Drinking microstructure in humans: A proof of concept study of a novel drinkometer in healthy adults.

Microstructural analysis of ingestion provides valuable insight into the roles of chemosensory signals, nutritional content, postingestive events, and physiological state. Our aim was to develop a novel drinkometer for humans to measure detailed aspects of ingestion of an entire liquid meal or drinking session. The drinkometer records, in high definition (1 kHz), the weight of a fluid reservoir from which participants drink via a tube. An ultrasonic sensor measures the height of the fluid to derive density. Drinking speed over time can be displayed as a waveform. The smallest units of ingestion are sucks, which are organized in bursts. By applying probability density functions (PDF) on loge-transformed inter-suck intervals (ISI), an optimal burst-pause criterion (PC) can be identified. Information on ingestive volumes, rates, and durations can be then computed for the entire session, as well as for sucks and bursts. We performed a validation study on 12 healthy adults in overnight-fasted and in non-fasted states in 16 drinking sessions with 8 concentrations of sucrose (0-280 mM) presented in a blinded and random fashion. PDF determined PC = 2.9 s as optimal. Two-way RM-ANOVA revealed that total caloric intake during a drinking session depended on sucrose concentration (P < .001) and fasted state (P = .006); total drinking time (P < .001), total consumed volume (P = .003), number of sucks in total (P < .001), number of sucks per burst (P = .03), and burst duration (P = .02) were significantly influenced by fasting. In contrast, volume per suck (P = .002), suck speed (P < .001), and maximal speed per suck (P < .001) depended on sucrose concentration. We conclude that the novel drinkometer is able to detect differences in microstructural parameters of drinking behavior dependent on different motivational states, thus, adds to the technological toolbox used to explore human ingestive behavior.

Selective retina therapy enhanced with optical coherence tomography for dosimetry control and monitoring: a proof of concept study.

Selective treatment of the retinal pigment epithelium (RPE) by using short-pulse lasers leads to a less destructive treatment for certain retinal diseases in contrast to conventional photocoagulation. The introduction of selective retina therapy (SRT) to clinical routine is still precluded by the challenges to reliably monitor treatment success and to automatically adjust dose within the locally varying therapeutic window. Combining micrometer-scale depth resolving capabilities of optical coherence tomography (OCT) with SRT can yield real-time information on the laser-induced changes within the RPE after a laser pulse or even during treatment with a laser pulse train. In the present study, SRT and OCT were combined to treat ex-vivo porcine eyes demonstrating closed-loop dose-control. We found a reliable correlation of specific signal changes in time resolved OCT images and physiological lesions in the RPE. First experiments, including 23 porcine eyes, prove the feasibility of the novel treatment concept.

Automatic hand phantom map generation and detection using decomposition support vector machines.

BACKGROUND: There is a need for providing sensory feedback for myoelectric prosthesis users. Providing tactile feedback can improve object manipulation abilities, enhance the perceptual embodiment of myoelectric prostheses and help reduce phantom limb pain. Many amputees have referred sensation from their missing hand on their residual limbs (phantom maps). This skin area can serve as a target for providing amputees with non-invasive tactile sensory feedback. One of the challenges of providing sensory feedback on the phantom map is to define the accurate boundary of each phantom digit because the phantom map distribution varies from person to person. METHODS: In this paper, automatic phantom map detection methods based on four decomposition support vector machine algorithms and three sampling methods are proposed, complemented by fuzzy logic and active learning strategies. The algorithms and methods are tested on two databases: the first one includes 400 generated phantom maps, whereby the phantom map generation algorithm was based on our observation of the phantom maps to ensure smooth phantom digit edges, variety, and representativeness. The second database includes five reported phantom map images and transformations thereof. The accuracy and training/ classification time of each algorithm using a dense stimulation array (with 100 [Formula: see text] 100 actuators) and two coarse stimulation arrays (with 3 [Formula: see text] 5 and 4 [Formula: see text] 6 actuators) are presented and compared. RESULTS: Both generated and reported phantom map images share the same trends. Majority-pooling sampling effectively increases the training size, albeit introducing some noise, and thus produces the smallest error rates among the three proposed sampling methods. For different decomposition architectures, one-vs-one reduces unclassified regions and in general has higher classification accuracy than the other architectures. By introducing fuzzy logic to bias the penalty parameter, the influence of pooling-induced noise is reduced. Moreover, active learning with different strategies was also tested and shown to improve the accuracy by introducing more representative training samples. Overall, dense arrays employing one-vs-one fuzzy support vector machines with majority-pooling sampling have the smallest average absolute error rate (8.78% for generated phantom maps and 11.5% for reported and transformed phantom map images). The detection accuracy of coarse arrays was found to be significantly lower than for dense array. CONCLUSIONS: The results demonstrate the effectiveness of support vector machines using a dense array in detecting refined phantom map shapes, whereas coarse arrays are unsuitable for this task. We therefore propose a two-step approach, using first a non-wearable dense array to detect an accurate phantom map shape, then to apply a wearable coarse stimulation array customized according to the detection results. The proposed methodology can be used as a tool for helping haptic feedback designers and for tracking the evolvement of phantom maps.

