Three Dimensional Electrical Impedance Tomography

The electrical resistivity of mammalian tissues varies widely and is correlated with physiological function. Electrical impedance tomography (EIT) can be used to probe such variations in vivo, and offers a non-invasive means of imaging the internal conductivity distribution of the human body. But the computational complexity of EIT has severe practical limitations, and previous work has been restricted to considering image reconstruction as an essentially two-dimensional problem. This simplification can limit significantly the imaging capabilities of EIT, as the electric currents used to determine the conductivity variations will not in general be confined to a two-dimensional plane. A few studies have attempted three-dimensional EIT image reconstruction, but have not yet succeeded in generating images of a quality suitable for clinical applications. Here we report the development of a three-dimensional EIT system with greatly improved imaging capabilities, which combines our 64-electrode data-collection apparatus with customized matrix inversion techniques. Our results demonstrate the practical potential of EIT for clinical applications, such as lung or brain imaging and diagnostic screening

CenTime: Event-conditional modelling of censoring in survival analysis

Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on baseline observations. This is particularly useful in healthcare to prognostically predict clinically important events based on patient data. However, existing approaches often have limitations; some focus only on ranking patients by survivability, neglecting to estimate the actual event time, while others treat the problem as a classification task, ignoring the inherent time-ordered structure of the events. Additionally, the effective utilisation of censored samples−data points where the event time is unknown− is essential for enhancing the model's predictive accuracy. In this paper, we introduce CenTime, a novel approach to survival analysis that directly estimates the time to event. Our method features an innovative event-conditional censoring mechanism that performs robustly even when uncensored data is scarce. We demonstrate that our approach forms a consistent estimator for the event model parameters, even in the absence of uncensored data. Furthermore, CenTime is easily integrated with deep learning models with no restrictions on batch size or the number of uncensored samples. We compare our approach to standard survival analysis methods, including the Cox proportional-hazard model and DeepHit. Our results indicate that CenTime offers state-of-the-art performance in predicting time-to-death while maintaining comparable ranking performance. Our implementation is publicly available at https://github.com/ahmedhshahin/CenTime

The systemic inflammatory response, weight loss, performance status and survival in patients with inoperable non-small cell lung cancer

The relationship between the magnitude of systemic inflammatory response and the nutritional/functional parameters in patients with inoperable non-small cell lung cancer were studied. The extent of weight loss, albumin, C-reactive protein, performance status and quality of life was measured in 106 patients with inoperable non-small cell lung cancer (stages III and IV). Survival analysis was performed using the Cox proportional hazard model. The majority of patients were male and almost 80% had elevated circulating C-reactive protein concentrations (>10 mg l−1). On multivariate analysis, age (P=0.012), tumour type (0.002), weight loss (P=0.056), C-reactive protein (P=0.047), Karnofsky performance status (P=0.002) and fatigue (P=0.046) were independent predictors of survival. The patients were grouped according to the magnitude of the C-reactive protein concentrations (⩽10, 11–100 and >100 mg l−1). An increase in the magnitude of the systemic inflammatory response was associated with increased weight loss (P=0.004), reduced albumin concentrations (P=0.001), reduced performance status (P=0.060), increased fatigue (P=0.011) and reduced survival (HR 1.936 95%CI 1.414–2.650, P<0.001). These results indicate that the majority of patients with inoperable non-small cell lung cancer have evidence of a systemic inflammatory response. Furthermore, an increase in the magnitude of the systemic inflammatory response resulted in greater weight loss, poorer performance status, more fatigue and poorer survival

