Respiratory Waveform Research Articles

Non-Contact Vital States Identification of Trapped Living Bodies Using Ultra-Wideband Bio-Radar

Identifying the vital states of trapped survivors during post-disaster rescue missions can result in improved rescue strategies and provide injury pre-diagnosis information. The most effective rescue method is the use of bio-radar based non-contact measurements. Presently, bio-radar techniques focus on detecting and locating. Herein, a method to identify vital states with an ultra-wideband bio-radar is proposed, while simulating a trapped condition with Beagle dogs. This investigation revealed three vital stages under the trapped condition: normal, transitioning, and agonal stages. Upon entering the transitioning stage, the heartrates were apparently high, and the respiratory rates increased sharply. The temperatures dropped rapidly once passing this stage. In particular, the respiratory waveforms from the bio-radar frequently change from a normal sine like curve to an “M” like curve within the transitioning stage. The accurate beginning and ending of the transitioning stage are defined by a newly proposed indicator of relative occurrence frequency. Pathological observations indicated that the fragmentation of lamellar bodies within type II alveolar cells caused the insufficiency of the lung surfactant, and further resulted in the occurrence of the “M” like curves. This pioneering work realizes the vital states identification only using a non-contact ultra-wideband bio-radar, thereby enables to infer the health conditions, life expectancy, and appropriate subsequent treatment of victims in the trapped condition. Therefore, it has the potential to promote the welfare of post-disaster trapped human victims.

Design of Low Power Multi-parameter Monitoring System Based on Bluetooth

This paper designs a bluetooth-based low-power multi-parameter monitoring system. The system is mainly composed of ECG signal acquisition, respiratory signal acquisition, body temperature acquisition, bluetooth 4.0 transmission module and Android mobile phone APP display. The system collects the corresponding physiological signals through various collection parts, and can realize the monitoring of three physiological signals of electrocardiogram, respiration and body temperature. The Android mobile APP can display ECG, respiratory waveform and temperature data in real time. The system is small in size and low in power consumption, and has a good application prospect in portable and wearable medical applications.

Furniture-Integrated Respiration Sensors by Notched Transmission Lines.

Non-invasive respiration sensors integrated into furniture can be invisible to the user and greatly enhance comfort and convenience to facilitate many applications. Current sensors often require user cooperation or fitting, which discourages frequent usage. We present a new respiration sensor integrated into a bed or a chair by modifying a radio-frequency (RF) coaxial cable structure with a designed notch. The lung motion is coupled to the electromagnetic leakage at the notch through near-field coherent sensing (NCS). The sensors, covered with fabrics and positioned under the abdomen and thorax, can capture the respiratory waveforms and derive the breath rate. The heart rate can also be evaluated in the same setup with proper filtering. The sensor design can tolerate large position variation to accommodate user uncertainties. Various voluntary exercises of normal, deep, fast, held and blocked breathing were measured under different postures of supine, recumbent and sitting by the carrier frequency range between 900MHz and 2.4GHz. The breath rate from 10 participants compare well with the synchronous commercial chest-belt sensors in all breathing routines.

Transient Respiratory-motion Artifact and Scan Timing during the Arterial Phase of Gadoxetate Disodium-enhanced MR Imaging: The Benefit of Shortened Acquisition and Multiple Arterial Phase Acquisition.

Purpose:To investigate whether shortened acquisition or multiple arterial phase acquisition improves image quality of the arterial phase compared with conventional protocol.Methods:This retrospective study was approved by the relevant Institutional Review Board. A total of 615 consecutive patients who underwent gadoxetate disodium-enhanced MRI including one of the following three sequences in three different periods were included: (i) conventional liver acquisition with volume acceleration (LAVA) (between October 2014 and January 2015, n = 149), (ii) Turbo-LAVA (between March and August 2016, n = 216), and (iii) differential sub-sampling with Cartesian ordering (DISCO) (between January and September 2015, n = 250). We monitored the respiratory bellows waveform during breath holding for each patient and recorded breath-hold fidelity of the patients. Two radiologists independently evaluated the degree of respiratory artifact and scan timing on the arterial phase and compared them between the three protocols (i.e., conventional LAVA, Turbo-LAVA, and DISCO), with conventional LAVA as control.Results:The ratio of patients with breath-hold failure was not significantly different among the three protocols (P = 0.6340 and 0.1085). Respiratory artifact was significantly lower in DISCO than in conventional LAVA (P = 0.0424), while there was no significant difference between Turbo-LAVA and conventional LAVA (P = 0.2593). The ratio of adequate scan timing and diagnosable image defined as no or mild artifact and adequate scan timing were higher in DISCO than in conventional LAVA (P = 0.0025 and 0.0019), while there was no significant difference between Turbo-LAVA and conventional LAVA (P = 0.0780 and 0.0657).Conclusion:Compared with conventional protocol, multiple arterial phase acquisition (DISCO) obtained a higher number of diagnosable images by reducing respiratory motion artifact and optimizing the scan timing of arterial phase.

