End Of Inspiration Research Articles

Intra-breath changes in respiratory mechanics assessed from multi-frequency oscillometry measurements

Objective. Recent studies in respiratory system impedance (Zrs) with single-frequency oscillometry have demonstrated the utility of novel intra-breath measures of Zrs in the detection of pathological alterations in respiratory mechanics. In the present work, we addressed the feasibility of extracting intra-breath information from Zrs data sets obtained with conventional oscillometry. Approach. Multi-frequency recordings obtained in a pulmonology practice were re-analysed to track the 11 Hz component of Zrs during normal breathing and compare the intra-breath measures to that obtained with a single 10 Hz signal in the same subjects. A nonlinear model was employed to simulate changes in Zrs in the breathing cycle. The values of resistance (R) and reactance (X) at end expiration and end inspiration and their corresponding differences (ΔR and ΔX) were compared. Main results. All intra-breath measures exhibited similar mean values at 10 and 11 Hz in each subject; however, the variabilities were higher at 11 Hz, especially for ΔR and ΔX. The poorer quality of the 11 Hz data was primarily caused by the overlapping of modulation side lobes of adjacent oscillation frequencies. This cross-talk was enhanced by double breathing frequency components due to flow nonlinearities. Significance. Retrospective intra-breath assessment of large or special data bases of conventional oscillometry can be performed to better characterise respiratory mechanics in different populations and disease groups. The results also have implications in the optimum design of multiple-frequency oscillometry (avoidance of densely spaced frequencies) and the use of filtering procedures that preserve the intra-breath modulation information.

Data-driven gated CT: An automated respiratory gating method to enable data-driven gated PET/CT.

The accuracy of positron emission tomography (PET) quantification and localization can be compromised if a misregistered computed tomography (CT) is used for attenuation correction (AC) in PET/CT. As data-driven gating (DDG) continues to grow in clinical use, these issues are becoming more relevant with respect to solutions for gated CT. In this work, a new automated DDG CT method was developed to provide average CT and DDG CT for AC of PET and DDG PET, respectively. An automatic DDG CT was developed to provide the end-expiratory (EE) and end-inspiratory (EI) phases of images from low-dose cine CT images, with all phases being averaged to generate an average CT. The respiratory phases of EE and EI were determined according to lung region Hounsfield unit (HU) values and body outline contours. The average CT was used for AC of baseline PET and DDG CT at EE phase was used for AC of DDG PET at the quiescent or EE phase. The EI and EE phases obtained with DDG CT were used for assessing the magnitude of respiratory motion. The proposed DDG CT was compared to two commercial CT gating methods: (1) 4D CT (external device based) and (2) D4D CT (DDG based) in 38 patient datasets with respect to respiratory phase image selection, lung HU, lung volume, and image artifacts. In a separate set of twenty consecutive PET/CT studies containing a mix of 18 F-FDG, 68 Ga-Dotatate, and 64 Cu-Dotatate scans, the proposed DDG CT was compared with D4D CT for impacts on registration and quantification in DDG PET/CT. In the EE phase, the images selected by DDG CT and 4D CT were identical 62.5% ± 21.6% of the time, whereas DDG CT and D4D CT were 6.5% ± 9.7%, and 4D CT and D4D CT were 8.6% ± 12.2%. These differences in EE phase image selection were significant (p < 0.0001). In the EI phase, the images selected by DDG CT and 4D CT were identical 68.2% ± 18.9% of the time, DDG CT and D4D CT were 63.9% ± 18.8%, and 4D CT and D4D CT were 61.2% ± 19.8%. These differences were not significant. The mean lung HU and volumes were not statistically different (p > 0.1) among the three methods. In some studies, DDG CT was better than D4D or 4D CT in the appropriate selection of the EE and EI phases, and D4D CT was found to reverse the EE and EI phases or not select the correct images by visual inspection. A statistically significant improvement of DDG CT over D4D CT for AC of DDG PET was also demonstrated with PET quantification analysis. When irregular breath cycles were present in the cine CT, DDG CT could be used to replace average CT for the improved AC of baseline PET. A new automatic DDG CT was developed to tackle the issues of misregistration and tumor motion in PET/CT imaging. DDG CT was significantly more consistent than D4D CT in selecting the EE phase images as the clinical standard of 4D CT. When compared to both commercial gated CT methods of 4D CT and D4D CT, DDG CT appeared to be more robust in the lower lung and upper diaphragm regions where misregistration and tumor motion often occur. DDG CT offered improved AC for DDG PET relative to D4D CT. In cases with irregular respiratory motion, DDG CT improved AC over average CT for baseline PET. The new DDG CT provides the benefits of 4D CT without the need for external device gating.

Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images

Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input.

Regional diaphragm motion analysis via dynamic MRI.

