m is the embedding dimension. Furthermore, an alternative approach for selection of r based on binning the distance values obtained by template matching to calculate ApEnbin is presented. It is observed that ApEnmax, ApEnchon and ApEnbin converge for ɛ opt = 0.6 in 50 realizations (n = 50) of random number series of N = 300. Similar analysis suggests ɛ opt = 0.65 and ɛ opt = 0.45 for 50 realizations each of fractional Brownian motion and MIX(P) series (Lu et al. in J Clin Monit Comput 22(1):23-29, 2008). ɛ opt = 0.5 is suggested for heart rate variability (HRV) and systolic blood pressure variability (SBPV) signals obtained from 50 young healthy subjects under supine and upright position. It is observed that (1) ApEnbin of HRV is lower than SBPV, (2) ApEnbin of HRV increases from supine to upright due to vagal inhibition and (3) ApEnbin of BPV decreases from supine to upright due to sympathetic activation. Moreover, merit of ApEnbin is that it provides an alternative to the cumbersome ApEnmax procedure.

Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

Adaptive correlation dimension method for analysing heart rate variability during the menstrual cycle.

Correlation dimension (CD) is used for analysing the chaotic behaviour of the nonlinear heart rate variability (HRV) time series. In CD, the autocorrelation function is used to calculate the time delay. However, it does not provide optimum values of time delays, which leads to an inaccurate estimation of the HRV between phases of the menstrual cycle. Thus, an adaptive CD method is presented here to calculate the optimum value of the time delay based upon the information content in the HRV signal. In the proposed method, the first step is to divide the HRV signal into overlapping windows. Afterwards, the time delay is calculated for each window based on the features of the signal. This procedure of finding the optimum time delay for each window is known as adaptive autocorrelation. Then, the CD for each window is calculated using optimum time delays. Finally, adaptive CD is calculated by averaging the CD of all windows. The proposed method is applied on two data sets: (i) the standard Physionet dataset and (ii) the dataset acquired using BIOPAC(®)MP150. The results show that the proposed method can accurately differentiate between normal and diseased subjects. Further, the results prove that the proposed method is more accurate in detecting HRV variations during the menstrual cycles of 74 young women in lying and standing postures. Three statistical parameters are used to find the effectiveness of adaptive autocorrelation in calculating time delays. The comparative analysis validates the superiority of the proposed method over detrended fluctuation analyses and conventional CD.

Improved HRV characterization using OCDWT.

In this paper an over-complete discrete wavelet transform (OCDWT) algorithm, obtained by blending two wavelet transform implementations that is redundant wavelet transform and the Mallat's multiresolution decomposition, has been proposed to retrieve the time-varying characteristics of HRV under two different postures, supine and standing. The OCDWT algorithm is critically sub-sampled to a given level of decomposition, below which it is then fully sampled. Five subjects were included to investigate posture-related HRV. The results showed that the high frequency fluctuations are larger in supine and get significantly reduced in standing in comparison to low frequency variations. Moreover, the very low frequency heart beat fluctuations during supine were greater than during standing. Further a comparative analysis has also been made between the Mallat's and OCDWT implementation in order to show the superiority of proposed algorithm.

In vitro antioxidant activity of pet ether extract of black pepper.

OBJECTIVE: To investigate the in vitro antioxidant activity of different fractions (R1, R2 and R3) obtained from pet ether extract of black pepper fruits (Piper nigrum Linn.) MATERIALS AND METHODS: The fractions R1, R2 and R3 were eluted from pet ether and ethyl acetate in the ratio of 6:4, 5:5 and 4:6, respectively. 1,1-Diphenyl-2-picryl-hydrazyl (DPPH) radical, superoxide anion radical, nitric oxide radical, and hydroxyl radical scavenging assays were carried out to evaluate the antioxidant potential of the extract. RESULTS: The free radical scavenging activity of the different fractions of pet ether extract of P. nigrum (PEPN) increased in a concentration dependent manner. The R3 and R2 fraction of PEPN in 500 microg/ml inhibited the peroxidation of a linoleic acid emulsion by 60.48+/-3.33% and 58.89+/-2.51%, respectively. In DPPH free radical scavenging assay, the activity of R3 and R2 were found to be almost similar. The R3 (100microg/ml) fraction of PEPN inhibited 55.68+/-4.48% nitric oxide radicals generated from sodium nitroprusside, whereas curcumin in the same concentration inhibited 84.27+/-4.12%. Moreover, PEPN scavenged the superoxide radical generated by the Xanthine/Xanthine oxidase system. The fraction R2 and R3 in the doses of 1000microg/ml inhibited 61.04+/-5.11% and 63.56+/-4.17%, respectively. The hydroxyl radical was generated by Fenton's reaction. The amounts of total phenolic compounds were determined and 56.98 microg pyrocatechol phenol equivalents were detected in one mg of R3. CONCLUSIONS: P. nigrum could be considered as a potential source of natural antioxidant.

Time-evolution of cardiovascular variability during autonomic function tests in physiological investigations.

Autonomic function testing forms an integral part of physiological investigations both for human and animal research. Clinically, recent times have seen them emerging as tools in settling diagnosis in several neurological, cardiovascular, endocrinal disorders where autonomic function are compromised. The reasons for such emergence have been their simplicity, noninvasiveness, and their ability to decipher the control systems. A time-varying spectrum estimation method for analyzing heart rate variability signals dynamics is presented. As a case study, the dynamics of heart rate variability during autonomic function tests is examined using wavelets. The obtained spectrum estimates have further been decomposed into separate components and, thus, the lime variation of low and high frequency components of heart rate variability can be examined separately. Thus, the present study aims to ascertain the association between heart rate changes and HRV parameters. The wavelet based HRV analysis has been found to faithfully represent the sympathovagal balance during standard autonomic battery test.