Publications

We aimed to characterize the cerebral hemodynamic response to obstructive sleep apnea/hypopnea events, and evaluate their association to polysomnographic parameters. The characterization of the cerebral hemodynamics in obstructive sleep apnea (OSA) may add complementary information to further the understanding of the severity of the syndrome beyond the conventional polysomnography.Severe OSA patients were studied during night sleep while monitored by polysomnography. Transcranial, bed-side diffuse correlation spectroscopy (DCS) and frequency-domain near-infrared diffuse correlation spectroscopy (NIRS-DOS) were used to follow microvascular cerebral hemodynamics in the frontal lobes of the cerebral cortex. Changes in cerebral blood flow (CBF), total hemoglobin concentration (THC), and cerebral blood oxygen saturation (StO2) were analyzed.We considered 3283 obstructive apnea/hypopnea events from sixteen OSA patients (Age (median, interquartile range) 57 (52-64.5); females 25%; AHI (apnea-hypopnea index) 84.4 (76.1-93.7)). A biphasic response (maximum/minimum followed by a minimum/maximum) was observed for each cerebral hemodynamic variable (CBF, THC, StO2), heart rate and peripheral arterial oxygen saturation (SpO2). Changes of the StO2 followed the dynamics of the SpO2, and were out of phase from the THC and CBF. Longer events were associated with larger CBF changes, faster responses and slower recoveries. Moreover, the extrema of the response to obstructive hypopneas were lower compared to apneas (p < .001).Obstructive apneas/hypopneas cause profound, periodic changes in cerebral hemodynamics, including periods of hyper- and hypo-perfusion and intermittent cerebral hypoxia. The duration of the events is a strong determinant of the cerebral hemodynamic response, which is more pronounced in apnea than hypopnea events.© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society.

JTD Keywords: cerebral hemodynamics, desaturation, diffuse correlation spectroscopy, duration, hypopnea, hypoxemia, near-infrared spectroscopy, optical pathlength, oxygenation, severity, sleep disorder, spectroscopy, tissue, Adult, Airway obstruction, Apnea hypopnea index, Arterial oxygen saturation, Article, Blood oxygen tension, Blood-flow, Brain blood flow, Brain cortex, Cerebral hemodynamics, Controlled study, Diffuse correlation spectroscopy, Disease severity, Female, Frequency, Frontal lobe, Heart rate, Hemodynamics, Hemoglobin, Hemoglobin determination, Human, Humans, Major clinical study, Male, Near infrared spectroscopy, Near-infrared spectroscopy, Obstructive sleep apnea, Oxygen, Periodicity, Polysomnography, Sleep apnea syndromes, Sleep apnea, obstructive, Sleep disorder, Spectroscopy, near-infrared

The association between sarcopenia and prognosis in patients with cirrhosis remains to be determined. In this study, we aimed to quantify the association between sarcopenia and the risk of mortality in patients with cirrhosis, by sex, underlying liver disease etiology, and severity of hepatic dysfunction.PubMed, Web of Science, EMBASE, and major scientific conference sessions were searched without language restriction through 13 January 2021 with additional manual search of bibliographies of relevant articles. Cohort studies of ?100 patients with cirrhosis and ?12 months of follow-up that evaluated the association between sarcopenia, muscle mass and the risk of mortality were included.22 studies with 6965 patients with cirrhosis were included. The pooled prevalence of sarcopenia in patients with cirrhosis was 37.5% overall (95% CI 32.4%-42.8%), higher in male patients, patients with alcohol associated liver disease (ALD), patients with CTP grade C, and when sarcopenia was defined in patients by lumbar 3- skeletal muscle index (L3-SMI). Sarcopenia was associated with the increased risk of mortality in patients with cirrhosis (adjusted-hazard ratio [aHR] 2.30, 95% CI 2.01-2.63), with similar findings in sensitivity analysis of cirrhosis patients without HCC (aHR 2.35, 95% CI 1.95-2.83) and in subgroup analysis by sex, liver disease etiology, and severity of hepatic dysfunction. The association between quantitative muscle mass index and mortality further supports the poor prognosis for patients with sarcopenia (aHR 0.95, 95% CI 0.93-0.98). There was no significant heterogeneity in all analyses.Sarcopenia was highly and independently associated with higher risk of mortality in patients with cirrhosis.The prevalence of sarcopenia and its association with death in patients with cirrhosis remain unclear. This meta-analysis indicated that sarcopenia affected about one-third of patients with cirrhosis and up to 50% in patients with ALD or Child's class C cirrhosis. Sarcopenia was independently associated with about 2-fold higher risk of mortality in patients with cirrhosis. The mortality rate increased with greater severity or longer period of having sarcopenia. Increasing awareness about the importance of sarcopenia in patients with cirrhosis among stakeholders must be prioritized.Copyright © 2021. Published by Elsevier B.V.