Multifocal VEP (mfVEP) reveals abnormal neuronal delays in diabetes

This pilot study examined the diagnostic role of multifocal visually evoked potentials (mfVEP) in a small number of patients with diabetes. mfVEP, mfERG, and fundus photographs of both eyes of five patients with diabetes, three with nonproliferative diabetic retinopathy (NPDR) and two without NPDR were examined. Thirteen control subjects were also examined. Eighteen zones were constructed from the 60-element mfVEP stimulus array. mfVEP implicit time (IT) and amplitude (SNR) differences were tested between subject groups. We also examined whether there was a difference in function for patches with and without retinopathy in the NPDR group. Lastly, we compared mfVEP and mfERG results in the same patients. We found significant mfVEP IT differences between controls and all patients with diabetes, controls and diabetics without retinopathy, and between controls and diabetics with retinopathy. The subject groups did not differ significantly in terms of SNR. In the retinopathy group, ITs from zones with retinopathy were significantly longer than ITs from zones without retinopathy (P = 0.016). mfERG IT was more frequently abnormal than mfVEP IT. In addition, mfERG hexagons were twice as likely to be abnormal if the corresponding mfVEP zone was abnormal (P < 0.05). mfVEP implicit times are significantly delayed in patients with diabetes even when there is no retinopathy. These cortical response results are similar, albeit considerably less abnormal, than those previously reported for retinal (mfERG) responses in patients with diabetes. A correlation exists between the location of abnormal mfERG hexagons and abnormal mfVEP zones

Psychometric evaluation of a newly developed measure of emotionalism after stroke (TEARS-Q)

Objective: To evaluate, psychometrically, a new measure of tearful emotionalism following stroke: Testing Emotionalism After Recent Stroke – Questionnaire (TEARS-Q). Setting: Acute stroke units based in nine Scottish hospitals, in the context of a longitudinal cohort study of post-stroke emotionalism. Subjects: A total of 224 clinically diagnosed stroke survivors recruited between October 1st 2015 and September 30th 2018, within 2 weeks of their stroke. Measures: The measure was the self-report questionnaire TEARS-Q, constructed based on post-stroke tearful emotionalism diagnostic criteria: (i) increased tearfulness, (ii) crying comes on suddenly, with no warning (iii) crying not under usual social control and (iv) crying episodes occur at least once weekly. The reference standard was presence/absence of emotionalism on a diagnostic, semi-structured post-stroke emotionalism interview, administered at the same assessment point. Stroke, mood, cognition and functional outcome measures were also completed by the subjects. Results: A total of 97 subjects were female, with a mean age 65.1 years. 205 subjects had sustained ischaemic stroke. 61 subjects were classified as mild stroke. TEARS-Q was internally consistent (Cronbach’s alpha 0.87). TEARS-Q scores readily discriminated the two groups, with a mean difference of −7.18, 95% CI (−8.07 to −6.29). A cut off score of 2 on TEARS-Q correctly identified 53 of the 61 stroke survivors with tearful emotionalism and 140 of the 156 stroke survivors without tearful emotionalism. One factor accounted for 57% of the item response variance, and all eight TEARS-Q items acceptably discriminated underlying emotionalism. Conclusion: TEARS-Q accurately diagnoses tearful emotionalism after stroke

Cost-effectiveness of nurse-delivered cognitive behavioural therapy (CBT) compared to supportive listening (SL) for adjustment to multiple sclerosis

Background: Cognitive Behavioural Therapy (CBT) reduces distress in multiple sclerosis, and helps manage adjustment, but cost-effectiveness evidence is lacking. Methods: An economic evaluation was conducted within a multi-centre trial. 94 patients were randomised to either eight sessions of nurse-led CBT or supportive listening (SL). Costs were calculated from the health, social and indirect care perspectives, and combined with additional quality-adjusted life years (QALY) or improvement on the GHQ-12 score, to explore cost-effectiveness at 12 months. Results: CBT had higher mean health costs (£1610, 95% CI, −£187 to 3771) and slightly better QALYs (0.0053, 95% CI, −0.059 to 0.103) compared to SL but these differences were not statistically significant. This yielded £301,509 per QALY improvement, indicating that CBT is not cost-effective according to established UK NHS thresholds. The extra cost per patient improvement on the GHQ-12 scale was £821 from the same perspective. Using a £20,000, threshold, CBT in this format has a 9% probability of being cost effective. Although subgroup analysis of patients with clinical levels of distress at baseline showed an improvement in the position of CBT compared to SL, CBT was still not cost-effective. Conclusion: Nurse delivered CBT is more effective in reducing distress among MS patients compared to SL, but is highly unlikely to be cost-effective using a preference-based measure of health (EQ-5D). Results from a diseasespecif ic measure (GHQ-12) produced comparatively lower Incremental Cost-Effectiveness Ratios, but there is currently no acceptable willingness-to-pay threshold for this measure to guide decision-making

