Time domain reconstruction of sound speed and attenuation in ultrasound computed tomography using full wave inversion

Ultrasound computed tomography (USCT) is a non-invasive imaging technique that provides information about the acoustic properties of soft tissues in the body, such as the speed of sound (SS) and acoustic attenuation (AA). Knowledge of these properties can improve the discrimination between benign and malignant masses, especially in breast cancer studies. Full wave inversion (FWI) methods for image reconstruction in USCT provide the best image quality compared to more approximate methods. Using FWI, the SS is usually recovered in the time domain, and the AA is usually recovered in the frequency domain. Nevertheless, as both properties can be obtained from the same data, it is desirable to have a common framework to reconstruct both distributions. In this work, an algorithm is proposed to reconstruct both the SS and AA distributions using a time domain FWI methodology based on the fractional Laplacian wave equation, an adjoint field formulation, and a gradient-descent method. The optimization code employs a Compute Unified Device Architecture version of the software k-Wave, which provides high computational efficiency. The performance of the method was evaluated using simulated noisy data from numerical breast phantoms. Errors were less than 0.5% in the recovered SS and 10% in the AA. V

Regularization of image reconstruction in ultrasound computed tomography

We propose two regularizations techniques for a bent-ray (BR) tracing algorithm to reconstruct the speed of sound maps of breast tissues in an Ultrasound Computed Tomography (USCT) system. When high frequencies are employed, the use of BR is a good approximation to describe the propagation of the front of the pressure wave. The quantitative accuracy of the images reconstructed with the BR algorithm was evaluated without any kind of regularization, and with two regularization methods. The regularizations were based on some available a priori information, namely the known higher and lower values of the speed of sound expected in the breast tissues, and the maps of the internal structures obtained from the standard reflection ultrasound (US) imaging. The use of the proposed regularizations in the implemented algorithm improves the convergence and quality of the resulting images, although further improvements are still possible. These methods will help obtaining quantitative US images in a reasonable amount of time, expanding the possibilities and applications of this technique

The Efficacy of Auditory Perceptual Training for Tinnitus: A Systematic Review

Auditory perceptual training affects neural plasticity and so represents a potential strategy for tinnitus management. We assessed the effects of auditory perceptual training on tinnitus perception and/or its intrusiveness via a systematic review of published literature. An electronic database search using the keywords ‘tinnitus and learning’ or ‘tinnitus and training’ was conducted, updated by a hand search. The ten studies identified were reviewed independently by two reviewers, data were extracted, study quality was assessed according to a number of specific criteria and the information was synthesised using a narrative approach. Nine out of the ten studies reported some significant change in either self-reported or psychoacoustic outcome measures after auditory training. However, all studies were quality rated as providing low or moderate levels of evidence for an effect. We identify a need for appropriately randomised and controlled studies that will generate high-quality unbiased and generalisable evidence to ascertain whether or not auditory perceptual training has a clinically relevant effect on tinnitus

Gameplay as a source of intrinsic motivation in a randomized controlled trial of auditory training

Background: Previous studies of frequency discrimination training (FDT) for tinnitus used repetitive task-based training programmes relying on extrinsic factors to motivate participation. Studies reported limited improvement in tinnitus symptoms. Purpose: To evaluate FDT exploiting intrinsic motivations by integrating training with computer-gameplay. Methods: Sixty participants were randomly assigned to train on a conventional taskbased training, or one of two interactive game-based training platforms over six weeks. Outcomes included assessment of motivation, tinnitus handicap, and performance on tests of attention. Results: Participants reported greater intrinsic motivation to train on the interactive game-based platforms, yet compliance of all three groups was similar (~70%) and changes in self-reported tinnitus severity were not significant. There was no difference between groups in terms of change in tinnitus severity or performance on measures of attention. Conclusion: FDT can be integrated within an intrinsically motivating game. Whilst this may improve participant experience, in this instance it did not translate to additional compliance or therapeutic benefit

The Role of Circulating Serotonin in the Development of Chronic Obstructive Pulmonary Disease