Motion-invariant SRT treatment detection from direct M-scan OCT imaging.

PURPOSE: Selective retina therapy (SRT) is a laser treatment targeting specific posterior retinal layers. It is focused on inducing damage to the retinal pigment epithelium (RPE), while sparing other retinal tissue compared to traditional photocoagulation. However, the targeted RPE layer is invisible with most imaging modalities and induced SRT lesions cannot be monitored. In this work, imaging scans acquired from an experimental setup that couples the SRT laser beam with an optical coherence tomography (OCT) beam are analyzed in order to evaluate the treatment as they occur. METHODS: We isolated a small part of the time-resolved scan corresponding to the end of the treatment, for which we have microscopic evidence of the SRT outcome. We then use a convolutional neural network to correspond each scan to the treatment result. We explore which aspects of the scan convey more valuable information for a robust therapy evaluation. By only using this adequately small part, we can achieve an online estimation, while being resilient to eye movement. RESULTS: The available dataset consists of time- resolved OCT scans of 98 ex vivo porcine eyes, treated with different energy levels. The proposed method yields high performance in the task of predicting whether the applied energy was adequate for SRT treatment, by focusing on the immediate OCT signal acquired during treatment time. CONCLUSIONS: We propose a strategy toward online noninvasive SRT treatment assessment, able to provide a satisfying evaluation of a treatment status, that therefore could be used for the planning of the treatment continuation.

Automated robust test framework for electrical impedance tomography.

An automated test system and procedure is proposed, designed to enable systematic testing of electrical impedance tomography (EIT) devices. The system is designed to calculate reliable, repeatable and accurate performance figures of merit of an EIT system using a saline phantom and an industrial robot arm. Applications of the test system are to compare EIT devices against requirements, or to help optimize a device for its operating parameters. A test methodology and sample test results are presented to illustrate its use. The system is used to compare image quality and contrast detection for a range of stimulation and measurement patterns, and results show the best images when the pair of current injection electrodes is spaced between 45 and 170 degrees on a tank. Finally, we propose a classification of the object detection errors, which can facilitate comparison of EIT instrument specifications.

Differential healing response attributed to culprit lesions of patients with acute coronary syndromes and stable coronary artery after implantation of drug-eluting stents: an optical coherence tomography study.

BACKGROUND: Pathology studies have shown delayed arterial healing in culprit lesions of patients with acute coronary syndrome (ACS) compared with stable coronary artery disease (CAD) after placement of drug-eluting stents (DES). It is unknown whether similar differences exist in-vivo during long-term follow-up. Using optical coherence tomography (OCT), we assessed differences in arterial healing between patients with ACS and stable CAD five years after DES implantation. METHODS AND RESULTS: A total of 88 patients comprised of 53 ACS lesions with 7864 struts and 35 stable lesions with 5298 struts were suitable for final OCT analysis five years after DES implantation. The analytical approach was based on a hierarchical Bayesian random-effects model. OCT endpoints were strut coverage, malapposition, protrusion, evaginations and cluster formation. Uncovered (1.7% vs. 0.7%, adjusted p=0.041) or protruding struts (0.50% vs. 0.13%, adjusted p=0.038) were more frequent among ACS compared with stable CAD lesions. A similar trend was observed for malapposed struts (1.33% vs. 0.45%, adj. p=0.072). Clusters of uncovered or malapposed/protruding struts were present in 34.0% of ACS and 14.1% of stable patients (adj. p=0.041). Coronary evaginations were more frequent in patients with ST-elevation myocardial infarction compared with stable CAD patients (0.16 vs. 0.13 per cross section, p=0.027). CONCLUSION: Uncovered, malapposed, and protruding stent struts as well as clusters of delayed healing may be more frequent in culprit lesions of ACS compared with stable CAD patients late after DES implantation. Our observational findings suggest a differential healing response attributable to lesion characteristics of patients with ACS compared with stable CAD in-vivo.

