Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Easily computable quality metrics for measured medical data at point-of-care are important for imaging technologies involving offline reconstruction. Accordingly, we developed a new data quality metric for <jats:italic>in vivo</jats:italic> transversely-isotropic (TI) magnetic resonance elastography (MRE) based on a generalization of the widely accepted octahedral shear-strain calculation. The metric uses MRE displacement data and an estimate of the TI property field to yield a ‘stability map’ which predicts regions of low versus high accuracy in the resulting material property reconstructions. We can also calculate an average TI parameter stability (TIPS) score over all voxels in a region of interest for a given measurement to indicate how reliable the recovered mechanical property estimate for the region is expected to be. The calculation is rapid and places little demand on computing resources compared to the computationally intensive material property reconstruction from non-linear inversion (TI-NLI) of displacement fields, making it ideal for point-of-care evaluation of data quality. We test the predictions of the stability map for both simulated phantoms and <jats:italic>in vivo</jats:italic> human brain data. We used a range of different displacement datasets from vibrations applied in the anterior-posterior (AP), left-right (LR) and combined AP + LR directions. The TIPS and variability maps (noise sensitivity or variation from the mean of repeated MRE scans) were consistently anti-correlated. Notably, Spearman correlation coefficients ∣R∣&gt;0.6 were found between variability and TIPS score for individual white matter tracts with <jats:italic>in vivo</jats:italic> data. These observations demonstrate the reliability and promise of this data quality metric to screen data rapidly in realistic clinical MRE applications.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Understanding the local dynamics of a neural network relies heavily on local field potential and cell-field interaction. But it is still unclear how local the local potential is and what kinds of consequences the trans-membrane current flow and produced electric field have on the local neural fiber. Mimicking signal transmission in neighboring nerve fiber, a simulation model is built to analyze local behavior due to trans-membrane current, cell-field interactions, and their repercussions on the bundled fiber system. Simulation studies reveal that depending on the coupling parameters, activity in one fiber can depolarize or hyper-polarize adjacent fibers. The suggested cell-field interaction model was tested using an orientation-selective coupled retinal ganglion cell network, which was compared to its uncoupled counterpart. The proposed work has been used to model and simulate local signal dynamics in a bundled fiber system of an orientation-selective RGC network due to cell-field interaction, as well as to gain insight into the possible significance of dendritic fiber coupling in orientation selectivity bandwidth adjustment.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Uncontrolled hemorrhage is a leading cause of death in trauma situations. Developing solutions to automate hemorrhagic shock resuscitation may improve the outcomes for trauma patients. However, testing and development of automated solutions to address critical care interventions, oftentimes require extensive large animal studies for even initial troubleshooting. The use of accurate laboratory or in-silico models may provide a way to reduce the need for large animal datasets. Here, a tabletop model, for use in the development of fluid resuscitation with physiologically relevant pressure-volume responsiveness for high throughput testing, is presented. The design approach shown can be applied to any pressure-volume dataset through a process of curve-fitting, 3D modeling, and fabrication of a fluid reservoir shaped to the precise curve fit. Two case studies are presented here based on different resuscitation fluids: whole blood and crystalloid resuscitation. Both scenarios were derived from data acquired during porcine hemorrhage studies, used a pressure-volume curve to design and fabricate a 3D model, and evaluated to show that the test platform mimics the physiological data. The vessels produced based on data collected from pigs infused with whole blood and crystalloid were able to reproduce normalized pressure-volume curves within one standard deviation of the porcine data with mean residual differences of 0.018 and 0.016, respectively. This design process is useful for developing closed-loop algorithms for resuscitation and can simplify initial testing of technologies for this life-saving medical intervention.</jats:p>