JTD Keywords: alcohol associated liver disease, alcohol-associated liver disease, cirrhosis, failure, frailty, impact, list, mass, model, mortality, prognosis, prognostic value, sarcopenia, severe muscle depletion, skeletal muscle index, Alcohol-associated liver disease, Cirrhosis, Liver-transplant candidates, Prognosis, Sarcopenia, Skeletal muscle index

Underpowered trials risk inaccurate results. Recruitment to stroke rehabilitation randomised controlled trials (RCTs) is often a challenge. Statistical simulations offer an important opportunity to explore the adequacy of sample sizes in the context of specific outcome measures. We aimed to examine and compare the adequacy of stroke rehabilitation RCT sample sizes using the Barthel Index (BI) or modified Rankin Scale (mRS) as primary outcomes.We conducted computer simulations using typical experimental event rates (EER) and control event rates (CER) based on individual participant data (IPD) from stroke rehabilitation RCTs. Event rates are the proportion of participants who experienced clinically relevant improvements in the RCT experimental and control groups. We examined minimum sample size requirements and estimated the number of participants required to achieve a number needed to treat within clinically acceptable boundaries for the BI and mRS.We secured 2350 IPD (18 RCTs). For a 90% chance of statistical accuracy on the BI a rehabilitation RCT would require 273 participants per randomised group. Accurate interpretation of effect sizes would require 1000s of participants per group. Simulations for the mRS were not possible as a clinically relevant improvement was not detected when using this outcome measure.Stroke rehabilitation RCTs with large sample sizes are required for accurate interpretation of effect sizes based on the BI. The mRS lacked sensitivity to detect change and thus may be unsuitable as a primary outcome in stroke rehabilitation trials.Copyright © 2021 Elsevier Inc. All rights reserved.

JTD Keywords:  , barthel index, design, increasing value, modified rankin scale, randomised controlled trials, recruitment, reducing waste, reliability, sample size calculations, simulations, stroke rehabilitation, Adult, Article, Barthel index, Calculation, Computer simulation, Controlled study, Effect size, Female, Human, Human experiment, Major clinical study, Male, Modified rankin scale, Numbers needed to treat, Outcome assessment, Randomised controlled trials, Randomized controlled trial, Randomized controlled-trials, Rankin scale, Recruitment, Rehabilitation, Sample size, Sample size calculations, Simulations, Stroke rehabilitation