A Single-Channel Amplifier for Simultaneously Monitoring Impedance Respiration Signal and ECG Signal

Physiological signals can reflect the physiological characteristics of the human body and serve as important reference for doctors in clinical diagnosis. Hence, wearable intelligent equipment for physiological signal monitoring has attracted increasing attention. Such equipment must be of a small size and must have low power consumption. To meet these demands, we designed a single-channel amplifier, that can simultaneously acquire the electrocardiograph (ECG) signal and impedance respiration signal. We used oversampling and fast digital lock-in technology to improve the measuring precision of the circuit without increasing the complexity of the circuit. The circuit makes use of the capacitive reactance of a capacitor, which changes with the frequency of the signal; this can meet the different impedance requirements of both the impedance respiratory signal and ECG signal during the measurements. The result of experiments shows that the circuit can obtain high-quality ECG and respiratory waveforms. This circuit can serve as a valuable reference for the design of wearable health monitoring equipment to simultaneously acquire multiple human physiological signals in a signal channel.

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

BackgroundThere has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as respiratory conditions such as asthma, where long-term monitoring of lung function has shown promising utility.ObjectiveIn this paper, we explore a long short-term memory (LSTM) architecture and predict measures of interbreath intervals, respiratory rate, and the inspiration-expiration ratio from a photoplethysmogram signal. This serves as a proof-of-concept study of the applicability of a machine learning architecture to the derivation of respiratory metrics.MethodsA pulse oximeter was mounted to the left index finger of 9 healthy subjects who breathed at controlled respiratory rates. A respiratory band was used to collect a reference signal as a comparison.ResultsOver a 40-second window, the LSTM model predicted a respiratory waveform through which breathing metrics could be derived with a bias value and 95% CI. Metrics included inspiration time (–0.16 seconds, –1.64 to 1.31 seconds), expiration time (0.09 seconds, –1.35 to 1.53 seconds), respiratory rate (0.12 breaths per minute, –2.13 to 2.37 breaths per minute), interbreath intervals (–0.07 seconds, –1.75 to 1.61 seconds), and the inspiration-expiration ratio (0.09, –0.66 to 0.84).ConclusionsA trained LSTM model shows acceptable accuracy for deriving breathing metrics and could be useful for long-term breathing monitoring in health. Its utility in respiratory disease (eg, asthma) warrants further investigation.

Post-hoc physiological waveform extraction from motion estimation in simultaneous multislice (SMS) functional MRI using separate stack processing.

Motion estimation is an essential step in functional MRI (fMRI) preprocessing. Usually, fMRI processing software packages (eg, FSL and AFNI) automatically estimate motion parameters in order to counteract the effects of motion. However, the time courses of the motion estimation for fMRI data also contain information about physiological processes. Here, we show that respiration and cardiac signals can be extracted from motion estimation at significantly higher bandwidth than is possible with current methods. To detect motion at high effective temporal resolution (HighRes), the motion parameters of stacks of simultaneously acquired slices were estimated separately, then combined. This method was validated by extracting physiological motion signals from resting state fMRI (rsfMRI) data (Enhanced Nathan Kline Institute-Rockland Sample) and comparing them to respiration belt and pulse oximeter signals. HighRes motion time-courses with an effective sampling rate of 15.5 and 11.4 Hz were extracted from repetition time (TR) = 0.645 and 1.4 s data, respectively. Respiration waveforms were extracted with significantly higher accuracy than the original motion parameters. Even cardiac waveforms could be extracted, despite the fact that the sampling time or TR values were too long to sample cardiac frequencies. HighRes motion traces provide insight into the subjects' motion at higher frequencies than can be estimated using standard techniques. In its simplest form, this technique can recover accurate respiration signals and may reveal additional complexity in brain motion.