Breathing-related movement analysis is important in the study of many disease processes. The analysis of diaphragmatic motion via thoracic imaging in particular is important in a variety of disorders. Compared to computed tomography (CT) and fluoroscopy, dynamic magnetic resonance imaging (dMRI) has several advantages, such as better soft tissue contrast, no ionizing radiation, and greater flexibility in selecting scanning planes. In this paper, we propose a novel method for full diaphragmatic motion analysis via free-breathing dMRI. Firstly, after 4D dMRI image construction in a cohort of 51 normal children, we manually delineated the diaphragm on sagittal plane dMRI images at end-inspiration and end-expiration. Then, 25 points were selected uniformly and homologously on each hemi-diaphragm surface. Based on the inferior-superior displacements of these 25 points between end-expiration (EE) and end-inspiration (EI) time points, we obtained their velocities. We then summarized 13 parameters from these velocities for each hemi-diaphragm to provide a quantitative regional analysis of diaphragmatic motion. We observed that the regional velocities of the right hemi-diaphragm were almost always statistically significantly greater than those of the left hemi-diaphragm in homologous locations. There was a significant difference for sagittal curvatures but not for coronal curvatures between the two hemi-diaphragms. Using this methodology, future larger scale prospective studies may be considered to confirm our findings in the normal state and to quantitatively assess regional diaphragmatic dysfunction when various disease conditions are present.

Seismocardiographic Signal Variability During Regular Breathing And Breath Holding

<h3>Introduction</h3> Seismocardiography signals (SCG) are acoustic vibrations generated by heart activity and measured non-invasively at the chest surface. The potential utility of SCG for HF diagnosis and monitoring may be limited by signal variability. Respiration is a known, yet not well understood, source of variability. The objective of this pilot study was to quantify the SCG variability during breathing maneuvers. <h3>Methods</h3> SCG, electrocardiography (ECG) and airflow signals were acquired in two healthy subjects during normal breathing and breath holding (at end-inspiration and end-expiration while the glottis remained open). Data recording was repeated three times, while subjects resting on a 45 degree-elevated tilt table. The SCG events were detected and segmented utilizing the ECG R wave. Although the waveform varied, using unsupervised machine learning (k-medoid clustering) one could separate SCG waveforms during breathing into two "clusters" of similar events. The SCG variability was calculated using Dynamic Time Warping (DTW). The time interval between SCG1 and SCG 2 (which corresponds to the heart-sound ejection-period or HSEP) was also calculated. <h3>Results</h3> Table 1 shows the mean and standard deviation (SD) of the following SCG features: intra-cluster variability, inter-session variability and HSEP during regular breathing, breath hold at end inspiration and end expiration. SCG average intra-cluster and inter session variability was 27% and 24% lower, respectively, during breath holding for both end-inspiration and end-expiration compared to normal breathing. In addition, HSEP was 12% lower during breath holding compared to normal breathing. <h3>Conclusion</h3> Appropriate accounting for SCG variability introduced by breathing appears to account for a significant portion of the signal variability. Hence algorithms integrating respiratory changes may lead to more robust SCG analysis for HF diagnosis and monitoring. In addition, the observed respiration-dependent variability may prove to be a useful feature for HF management. Further studies are needed to confirm these findings in HF patients.

A Minimally Interactive Method for Labeling Respiratory Phases in Free-Breathing Thoracic Dynamic MRI for Constructing 4D Images.

Determination of end-expiration (EE) and end-inspiration (EI) time points in the respiratory cycle in free-breathing slice image acquisitions of the thorax is one key step needed for 4D image construction via dynamic magnetic resonance imaging. The purpose of this paper is to realize the automation of the labeling process. The diaphragm is used as a surrogate for tracking respiratory motion and determining the state of breathing. Regions of interest (ROIs) containing the hemi-diaphragms are set by human interaction to compute the optical flow matrix between two adjacent 2D time slices. Subsequently, our approach examines the diaphragm speed and direction and by considering the change in the optical flow matrix, the EE or EI points are detected. The labeling accuracy for the lateral aspect of the left lung and the lateral aspect of the right lung (0.63±0.71) is significantly lower (P < 0.05) than the accuracy for other positions (0.42±0.44), but the error in almost all scenarios is less than 1 time point. By comparing between automatic and manual labeling in 12 scenarios, we found out that 9 scenarios showed no significant difference (P > 0.05) between two methods. Overall, our method is found to be highly agreeable with manual labeling and greatly shortens the labeling time, requiring less than 8 minutes/ study compared to 4 hours/ study for manual labeling. Our method achieves automatic labeling of EE and EI points without the need for use of patientinternal or external markers.