Electrical impedance tomography system: an open access circuit design

BACKGROUND: This paper reports a simple 2-D system for electrical impedance tomography EIT, which works efficiently and is low cost. The system has been developed in the Sharif University of Technology Tehran-Iran (for the author's MSc Project). METHODS: The EIT system consists of a PC in which an I/O card is installed with an external current generator, a multiplexer, a power supply and a phantom with an array of electrodes. The measurement system provides 12-bit accuracy and hence, suitable data acquisition software has been prepared accordingly. The synchronous phase detection method has been implemented for voltage measurement. Different methods of image reconstruction have been used with this instrument to generate electrical conductivity images. RESULTS: The results of simulation and real measurement of the system are presented. The reconstruction programs were written in MATLAB and the data acquisition software in C++. The system has been tested with both static and dynamic mode in a 2-D domain. Better results have been produced in the dynamic mode of operation, due to the cancellation of errors. CONCLUSION: In the spirit of open access publication the design details of this simple EIT system are made available here

Balancing the dilution and oddity effects: Decisions depend on body size

Background Grouping behaviour, common across the animal kingdom, is known to reduce an individual's risk of predation; particularly through dilution of individual risk and predator confusion (predator inability to single out an individual for attack). Theory predicts greater risk of predation to individuals more conspicuous to predators by difference in appearance from the group (the ‘oddity’ effect). Thus, animals should choose group mates close in appearance to themselves (eg. similar size), whilst also choosing a large group. Methodology and Principal Findings We used the Trinidadian guppy (Poecilia reticulata), a well known model species of group-living freshwater fish, in a series of binary choice trials investigating the outcome of conflict between preferences for large and phenotypically matched groups along a predation risk gradient. We found body-size dependent differences in the resultant social decisions. Large fish preferred shoaling with size-matched individuals, while small fish demonstrated no preference. There was a trend towards reduced preferences for the matched shoal under increased predation risk. Small fish were more active than large fish, moving between shoals more frequently. Activity levels increased as predation risk decreased. We found no effect of unmatched shoal size on preferences or activity. Conclusions and Significance Our results suggest that predation risk and individual body size act together to influence shoaling decisions. Oddity was more important for large than small fish, reducing in importance at higher predation risks. Dilution was potentially of limited importance at these shoal sizes. Activity levels may relate to how much sampling of each shoal was needed by the test fish during decision making. Predation pressure may select for better decision makers to survive to larger size, or that older, larger fish have learned to make shoaling decisions more efficiently, and this, combined with their size relative to shoal-mates, and attractiveness as prey items influences shoaling decisions

Matching Models Across Abstraction Levels with Gaussian Processes

Biological systems are often modelled at different levels of abstraction depending on the particular aims/resources of a study. Such different models often provide qualitatively concordant predictions over specific parametrisations, but it is generally unclear whether model predictions are quantitatively in agreement, and whether such agreement holds for different parametrisations. Here we present a generally applicable statistical machine learning methodology to automatically reconcile the predictions of different models across abstraction levels. Our approach is based on defining a correction map, a random function which modifies the output of a model in order to match the statistics of the output of a different model of the same system. We use two biological examples to give a proof-of-principle demonstration of the methodology, and discuss its advantages and potential further applications.Comment: LNCS forma