Breathing process monitoring with a biaxially oriented polypropylene film based fiber Fabry–Perot sensor

The breathing process monitoring with a biaxially oriented polypropylene (BOPP) film based fiber Fabry–Perot (F–P) sensor is presented. The fiber F–P sensor is fabricated with 3-D printing technology and fixed on a medical respirator for breathing process monitoring. Due to the low Young’s modulus of the BOPP film and its thinner thickness, the breathing sensor shows the high pressure sensitivity of -0.581 nm/Pa. By monitoring its intensity response to the pressure induced by breathing, the breathing process can be monitored accurately, including respiratory waveform, respiratory rate, inspiratory duration and amplitude, expiratory duration and amplitude, and inspiratory and expiratory rhythm. Since the sensor is all fiber design with the inherent advantages of small size, anti-electromagnetic interference, green environmental protection, pollution-free and no harm to body, it is expected to be widely used in respiratory disease monitoring.

Relationship of the Respiration Waveform to a Chest Worn Inertial Sensor.

Demand of portable health monitoring has been growing due to increasing cardiovascular and respiratory diseases. While both cardiovascular monitoring and respiratory monitoring have been developed independently, there lacks a simple integrated solution to monitor both simultaneously. Seismocardiography (SCG), a method of recording cardiac vibrations with an accelerometer can also be used to extract respiratory information via low frequency chest oscillations. This study used an inertial measurement unit which pairs a 3-axis accelerometer and a 3-axis gyroscope to monitor respiration while maintaining optimum placement protocol for recording SCG. Additionally, the connection between inertial measurement and both respiratory rate and volume were explored based on their correlation with a Spirometer. Respiratory volume was shown to have moderate correlation with chest motion with an average best-case correlation coefficient of 0.679 across acceleration and gyration. The techniques described will assist the design of future SCG algorithms by understanding the sources behind their modulation from respiration. This paper shows that a simplified processing technique can be added to SCG algorithms for respiration monitoring.

1243 A Guinness Book Challenge in Upper Airway Stimulation Activation

Abstract Introduction Upper airway stimulation is a option for CPAP-intolerant patients. Device activation is typically ~4 weeks after the implant procedure. Report of Case A 61yo male with severe OSA had an upper airway stimulation device placed by ENT. At that time, stimulation produced bilateral tongue protrusion. In the immediate post-operative period, after closure, a hematoma, at the inferior chest incision, was discovered and drained with cauterization of the bleeding vessel. Seven weeks after implant, patient reported to our sleep clinic for activation of the device; and at that time, there was no sensation or activation up to the maximum amplitude of 5mV. The device reported an acceptable respiratory waveform, and triggering on and off sets but without sensory outcomes. Changing of the electrode configuration with advanced settings had no effect. Impedance values were acceptable. Tongue movements were grossly intact. At 2 months, ENT evaluation found mild hypoglossal nerve neuropraxia. To assess for a device related issue, x-rays of the neck and chest were performed and showed proper placement of the device. At 3.5 months, neuropraxia had resolved but device activation was unsuccessful, with no sensory or motor activation to 5mV stimulation. Plans were made for a procedure during which the lead electrode or implantable pulse generator would be assessed or replaced. At 4 months after implantation, in a multidisciplinary appointment with Sleep, ENT and the device representative, with a 3 electrode negative pole and the generator as the + pole, at 2.3mV, the device was activated. At the present time, the patient is exploring higher and lower mV settings and a PSG titration is scheduled. Conclusion This is the longest recorded duration (3.5+ months) of unsuccessful post-operative activation; and it occurred ~2 months after clinical signs of hypoglossal nerve neuropraxia had resolved.

A Novel Negative Pressure-Flow Waveform to Ventilate Lungs for Normothermic Ex Vivo Lung Perfusion.