Ultrasound-assessed diaphragmatic dysfunction as a predictor of weaning outcome in mechanically ventilated patients with sepsis in intensive care unit

BackgroundWeaning from mechanical ventilation is one of the most common challenges in the intensive care unit (ICU). Most of predictive indices of weaning from mechanical ventilation are often inaccurate. This study was performed to assess the accuracy of diaphragmatic ultrasonography for predicting weaning outcome in mechanically ventilated patients with sepsis in ICU.ResultsSixty patients with sepsis in medical ICU were prospectively enrolled. All patients were ventilated in pressure support. Patients underwent a spontaneous breathing trial (SBT) on T-piece when they met all the following criteria: FiO2 < 0.6, PEEP ≤5 cmH2O, PaO2/FiO2 > 200, respiratory rate <30 breaths per minute, absence of fever, alert and cooperative, hemodynamic stability without or with low-dose vasoactive therapy support, and rapid shallow breathing index (RSBI)<105. During the trial, the patient was instructed to perform deep breathing to total lung capacity (TLC) and then exhaling to residual volume (RV) and the diaphragm was visualized in the 8th or 9th intercostal space between anterior and mid-axillary lines using a 3–5-MHz curved ultrasound probe to measure diaphragmatic excursion (DE) and a 7–11-MHz linear ultrasound probe to measure diaphragmatic thickness (DT) at TLC and RV, and the diaphragmatic thickness fraction (DTF) was calculated as percentage from the following formula (thickness at end inspiration—thickness at end expiration)/thickness at end expiration. According to weaning outcome, patients were divided into 2 groups: successful weaning group and weaning failure group. Weaning failure was defined as the inability to maintain spontaneous breathing for at least 48 h, without any form of ventilatory support.In the present study, right DTF of more than 37% and DE during deep breathing of more than 6.1 and 5.4 cm on the Rt and Lt side, respectively, were associated with successful weaning from MV. In the study, the sensitivities for right and left DE and DTF were 58.33, 62.5, and 58.33%, respectively, and the pooled specificities were 83.33, 83.33, and 100%, respectively, with p value = 0.032, 0.028, and 0.001, respectively. The area under curve (AUC) for Rt, Lt DE, and DTF were 0.701, 0.712, and 0.840, respectively. The present data indicate a satisfactory diagnostic accuracy in predicting extubation outcome.ConclusionsUltrasonography-based determination of diaphragm function by assessing DTF and DE can be used as predictor of weaning outcome in mechanically ventilated patients with sepsis.

Prospective Study of Surface Guided Radiation Therapy (SGRT) for Breath Hold SBRT Treatments of the Lung: Analysis of Reliability of Surface Guidance Alone for Internal Tumor Position During Breath Hold

<h3>Purpose/Objective(s)</h3> Respiratory motion management with breath hold (BH) is one technique to limit normal lung and other organ dose during SBRT treatments of the lung. Surface guidance (SGRT) has been utilized for BH in larger targets such as breast cancer, but its reliability in BH treatments of small targets has not been investigated. We report the initial results of the reliability of utilizing SGRT alone as a technique for BH during a prospective study of treatment of primary and metastatic lung tumors. <h3>Materials/Methods</h3> An IRB approved prospective study was conducted in patients (pts) with primary NSCLC or lung metastasis undergoing SBRT. Eligible pts had at least 1 cm of respiratory associated motion on free breathing 4DCT. Pts underwent planning CT with BH either in end inspiration or expiration per investigator choice. The GTV was contoured on the BH planning CT and a 5mm margin added for PTV expansion. During each SBRT treatment, pts performed BH and were aligned within tolerance based on the reference BH surface capture created from the BH planning CT. Pts underwent short-arc CBCT during BH for volumetric match of the target. Before shifts were made for target match, pts performed a BH within tolerance, then shifts were made prior to a new reference surface capture being immediately obtained during the same BH. Pts were then treated in BH based on the new reference surface with a tolerance of 3mm translations and 2 degree rotations. Treatment was stopped if pts fell outside of the predefined tolerances. Midway through treatment, pts underwent a second short arc CBCT during BH to verify the reliability of target position during BH treatment utilizing SGRT. Any subsequent shifts on target volumetric match after the second CBCT were recorded. Linear mixed models for repeated measures were used to analyze rotational and translational shift measurements. <h3>Results</h3> 13 pts and 39 SBRT fractions were treated utilizing SGRT alone for BH. All pts were treated with 54 Gy in 3 fractions. Median free breathing range of motion (4D ROM) was 1.3 cm. Mean displacements after mid-treatment CBCT were minimal in all directions as shown in Table 1. Only one observed fraction had a displacement that exceeded the 5mm PTV expansion (longitudinal shift of 0.59 cm with resulting vector shift of 0.68cm). Factors evaluated for association with shift magnitude included age, BMI, gender, tumor location, 4D ROM, and GTV and PTV size. Higher 4D ROM was associated with increased longitudinal and vector shifts (<i>P</i> = 0.019 and 0.046). <h3>Conclusion</h3> SGRT provides a reliable technique for BH SBRT treatments of the lung. Minimal target displacements on mid treatment BH CBCT were observed. Higher 4D ROM on free breathing scans correlated with larger displacements in tumor position utilizing this technique.