<jats:title>Abstract</jats:title> <jats:p> <jats:italic>Objective.</jats:italic> To propose novel SSVEP classification methodologies using deep neural networks (DNNs) and improve performances in single-channel and user-independent brain-computer interfaces (BCIs) with small data lengths. <jats:italic>Approach.</jats:italic> We propose the utilization of filter banks (creating sub-band components of the EEG signal) in conjunction with DNNs. In this context, we created three different models: a recurrent neural network (FBRNN) analyzing the time domain, a 2D convolutional neural network (FBCNN-2D) processing complex spectrum features and a 3D convolutional neural network (FBCNN-3D) analyzing complex spectrograms, which we introduce in this study as possible input for SSVEP classification. We tested our neural networks on three open datasets and conceived them so as not to require calibration from the final user, simulating a user-independent BCI. <jats:italic>Results.</jats:italic> The DNNs with the filter banks surpassed the accuracy of similar networks without this preprocessing step by considerable margins, and they outperformed common SSVEP classification methods (SVM and FBCCA) by even higher margins. <jats:italic>Conclusion and significance.</jats:italic> Filter banks allow different types of deep neural networks to more efficiently analyze the harmonic components of SSVEP. Complex spectrograms carry more information than complex spectrum features and the magnitude spectrum, allowing the FBCNN-3D to surpass the other CNNs. The performances obtained in the challenging classification problems indicates a strong potential for the construction of portable, economical, fast and low-latency BCIs.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Preventing bone stress injuries (BSI) requires a deep understanding of the condition’s underlying causes and risk factors. Subject-specific computer modeling studies of gait mechanics, including the effect of changes in running speed, stride length, and landing patterns on tibial stress injury formation can provide essential insights into BSI prevention. This study aimed to computationally examine the effect of different exercise protocols on tibial fatigue life in male and female runners during prolonged walking and running at three different speeds. To achieve these aims, we combined subject-specific magnetic resonance imaging (MRI), gait data, finite element analysis, and a fatigue life prediction algorithm, including repair and adaptation’s influence. The algorithm predicted a steep increase in the likelihood of developing a BSI within the first 40 days of activity. In five of the six subjects simulated, faster running speeds corresponded with higher tibial strains and higher probability of failure. Our simulations also showed that female subjects had a higher mean peak probability of failure in all four gait conditions than the male subjects studied. The approach used in this study could lay the groundwork for studies in larger populations and patient-specific clinical tools and decision support systems to reduce BSIs in athletes, military personnel, and other active individuals.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We conduct a simulation-based study to investigate the impact of a dynamic temperature environment on the characteristics of microwave-induced thermoacoustic signals. We investigate thermoacoustic signals that are generated using an interstitial microwave ablation antenna powered by a microsecond pulsed microwave source. Two temperature regimes are examined: first, a spatially uniform temperature throughout the medium to experimentally validate the simulation model, and second, the realistic, spatially nonuniform temperature profiles that arise during microwave ablation. We employ a multi-physics model that considers electromagnetics, heat transfer, and acoustic physics to simulate the coupled processes of microwave absorption and heating of the medium and thermoacoustic signal generation and propagation. An interstitial coaxial antenna is used to generate microsecond microwave pulses that simultaneously induce microwave heating and excite thermoacoustic signals via microwave pulse absorption. We find that thermoacoustic signal characteristics are highly temperature-dependent and thus change significantly within an environment where temperature varies through space and time. Furthermore, the temperature-dependent properties within the active region of the antenna drive the evolution of thermoacoustic signal characteristics. Temperature-dependent thermoacoustic signal characteristics can be exploited to track the progress of microwave ablation. Consequently, microwave-induced thermoacoustic imaging is a promising method for monitoring microwave ablation in real-time.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The Gleason grade system is the main standard to quantify the aggressiveness and progression of prostate cancer. Currently, exists a high disagreement among experts in the diagnosis and stratification of this disease. Deep learning models have emerged as an alternative to classify and support experts automatically. However, these models are limited to learn a rigid stratification rule that can be biased during training to a specific observer. Therefore, this work introduces an embedding representation that integrates an auxiliary task learning to deal with the high inter and intra appearance of the Gleason system. The proposed strategy implements as a main task a triplet loss scheme that builds a feature embedding space with respect to batches of positive and negative histological training patches. As an auxiliary task is added a cross-entropy that helps with inter-class variability of samples while adding robust representations to the main task. The proposed approach shows promising results achieving an average accuracy of 66% and 64%, for two experts without statistical difference. Additionally, reach and average accuracy of 73% in patches where both pathologists are agree, showing the robustness patterns learning from the approach.