Introduction: After a stroke, a wide range of deficits can occur with varying onset latencies. As a result, assessing impairment and recovery are enormous challenges in neurorehabilitation. Although several clinical scales are generally accepted, they are time-consuming, show high inter-rater variability, have low ecological validity, and are vulnerable to biases introduced by compensatory movements and action modifications. Alternative methods need to be developed for efficient and objective assessment. In this study, we explore the potential of computer-based body tracking systems and classification tools to estimate the motor impairment of the more affected arm in stroke patients. Methods: We present a method for estimating clinical scores from movement parameters that are extracted from kinematic data recorded during unsupervised computer-based rehabilitation sessions. We identify a number of kinematic descriptors that characterise the patients' hemiparesis (e.g., movement smoothness, work area), we implement a double-noise model and perform a multivariate regression using clinical data from 98 stroke patients who completed a total of 191 sessions with RGS. Results: Our results reveal a new digital biomarker of arm function, the Total Goal-Directed Movement (TGDM), which relates to the patients work area during the execution of goal-oriented reaching movements. The model's performance to estimate FM-UE scores reaches an accuracy of R-2: 0.38 with an error (sigma: 12.8). Next, we evaluate its reliability (r = 0.89 for test-retest), longitudinal external validity (95% true positive rate), sensitivity, and generalisation to other tasks that involve planar reaching movements (R-2: 0.39). The model achieves comparable accuracy also for the Chedoke Arm and Hand Activity Inventory (R-2: 0.40) and Barthel Index (R-2: 0.35). Conclusions: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.

JTD Keywords: interactive feedback, motion classification, motion sensing, multivariate regression, posture monitoring, rehabilitation, stroke, Adult, Aged, Analytic method, Arm movement, Article, Barthel index, Brain hemorrhage, Cerebrovascular accident, Chedoke arm and hand activity inventory, Clinical protocol, Cognitive defect, Computer analysis, Controlled study, Convergent validity, Correlation coefficient, Disease severity, External validity, Female, Fugl meyer assessment for the upper extremity, Functional assessment, Functional status assessment, General health status assessment, Hemiparesis, Human, Interactive feedback, Ischemic stroke, Kinematics, Major clinical study, Male, Mini mental state examination, Motion classification, Motion sensing, Motor analog scale, Movement, Multivariate regression, Muscle function, Posture monitoring, Probability, Recovery, Rehabilitation, Reliability, Retrospective study, Stroke, Stroke patient, Test retest reliability, Therapy, Total goal directed movement, Upper extremities, Upper limb, Upper-limb, Wolf motor function test

Abstract The development of nanostructured plasmonic biosensors has been widely widespread in the last years, motivated by the potential benefits they can offer in integration, miniaturization, multiplexing opportunities, and enhanced performance label-free biodetection in a wide field of applications. Between them, engineering tissues represent a novel, challenging, and prolific application field for nanostructured plasmonic biosensors considering the previously described benefits and the low levels of secreted biomarkers (?pM–nM) to detect. Here, we present an integrated plasmonic nanocrystals-based biosensor using high throughput nanostructured polycarbonate substrates. Metallic film thickness and incident angle of light for reflectance measurements were optimized to enhance the detection of antibody–antigen biorecognition events using numerical simulations. We achieved an enhancement in biodetection up to 3× as the incident angle of light decreases, which can be related to shorter evanescent decay lengths. We achieved a high reproducibility between channels with a coefficient of variation below 2% in bulk refractive index measurements, demonstrating a high potential for multiplexed sensing. Finally, biosensing potential was demonstrated by the direct and label-free detection of interleukin-6 biomarker in undiluted cell culture media supernatants from bioengineered 3D skeletal muscle tissues stimulated with different concentrations of endotoxins achieving a limit of detection (LOD) of ? 0.03 ng/mL (1.4 pM).

JTD Keywords: assay, crystals, drug, label-free biosensing, molecules, plasmonic nanostructures, sensors, skeletal muscle, tissue engineering, Biodetection, Biomarkers, Biosensors, Cell culture, Cells, Chemical detection, Histology, Interleukin-6, Interleukin6 (il6), Label free, Label-free biosensing, Muscle, Nano-structured, Nanocrystals, Plasmonic nanocrystals, Plasmonic nanostructures, Plasmonics, Polycarbonate substrates, Polycarbonates, Refractive index, Sensitivity, Skeletal muscle, Tissue engineering, Tissues engineerings