Deriving Regionally Specific Biomarkers of Emphysema and Small Airways Disease Using Variable Threshold Parametric Response Mapping on Volumetric Lung CT Images

This study aims to develop and validate a parametric response mapping (PRM) methodology to accurately identify diseased regions of the lung by using variable thresholds to account for alterations in regional lung function between the gravitationally-independent (anterior) and gravitationally-dependent (posterior) lung in CT images acquired in the supine position. 34 male Sprague-Dawley rats (260-540 g) were imaged, 4 of which received elastase injection (100 units/kg) as a model for emphysema (EMPH). Gated volumetric CT was performed at end-inspiration (EI) and end-expiration (EE) on separate groups of free-breathing (n=20) and ventilated (n=10) rats in the supine position. To derive variable thresholds for the new PRM methodology, voxels were first grouped into 100 bins based on the fractional distance along the anterior-to-posterior direction. Lower limits of normal (LLN) for x-ray attenuation in each bin were set by determining the smallest region that enclosed 98% of voxels from healthy, ventilated animals. When utilizing fixed thresholds in the conventional PRM methodology, a distinct posterior-anterior gradient was seen, in which nearly the entire posterior region of the lung was identified as HEALTHY, while the anterior lung was labeled as significantly less so (t(29)=-3.27, p=0.003). In both cohorts, %SAD progressively increased from posterior to anterior, while %HEALTHY lung decreased in the same direction. After applying our PRM methodology with variable thresholds to the same rat images, the posterior-anterior trend in %SAD quantification was removed from all rats and the significant increase of diseased lung in the anterior was removed. The PRM methodology using variable thresholds provides regionally specific markers of %SAD and %EMPH by correcting for alterations in regional lung function associated with the naturally occurring vertical gradient of dependent vs. non-dependent lung density and compliance.

Intrabreath oscillometry is a sensitive test for assessing disease control in adults with severe asthma

BackgroundAsthma control is not well reflected by spirometry, yet this is the most frequently used measure of lung function in asthma clinics. Oscillometry is an alternative technique suitable for those with severe asthma. ObjectiveTo investigate usefulness of oscillometry in subjects with severe asthma to determine which outcome variables best reflected asthma control. MethodsAdults with severe asthma were recruited from a severe asthma clinic in Brazil. Oscillometry (conventional multifrequency measurements between 6 and 32 Hz; intrabreath tracking at 8 Hz) and spirometry were performed. Asthma control was determined by the asthma control test. ResultsA total of 60 adults were evaluated; mean age was 56.7 years. There was predominance of women (82%), and most patients (63%) reported onset of asthma symptoms in childhood or adolescence. There were no differences between controlled and uncontrolled asthma in spirometry. Uncontrolled asthma was associated with higher resistance (at 8 and 10 Hz) and more negative reactance (for 6, 8, and 10 Hz) (P < .05) on conventional oscillometry. Intrabreath oscillometry revealed significant differences between controlled and uncontrolled patients with asthma (P < .01 for changes in resistance and reactance between end expiration and end inspiration). The accuracy of the lung function tests in discriminating between controlled and uncontrolled asthma was higher for intrabreath variables (area under the curve = 0.65-0.72). ConclusionOscillometry, particularly the intrabreath technique, better reflected asthma control than spirometry measures. Our findings suggest that oscillometry may be a useful technique to aid management of severe asthma, with a potential to reflect loss of disease control.

Automatic Screening of Lung Diseases by 3D Active Contour Method for Inhomogeneous Motion Estimation in CT Image Pairs

Lung diseases are now the third leading cause of death worldwide because of the many risk factors we are exposed to daily, such as air pollution, tobacco use, viruses (such as COVID-19), and bacteria. This work introduces a new approach of the 3D Active Contour Model (3D ACM) to estimate an inhomogeneous motion of lungs, which can be used to analyze lung disease patterns using a hierarchical predictive model. The biophysical model of lungs consists of End Expiratory (EE) and End Inspiratory (EI) models, generated by high-resolution computed tomography images (HRCT). A proposed technique uses the 3D ACM to estimate the velocity vector by using the corresponding points on the parametric surface model of the EE model to the EI model. The external energy from the EI models is the external force that pushes the 3D parametric surface to reach the boundary. The external forces, such as the balloon force and Gradient Vector Flow (GVF), were adjusted adaptively based on the which was calculated from the ratio of the maximum value of EI to EE on the Z axis. Next, the feature representation is studied and evaluated based on the lung structure, separated into five lobes. The stepwise regression, Support Vector Machine (SVM), and Artificial Neural Network (ANN) techniques are applied to classify the lung diseases into normal, obstructive lung, and restrictive lung diseases. In conclusion, the inhomogeneous motion pattern of lungs integrated with medical-based knowledge can be used to analyze lung diseases by differentiating normal and abnormal motion patterns and separating restrictive and obstructive lung diseases. HIGHLIGHTS Inhomogeneous motion analysis from the expanding and shrinking lungs of HRCT pair Adaptive 3D Active Contour Model (ACM) for detecting the shape of the lung by balancing the balloon force with the stopping condition Lung lopes separation using oblique fissure and anatomical location Structure the velocity vector map of lung motion using bag of words of the magnitude Neural Network model for predicting obstructive and restrictive lung diseases GRAPHICAL ABSTRACT

