Florian Tetschke

Indices of fetal development derived from heart rate patterns

BACKGROUND The fetal precursors of mental and cardiovascular disease caused by adverse prenatal environmental influences and manifesting in later age are an important issue of developmental medicine. However the number of measurable functional parameters of a fetus is limited. Evaluation of key parameters involving fetal autonomic control could permit an earlier detection of developmental problems and improved therapeutic strategies. Thus far, however, even the maturation of normal autonomic control has not been sufficiently assessed. AIM The objective of the present work is to describe normal fetal maturation based on indices of autonomic heart rate modulation. STUDY DESIGN Heart beat interval series were magnetocardiographically recorded with 1 kHz sampling rate over 30 min in 78 normal fetuses, gestational age (GA) 23-40 weeks. Indices considered were: number of accelerations (AC) and decelerations (DC), RMSSD, SDNN, and short-term/long-term autonomic information flows (AIF_NN, AIF_fVLF). These were measured from the entire 30 min data sets and from activity-specific subsets (10 min). RESULTS In the 30 min recordings: the number of AC increased, number of DC decreased, rMSSD and SDNN increased and AIF_fVLF increased with GA, but AIF_NN remained constant. In the 10 min subsets: SDNN increased in the active state but remained constant in the quiet state and AIF_NN decreased with GA in the quiet state. CONCLUSION Heart rate patterns from 30 min biomagnetic recordings may provide new indices with which to assess the normal and abnormal maturation of fetal autonomic control and to identify risk of possible disorders in later life.

Development of multiscale complexity and multifractality of fetal heart rate variability.

During fetal development a complex system grows and coordination over multiple time scales is formed towards an integrated behavior of the organism. Since essential cardiovascular and associated coordination is mediated by the autonomic nervous system (ANS) and the ANS activity is reflected in recordable heart rate patterns, multiscale heart rate analysis is a tool predestined for the diagnosis of prenatal maturation. The analyses over multiple time scales requires sufficiently long data sets while the recordings of fetal heart rate as well as the behavioral states studied are themselves short. Care must be taken that the analysis methods used are appropriate for short data lengths. We investigated multiscale entropy and multifractal scaling exponents from 30 minute recordings of 27 normal fetuses, aged between 23 and 38 weeks of gestational age (WGA) during the quiet state. In multiscale entropy, we found complexity lower than that of non-correlated white noise over all 20 coarse graining time scales investigated. Significant maturation age related complexity increase was strongest expressed at scale 2, both using sample entropy and generalized mutual information as complexity estimates. Multiscale multifractal analysis (MMA) in which the Hurst surface h(q,s) is calculated, where q is the multifractal parameter and s is the scale, was applied to the fetal heart rate data. MMA is a method derived from detrended fluctuation analysis (DFA). We modified the base algorithm of MMA to be applicable for short time series analysis using overlapping data windows and a reduction of the scale range. We looked for such q and s for which the Hurst exponent h(q,s) is most correlated with gestational age. We used this value of the Hurst exponent to predict the gestational age based only on fetal heart rate variability properties. Comparison with the true age of the fetus gave satisfying results (error 2.17±3.29 weeks; p<0.001; R(2)=0.52). In addition, we found that the normally used DFA scale range is non-optimal for fetal age evaluation. We conclude that 30 min recordings are appropriate and sufficient for assessing fetal age by multiscale entropy and multiscale multifractal analysis. The predominant prognostic role of scale 2 heart beats for MSE and scale 39 heart beats (at q=-0.7) for MMA cannot be explored neither by single scale complexity measures nor by standard detrended fluctuation analysis.

Fetal functional brain age assessed from universal developmental indices obtained from neuro-vegetative activity patterns.

Fetal brain development involves the development of the neuro-vegetative (autonomic) control that is mediated by the autonomic nervous system (ANS). Disturbances of the fetal brain development have implications for diseases in later postnatal life. In that context, the fetal functional brain age can be altered. Universal principles of developmental biology applied to patterns of autonomic control may allow a functional age assessment. The work aims at the development of a fetal autonomic brain age score (fABAS) based on heart rate patterns. We analysed n = 113 recordings in quiet sleep, n = 286 in active sleep, and n = 29 in active awakeness from normals. We estimated fABAS from magnetocardiographic recordings (21.4–40.3 weeks of gestation) preclassified in quiet sleep (n = 113, 63 females) and active sleep (n = 286, 145 females) state by cross-validated multivariate linear regression models in a cross-sectional study. According to universal system developmental principles, we included indices that address increasing fluctuation range, increasing complexity, and pattern formation (skewness, power spectral ratio VLF/LF, pNN5). The resulting models constituted fABAS. fABAS explained 66/63% (coefficient of determination R2 of training and validation set) of the variance by age in quiet, while 51/50% in active sleep. By means of a logistic regression model using fluctuation range and fetal age, quiet and active sleep were automatically reclassified (94.3/93.1% correct classifications). We did not find relevant gender differences. We conclude that functional brain age can be assessed based on universal developmental indices obtained from autonomic control patterns. fABAS reflect normal complex functional brain maturation. The presented normative data are supplemented by an explorative study of 19 fetuses compromised by intrauterine growth restriction. We observed a shift in the state distribution towards active awakeness. The lower WGA dependent fABAS values found in active sleep may reflect alterations in the universal developmental indices, namely fluctuation amplitude, complexity, and pattern formation that constitute fABAS.

