Annotated real and synthetic datasets for non-invasive foetal electrocardiography post-processing benchmarking

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

Wavelet denoising as a post-processing enhancement method for non-invasive foetal electrocardiography

Background and Objective: The detection of a clean and undistorted foetal electrocardiogram (fECG) from non-invasive abdominal recordings is an open research issue. Several physiological and instrumental noise sources hamper this process, even after that powerful fECG extraction algorithms have been used. Wavelet denoising is widely used for the improvement of the SNR in biomedical signal processing. This work aims to systematically assess conventional and unconventional wavelet denoising approaches for the post-processing of fECG signals by providing evidence of their effectiveness in improving fECG SNR while preserving the morphology of the signal of interest. Methods: The stationary wavelet transform (SWT) and the stationary wavelet packet transform (SWPT) were considered, due to their different granularity in the sub-band decomposition of the signal. Three thresholds from the literature, either conventional (Minimax and Universal) and unconventional, were selected. To this aim, the unconventional one was adapted for the first time to SWPT by trying different approaches. The decomposition depth was studied in relation to the characteristics of the fECG signal. Synthetic and real datasets, publicly available for benchmarking and research, were used for quantitative analysis in terms of noise reduction, foetal QRS detection performance and preservation of fECG morphology. Results: The adoption of wavelet denoising approaches generally improved the SNR. Interestingly, the SWT methods outperformed the SWPT ones in morphology preservation (p<0.04) and SNR (p<0.0003), despite their coarser granularity in the sub-band analysis. Remarkably, the Han et al. threshold, adopted for the first time for fECG processing, provided the best quality improvement (p<0.003). Conclusions: The findings of our systematic analysis suggest that particular care must be taken when selecting and using wavelet denoising for non-invasive fECG signal post-processing. In particular, despite the general noise reduction capability, signal morphology can be significantly altered on the basis of the parameterization of the wavelet methods. Remarkably, the adoption of a finer sub-band decomposition provided by the wavelet packet was not able to improve the quality of the processing

Inferring DNA sequences from mechanical unzipping data: the large-bandwidth case

The complementary strands of DNA molecules can be separated when stretched apart by a force; the unzipping signal is correlated to the base content of the sequence but is affected by thermal and instrumental noise. We consider here the ideal case where opening events are known to a very good time resolution (very large bandwidth), and study how the sequence can be reconstructed from the unzipping data. Our approach relies on the use of statistical Bayesian inference and of Viterbi decoding algorithm. Performances are studied numerically on Monte Carlo generated data, and analytically. We show how multiple unzippings of the same molecule may be exploited to improve the quality of the prediction, and calculate analytically the number of required unzippings as a function of the bandwidth, the sequence content, the elasticity parameters of the unzipped strands

Extensive solitary lymphatic malformation of the liver in a child: a case report and literature review

Intrabdominal lymphatic malformations are rare benign congenital vascular anomalies that account for less than 5% of benign masses in childhood, with an extremely variable clinical presentation. For this reason, although their radiological appearance is usually typical, diagnosis can be challenging and not always immediate. This report describes a unique case of extensive solitary hepatic lymphatic malformation in a 10-year-old boy with both extra- and intraparenchymal development with no associated symptoms. A literature review of reported cases of solitary hepatic lymphatic malformation is also included

Robotic treatment of colorectal endometriosis: technique, feasibility and short-term results

background: Deep infiltrating endometriosis (DIE) is a complex disease that impairs the quality of life and the fertility of women. Since a medical approach is often insufficient, a minimally invasive approach is considered the gold standard for complete disease excision. Roboticassisted surgery is a revolutionary approach, with several advantages compared with traditional laparoscopic surgery. methods: From March 2010 to May 2011, we performed 22 consecutive robotic-assisted complete laparoscopic excisions of DIE endometriosis with colorectal involvement. All clinical data were collected by our team and all patients were interviewed preoperatively and 3 and 6 months post-operatively and yearly thereafter regarding endometriosis-related symptoms. Dysmenorrhoea, dyschezia, dyspareunia and dysuria were evaluated with a 10-point analog rating scale. results: There were 12 patients, with a median larger endometriotic nodule of 35 mm, who underwent segmental resection, and 10 patients, with a median larger endometriotic nodule of 30 mm, who underwent complete nodule debulking by colorectal wall-shaving technique. No laparotomic conversions were performed, nor was any blood transfusion necessary. No intra-operative complications were observed and, in particular, there were no inadvertent rectal perforations in any of the cases treated by the shaving technique. None of the patients had ileostomy or colostomy. No major post-operative complications were observed, except one small bowel occlusion 14 days post-surgery that was resolved in 3 days with medical treatment. Post-operatively, a statistically significant improvement of patient symptoms was shown for all the investigated parameters. conclusions: To our knowledge, this is the first study reporting the feasibility and short-term results and complications of laparoscopic robotic-assisted treatment of DIE with colorectal involvement.We demonstrate that this approach is feasible and safe, without conversion to laparotomy