OFx: A method of 4D image construction from free-breathing non-gated MRI slice acquisitions of the thorax via optical flux.

Since real-time 4D dynamic magnetic resonance imaging (dMRI) methods with adequate spatial and temporal resolution for imaging the pediatric thorax are currently not available, free-breathing slice acquisitions followed by appropriate 4D construction methods are currently employed. Self-gating methods, which extract breathing signals only from image information without any external gating technology, have much potential for this purpose, such as for use in studying pediatric thoracic insufficiency syndrome (TIS). Patients with TIS frequently suffer from extreme malformations of the chest wall, diaphragm, and spine, leading to breathing that is very complex, including deep or shallow respiratory cycles. Existing 4D construction methods cannot perform satisfactorily in this scenario, and most are not fully automatic, requiring manual interactive operations. In this paper, we propose a novel fully automatic 4D image construction method based on an image-derived concept called flux to address these challenges. We utilized 25 dMRI data sets from 25 pediatric subjects with no known thoracic anomalies and 58 dMRI data sets from 29 patients with TIS where each patient had a dMRI scan before and after surgery. A time sequence of 80 slices are acquired at each sagittal location continuously at a rate of ~480ms per slice under free-breathing conditions, with 30-40 sagittal locations across the chest for each subject depending on the thoracic size. In our approach, we first extract the breathing signal for each sagittal location based on the flux of the optical flow vector field of the body region from the image time series. Here, for each time point of respiratory phase, the net flux of the body region can be regarded as the flux going into or out of the body region, which we term Optical Flux (OFx). OFx provides a very robust representation of the real breathing motion of the thorax. OFx allows us to perform a full analysis of all respiratory cycles, extract only normal cycles in a robust manner, and map all extracted normal cycles on to one cosine respiration model for each sagittal location. Subsequently, we re-sample one normal cycle from the respiration model for each location independently. The normal cycle models associated with the different sagittal locations are finally composited to form the final constructed 4D image. We employ several metrics to evaluate the quality of the 4D construction results: Eie - error in locating time instants corresponding to end inspiration and end expiration; Eto - deviation from correct temporal order in each detected normal cycle; Ess - deviation in spatial smoothness; and Esc - deviation from spatial continuity as scored by a reader. The means and standard deviations of these metrics for normal subjects and TIS patients are found to be, respectively: Eie: 0.25±0.05 and 0.38±0.16 in units of time instance (ideal value=0); Eto: 2.7% ± 2.3% and 1.8%±2% (ideal value=0%); Ess: 0.5±0.17 and 0.54±0.25 in pixel units (ideal value=0); Esc: 4.6±0.48 and 4.56±0.98 (score range: best=5, worst=1). The results show that the OFx method achieves excellent spatial and temporal continuity and its yield was 100% meaning that it successfully performed 4D construction on every data set tested. Compared to a recently published method, OFx is fully automatic requiring about 5min of computational time per study starting from acquired dMRI scans. The method achieves high temporal and spatial continuity even on complex TIS data sets that include many abnormal respiratory cycles. A new 4D dMRI construction method based on the concept of optical flux is presented which is fully automatic and very robust in deriving respiratory signals purely from dynamic image sequences even when presented with complex breathing patterns due to severe disease conditions like TIS. Evaluations show that its accuracy is comparable to the variations found in manual annotations. An important characteristic of the method is that it is independent of the number of sagittal locations used in the construction process, which suggests that it is applicable to imaging techniques where data are acquired at only a few sagittal locations instead of the full width of the thorax. The method is not tied to any specific imaging modality, as demonstrated in this paper on not just dMRI but dynamic computed tomography (CT) as well.

Recurrent pneumothorax following chest tube removal in thoracic stab wounds: a comparative study between end inspiratory versus end expiratory removal techniques at a major trauma centre in South Africa.

