G.J.J. Warmerdam

Using uterine activity to improve fetal heart rate variability analysis for detection of asphyxia during labor

During labor, uterine contractions can cause temporary oxygen deficiency for the fetus. In case of severe and prolonged oxygen deficiency this can lead to asphyxia. The currently used technique for detection of asphyxia, cardiotocography (CTG), suffers from a low specificity. Recent studies suggest that analysis of fetal heart rate variability (HRV) in addition to CTG can provide information on fetal distress. However, interpretation of fetal HRV during labor is difficult due to the influence of uterine contractions on fetal HRV. The aim of this study is therefore to investigate whether HRV features differ during contraction and rest periods, and whether these differences can improve the detection of asphyxia. To this end, a case-control study was performed, using 14 cases with asphyxia that were matched with 14 healthy fetuses. We did not find significant differences for individual HRV features when calculated over the fetal heart rate without separating contractions and rest periods (p  >  0.30 for all HRV features). Separating contractions from rest periods did result in a significant difference. In particular the ratio between HRV features calculated during and outside contractions can improve discrimination between fetuses with and without asphyxia (p  <  0.04 for three out of four ratio HRV features that were studied in this paper).

Influence of imaging source and panel position uncertainties on the accuracy of 2D/3D image registration of cranial images

PURPOSE To determine the effects of imager source and panel positioning uncertainties on the accuracy of dual intensity-based 2D∕3D image registration of cranial images. METHODS An open source 2D∕3D image registration algorithm has been developed for registration of two orthogonal x-rays to a 3D volumetric image. The initialization files of the algorithm allow for nine degrees of freedom system calibration including x, y, z positions of the source and panel, and three rotational degrees of freedom of the panel about each of the three translational axes. A baseline system calibration was established and a baseline 2D∕3D registration between two orthogonal x-rays and the volumetric image was determined. The calibration file was manipulated to insert errors into each of the nine calibration variables of both imager geometries. Rigid six degrees of freedom registrations were iterated for each panel or source positional error over a range of predetermined calibration errors to determine the resulting error in the registration versus the baseline registration due to the manipulated error of the panel or source calibration. RESULTS Panel and source translational errors orthogonal to the imager∕panel axis introduced the greatest errors in the registration accuracy (4.0 mm geometric error results in up to 2.7 mm registration error). Panel rotation about the imaging direction also resulted in errors of the registration (2.0° geometric error results in up to 1.7° registration error). Differences in magnification and panel tilt and roll, i.e., source and∕or panel translation along the imaging direction and panel rotations about the orthogonal axes had minimal effects on the registration accuracy (below 0.3 mm and 0.2° registration error). CONCLUSIONS While five of the nine imaging system variables were found to have a considerable effect on 2D∕3D registration accuracy of cranial images, the other four variables showed minimal effects. Vendors typically provide simplified calibration procedures which aim to remove encountered geometric uncertainties by accounting for two panel translations. This study shows that at least the five relevant positional variables should be separately calibrated, if accurate alignment is required for 2D∕3D registration.

A Fixed-Lag Kalman Smoother to Filter Power Line Interference in Electrocardiogram Recordings

Objective: Filtering power line interference (PLI) from electrocardiogram (ECG) recordings can lead to significant distortions of the ECG and mask clinically relevant features in ECG waveform morphology. The objective of this study is to filter PLI from ECG recordings with minimal distortion of the ECG waveform. Methods : In this paper, we propose a fixed-lag Kalman smoother with adaptive noise estimation. The performance of this Kalman smoother in filtering PLI is compared to that of a fixed-bandwidth notch filter and several adaptive PLI filters that have been proposed in the literature. To evaluate the performance, we corrupted clean neonatal ECG recordings with various simulated PLI. Furthermore, examples are shown of filtering real PLI from an adult and a fetal ECG recording. Results: The fixed-lag Kalman smoother outperforms other PLI filters in terms of step response settling time (improvements that range from 0.1 to 1 s) and signal-to-noise ratio (improvements that range from 17 to 23 dB). Our fixed-lag Kalman smoother can be used for semi real-time applications with a limited delay of 0.4 s. Conclusion and Significance: The fixed-lag Kalman smoother presented in this study outperforms other methods for filtering PLI and leads to minimal distortion of the ECG waveform.

Reliability of spectral analysis of fetal heart rate variability

Spectral analysis of fetal heart rate variability could provide information on fetal wellbeing. Unfortunately, fetal heart rate recordings are often contaminated by artifacts. Correction of these artifacts affects the outcome of spectral analysis, but it is currently unclear what level of artifact correction facilitates reliable spectral analysis. In this study, a method is presented that estimates the error in spectral powers due to artifact correction, based on the properties of the Continuous Wavelet Transformation. The results show that it is possible to estimate the error in spectral powers. The information about this error makes it possible for clinicians to assess the reliability of spectral analysis of fetal heart rate recordings that are contaminated by artifacts.