Fetal development of complex autonomic control evaluated from multiscale heart rate patterns

Development of the fetal autonomic nervous systems integrative capacity in relation to gestational age and emerging behavioral pattern is reflected in fetal heart rate patterns. Conventional indices of vagal and sympathetic rhythms cannot sufficiently reflect their complex interrelationship. Universal behavioral indices of developing complex systems may provide additional information regarding the maturating complex autonomic control. We investigated fetal magnetocardiographic recordings undertaken at 10-min intervals in active (n = 248) and quiet (n = 111) states between 22 and 39 wk gestational age. Standard deviation of heartbeat intervals, skewness, contribution of particular rhythms to the total power, and multiscale entropy were analyzed. The multiscale entropy methodology was validated for 10-min data sets. Age dependence was analyzed by linear regression. In the quiet state, contribution of sympathovagal rhythms and their complexity over a range of corresponding short scales increased with rising age, and skewness shifted from negative to positive values. In the active state, age dependencies were weaker. Skewness as the strongest parameter shifted in the same direction. Fluctuation amplitude and the complexity of scales associated with sympathovagal rhythms increased. We conclude that in the quiet state, stable complex organized rhythms develop. In the active state, however, increasing behavioral variability due to multiple internal coordinations, such as movement-related heart rate accelerations, and external influences develop. Hence, the state-selective assessment in association with developmental indices used herein may substantially improve evaluation of maturation age and early detection and interpretation of developmental problems in prenatal diagnosis.

Fetal development assessed by heart rate patterns-Time scales of complex autonomic control

The increasing functional integrity of the organism during fetal maturation is connected with increasing complex internal coordination. We hypothesize that time scales of complexity and dynamics of heart rate patterns reflect the increasing inter-dependencies within the fetal organism during its prenatal development. We investigated multi-scale complexity, time irreversibility and fractal scaling from 73 fetal magnetocardiographic 30min recordings over the third trimester. We found different scale dependent complexity changes, increasing medium scale time irreversibility, and increasing long scale fractal correlations (all changes p<0.05). The results confirm the importance of time scales to be considered in fetal heart rate based developmental indices.

Fetal autonomic brain age scores, segmented heart rate variability analysis, and traditional short term variability

Disturbances of fetal autonomic brain development can be evaluated from fetal heart rate patterns (HRP) reflecting the activity of the autonomic nervous system. Although HRP analysis from cardiotocographic (CTG) recordings is established for fetal surveillance, temporal resolution is low. Fetal magnetocardiography (MCG), however, provides stable continuous recordings at a higher temporal resolution combined with a more precise heart rate variability (HRV) analysis. A direct comparison of CTG and MCG based HRV analysis is pending. The aims of the present study are: (i) to compare the fetal maturation age predicting value of the MCG based fetal Autonomic Brain Age Score (fABAS) approach with that of CTG based Dawes-Redman methodology; and (ii) to elaborate fABAS methodology by segmentation according to fetal behavioral states and HRP. We investigated MCG recordings from 418 normal fetuses, aged between 21 and 40 weeks of gestation. In linear regression models we obtained an age predicting value of CTG compatible short term variability (STV) of R2 = 0.200 (coefficient of determination) in contrast to MCG/fABAS related multivariate models with R2 = 0.648 in 30 min recordings, R2 = 0.610 in active sleep segments of 10 min, and R2 = 0.626 in quiet sleep segments of 10 min. Additionally segmented analysis under particular exclusion of accelerations (AC) and decelerations (DC) in quiet sleep resulted in a novel multivariate model with R2 = 0.706. According to our results, fMCG based fABAS may provide a promising tool for the estimation of fetal autonomic brain age. Beside other traditional and novel HRV indices as possible indicators of developmental disturbances, the establishment of a fABAS score normogram may represent a specific reference. The present results are intended to contribute to further exploration and validation using independent data sets and multicenter research structures.