High ambient temperature and humidity greatly increase the risk of hyperthermia and mortality, particularly in infants, who are especially prone to dehydration. World areas at high risk of heat stress include many of the low-and middle-income countries (LMICs) where most of their inhabitants have no access to air conditioning. This study aimed to design, evaluate, and test a novel low-cost and easy-to-assemble device aimed at preventing the risk of infant hyperthermia in LMICs. The device is based on optimizing negative heat transfer from a small amount of ice and transferring it directly to the infant by airflow of refrigerated air. As a proof of concept, a device was assembled mainly using recycled materials, and its performance was assessed under laboratory-controlled conditions in a climatic chamber mimicking realistic stress conditions of high temperature and humidity. The device, which can be assembled by any layperson using easily available materials, provided sufficient refrigerating capacity for several hours from just 1–2 kg of ice obtained from a domestic freezer. Thus, application of this novel device may serve to attenuate the adverse effects of heat stress in infants, particularly in the context of the evolving climatic change trends. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

JTD Keywords: air conditioning, ambient-temperature, death, heat, heat index, heat shock, heatwave, high ambient temperature, hyperthermia, low-cost refrigeration, low-middle income countries, mortality, negative heat transfer, Air conditioning, Algorithm, Article, Climate change, Cost benefit analysis, Environmental temperature, Heat index, Heat shock, Heat stress, Heat transfer, Heating, Heatwave, High ambient temperature, High temperature, Humidity, Hyperthermia, Low income country, Low-cost refrigeration, Low-middle income countries, Middle income country, Middle-income countries, Negative heat transfer, Prevention study, Refrigeration, Temperature stress, Thawing

Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG.

JTD Keywords: accelerometry, actigraphy, association, biomedical signal processing, index, latency, mhealth, monitoring, pathophysiology, quality, questionnaire, score, sleep apnea, sleep position, smartphone, time, Accelerometry, Biomedical signal processing, Mhealth, Monitoring, Sleep apnea, Sleep position, Smartphone, Supine position

Heart diseases are the leading cause of death in developed countries. Ascertaining the etiology of cardiomyopathies is still a challenge. The objective of this study was to classify cardiomyopathy patients through cardio, respiratory and vascular variability analysis, considering the vascular activity as the input and output of the baroreflex response. Forty-one cardiomyopathy patients (CMP) classified as ischemic (ICM, 24 patients) and dilated (DCM, 17 patients) were analyzed. Thirty-nine elderly control subjects (CON) were used as reference. From the electrocardiographic, respiratory flow, and blood pressure signals, following temporal series were extracted: beat-to-beat intervals (BBI), total respiratory cycle time series (TT), and end– systolic (SBP) and diastolic (DBP) blood pressure amplitudes, respectively. Three-dimensional representation of the cardiorespiratory and vascular activities was characterized geometrically, by fitting a polygon that contains 95% of data, and by statistical descriptive indices. The best classifiers were used to build support vector machine models. The optimal model to classify ICM versus DCM patients achieved 92.7% accuracy, 94.1% sensitivity, and 91.7% specificity. When comparing CMP patients and CON subjects, the best model achieved 86.2% accuracy, 82.9% sensitivity, and 89.7% specificity. These results suggest a limited ability of cardiac and respiratory systems response to regulate the vascular variability in these patients.

JTD Keywords: Time series analysis, Support vector machines, Blood pressure, Sensitivity, Indexes, Electrocardiography, Kernel

Concentrations down to 3 nM of the rhS100A4 protein, associated with human tumor development, have been detected in undiluted urine using an integrated sensor based on microring resonators in the emerging Al2O3 photonic platform. The fabricated microrings were designed for operation in the C-band (λ = 1565 nm) and exhibited a high-quality factor in air of 3.2 × 105. The bulk refractive index sensitivity of the devices was ~100 nm/RIU (for TM polarization) with a limit of detection of ~10−6 RIU. A surface functionalization protocol was developed to allow for the selective binding of the monoclonal antibodies designed to capture the target biomarker to the surface of the Al2O3 microrings. The detection of rhS100A4 proteins at clinically relevant concentrations in urine is a big milestone towards the use of biosensors for the screening and early diagnosis of different cancers. Biosensors based on this microring technology can lead to portable, multiplexed and easy-to-use point of care devices.