The influence of betamethasone on fetal heart rate variability, obtained by non-invasive fetal electrocardiogram recordings.

BACKGROUND Betamethasone is widely used to enhance fetal lung maturation in case of threatened preterm labour. Fetal heart rate variability is one of the most important parameters to assess in fetal monitoring, since it is a reliable indicator for fetal distress. AIM To describe the effect of betamethasone on fetal heart rate variability, by applying spectral analysis on non-invasive fetal electrocardiogram recordings. STUDY DESIGN Prospective cohort study. SUBJECTS Patients that require betamethasone, with a gestational age from 24 weeks onwards. OUTCOME MEASURES Fetal heart rate variability parameters on day 1, 2, and 3 after betamethasone administration are compared to a reference measurement. RESULTS Following 68 inclusions, 12 patients remained with complete series of measurements and sufficient data quality. During day 1, an increase in absolute fetal heart rate variability values was seen. During day 2, a decrease in these values was seen. All trends indicate to return to pre-medication values on day 3. Normalised high- and low-frequency power show little changes during the study period. CONCLUSIONS The changes in fetal heart rate variability following betamethasone administration show the same pattern when calculated by spectral analysis of the fetal electrocardiogram, as when calculated by cardiotocography. Since normalised spectral values show little changes, the influence of autonomic modulation seems minor.

QRS classification and spatial combination for robust heart rate detection in low-quality fetal ECG recordings

Non-invasive fetal electrocardiography (ECG) can be used for prolonged monitoring of the fetal heart rate (FHR). However, the signal-to-noise-ratio (SNR) of non-invasive ECG recordings is often insufficient for reliable detection of the FHR. To overcome this problem, source separation techniques can be used to enhance the fetal ECG. This study uses a physiology-based source separation (PBSS) technique that has already been demonstrated to outperform widely used blind source separation techniques. Despite the relatively good performance of PBSS in enhancing the fetal ECG, PBSS is still susceptible to artifacts. In this study an augmented PBSS technique is developed to reduce the influence of artifacts. The performance of the developed method is compared to PBSS on multi-channel non-invasive fetal ECG recordings. Based on this comparison, the developed method is shown to outperform PBSS for the enhancement of the fetal ECG.

Detection rate of fetal distress using contraction-dependent fetal heart rate variability analysis

OBJECTIVE Monitoring of the fetal condition during labor is currently performed by cardiotocograpy (CTG). Despite the use of CTG in clinical practice, CTG interpretation suffers from a high inter- and intra-observer variability and a low specificity. In addition to CTG, analysis of fetal heart rate variability (HRV) has been shown to provide information on fetal distress. However, fetal HRV can be strongly influenced by uterine contractions, particularly during the second stage of labor. Therefore, the aim of this study is to examine if distinguishing contractions from rest periods can improve the detection rate of HRV features for fetal distress during the second stage of labor. APPROACH We used a dataset of 100 recordings, containing 20 cases of fetuses with adverse outcome. The most informative HRV features were selected by a genetic algorithm and classification performance was evaluated using support vector machines. MAIN RESULTS Classification performance of fetal heart rate segments closest to birth improved from a geometric mean of 70% to 79%. If the classifier was used to indicate fetal distress over time, the geometric mean at 15 minutes before birth improved from 60% to 72%. SIGNIFICANCE Our results show that combining contraction-dependent HRV features with HRV features calculated over the entire fetal heart rate signal improves the detection rate of fetal distress.

Selective heart rate variability analysis to account for uterine activity during labor and improve classification of fetal distress

Cardiotocography (CTG) is currently the most often used technique for detection of fetal distress. Unfortunately, CTG has a poor specificity. Recent studies suggest that, in addition to CTG, information on fetal distress can be obtained from analysis of fetal heart rate variability (HRV). However, uterine contractions can strongly influence fetal HRV. The aim of this study is therefore to investigate whether HRV analysis for detection of fetal distress can be improved by distinguishing contractions from rest periods. Our results from feature selection indicate that HRV features calculated separately during contractions or during rest periods are more informative on fetal distress than HRV features that are calculated over the entire fetal heart rate. Furthermore, classification performance improved from a geometric mean of 69.0% to 79.6% when including the contraction-dependent HRV features, in addition to HRV features calculated over the entire fetal heart rate.Cardiotocography (CTG) is currently the most often used technique for detection of fetal distress. Unfortunately, CTG has a poor specificity. Recent studies suggest that, in addition to CTG, information on fetal distress can be obtained from analysis of fetal heart rate variability (HRV). However, uterine contractions can strongly influence fetal HRV. The aim of this study is therefore to investigate whether HRV analysis for detection of fetal distress can be improved by distinguishing contractions from rest periods. Our results from feature selection indicate that HRV features calculated separately during contractions or during rest periods are more informative on fetal distress than HRV features that are calculated over the entire fetal heart rate. Furthermore, classification performance improved from a geometric mean of 69.0% to 79.6% when including the contraction-dependent HRV features, in addition to HRV features calculated over the entire fetal heart rate.