Ex vivo lung perfusion (EVLP) is increasingly used to treat and assess lungs before transplant. Minimizing ventilator induced lung injury (VILI) during EVLP is an important clinical need, and negative pressure ventilation (NPV) may reduce VILI compared with conventional positive pressure ventilation (PPV). However, it is not clear if NPV is intrinsically lung protective or if differences in respiratory pressure-flow waveforms are responsible for reduced VILI during NPV. In this study, we quantified lung injury using novel pressure-flow waveforms during normothermic EVLP. Rat lungs were ventilated-perfused ex vivo for 2 hours using tidal volume, positive end-expiratory pressure (PEEP), and respiratory rate matched PPV or NPV protocols. Airway pressures and flow rates were measured in real time and lungs were assessed for changes in compliance, pulmonary vascular resistance, oxygenation, edema, and cytokine secretion. Negative pressure ventilation lungs demonstrated reduced proinflammatory cytokine secretion, reduced weight gain, and reduced pulmonary vascular resistance (p < 0.05). Compliance was higher in NPV lungs (p < 0.05), and there was no difference in oxygenation between the two groups. Respiratory pressure-flow waveforms during NPV and PPV were significantly different (p < 0.05), especially during the inspiratory phase, where the NPV group exhibited rapid time-dependent changes in pressure and airflow whereas the PPV group exhibited slower changes in airflow/pressures. Lungs ventilated with PPV also had a greater transpulmonary pressure (p < 0.05). Greater improvement in lung function during NPV EVLP may be caused by favorable airflow patterns and/or pressure dynamics, which may better mimic human respiratory patterns.

Fast Fourier transform combined with phase leading compensator for respiratory motion compensation system.

The reduction of the delaying effect in the respiratory motion compensation system (RMCS) is still impossible to completely correct the respiratory waveform of the human body due to each patient has a unique respiratory rate. In order to further improve the effectiveness of radiation therapy, this study evaluates our previously developed RMCS and uses the fast Fourier transform (FFT) algorithm combined with the phase lead compensator (PLC) to further improve the compensation rate (CR) of different respiratory frequencies and patterns of patients. In this study, an algorithm of FFT automatic frequency detection was developed by using LabVIEW software, uisng FFT combined with PLC and RMCS to compensate the system delay time. Respiratory motion compensation experiments were performed using pre-recorded respiratory signals of 25 patients. During the experiment, the respiratory motion simulation system (RMSS) was placed on the RMCS, and the pre-recorded patient breathing signals were sent to the RMCS by using our previously developed ultrasound image tracking algorithm (UITA). The tracking error of the RMCS is obtained by comparing the encoder signals of the RMSS and RMCS. The compensation effect is verified by root mean squared error (RMSE) and system CR. The experimental results show that the patient's respiratory patterns compensated by the RMCS after using the proposed FFT combined with PLC control method, the RMSE is between 1.50-5.71 and 3.15-8.31 mm in the right-left (RL) and superior-inferior (SI) directions, respectively. CR is between 72.86-93.25% and 62.3-83.81% in RL and SI, respectively. This study used FFT combined with PLC control method to apply to RMCS, and used UITA for respiratory motion compensation. Under the automatic frequency detection, the best dominant frequency of the human respiratory waveform can be determinated. In radiotherapy, it can be used to compensate the tumor movement caused by respiratory motion and reduce the radiation damage and side effects of normal tissues nearby the tumor.

Data-Driven Respiratory Gating Outperforms Device-Based Gating for Clinical 18F-FDG PET/CT.

A data-driven method for respiratory gating in PET has recently been commercially developed. We sought to compare the performance of the algorithm with an external, device-based system for oncologic 18F-FDG PET/CT imaging. Methods: In total, 144 whole-body 18F-FDG PET/CT examinations were acquired, with a respiratory gating waveform recorded by an external, device-based respiratory gating system. In each examination, 2 of the bed positions covering the liver and lung bases were acquired with a duration of 6 min. Quiescent-period gating retaining approximately 50% of coincidences was then able to produce images with an effective duration of 3 min for these 2 bed positions, matching the other bed positions. For each examination, 4 reconstructions were performed and compared: data-driven gating (DDG) (we use the term DDG-retro to distinguish that we did not use the real-time R-threshold-based application of DDG that is available within the manufacturer's product), external device-based gating (real-time position management (RPM)-gated), no gating but using only the first 3 min of data (ungated-matched), and no gating retaining all coincidences (ungated-full). Lesions in the images were quantified and image quality scored by a radiologist who was masked to the method of data processing. Results: Compared with the other reconstruction options, DDG-retro increased the SUVmax and decreased the threshold-defined lesion volume. Compared with RPM-gated, DDG-retro gave an average increase in SUVmax of 0.66 ± 0.1 g/mL (n = 87, P < 0.0005). Although the results from the masked image evaluation were most commonly equivalent, DDG-retro was preferred over RPM-gated in 13% of examinations, whereas the opposite occurred in just 2% of examinations. This was a significant preference for DDG-retro (P = 0.008, n = 121). Liver lesions were identified in 23 examinations. Considering this subset of data, DDG-retro was ranked superior to ungated-full in 6 of 23 (26%) cases. Gated reconstruction using the external device failed in 16% of examinations, whereas DDG-retro always provided a clinically acceptable image. Conclusion: In this clinical evaluation, DDG-retro provided performance superior to that of the external device-based system. For most examinations the performance was equivalent, but DDG-retro had superior performance in 13% of examinations, leading to a significant preference overall.