JTD Keywords: Distributed feedback lasers, Effective refractive index, Laser coupling, Polarization maintaining fibers, Refractive index, Scanning electron microscopy

Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI. The aim of this work was to study the effect of obstructive event type and duration on the subsequent oxygen desaturation (SaO2) by mixed-effects models. These models allow continuous and categorical independent variables and can model within-subject variability through random effects. The desaturation depth dSaO2, desaturation duration dtSaO2 and desaturation area dSaO2A were analyzed in the 2022 apneas and hypopneas of eight severe patients. A mixed-effects model was defined to account for the influence of event duration (AD), event type, and their interaction on SaO2 parameters. A two-step backward model reduction process was applied for random and fixed effects optimization. The optimum model obtained for dtSaO2 suggests an almost subject-independent proportion increase with AD, which did not significantly change in apneas as compared to hypopneas. The optimum model for dSaO2 reveals a significantly higher increase as a function of AD in apneas than hypopneas. Dependence of on event type and duration was different in every subject, and a subject-specific model could be obtained. The optimum model for SaO2A combines the effects of the other two. In conclusion, the proposed mixed-effects models for SaO2 parameters allow to study the effect of respiratory event duration and type, and to include repeated events within each subject. This simple model can be easily extended to include the contribution of other important factors such as patient severity, sleep stage, sleeping position, or the presence of arousals.

JTD Keywords: Biological system modeling, Sleep apnea, Mathematical model, Indexes, Reduced order systems, Optimization

Hypoxia induced by obstructive sleep apnea (OSA) leads to the deregulation of the autonomic nervous system (ANS), resulting in an abnormally increased sympathetic activity. Since ANS modulation varies throughout the night, notably for each sleep stage, the hypno-gram and heart rate signals of 81 OSA patients were collected during a polysomnography. They were classified as mild-moderate (n=44) or severe (n=37) based on their apnea-hypopnea index (AHI). Spectral heart rate variability (HRV) series were extracted by a time-frequency approach. These series were then averaged for each sleep stage, in order to compare the sympathetic modulation of mild-moderate and severe patients at the following phases: rapid eye movement (REM), S1, S2 and SWS (slow wave sleep). According to normalized power at the low-frequency band (LFnu) values, severe OSA seems to be associated with an increased sympathetic modulation at non-REM sleep. Moreover, a decreased autonomic variability throughout the night may be related to a reduced adaptability of the cardiovascular system, characterizing a more advanced stage of the disease. These results provide further evidence for the role of autonomic alterations induced by hypoxia, suggesting the use of HRV analysis, together with AHI, for the study of OSA severity.

JTD Keywords: Sleep apnea, Heart rate variability, Modulation, Indexes, Standards

Obstructive Sleep Apnea (OSA) is a sleep disorder with a high prevalence in the general population. It is a risk factor for many cardiovascular diseases, and an independent risk factor for cerebrovascular diseases such as stroke. After an apnea episode, both arterial blood pressure and cerebral blood flow velocity change in function of the apnea duration (AD). We hypothesized that the relative excursion in heart rate (AHR), defined as the percentage difference between the maximum and the minimum heart rate values associated to an obstructive apnea event, is also related to AD. In this work we studied the relationship between apnea-related AHR and AD in a population of eight patients with severe OSA. AHR and AD showed a moderate but statistically significant correlation (p <; 0.0001) in a total of 1454 obstructive apneas analyzed. The average heart rate excursion for apneas with AD ≥ 30s (ΔHR = 31.29 ± 6.64%) was significantly greater (p = 0.0002) than for apneas with AD ∈ [10,20)s (ΔHR = 18.14±3.08%). We also observed that patients with similar Apnea-Hypopnea Index (AHI) may exhibit remarkably different distributions of AHR and AD, and that patients with a high AHI need not have a higher average AHR than others with a lower severity index. We conclude that the overall apnea-induced heart rate excursion is partially explained by the duration of apnoeic episodes, and it may be a simple measure of the cardiovascular stress associated with OSA that is not directly reflected in the AHI.