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Quantification of physiological parameters in preclinical pharmacokinetic studies based on nuclear imaging requires the monitoring of arterial radioactivity over time, known as the arterial input function (AIF). Continuous derivation of the AIF in rodent models is very challenging because of the limited blood volume available for sampling. To address this challenge, an Ultra High Sensitivity Blood Counter (UHS-BC) was developed. The device detects beta particles in real-time using silicon photodiodes, custom low-noise electronics, and 3D-printed plastic cartridges to hold standard catheters. Two prototypes were built and characterized in two facilities. Sensitivities up to 39% for <jats:sup>18</jats:sup>F and 58% for <jats:sup>11</jats:sup>C-based positron emission tomography (PET) tracers were demonstrated. <jats:sup>99m</jats:sup>Tc and <jats:sup>125</jats:sup>I based Single Photon Emission Computed Tomography (SPECT) tracers were detected with greater than 3% and 10% sensitivity, respectively, opening new applications in nuclear imaging and fundamental biology research. Measured energy spectra show all relevant peaks down to a minimum detectable energy of 20 keV. The UHS-BC was shown to be highly reliable, robust towards parasitic background radiation and electromagnetic interference in the PET or MRI environment. The UHS-BC provides reproducible results under various experimental conditions and was demonstrated to be stable over days of continuous operation. Animal experiments showed that the UHS-BC performs accurate AIF measurements using low detection volumes suitable for small animal models in PET, SPECT and PET/MRI investigations. This tool will help to reduce the time and number of animals required for pharmacokinetic studies, thus increasing the throughput of new drug development.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Cardiovascular diseases are the major cause of sudden death. Brugada syndrome is an inherited rare disease, that leads to death due to ventricular fibrillation (VF). Brugada Syndrome is related to mutations in the genes that encode SCN5A, a subunit of sodium ion channel (NaV). This computational study investigates the mechanism of loss of function gene mutation (SCN5A L812Q) in sodium ion channel that leads to spiral wave and further develops into VF in an epicardial tissue with homozygous condition. Study was made on wild type, L812Q heterozygous mutated and homozygous mutated ventricular tissues. Ten Tusscher human ventricular cell model (TP06) was used for the simulation study. VF is developed when a spiral wave that causes ventricular arrhythmia breaks. This leads to the formation of multiple spiral waves that are activated on different regions of the ventricles called wave break. This is observed in the epicardial tissue with homozygous condition as the effect of SCN5A L812Q gene mutation. This indicates that VF occurs in the SCN5A L812Q gene mutated homozygous ventricular epicardial tissue that may further lead to Brugada syndrome.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Transmembrane ion transport under tonicity imbalance has been investigated using a combination of low frequency-electrical impedance spectroscopy (LF-EIS) and improved ion transport model, by considering the cell diameter <jats:italic>d</jats:italic> [m] and the initial intracellular ion concentration <jats:italic>c</jats:italic> <jats:sub> <jats:italic>in</jats:italic> </jats:sub> [mM] as a function of tonicity expressed by sucrose concentration <jats:italic>c</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> [mM]. The transmembrane ion transport is influenced by extracellular tonicity conditions, leading to a facilitation/inhibition of ion passage through the cell membrane. The transmembrane transport coefficient <jats:italic>P</jats:italic> [m s<jats:sup>−1</jats:sup>], which represents the ability of transmembrane ion transport, is calculated by the extracellular ion concentrations obtained by improved ion transport model and LF-EIS measurement. <jats:italic>P</jats:italic> is calculated as 4.11 × 10<jats:sup>−6</jats:sup> and 3.44 × 10<jats:sup>−6</jats:sup> m s<jats:sup>−1</jats:sup> at <jats:italic>c</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> of 10 and 30 mM representing hypotonic condition, 2.44 × 10<jats:sup>−6</jats:sup> m s<jats:sup>−1</jats:sup> at <jats:italic>c</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> of 50 mM representing isotonic condition, and 3.68 × 10<jats:sup>−6</jats:sup>, 5.16 × 10<jats:sup>−6</jats:sup> , 9.51 × 10<jats:sup>−6</jats:sup>, and 14.89 × 10<jats:sup>−6</jats:sup> m s<jats:sup>−1</jats:sup> at <jats:italic>c</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> of 75, 100, 125 and 150 mM representing hypertonic condition. The LF-EIS results indicate that the transmembrane ion transport is promoted under hypertonic and hypotonic conditions compared to isotonic condition. To verify the LF-EIS results, fluorescence intensity <jats:italic>F</jats:italic> [–] of extracellular potassium ions is observed to obtain the temporal distribution of average potassium ion concentration within the region of 3.6 <jats:italic>μ</jats:italic>m from cell membrane interface <jats:italic>c</jats:italic> <jats:sub> <jats:italic>ROI</jats:italic> </jats:sub> [mM]. The slopes of ∆<jats:italic>c</jats:italic> <jats:sub> <jats:italic>ROI</jats:italic> </jats:sub> <jats:italic>/c</jats:italic> <jats:sub> <jats:italic>ROI</jats:italic>1</jats:sub> to time <jats:italic>t</jats:italic> are 0.0003, 0.0002, and 0.0006 under hypotonic, isotonic, and hypertonic conditions, where <jats:italic>c</jats:italic> <jats:sub> <jats:italic>ROI</jats:italic>1</jats:sub> denotes initial <jats:italic>c</jats:italic> <jats:sub> <jats:italic>ROI</jats:italic> </jats:sub>, which shows the same tendency with LF-EIS result that is verified by the potassium ion fluorescence observation.</jats:p>