Reliability of voluntary cough assessments using respiratory flow waveform.

[Purpose] Voluntary cough can be assessed by recording flow waves. The purpose of this study was to examine the reliability of the measurements of respiratory flow waveforms, using equipment that recorded flow waves during cough. [Participants and Methods] Twenty healthy participants were recruited for this study. They underwent spirometry on them and, subsequently, their flow waves during single and consecutive voluntary cough tasks in the sitting position were recorded. The intra-class correlation coefficient was used to assess the intra-rater and inter-rater reliabilities for the voluntary cough data. [Results] The intra-class correlation coefficients were 0.6 to 0.8 for ‘intra-rater reliability’ and higher than 0.9 for ‘inter-rater reliability’, for single and consecutive cough tasks. The first assessment of cough peak flow was significantly higher than the second, during consecutive cough tasks. Similarly, the first assessment of cough volume acceleration was significantly higher than the second. [Conclusion] Our results demonstrated high intra-rater and inter-rater reliabilities for single and consecutive cough tasks. Following additional procedures and valuations, including the storage of data and standard range decisions, this method of cough assessment will be applied to patients with reduced cough function.

Characterization of continuous bed motion effects on patient breathing and respiratory motion correction in PET/CT imaging.

Continuous bed motion (CBM) was recently introduced as an alternative to step‐and‐shoot (SS) mode for PET/CT data acquisition. In CBM, the patient is continuously advanced into the scanner at a preset speed, whereas in SS, the patient is imaged in overlapping bed positions. Previous investigations have shown that patients preferred CBM over SS for PET data acquisition. In this study, we investigated the effect of CBM versus SS on patient breathing and respiratory motion correction. One hundred patients referred for PET/CT were scanned using a Siemens mCT scanner. Patient respiratory waveforms were recorded using an Anzai system and analyzed using four methods: Methods 1 and 2 measured the coefficient of variation (COV) of the respiratory cycle duration (RCD) and amplitude (RCA). Method 3 measured the respiratory frequency signal prominence (RSP) and method 4 measured the width of the HDChest optimal gate (OG) window when using a 35% duty cycle. Waveform analysis was performed over the abdominothoracic region which exhibited the greatest respiratory motion and the results were compared between CBM and SS. Respiratory motion correction was assessed by comparing the ratios of SUVmax, SUVpeak, and CNR of focal FDG uptake, as well as Radiologists’ visual assessment of corresponding image quality of motion corrected and uncorrected images for both acquisition modes. The respiratory waveforms analysis showed that the RCD and RCA COV were 3.7% and 33.3% lower for CBM compared to SS, respectively, while the RSP and OG were 30.5% and 2.0% higher, respectively. Image analysis on the other hand showed that SUVmax, SUVpeak, and CNR were 8.5%, 4.5%, and 3.4% higher for SS compared to CBM, respectively, while the Radiologists’ visual comparison showed similar image quality between acquisition modes. However, none of the results showed statistically significant differences between SS and CBM, suggesting that motion correction is not impacted by acquisition mode.

Neurally adjusted ventilatory assist mitigates ventilator-induced diaphragm injury in rabbits