JTD Keywords: Heart rate, Sleep apnea, Correlation, Indexes, Sociology, Blood vessels

Disconnection from mechanical ventilation, called the weaning process, is an additional difficulty in the management of patients in intensive care units (ICU). Unnecessary delays in the discontinuation process and a weaning trial that is undertaken too early are undesirable. In this study, we propose an extubation index based on the power of the respiratory flow signal (Pi). A total of 132 patients on weaning trials were studied: 94 patients with successful trials (group S) and 38 patients who failed to maintain spontaneous breathing and were reconnected (group F). The respiratory flow signals were processed considering the following three stages: a) zero crossing detection of the inspiratory phase, b) inflection point detection of the flow curve during the inspiratory phase, and c) calculation of the signal power on the time instant indicated by the inflection point. The zero crossing detection was performed using an algorithm based on thresholds. The inflection points were marked considering the zero crossing of the second derivative. Finally, the inspiratory power was calculated from the energy contained over the finite time interval (between the instant of zero crossing and the inflection point). The performance of this parameter was evaluated using the following classifiers: logistic regression, linear discriminant analysis, the classification and regression tree, Naive Bayes, and the support vector machine. The best results were obtained using the Bayesian classifier, which had an accuracy, sensitivity and specificity of 87%, 90% and 81% respectively.

JTD Keywords: Bayes methods, Bayesian classifier, Indexes, Logistics, Niobium, Regression tree analysis, Support vector machines, Ventilation

The low pH in the gastric juice of the stomach makes it difficult to fabricate stable and functional all-solid-state pH ISE sensors to sense ischemia, mainly because of anion interference and adhesion problem between the ISE membrane and the electrode surface. In this work, the adhesion of ISE membrane on solid surface at low pH was improved by modifying the surface with a conductive substrate containing hydrophilic and hydrophobic groups. This creates a stable and robust candidate for low pH applications. Moreover, anion interference problem at low pH was solved by integration of all-solid-state ISE and internal reference electrodes on an array. So, the same tendencies of anion interferences for all-solid-state ISE and all-solid-state reference electrodes cancel each other in differential potentiometric detection. The developed sensor presents a novel all-solid-state potentiometric, miniaturized and mass producible pH ISE sensor for detecting ischemia on the stomach tissue on an array designed for endoscopic applications.

JTD Keywords: Index Medicus

Purpose: In proton therapy, complex density heterogeneities within the beam path constitute a challenge to dose calculation algorithms. This might question the reliability of dose distributions predicted by treatment planning systems based on analytical dose calculation. For cases in which substantial dose errors are expected, resorting to Monte Carlo dose calculations might be essential to ensure a successful treatment outcome and therefore the benefit is worth a presumably long computation time. The aim of this study was to define an indicator for the accuracy of dose delivery based on analytical dose calculations in treatment planning systems for small proton therapy fields to identify those patients for which Monte Carlo dose calculation is warranted. Methods: Fourteen patients treated at our facility with small passively scattered proton beams (apertures diameters below 7 cm) were selected. Plans were generated in the XiO treatment planning system in combination with a pencil beam algorithm developed at the Massachusetts General Hospital and compared to Monte Carlo dose calculations. Differences in the dose to the 50% of the gross tumor volume (D50, GTV) were assessed in a field-by-field basis. A simple and fast methodology was developed to quantify the inhomogeneity of the tissue traversed by a single small proton beam using a heterogeneity index (HI) - a concept presented by Plugfelder [Med. Phys. 34, 1506-1513 (2007)10.1118/1. 2710329] for scanned proton beams. Finally, the potential correlation between the error made by the pencil beam based treatment planning algorithm for each field and the level of tissue heterogeneity traversed by the proton beam given by the HI was evaluated. Results: Discrepancies up to 5.4% were found in D50 for single fields, although dose differences were within clinical tolerance levels (<3%) when combining all of the fields involved in the treatment. The discrepancies found for each field exhibited a strong correlation to their associated HI-values (Spearman's ρ = 0.8, p < 0.0001); the higher the level of tissue inhomogeneities for a particular field, the larger the error by the analytical algorithm. With the established correlation a threshold for HI can be set by choosing a tolerance level of 2-3% - commonly accepted in radiotherapy. Conclusions: The HI is a good indicator for the accuracy of proton field delivery in terms of GTV prescription dose coverage when small fields are delivered. Each HI-value was obtained from the CT image in less than 3 min on a computer with 2 GHz CPU allowing implementation of this methodology in clinical routine. For HI-values exceeding the threshold, either a change in beam direction (if feasible) or a recalculation of the dose with Monte Carlo would be highly recommended.

