Non-invasive Foetal ECG - a Comparable Alternative to the Doppler CTG?
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ABSTRACT:
SUBMITTER: Reinhard J
PROVIDER: S-EPMC4168331 | biostudies-literature | 2012 Mar
REPOSITORIES: biostudies-literature
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Non-invasive Foetal ECG - a Comparable Alternative to the Doppler CTG?
Geburtshilfe und Frauenheilkunde 20120301 3
This review discusses the alternative of using the non-invasive foetal ECG compared with the conventionally used Doppler CTG. Non-invasive abdominal electrocardiograms (ECG) have been approved for clinical routine since 2008; subsequently they were also approved for antepartum and subpartum procedures. The first study results have been published. Non-invasive foetal ECG is especially indicated during early pregnancy, while the Doppler CTG is recommended for the vernix period. Beyond the vernix p ...[more]
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Project description:Introduction: This study aimed to evaluate foetal signal quality obtained using an antenatal foetal ECG system (Monica 24™) and compare it with Doppler ultrasound CTG monitoring (Corometrics® 250 series). Material and Methods: Seventy pregnant women (gestational age: between 20?+?0 weeks and 40?+?0 weeks) were examined using the Monica AN24™ system and also underwent Doppler CTG. The signal quality of both methods was compared and correlated with gestational age and pre-pregnancy body mass index (BMI). Results: Overall, ECG had a signal quality of 77.4?% and CTG had a signal quality of 73.1?% (p?>?0.05). In gestational weeks (GW) 20-26, the signal quality of ECG was significantly better compared to that obtained with CTG (75.5 vs. 45.3?%; p?=?0.003), while in GW 27-36, the signal quality was better with CTG (72.3 vs. 83.0?%, p?=?0.001). No difference in signal quality was found between the two methods after the 37th GW (87.7 vs. 86.1?%; p?>?0.05). CTG showed a statistically significant correlation with BMI (rho 0.25, p?<?0.05) while ECG showed no such correlation. Conclusion: The use of non-invasive ECG is particularly indicated in the early weeks of pregnancy, while CTG offers superior results during the vernix period. There was no difference in signal quality after the vernix period. The signal quality with ECG was found to be independent of BMI, while the signal quality of CTG deteriorated with increasing BMI.
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Project description:Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided.
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Project description:Non-invasive foetal electrocardiography (fECG) can be obtained at different gestational ages by means of surface electrodes applied on the maternal abdomen. The signal-to-noise ratio (SNR) of the fECG is usually low, due to the small size of the foetal heart, the foetal-maternal compartment, the maternal physiological interferences and the instrumental noise. Even after powerful fECG extraction algorithms, a post-processing step could be required to improve the SNR of the fECG signal. In order to support the researchers in the field, this work presents an annotated dataset of real and synthetic signals, which was used for the study "Wavelet Denoising as a Post-Processing Enhancement Method for Non-Invasive Foetal Electrocardiography" [1]. Specifically, 21 15 s-long fECG, dual-channel signals obtained by multi-reference adaptive filtering from real electrophysiological recordings were included. The annotation of the foetal R peaks by an expert cardiologist was also provided. Recordings were performed on 17 voluntary pregnant women between the 21st and the 27th week of gestation. The raw recordings were also included for the researchers interested in applying a different fECG extraction algorithm. Moreover, 40 10 s-long synthetic non-invasive fECG were provided, simulating the electrode placement of one of the abdominal leads used for the real dataset. The annotation of the foetal R peaks was also provided, as generated by the FECGSYN tool used for the signals' creation. Clean fECG signals were also included for the computation of indexes of signal morphology preservation. All the signals are sampled at 2048 Hz. The data provided in this work can be used as a benchmark for fECG post-processing techniques but can also be used as raw signals for researchers interested in foetal QRS detection algorithms and fECG extraction methods.