Tube thoracostomy (TT) insertion is a commonly performed procedure in trauma that is standardised, but the optimal removal technique based on the timing in relation to the respiratory cycle remains controversial. A prospective study was undertaken at a major trauma centre in South Africa over a 4-year period from January 2010 to December 2013, and included all patients with pneumothorax secondary to thoracic stab wounds. TTs were removed by either end of inspiration technique (EIT) or end of expiration (EET) technique and the rate of recurrent pneumothorax (RPTX) following removal was compared. We hypothesized that there is no difference in the rate of RPTX between the end inspiratory (EI) and end expiratory (EE) removal technique. A total 347 patients were included. Of the 184 TTs removed by EIT, there were 17 (9%) RPTXs. Of the 163 with EET, there were 11 RPTXs (7%), (9% versus 7%, chi-squared, P = 0.395). Of the total 28 (9%) patients with RPTXs following removal of chest tubes, two (7%) required reinsertion of chest tube (0.5% (1/184) in EIT and 0.6% (1/163) in EET, P = 0.747). Timing of TT removal in relation to the respiratory cycle does not appear to influence the incidence of RPTX in patients with thoracic stab wounds. Technique of removal may well be a more important consideration and more attention must be focused on refining the optimal technique.

Lung parenchymal characterization via thoracic dynamic MRI in normal children and pediatric patients with TIS.

Quantitative thoracic dynamic magnetic resonance imaging (QdMRI), a recently developed technique, provides a potential solution for evaluating treatment effects in thoracic insufficiency syndrome (TIS). In this paper, we demonstrate how lung parenchymal characteristics can be assessed via intensity properties in lung dynamic MRI, a modality suitable for use in pediatric patients. The QdMRI-based approach includes dynamic MR image acquisition, 4D image construction, image pre-processing with non-uniformity correction and intensity standardization, and lung segmentation from the 4D constructed image via a deep learning approach, as well as extraction of image parenchymal intensity properties from the segmented lungs and statistical comparisons among different clinical scenarios. We include 22 dMRI scans from 11 TIS patients (each with both pre-operative and post-operative scans) and 23 dMRI scans from healthy children. Two-sided paired t-testing is performed to compare lung intensity properties between end of expiration (EE) and end of inspiration (EI) within TIS patients (pre-operative and post-operative, separately) and normal children. We also compare the lung intensity properties at EE and EI among pre-operative TIS patients, post-operative TIS patients, and normal children. Experimental results show that lung (T2) intensity at EI is significantly lower than that at EE and lung intensity of post-operative TIS patients is significantly lower than that in pre-operative TIS patients and closer to that of normal children than to that of pre-operative TIS patients, indicating improvement in lung aeration. To our knowledge, this is the first study to provide a quantitative dynamic functional method to analyze lung parenchyma during tidal breathing on dynamic MRI in both healthy children and pediatric patients with TIS.

Influences of assisted breathing and mechanical ventilator settings on tidal volume and alveolar pressures in acute respiratory distress syndrome: a bench study.

Objective:To evaluate the influences of respiratory muscle efforts and respiratory rate setting in the ventilator on tidal volume and alveolar distending pressures at end inspiration and expiration in volume-controlled ventilation and pressure-controlled ventilation modes in acute respiratory distress syndrome.Methods:An active test lung (ASL 5000™) connected to five intensive care unit ventilators was used in a model of acute respiratory distress syndrome. Respiratory muscle efforts (muscle pressure) were configured in three different ways: no effort (muscle pressure: 0cmH2O); inspiratory efforts only (muscle pressure:-5cmH2O, neural inspiratory time of 0.6s); and both inspiratory and expiratory muscle efforts (muscle pressure:-5/+5cmH2O). Volume-controlled and pressure-controlled ventilation modes were set to deliver a target tidal volume of 420mL and positive end-expiratory pressure of 10cmH2O. The tidal volume delivered to the lungs, alveolar pressures at the end of inspiration, and alveolar pressures at end expiration were evaluated.Results:When triggered by the simulated patient, the median tidal volume was 27mL lower than the set tidal volume (range-63 to +79mL), and there was variation in alveolar pressures with a median of 25.4cmH2O (range 20.5 to 30cmH2O). In the simulated scenarios with both spontaneous inspiratory and expiratory muscle efforts and with a mandatory respiratory rate lower than the simulated patient's efforts, the median tidal volume was higher than controlled breathing.Conclusion:Adjusting respiratory muscle effort and pulmonary ventilator respiratory rate to a value above the patient’s respiratory rate in assisted/controlled modes generated large variations in tidal volume and pulmonary pressures, while the controlled mode showed no variations in these outcomes.

5D Flow MRI: A Fully Self-gated, Free-running Framework for Cardiac and Respiratory Motion-resolved 3D Hemodynamics.