The X-Gamma Imaging Spectrometer (XGIS) onboard THESEUS

A compact and modular X and gamma-ray imaging spectrometer (XGIS) has been designed as one of the instruments foreseen on-board the THESEUS mission proposed in response to the ESA M5 call. The experiment envisages the use of CsI scintillator bars read out at both ends by single-cell 25 mm 2 Silicon Drift Detectors. Events absorbed in the Silicon layer (lower energy X rays) and events absorbed in the scintillator crystal (higher energy X rays and Gamma-rays) are discriminated using the on-board electronics. A coded mask provides imaging capabilities at low energies, thus allowing a compact and sensitive instrument in a wide energy band (~2 keV up to ~20 MeV). The instrument design, expected performance and the characterization performed on a series of laboratory prototypes are discussed.Comment: To be published in the Proceedings of the THESEUS Workshop 2017 (http://www.isdc.unige.ch/theseus/workshop2017.html), Journal of the Italian Astronomical Society (Mem.SAIt), Editors L. Amati, E. Bozzo, M. Della Valle, D. Gotz, P. O'Brien. Details on the THESEUS mission concept can be found in the white paper Amati et al. 2017 (arXiv:171004638) and Stratta et al. 2017 (arXiv:1712.08153

Arrhythmogenic sites identification in post-ischemic ventricular tachycardia electrophysiological studies by explainable deep learning

Background and objective: Abnormal ventricular potentials (AVPs) in intracardiac electrograms (EGMs) are frequently considered as markers of arrhythmogenic sites in post-ischemic ventricular tachycardia (VT) during electroanatomic mapping (EAM) procedures. Their detection is strongly operator-dependent and time-consuming. This work explores the adoption of explainable deep learning to support the discrimination between physiological EGMs and AVPs. Methods: Three convolutional neural networks were trained to discriminate the target signals based on their time–frequency representations by synchrosqueezed wavelet transform. The efficacy of the method was assessed on 2561 real bipolar EGMs collected from nine post-ischemic VT patients. Results: The proposed approach achieved high performance, with accuracy levels reaching up to 89%. It also demonstrated coherent localization of the arrhythmogenic sites with respect to conventional voltage and local activation time maps. Moreover, by using saliency maps, AVPs discriminant signatures were highlighted at high frequencies (i.e., in the 103–125 Hz band, which was generally relevant for every network), in line with prior evidence. Conclusion: For the first time, deep learning has been successfully applied and robustly evaluated in the field. The proposed approach paves the way to the development of effective AI-driven systems. These systems will enable a faster, trustworthy and operator-independent identification of AVPs in VT EAM procedures. Furthermore, even without injecting prior knowledge in the adopted models, the analysis of saliency maps revealed that CNNs are prone to autonomously select time–frequency ranges of the EGMs in agreement with the current knowledge

Development and tests of a new prototype detector for the XAFS beamline at Elettra Synchrotron in Trieste

The XAFS beamline at Elettra Synchrotron in Trieste combines X-ray absorption spectroscopy and X-ray diffraction to provide chemically specific structural information of materials. It operates in the energy range 2.4-27 keV by using a silicon double reflection Bragg monochromator. The fluorescence measurement is performed in place of the absorption spectroscopy when the sample transparency is too low for transmission measurements or the element to study is too diluted in the sample. We report on the development and on the preliminary tests of a new prototype detector based on Silicon Drift Detectors technology and the SIRIO ultra low noise front-end ASIC. The new system will be able to reduce drastically the time needed to perform fluorescence measurements, while keeping a short dead time and maintaining an adequate energy resolution to perform spectroscopy. The custom-made silicon sensor and the electronics are designed specifically for the beamline requirements.Comment: Proceeding of the 6YRM 12th-14th Oct 2015 - L'Aquila (Italy). Accepted for publication on Journal of Physics: Conference Serie

Dual energy imaging in mammography: Cross-talk study in a Si array detector

Abstract One of the main limitation to the extensive use of breast-cancer screening as a prevention method is the relatively high X-ray dose released to the patient. A new approach is under study in which two quasi-monochromatic beamswith mean energies of 18.0 and 36.0 keV -are produced simultaneously, starting from an X-ray tube, by means of a monochromator based on a pyrolytic graphite crystal. The two beams are superimposed in space. The removal of the energy components with low content of diagnostic information from the spectrum, leads to a reduction of the dose released to patients maintaining (or improving) the image quality. The two quasi-monochromatic beams impinge on the patient and then are detected with a solid-state array detector; the image results as the difference between the transmitted intensities of the two detected beams. In this work, the performances of two different electronic readouts and three pixel widths of a silicon position sensitive array detector are simulated and described in order to minimize cross-talk effects between adjacent pixels. The use of a detector with spectrometric capabilities is necessary to separate, by means of thresholds, the high energy photons from the low energy ones