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Project description:There is a broad consensus that pulmonary hypertension (PH) is to be diagnosed by right heart catheterization (RHC) and that the most important non-invasive tool is echocardiography. However, the role of simple non-invasive tools in the work-up of PH is not clearly defined. We hypothesized that the use of simple non-invasive techniques may help to guide important decisions in the diagnostics of pulmonary hypertension.We aimed to develop an algorithm with the use of simple, non-invasive tools in order to identify patients with very high or very low likelihood of PH.We retrospectively analyzed all consecutive patients undergoing RHC between 2005 and 2010 in our center and performed logistic regression of simple non-invasive parameters regarding detection and exclusion of PH and derived a two-step algorithm. In a prospective study we evaluated this algorithm between 2011 and 2013.The retrospective cohort consisted of n = 394 patients of which 49% presented with PH. Right axis deviation in the ECG was present in 90/394 patients and had a positive predictive value (PPV) of 93% for PH. The combination of non-right axis deviation, N-terminal pro brain natriuretic peptide (NT-proBNP)<333pg/ml, arterial oxygen saturation (SO2)?95.5% and WHO functional class I-II was present in 69/394 patients and excluded PH with a negative predictive value (NPV) of 96%. The prospective study confirmed these results in a cohort of n = 168 patients (PPV:92%, NPV:97%). Taken together, simple non-invasive tools allowed a prediction regarding the presence or absence of PH in 42% of patients with suspected PH.ECG, NT-proBNP, SO2 and WHO functional class may predict the presence or absence of PH in almost half of the patients with suspected PH, suggesting an important role for these variables in the work-up of patients at risk for PH.NCT01607502.
| S-EPMC5193419 | biostudies-literature
Project description:BackgroundThe discovery of the cell-free foetal DNA (cffDNA) circulating in the maternal plasma enabled prediction of foetal RHD thus eliminating the risks associated with invasive procedures. Non-invasive foetal RHD genotyping has now become the standard approach in developed countries for management of alloimmunised women and is also used for targeted antenatal prophylaxis in non-alloimmunised women.Materials and methodscffDNA was extracted from the plasma of 217 RhD negative pregnant women at a gestational age of 10-34 weeks. The foetal RHD genotype was determined by real-time polymerase chain reaction (real-time PCR) amplification of exons 4, 5 and 10 in duplicates. After an initial 54 samples, foetal typing was carried out with RHD exons 5 and 10 for the remaining samples. CCR5, SRY and RASSF1A genes were used as controls. Results were compared with cord blood serological typing at birth.ResultsOut of the 217 women, 193 were non-immunised and 24 were alloimmunised. A conclusive diagnosis was obtained in 203 samples. Diagnosis was inconclusive in 14 samples; of these, foetal RHD genotype could be resolved in six samples after maternal and paternal RHD genotyping. A 100% diagnostic accuracy, sensitivity and specificity were demonstrated in 209 women who had had a conclusive result. When the inconclusive samples were included, diagnostic accuracy and sensitivity were more than 95% and specificity was 78.95%.DiscussionAnti-D is still the leading cause of haemolytic disease of the foetus and the newborn in India. There is, therefore, a need to establish and develop an algorithm for antenatal RhD negative women in India. The positive results of non-invasive foetal RHD genotyping, from the start of the 10th week of gestation using two RHD exons giving 100% diagnostic accuracy, show promise for routine diagnostic use to the benefit of the antenatal RhD negative Indian population.
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Project description:BackgroundGlobally, the cases of diabetes mellitus (diabetes) have increased in the past three decades, and it is recorded as one of the leading cause of death. This epidemic is a metabolic condition where the body cannot regulate blood glucose, thereby leading to abnormally high blood sugar. Genetic condition plays a significant role to determine a person susceptibility to the condition, a sedentary lifestyle and an unhealthy diet are behaviour that supports the current global epidemic. The complication that arises from diabetes includes loss of vision, peripheral neuropathy, cardiovascular complications and so on. Victims of this condition require constant monitoring of blood glucose which is done by the pricking of the finger. This procedure is painful, inconvenient and can lead to disease infection. Therefore, it is important to find a way to measure blood glucose non-invasively to minimize or eliminate the disadvantages encountered with the usual monitoring of blood glucose.MethodIn this paper, we performed two experiments on 16 participants while electrocardiogram (ECG) data was continuously captured. In the first experiment, participants are required to consume 75 g of anhydrous glucose solution (oral glucose tolerance test) and the second experiment, no glucose solution was taken. We explored statistical and spectral analysis on HRV, HR, R-H, P-H, PRQ, QRS, QT, QTC and ST segments derived from ECG signal to investigate which segments should be considered for the possibility of achieving non-invasive blood glucose monitoring. In the statistical analysis, we examined the pattern of the data with the boxplot technique to reveal the change in the statistical properties of the data. Power spectral density estimation was adopted for the spectral analysis to show the frequency distribution of the data.ResultsHRV segment obtained a statistical score of 81% for decreasing pattern and HR segment have the same statistical score for increasing pattern among the participants in the first quartile, median and mean properties. While ST segment has a statistical score of 81% for decreasing pattern in the third quartile, QT segment has 81% for increasing pattern for the median. From a total change score of 6, ST, QT, PRQ, P-H, HR and HRV obtained 4, 5, 4, 5 and 6 respectively. For spectral analysis, HRV and HR segment scored 81 and 75% respectively. ST, QT, PRQ have 75, 62 and 68% respectively.ConclusionsThe results obtained demonstrate that HR, HRV, PRQ, QT and ST segments under a normal, healthy condition are affected by glucose and should be considered for modelling a system to achieve the possibility of non-invasive blood glucose measurement with ECG.