BACKGROUND: Cigarette smoking is a major risk factor in the development of age-related chronic obstructive pulmonary disease (COPD). The serotonin transporter (SERT) gene polymorphism has been reported to be associated with COPD, and the degree of cigarette smoking has been shown to be a significant mediator in this relationship. The interrelation between circulating serotonin (5-hydroxytyptamine, 5-HT), cigarette smoking and COPD is however largely unknown. The current study aimed at investigating the mediation effects of plasma 5-HT on cigarette smoking-induced COPD and the relation between plasma 5-HT levels and age. METHODS: The association between plasma 5-HT, age and COPD was analyzed in a total of 62 COPD patients (ever-smokers) and 117 control subjects (healthy non-smokers and ever-smokers). Plasma 5-HT levels were measured by enzyme-linked immuno assay (EIA). RESULTS: The elevated plasma 5-HT levels were significantly associated with increased odds for COPD (OR = 1.221, 95% CI = 1.123 to 1.319, p<0.0001). The effect remained significant after being adjusted for age and pack-years smoked (OR = 1.271, 95% CI = 1.134 to 1.408, p = 0.0003). Furthermore, plasma 5-HT was found to mediate the relation between pack-years smoked and COPD. A positive correlation (r = 0.303, p = 0.017) was found between plasma 5-HT levels and age in COPD, but not in the control subjects (r = -0.149, p = 0.108). CONCLUSION: Our results suggest that cigarette smoke-induced COPD is partially mediated by the plasma levels of 5-HT, and that these become elevated with increased age in COPD. The elevated plasma 5-HT levels in COPD might contribute to the pathogenesis of this disease.published_or_final_versio

External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis

Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.Peer reviewe

Deep-learning-driven full-waveform inversion for ultrasound breast imaging

Ultrasound breast imaging is a promising alternative to conventional mammography because it does not expose women to harmful ionising radiation and it can successfully image dense breast tissue. However, conventional ultrasound imaging only provides morphological information with limited diagnostic value. Ultrasound computed tomography (USCT) uses energy in both transmission and reflection when imaging the breast to provide more diagnostically relevant quantitative tissue properties, but it is often based on time-of-flight tomography or similar ray approximations of the wave equation, resulting in reconstructed images with low resolution. Full-waveform inversion (FWI) is based on a more accurate approximation of wave-propagation phenomena and can consequently produce very high resolution images using frequencies below 1 megahertz. These low frequencies, however, are not available in most USCT acquisition systems, as they use transducers with central frequencies well above those required in FWI. To circumvent this problem, we designed, trained, and implemented a two-dimensional convolutional neural network to artificially generate missing low frequencies in USCT data. Our results show that FWI reconstructions using experiment data after the application of the proposed method successfully converged, showing good agreement with X-ray CT and reflection ultrasound-tomography images

A general framework to study positron range distributions

The positron range, that is, the distance from the positron emission point to the annihilation one in beta(+) decay, limits the spatial resolution of PET images. Thus, any realistic simulation of PET acquisitions must include this effect as accurately as possible. Positron range distributions have been computed and compared in the literature. Not all authors present it in the same way. For instance, accumulated range distributions, ID projection of the positrons annihilation coordinates, or angular integrated 3D radial distributions, have been used. Any of these presentations may emphasize a different physical property. Thus it is difficult to perform a meaningful comparison of the results obtained by different authors. The aim of this work is to present a general framework to compare positron range distributions. We use a genetic algorithm to fit the radial, angle integrated, g(3D)(r) distribution of the annihilation points to any positron annihilation distribution chosen as reference. Therefore, given a positron range distribution presented in a certain way, we can obtain the distributions, first fitting g(3D) and then using the relations between distributions. Using this procedure, positron range distributions available in the literature are compared with the ones computed with the simulation package PeneloPE

140 Proceedings of The South African Sugar Technologists &apos; Association- June 1983 THE EFFECT OF GEAR RATIO AND IMPLEMENT SIZE ON THE INFIELD PERFORMANCE OF A 58 kW TRACTOR

The performance of a 58 kW tractor was measured for different gear ratios and implement sizes and a performance index was established. The productivity and fuel consumption were determined and results indicated that considerable savings in fuel consumption and improvements in productivity could be achieved by simple changes in the operating technique

PeneloPET simulations of the Biograph ToF clinical PET scanner

Monte Carlo simulations are widely used in positron emission tomography (PET) for optimizing detector design, acquisition protocols, as well as for developing and assessing corrections and reconstruction methods. PeneloPET is a Monte Carlo code for PET simulations which considers detector geometry, acquisition electronics and materials, and source definitions. PeneloPET is based on PENELOPE, a Monte Carlo code for the simulation of the transport in matter of electrons, positrons and photons, with energies up to 1 GeV. In this work we use PeneloPET to simulate the Biograph TruePoint (B-TP), Biograph TruePoint with TrueV (B-TPTV) and Biograph mCT PET/CT scanners. These configurations consist of three (B-TP) and four (B-TPTV and mCT) rings of 48 detector blocks. Each block comprises a 13 x 13 matrix of 4 x 4 x 20 mm(3) LSO crystals. Simulations were adjusted to reproduce some experimental results from the actual scanners and validated by comparing their predictions to further experimental results. Sensitivity, spatial resolution, noise equivalent count (NEC) rate and scatter fraction (SF) were estimated. The simulations were then employed to estimate the optimum values of system parameters, such as energy and time coincidence windows and to assess the effect of system modifications (such as number of rings) on performance