BackgroundVentilator-induced diaphragmatic dysfunction is a serious complication associated with higher ICU mortality, prolonged mechanical ventilation, and unsuccessful withdrawal from mechanical ventilation. Although neurally adjusted ventilatory assist (NAVA) could be associated with lower patient-ventilator asynchrony compared with conventional ventilation, its effects on diaphragmatic dysfunction have not yet been well elucidated.MethodsTwenty Japanese white rabbits were randomly divided into four groups, (1) no ventilation, (2) controlled mechanical ventilation (CMV) with continuous neuromuscular blockade, (3) NAVA, and (4) pressure support ventilation (PSV). Ventilated rabbits had lung injury induced, and mechanical ventilation was continued for 12 h. Respiratory waveforms were continuously recorded, and the asynchronous events measured. Subsequently, the animals were euthanized, and diaphragm and lung tissue were removed, and stained with Hematoxylin-Eosin to evaluate the extent of lung injury. The myofiber cross-sectional area of the diaphragm was evaluated under the adenosine triphosphatase staining, sarcomere disruptions by electron microscopy, apoptotic cell numbers by the TUNEL method, and quantitative analysis of Caspase-3 mRNA expression by real-time polymerase chain reaction.ResultsPhysiological index, respiratory parameters, and histologic lung injury were not significantly different among the CMV, NAVA, and PSV. NAVA had lower asynchronous events than PSV (median [interquartile range], NAVA, 1.1 [0–2.2], PSV, 6.8 [3.8–10.0], p = 0.023). No differences were seen in the cross-sectional areas of myofibers between NAVA and PSV, but those of Type 1, 2A, and 2B fibers were lower in CMV compared with NAVA. The area fraction of sarcomere disruptions was lower in NAVA than PSV (NAVA vs PSV; 1.6 [1.5–2.8] vs 3.6 [2.7–4.3], p < 0.001). The proportion of apoptotic cells was lower in NAVA group than in PSV (NAVA vs PSV; 3.5 [2.5–6.4] vs 12.1 [8.9–18.1], p < 0.001). There was a tendency in the decreased expression levels of Caspase-3 mRNA in NAVA groups. Asynchrony Index was a mediator in the relationship between NAVA and sarcomere disruptions.ConclusionsPreservation of spontaneous breathing using either PSV or NAVA can preserve the cross sectional area of the diaphragm to prevent atrophy. However, NAVA may be superior to PSV in preventing sarcomere injury and apoptosis of myofibrotic cells of the diaphragm, and this effect may be mediated by patient-ventilator asynchrony.

Application of modified tracking components in CyberKnife treatment of thoracic and abdominal tumors

Objective To improve synchrony tracking components of CyberKnife (tracking vest and tracking markers) and to analyze the clinical application value of the improved tracking components in CyberKnife treatment of thoracic and abdominal tumors. Methods The tracking apron was made of knitted four-side elastic spandex cloth and suture design of Velcro, which was used to stick the tracking markers on the chest and abdomen of patients. The tracking markers added a 2 cm thick light foam block to the bottom of the original markers, and then the hook face of the Velcro was fixed to the bottom of the light foam. The improved trace component (the improved component) and the original component (the vendor component) were applied to the lung tracking treatment model, and the manufacturer components were included in the reference group. Adoption of improved components into the observation group; 20 different types of respiratory waveforms were simulated and applied to the same mold plan. After treatment, the coverage rate, mean standard deviation, maximum standard deviation and the slope of XYZ-axis vs. R correlation graph were recorded. The relevant parameters of Synchrony model and wearable time of two components were compared, and the application significances of the improved tracking component in the breathing tracking process of the CyberKnife were evaluated. Results The maximum slope [median(interquartile range)] of XYZ-axis vs. R related graph in the reference group was 0.73 (3.89), 0.27 (0.49) and 0.34 (1.02), respectively. The maximum slope of XYZ-axis vs. R related graph in the observation group was 0.70 (2.78), 0.31 (0.30) and 0.36 (0.75), respectively. There was no statistically significant difference in the slope of XYZ-axis vs. R between the reference group and the observation group (all P > 0.05). There was no significant difference in the average standard error and maximum standard error between the reference group and the observation group [(1.7±0.4) mm vs. (1.7±0.5) mm, t=-0.382, P= 0.710; (2.0±0.6) mm vs. (1.7±0.5) mm, t=-0.877, P= 0.401], and the difference of the model coverage rate between the two groups was statistically significant [(48±18)% vs. (60±22)%, t= 2.762, P= 0.042]. The setup time of tracking components in the observation group was less than that in the reference group, and the difference was statistically significant [(44±24) s vs. (81±15) s, t=-4.310, P= 0.001]. Conclusions The improved tracking components are comparable to the manufacturer tracking components in the standard error of the Synchrony model. The improved components shorten the wear time and appropriately improve the coverage of the Synchrony model. Key words: Thoracic neoplasms; Abdominal neoplasms; CyberKnife; Stereotactic body radiation therapy; Standard error; Synchrony model

Quantitative Assessment of Spontaneous Breathing in Children: Evaluation of a Depth Camera System