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Project description:Given the associated risks with transcatheter aortic valve replacement (TAVR), it is crucial to determine how the implant will affect the valve dynamics and cardiac function, and if TAVR will improve or worsen the outcome of the patient. Effective treatment strategies, indeed, rely heavily on the complete understanding of the valve dynamics. We developed an innovative Doppler-exclusive non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics in patients with aortic stenosis in both pre- and post-TAVR status. Clinical Doppler pressure was reduced by TAVR (52.2 ± 20.4 vs. 17.3 ± 13.8 [mmHg], p < 0.001), but it was not always accompanied by improvements in valve dynamics and left ventricle (LV) hemodynamics metrics. TAVR had no effect on LV workload in 4 patients, and LV workload post-TAVR significantly rose in 4 other patients. Despite the group level improvements in maximum LV pressure (166.4 ± 32.2 vs 131.4 ± 16.9 [mmHg], p < 0.05), only 5 of the 12 patients (41%) had a decrease in LV pressure. Moreover, TAVR did not always improve valve dynamics. TAVR did not necessarily result in a decrease (in 9 out of 12 patients investigated in this study) in major principal stress on the aortic valve leaflets which is one of the main contributors in valve degeneration and, consequently, failure of heart valves. Diastolic stresses increased significantly post-TAVR (34%, 109% and 81%, p < 0.001) for each left, right and non-coronary leaflets respectively. Moreover, we quantified the stiffness and material properties of aortic valve leaflets which correspond with the reduced calcified region average stiffness among leaflets (66%, 74% and 62%; p < 0.001; N = 12). Valve dynamics post-intervention should be quantified and monitored to ensure the improvement of patient conditions and prevent any further complications. Improper evaluation of biomechanical valve features pre-intervention as well as post-intervention may result in harmful effects post-TAVR in patients including paravalvular leaks, valve degeneration, failure of TAVR and heart failure.
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Project description:Non-invasive fetal electrocardiography appears to be one of the most promising fetal monitoring techniques during pregnancy and delivery nowadays. This method is based on recording electrical potentials produced by the fetal heart from the surface of the maternal abdomen. Unfortunately, in addition to the useful fetal electrocardiographic signal, there are other interference signals in the abdominal recording that need to be filtered. The biggest challenge in designing filtration methods is the suppression of the maternal electrocardiographic signal. This study focuses on the extraction of fetal electrocardiographic signal from abdominal recordings using a combination of independent component analysis, recursive least squares, and ensemble empirical mode decomposition. The method was tested on two databases, the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations and the PhysioNet Challenge 2013 database. The evaluation was performed by the assessment of the accuracy of fetal QRS complexes detection and the quality of fetal heart rate determination. The effectiveness of the method was measured by means of the statistical parameters as accuracy, sensitivity, positive predictive value, and F1-score. Using the proposed method, when testing on the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database, accuracy higher than 80% was achieved for 11 out of 12 recordings with an average value of accuracy 92.75% [95% confidence interval: 91.19-93.88%], sensitivity 95.09% [95% confidence interval: 93.68-96.03%], positive predictive value 96.36% [95% confidence interval: 95.05-97.17%] and F1-score 95.69% [95% confidence interval: 94.83-96.35%]. When testing on the Physionet Challenge 2013 database, accuracy higher than 80% was achieved for 17 out of 25 recordings with an average value of accuracy 78.24% [95% confidence interval: 73.44-81.85%], sensitivity 81.79% [95% confidence interval: 76.59-85.43%], positive predictive value 87.16% [95% confidence interval: 81.95-90.35%] and F1-score 84.08% [95% confidence interval: 80.75-86.64%]. Moreover, the non-invasive ST segment analysis was carried out on the records from the Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations database and achieved high accuracy in 7 from in total of 12 records (mean values μ < 0.1 and values of ±1.96σ < 0.1).
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