JTD Keywords: Heterogeneities, Heterogeneity index, Monte Carlo, Proton therapy, Small fields

Classification algorithms with unbalanced datasets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine (SVM)-based optimized feature selection method, to select the most relevant features and maintain an accurate and well-balanced sensitivity–specificity result between unbalanced groups. A new metric called the balance index (B) is defined to implement this optimization. The balance index measures the difference between the misclassified data within each class. The proposed optimized feature selection is applied to the classification of patients' weaning trials from mechanical ventilation: patients with successful trials who were able to maintain spontaneous breathing after 48 h and patients who failed to maintain spontaneous breathing and were reconnected to mechanical ventilation after 30 min. Patients are characterized through cardiac and respiratory signals, applying joint symbolic dynamic (JSD) analysis to cardiac interbeat and breath durations. First, the most suitable parameters (C+,C−,σ) are selected to define the appropriate SVM. Then, the feature selection process is carried out with this SVM, to maintain B lower than 40%. The best result is obtained using 6 features with an accuracy of 80%, a B of 18.64%, a sensitivity of 74.36% and a specificity of 82.42%.

JTD Keywords: Support vector machines, Balance index, Sensitivity-specificity balance, Cardiorespiratory interaction, Joint symbolic dynamics, Feature selection, Weaning procedure

Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (T_I), expiratory time (T_E), breathing cycle duration (T_Tot), tidal volume (V_T), inspiratory fraction (T_I/T_Tot), half inspired flow (V_T/T_I), and rapid shallow index (f/V_T), where f is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification.

JTD Keywords: Accuracy, Indexes, Logistics, Regression tree analysis, Support vector machines, Time series analysis, Autoregressive moving average processes, Medical signal processing, Pattern classification, Pneumodynamics, Regression analysis, Sensitivity, Signal classification, Support vector machines, Time series, SVM, T-tube testing, Autoregressive models-with-exogenous input, Autoregressive moving average models, Breathing cycle duration, Classification-and-regression tree, Expiratory time, Extubation process, Half inspired flow, Inspiratory fraction, Inspiratory time, Intensive care units, Linear discriminant analysis, Logistic regression, Rapid shallow index, Respiratory pattern parameter performance, Sensitivity, Spontaneous breathing, Support vector machines, Tidal volume, Time 48 hr, Time series, Weaning process classifiers

This paper presents a novel teleoperation paradigm, the Virtual Robot (VR), focused on facilitating the surgeon tasks in minimally invasive robotic surgery. The VR has been conceived to increase the range of applicability of traditional master slave teleoperation architectures by means of an automatic cooperative behavior that assigns the execution of the ongoing task to the most suitable robot. From the user's point of view, the VR internal operation must be automatic and transparent. A set of evaluation indexes have been developed to obtain the suitability of each robot as well as an algorithm to determine the optimal instant of time to execute a task transfer. Several experiments demonstrate the usefulness of the VR, as well as indicates the next steps of the research.

JTD Keywords: Cameras, Collision avoidance, Indexes, Joints, Robots, Surgery, Trajectory, Medical robotics, Surgery, Telerobotics, VR internal operation, Automatic cooperative behavior, Evaluation indexes, Master slave teleoperation architectures, Minimally invasive robotic surgery, Task transfer, Virtual robot