Assessment of fetal maturation age by heart rate variability measures using random forest methodology

Fetal maturation age assessment based on heart rate variability (HRV) is a predestinated tool in prenatal diagnosis. To date, almost linear maturation characteristic curves are used in univariate and multivariate models. Models using complex multivariate maturation characteristic curves are pending. To address this problem, we use Random Forest (RF) to assess fetal maturation age and compare RF with linear, multivariate age regression. We include previously developed HRV indices such as traditional time and frequency domain indices and complexity indices of multiple scales. We found that fetal maturation was best assessed by complexity indices of short scales and skewness in state-dependent datasets (quiet sleep, active sleep) as well as in state-independent recordings. Additionally, increasing fluctuation amplitude contributed to the model in the active sleep state. None of the traditional linear HRV parameters contributed to the RF models. Compared to linear, multivariate regression, the mean prediction of gestational age (GA) is more accurate with RF than in linear, multivariate regression (quiet state: R(2)=0,617 vs. R(2)=0,461, active state: R(2)=0,521 vs. R(2)=0,436, state independent: R(2)=0,583 vs. R(2)=0,548). We conclude that classification and regression tree models such as RF methodology are appropriate for the evaluation of fetal maturation age. The decisive role of adjustments between different time scales of complexity may essentially extend previous analysis concepts mainly based on rhythms and univariate complexity indices. Those system characteristics may have implication for better understanding and accessibility of the maturating complex autonomic control and its disturbance.

In vivo imaging in the oral cavity by endoscopic optical coherence tomography

Abstract. The common way to diagnose hard and soft tissue irregularities in the oral cavity is initially the visual inspection by an experienced dentist followed by further medical examinations, such as radiological imaging and/or histopathological investigation. For the diagnosis of oral hard and soft tissues, the detection of early transformations is mostly hampered by poor visual access, low specificity of the diagnosis techniques, and/or limited feasibility of frequent screenings. Therefore, optical noninvasive diagnosis of oral tissue is promising to improve the accuracy of oral screening. Considering this demand, a rigid handheld endoscopic scanner was developed for optical coherence tomography (OCT). The novelty is the usage of a commercially near-infrared endoscope with fitting optics in combination with an established spectral-domain OCT system of our workgroup. By reaching a high spatial resolution, in vivo images of anterior and especially posterior dental and mucosal tissues were obtained from the oral cavity of two volunteers. The convincing image quality of the endoscopic OCT device is particularly obvious for the imaging of different regions of the human soft palate with highly scattering fibrous layer and capillary network within the lamina propria.

Visualization of interfacial adhesive defects at dental restorations with spectral domain and polarization sensitive optical coherence tomography

Abstract Restoration loss based on interfacial adhesive defects and associated caries at the restoration margin are the main causes for invasive replacement of dental restorations. Assessment of the interfacial quality based on clinical inspection and radiographic examination is often difficult and not reliable. In this work, we present spectral domain optical coherence tomography (SDOCT) and polarization sensitive optical coherence tomography (PSOCT) for the evaluation of tooth-composite bond failure. Imaging of two composite restorations at the occlusal surface are presented using intensity-based images obtained by SDOCT and PSOCT based degree of polarization uniformity (DOPU). Both modalities revealed several defects beneath the surface such as inhomogeneous adhesive layers, marginal gaps and bubbles. In addition, DOPU representation showed an inhomogeneous structure within the composite material. OCT based imaging of dental restorations could add a valuable diagnostic tool for the evaluation of structural defects in clinical practice. The representation of polarization characteristics with the DOPU algorithm provides further information on the homogeneity of the restoration.

Cross-sectional and en-face depolarization imaging for the assessment of dental lesions

Abstract Dental caries is one of the most widespread diseases and the early and non-invasive detection of carious lesions remains an ongoing topic in biomedical research. In contrast, optical coherence tomography (OCT) is an emerging, non-invasive imaging technique for near-surface structures, that has already proved its capability for manifold biomedical applications and can be extended by several modalities such as polarization sensitivity. We have recently shown that polarization sensitive OCT combined with an algorithm for depolarization imaging, visualizing the degree of polarization uniformity (DOPU), is a promising tool for the detection and assessment of carious lesions. In this paper, we evaluate different visualization approaches based on both the intensity and DOPU data with cross-sectional and en-face representations and discuss limitations and the potential of the proposed method for the assessment of dental lesions on the example of a molar tooth with a brown spot.