SU‐E‐J‐22: Implementation and Validation of a 2D‐3D Rigid Registration Algorithm for Proton Gantry and Stereotactic Radiosurgery Systems

PURPOSE To implement and validate the accuracy of an intensity-based 2D to 3D rigid registration algorithm for proton treatment systems. METHODS A 2D-3D rigid registration algorithm (REG23) was previously validated for linac machines. We adapted REG23 for use in both gantry-based and Stereotactic Alignment in Radiosurgery (STAR) proton treatment systems. REG23 registration was run on NVIDIA Quadra600 GPU card using NCC metrics and AMOEBA optimizer and validated using dual orthogonal kV images acquired during cranial target treatments: 66 fractions to 7 patients in gantry system and 135 fractions to 9 patients in STAR. Rectangle ROIs covering the whole region superior to the base-of-skull were used for REG23 registration and the accuracy was evaluated using clinical utilized fiducial-based 2D-3D ray back-projection rigid registration as the baseline. RESULTS For the gantry system, the differences between REG23 and baseline were - 0.01±0.63 mm, 0.43±0.61 mm, 0.12±0.60 mm in the left-right, superior-inferior, and anterior-posterior directions; 0.15±0.44°, 0.11±0.23°, and 0.19±0.37° in pitch, roll, and yaw, respectively. The vector difference was 1.04±0.48 mm. For STAR system, the REG23 results were - 0.34±0.45 mm, -0.10±0.36 mm, -0.38±0.75 mm, -0.14±0.54°, 0.04±0.18°, and 0.03±0.35° different than the baseline in the left-right, superior-inferior, and anterior-posterior directions, pitch, roll, and yaw. The vector difference was 0.93±0.53 mm. The time for REG23 automatic registration was 29.7±9.5 seconds. CONCLUSION We demonstrated that the intensity based 2D-3D rigid registration algorithm REG23 provided sub-millimeter accuracy and better than 0.5° for both gantry-based and STAR proton treatment systems for cranial patients. This accuracy is within patient setup tolerance for current fractionated proton treatment systems. Given its accuracy and efficiency, we believe REG23 has great potential for clinical utilization in proton radiation therapy by replacing the implanted fiducial or anatomic feature based patient setup method. The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center.

TH‐C‐BRA‐10: An Open‐Source 2D/3D‐Image‐Registration Algorithm: Cranial Image Guided Radiotherapy

Purpose: To determine the robustness and accuracy of an open source 2D/3D GPU accelerated image registration algorithm in the context of cranial image guided radiotherapy.Methods: The open source 2D/3D image registration algorithm, Reg23, has been released under the GNU license. The algorithm utilizes an iterative digitally reconstructedradiograph(DRR) approach to the image registration problem. The DRR generator is accelerated on a GPU to rapidly iterate the optimization process. Multiple cost functions are supported and were analyzed. Robustness was determined by comparing a baseline set of orthogonal kV images of a cranial phantom with a predetermined isocenter to the planned isocenter in the CTimage set and introducing more than 6000 combinations of rotations and translation to the position of the isocenter in the CT. Accuracy and time efficiency of various cost function were analyzed for the virtual patient shifts. Furthermore, a set of 43 experimental orthogonal images were acquired with a linac mounted kV imaging system of predetermined physical shifts which were compared to the results of the Reg23 algorithm. Results: The Reg23 algorithm was found to be accurate to 0.04±0.02mm for the virtual isocenter shifts and 0.23±0.40mm for real images compared to the CBCT registration results. Time to solution could be reduced from >70 s to < 40 s without a significant change in the algorithm accuracy depending upon the cost function employed. Conclusions: The Reg23 algorithm is robust and sensitive to sub‐mm variations of virtual shifts of the isocenter position. The Normalized Cross Correlation (NCC) cost function was determined to be most accurate and fastest for cranial image registration. For real experimental data, the Gradent Difference (GD) cost function was most accurate and both GD and NCC delivered results accurate to within 0.5 mm and 0.4° when compared to CBCT/CT registrations.