To implement, validate, and apply a self-gated free-running whole-heart five-dimensional (5D) flow MRI framework to evaluate respiration-driven effects on three-dimensional (3D) hemodynamics in a clinical setting. In this prospective study, a free-running five-dimensional (5D) flow sequence was implemented with 3D radial sampling, self-gating, and a compressed-sensing reconstruction. The 5D flow was evaluated in a pulsatile phantom and adult participants with aortic and/or valvular disease who were enrolled between May and August 2019. Conventional twofold-accelerated four-dimensional (4D) flow of the thoracic aorta with navigator gating was performed as a reference comparison. Continuous parameters were evaluated for parameter normality and were compared between conventional 4D flow and 5D flow using a signed-rank or two-tailed paired t test. Differences between respiratory states were evaluated using a repeated-measure analysis of variance or a nonparametric Friedman test. A total of 20 adult participants (mean age, 49 years ± 17 [standard deviation]; 18 men and two women) were included. In vitro 5D flow results showed excellent agreement with conventional 4D flow-derived values (peak and net flow, <7% difference over all quantified planes). Whole-heart 5D flow data were collected in all participants in 7.65 minutes ± 0.35 (acceleration rate = 36.0-76.9) versus 9.88 minutes ± 3.17 for conventional aortic 4D flow. In vivo, 5D flow demonstrated moderate agreement with conventional 4D flow but demonstrated overestimation in net flow and peak velocity (up to 26% and 12%, respectively) in the ascending aorta and underestimation (<12%) in the arch and descending aorta. Respiratory-resolved analyses of caval veins showed significantly increased net and peak flow in the inferior vena cava in end inspiration compared with end expiration, and the opposite trend was shown in the superior vena cava. A free-running 5D flow MRI framework consistently captured cardiac and respiratory motion-resolved 3D hemodynamics in less than 8 minutes. Supplemental material is available for this article. © RSNA, 2020.

The effect of airway motion and breathing phase during imaging on CFD simulations of respiratory airflow

RationaleComputational fluid dynamics (CFD) simulations of respiratory airflow can quantify clinically useful information that cannot be obtained directly, such as the work of breathing (WOB), resistance to airflow, and pressure loss. However, patient-specific CFD simulations are often based on medical imaging that does not capture airway motion and thus may not represent true physiology, directly affecting those measurements. ObjectivesTo quantify the variation of respiratory airflow metrics obtained from static models of airway anatomy at several respiratory phases, temporally averaged airway anatomies, and dynamic models that incorporate physiological motion. MethodsNeonatal airway images were acquired during free-breathing using 3D high-resolution MRI and reconstructed at several respiratory phases in two healthy subjects and two with airway disease (tracheomalacia). For each subject, five static (end expiration, peak inspiration, end inspiration, peak expiration, averaged) and one dynamic CFD simulations were performed. WOB, airway resistance, and pressure loss across the trachea were obtained for each static simulation and compared with the dynamic simulation results. ResultsLarge differences were found in the airflow variables between the static simulations at various respiratory phases and the dynamic simulation. Depending on the static airway model used, WOB, resistance, and pressure loss varied up to 237%, 200%, and 94% compared to the dynamic simulation respectively. ConclusionsChanges in tracheal size and shape throughout the breathing cycle directly affect respiratory airflow dynamics and breathing effort. Simulations incorporating realistic airway wall dynamics most closely represent airway physiology; if limited to static simulations, the airway geometry must be obtained during the respiratory phase of interest for a given pathology.

Assessment of diaphragm dysfunction during cardiac rehabilitation after heart surgery: the role of ultrasound imaging