This article describes a new approach for quantitative evaluation of respiration in the pediatric intensive care unit (PICU). Video sequences of thorax movements are recorded by two depth cameras to cover the 3-D surface of the torso and its lateral sides. The breathing activity implies a frame-by-frame surface deformation, which can be described by the volume variation of reconstructed surfaces between the consecutive video frames. A quantitative evaluation of the breathing pattern is then performed through a subtraction technique, thereby detecting the volume variation between the subsequent frames. A high-fidelity simulation was performed in a realistic environment designed for critically ill children. The simulation was then followed by a real-world evaluation, involving two newborn babies (one female and one male) who required ventilator support. The breathing signal patterns resulting from our approach were compared to those measured by mechanical ventilation in terms of their waveforms, evaluating the most significant dynamic parameters: tidal volume, respiratory rate, and minute ventilation. Our experimental study showed a significant agreement between the proposed 3-D imaging system and the gold standard method in estimating respiratory waveforms and parameters. This article presents the following innovations. First, we suggest a 3-D imaging system specifically designed for PICUs based on a contactless design. Second, we propose an efficient positioning mechanism for the cameras, offering a very high spatial coverage of the thoracoabdominal zone and considering the PICU constraints. Finally, we propose an objective vision-based method to quantitatively measure respiration for spontaneous breathing patients in PICUs.

Intrapleural Impedance Sensor Real-Time Tracking of Pneumothorax in a Porcine Model of Air Leak

In patients with alveolar-to-pleural air leak due to recent surgery or trauma, clinicians tend to manage chest tubes with suction therapy. Nonsuction therapy is associated with shorter chest tube duration but also a higher risk of pneumothorax. We sought to develop an intrapleural electrical impedance sensor for continuous, real-time monitoring of pneumothorax development in a porcine model of air leak as a means of promoting nonsuction therapy. Using thoracoscopy, 2 chest tubes and the pleural impedance sensor were introduced into the pleural space of 3 pigs. Continuous air leak was introduced through 1 chest tube by carbon dioxide insufflation. The second chest tube was placed to suction then transitioned to no suction at increasingly higher air leaks until pneumothorax developed. Simultaneously, real-time impedance measurements were obtained from the pleural sensor. Fluoroscopy spot images were captured to verify the presence or absence of pneumothorax. Statistical Analysis Software was used throughout. With the chest tube on suction, a fully expanded lung was identified by a distinct pleural electrical impedance respiratory waveform. With transition of the chest tube to water seal, loss of contact of the sensor with the lung resulted in an immediate measurement of infinite electrical impedance. Pneumothorax resolution by restoring suction therapy was detected in real time by a return of the normal respiratory impedance waveform. Pleural electrical impedance monitoring detected pneumothorax development and resolution in real time. This simple technology has the potential to improve the safety and quality of chest tube management.

Respiratory Motion Prediction Using Fusion-Based Multi-Rate Kalman Filtering and Real-Time Golden-Angle Radial MRI.

Magnetic resonance imaging (MRI) can provide guidance for interventions in organs affected by respiration (e.g., liver). This study aims to: 1) investigate image-based and surrogate-based motion tracking methods using real-time golden-angle radial MRI; and 2) propose and evaluate a new fusion-based respiratory motion prediction framework with multi-rate Kalman filtering. Images with different temporal footprints were reconstructed from the same golden-angle radial MRI data stream to simultaneously enable image-based and surrogate-based tracking at 10Hz. A custom software pipeline was constructed to perform online tracking and calibrate tracking error and latency using a programmable motion phantom. A fusion-based motion prediction method was developed to combine the lower tracking error of image-based tracking with the lower latency of surrogate-based tracking. The fusion-based method was evaluated in retrospective studies using in vivo real-time free-breathing liver MRI. Phantom experiments confirmed that the median online tracking error of image-based tracking was lower than surrogate-based methods, however, with higher median system latency (350 ms vs. 150 ms). In retrospective in vivo studies, 75 respiratory waveforms of target features from eight subjects were analyzed. The median root-mean-squared prediction error (RMSE) for the fusion-based method (0.97mm) was reduced (Wilcoxon signed rank test p < 0.05) compared to surrogate-based (1.18mm) and image-based (1.3mm) methods. The proposed fusion-based respiratory motion prediction framework using golden-angle radial MRI can achieve low-latency feedback with improved accuracy. Respiratory motion prediction using the fusion-based method can overcome system latency to provide accurate feedback information for MRI-guided interventions.