Evaluation and real-time monitoring of data quality in electrical impedance tomography.

Electrical impedance tomography (EIT) is a noninvasive method to image conductivity distributions within a body. One promising application of EIT is to monitor ventilation in patients as a real-time bedside tool. Thus, it is essential that an EIT system reliably provide meaningful information, or alert clinicians when this is impossible. Because the reconstructed images are very sensitive to system instabilities (primarily from electrode connection variability and movement), EIT systems should continuously monitor and, if possible, correct for such errors. Motivated by this requirement, we describe a novel approach to quantitatively measure EIT data quality. Our goals are to define the requirements of a data quality metric, develop a metric q which meets these requirements, and an efficient way to calculate it. The developed metric q was validated using data from saline tank experiments and a retrospective clinical study. Additionally, we show that q may be used to compare the performance of EIT systems using phantom measurements. Results suggest that the calculated metric reflects well the quality of reconstructed EIT images for both phantom and clinical data. The proposed measure can thus be used for real-time assessment of EIT data quality and, hence, to indicate the reliability of any derived physiological information.

Long-term vascular healing in response to sirolimus- and paclitaxel-eluting stents: an optical coherence tomography study.

OBJECTIVES: This study sought to assess stent strut coverage, malapposition, protrusion, and coronary evaginations as markers of healing 5 years after implantation of sirolimus-eluting stents (SES) and paclitaxel-eluting stents (PES), by optical coherence tomography (OCT). BACKGROUND: Early-generation drug-eluting stents have been shown to delay vascular healing. METHODS: A total of 88 event-free patients with 1 randomly selected lesion were suitable for final OCT analysis 5 years after drug-eluting stent implantation. The analytical approach was based on a hierarchical Bayesian random-effects model. RESULTS: OCT analysis was performed at 5 years in 41 SES lesions with 6,380 struts, and in 47 PES lesions with 6,782 struts. A total of 196 struts were uncovered in SES (1.5%) compared with 185 struts in PES lesions (1.0%, 95% credibility interval [CrI]: 0.5 to 1.6; p = 0.32). Malapposed struts were present in 1.2% of SES compared with 0.7% of PES struts (0.7%, 95% CrI: 0.03 to 1.6; p = 0.23). Protruding struts were more frequent among SES (n = 114; 0.8%) than PES lesions (n = 24; 0.1%, 95% CrI: 0.3 to 1.3; p < 0.01). Coronary evaginations were more common among SES- than PES-treated lesions (17 vs. 7 per 100 cross sections, p = 0.003). During extended clinical follow-up, 2 patients suffered from very late stent thrombosis showing a high degree of malapposition, protrusion, and coronary evaginations at the time of OCT investigation. CONCLUSIONS: Early-generation drug-eluting stents show a similar degree of strut coverage and malapposition at 5 years of follow-up. Despite an overall low degree of uncovered and malapposed struts in event-free patients, some lesions show a clustering of these characteristics, indicating a heterogeneous healing response, which may be the source for very late adverse events.

In vitro time-dependent response of periodontal ligament to mechanical loading.

This study examined the time-dependent response of bovine periodontal ligament (PDL). Applying linear viscoelastic theory, the objective was 1) to examine the linearity of the PDL's response in terms of its scaling and superposition property and 2) to generate the phase lag-vs.-frequency spectrum graph. PDL specimens were tested under three separate straining conditions: 1) tension ramp tests conducted at different strain rates, 2) pulling step-straining to 0.3 in discrete tests and to 0.3 and 0.6 in one continuous run, and 3) tension-compression sinusoidal oscillations. To this effect, bar-shaped specimens of bovine roots that comprised portions of dentin, PDL tissue, and alveolar bone were produced and strained in a microtensile machine. The experimental data demonstrated that neither the scaling nor the superposition properties were verified and that the viscoelastic response of the PDL was nonlinear. The PDL's elastic response was essentially stiffening, and its viscous component was pseudoplastic. The tangent of the PDL's strain-stress phase lag was in the 0-0.1 range in the tensile direction and in the 0.35-0.45 range in the compressive direction. In line with other biological tissues, the phase lag was largely independent of frequency. By use of the data generated, a mathematical model is outlined that reproduces both the elastic stiffening and viscous thinning of the PDL's response.