Abstract Background Diaphragm dysfunction is a frequent and underdiagnosed complication of cardiac surgery. It can cause dyspnoea, decreased exercise performance and, in more severe cases, respiratory failure. Ultrasonography (US) is a valuable, non-invasive technique for the assessment of diaphragm function. Only few trials have been conducted using US to evaluate diaphragm functional recovery after cardiovascular rehabilitation (CR). Purpose The aim of the study was to assess with US the incidence of diaphragm dysfunction after heart surgery and to define the impact of an inpatient CR programme on diaphragm functional recovery. Methods We performed a single-centre prospective cohort study, enrolling 185 patients hospitalized in our CR unit: 99 patients underwent mitral valve repair or replacement, 28 tricuspid valve repair or replacement, 53 aortic valve replacement, 30 coronary artery bypass grafting, 59 combined surgery and 14 other surgical procedures. Diaphragm US was performed at admission and after 10 rehabilitative sessions. We assess the following parameters on quiet breathing: excursion, time of inspiration, time of a respiratory cycle and contraction velocity (slope) in M-mode on the right anterior subcostal projections and thickening fraction (TF) in B-mode on the right intercostal projections. TF was defined as [(thickness at end inspiration–thickness at end expiration)/thickness at end expiration]. Results The median excursion at admission was 1.6 cm. Patients with excursion &amp;lt;2 cm (lower limit for the general population) were considered with diaphragm dysfunction. Following cardiac surgery, the incidence of diaphragm dysfunction was 70.8%. Patients with excursion &amp;lt;2 cm at admission gained an important benefit from CR, with a significant improvement in TF (p&amp;lt;0.001), excursion (p&amp;lt;0.001), time of inspiration (p&amp;lt;0.001), time of a respiratory cycle (p&amp;lt;0.001) and slope (p&amp;lt;0.001). Conversely, in patients with excursion ≥2 cm there was no significant improvement in slope (p=0.539) and excursion (p=0.179). At the final assessment, diaphragm function recovered in 50.5% of the patients, whilst 49.5% had a failure of recovery (excursion relative change between admission and discharge &amp;lt;33%). The multivariate analysis identified combined surgery (OR 3.08; 95% CI 1.59–5.99, p=0.001) and post-surgical pneumothorax (OR 3.05; 95% CI 1.23–7.55, p=0.036) as independent predictors of failure of diaphragm function recovery. Conclusions US might be a valuable tool for initial and follow-up assessment of patients after cardiac surgery. CR has been shown to be an effective strategy to improve diaphragm parameters in patients with post-surgical dysfunction. Patients undergoing combined surgery or developing post-surgical pneumothorax might benefit from a personalised rehabilitation programme to improve diaphragm function. Funding Acknowledgement Type of funding source: None

Dynamic brain-body coupling of breath-by-breath O2-CO2 exchange ratio with resting state cerebral hemodynamic fluctuations.

BackgroundThe origin of low frequency cerebral hemodynamic fluctuations (CHF) in the resting state remains unknown. Breath-by breath O2-CO2 exchange ratio (bER) has been reported to correlate with the cerebrovascular response to brief breath hold challenge at the frequency range of 0.008–0.03Hz in healthy adults. bER is defined as the ratio of the change in the partial pressure of oxygen (ΔPO2) to that of carbon dioxide (ΔPCO2) between end inspiration and end expiration. In this study, we aimed to investigate the contribution of respiratory gas exchange (RGE) metrics (bER, ΔPO2 and ΔPCO2) to low frequency CHF during spontaneous breathing.MethodsTwenty-two healthy adults were included. We used transcranial Doppler sonography to evaluate CHF by measuring the changes in cerebral blood flow velocity (ΔCBFv) in bilateral middle cerebral arteries. The regional CHF were mapped with blood oxygenation level dependent (ΔBOLD) signal changes using functional magnetic resonance imaging. Temporal features and frequency characteristics of RGE metrics during spontaneous breathing were examined, and the simultaneous measurements of RGE metrics and CHF (ΔCBFv and ΔBOLD) were studied for their correlation.ResultsWe found that the time courses of ΔPO2 and ΔPCO2 were interdependent but not redundant. The oscillations of RGE metrics were coherent with resting state CHF at the frequency range of 0.008–0.03Hz. Both bER and ΔPO2 were superior to ΔPCO2 in association with CHF while CHF could correlate more strongly with bER than with ΔPO2 in some brain regions. Brain regions with the strongest coupling between bER and ΔBOLD overlapped with many areas of default mode network including precuneus and posterior cingulate.ConclusionAlthough the physiological mechanisms underlying the strong correlation between bER and CHF are unclear, our findings suggest the contribution of bER to low frequency resting state CHF, providing a novel insight of brain-body interaction via CHF and oscillations of RGE metrics.

Generation of a local lung respiratory motion model using a weighted sparse algorithm and motion prior-based registration

Respiration-introduced tumor location uncertainty is a challenge in lung percutaneous interventions, especially for the respiratory motion estimation of the tumor and surrounding vessel structures. In this work, a local motion modeling method is proposed based on whole-chest computed tomography (CT) and CT-fluoroscopy (CTF) scans. A weighted sparse statistical modeling (WSSM) method that can accurately capture location errors for each landmark point is proposed for lung motion prediction. By varying the sparse weight coefficients of the WSSM method, newly input motion information is approximately represented by a sparse linear combination of the respiratory motion repository and employed to serve as prior knowledge for the following registration process. We have also proposed an adaptive motion prior-based registration method to improve the motion prediction accuracy of the motion model in the region of interest (ROI). This registration method adopts a B-spline scheme to interactively weight the relative influence of the prior knowledge, model surface and image intensity information by locally controlling the deformation in the CTF image region. The proposed method has been evaluated on 15 image pairs between the end-expiratory (EE) and end-inspiratory (EI) phases and 31 four-dimensional CT (4DCT) datasets. The results reveal that the proposed WSSM method achieved a better motion prediction performance than other existing lung statistical motion modeling methods, and the motion prior-based registration method can generate more accurate local motion information in the ROI.