Influence of posture,sex, and age on breathing pattern and chest wall motion in healthy subjects

ObjectiveWe evaluated the effects of posture, sex, and age on breathing pattern and chest wall motion during quiet breathing in healthy participants.MethodsEighty-three participants aged 42.72 (SD = 21.74) years presenting normal pulmonary function were evaluated by optoelectronic plethysmography in the seated, inclined (with 45° of trunk inclination), and supine positions. This method allowed to assess the chest wall in a three dimensional way considering the chest wall as three compartments: pulmonary rib cage, abdominal rib cage and abdomen.ResultsPosture influenced all variables of breathing pattern and chest wall motion, except respiratory rate and duty cycle. Chest wall tidal volume and minute ventilation were reduced (p < 0.05) in both sexes from seated to inclined and from seated to supine positions, mainly in males. Moreover, moving from seated to supine position significantly increased the percentage contribution of the abdomen to the tidal volume in both sexes (p < 0.0001). Regarding sex, women showed higher contribution of thoracic compartment compared to men (p = 0.008). Aging provided reductions on rib cage contributions to tidal volume that were compensated by increases of abdomen contributions (p < 0.0001). In addition, increases in end-inspiratory and end-expiratory volumes over the years were observed.ConclusionThe degree of contribution of chest wall compartments is dependent on posture, sex, and age. Therefore, verticalization increases expansion of pulmonary rib cage as well as horizontalization increases abdominal displacement. Women presented higher thoracic contribution to tidal volume than men. Aging reduces rib cage contributions to tidal volume that were compensated by increases of abdomen contributions.     

Respiratory motion compensation by model-based catheter tracking during EP procedures

In many cases, radio-frequency catheter ablation of the pulmonary veins attached to the left atrium still involves fluoroscopic image guidance. Two-dimensional X-ray navigation may also take advantage of overlay images derived from static pre-operative 3D volumetric data to add anatomical details otherwise not visible under X-ray. Unfortunately, respiratory motion may impair the utility of static overlay images for catheter navigation. We developed a novel approach for image-based 3D motion estimation and compensation as a solution to this problem. It is based on 3D catheter tracking which, in turn, relies on 2D/3D registration. To this end, a bi-plane C-arm system is used to take X-ray images of a special circumferential mapping catheter from two directions. In the first step of the method, a 3D model of the device is reconstructed. Three-dimensional respiratory motion at the site of ablation is then estimated by tracking the reconstructed catheter model in 3D based on bi-plane fluoroscopy. Phantom data and clinical data were used to assess model-based catheter tracking. Our phantom experiments yielded an average 2D tracking error of 1.4 mm and an average 3D tracking error of 1.1 mm. Our evaluation of clinical data sets comprised 469 bi-plane fluoroscopy frames (938 monoplane fluoroscopy frames). We observed an average 2D tracking error of 1.0 ± 0.4 mm and an average 3D tracking error of 0.8 ± 0.5 mm. These results demonstrate that model-based motion-compensation based on 2D/3D registration is both feasible and accurate.     

Computerized identification of airway wall in CT examinations using a 3D active surface evolution approach

Airway diseases (e.g., asthma, emphysema, and chronic bronchitis) are extremely common worldwide. Any morphological variations (abnormalities) of airways may physically change airflow and ultimately affect the ability of the lungs in gas exchange. In this study, we describe a novel algorithm aimed to automatically identify airway walls depicted on CT images. The underlying idea is to place a three-dimensional (3D) surface model within airway regions and thereafter allow this model to evolve (deform) under predefined external and internal forces automatically to the location where these forces reach a state of balance. By taking advantage of the geometric and the density characteristics of airway walls, the evolution procedure is performed in a distance gradient field and ultimately stops at regions with the highest contrast. The performance of this scheme was quantitatively evaluated from several perspectives. First, we assessed the accuracy of the developed scheme using a dedicated lung phantom in airway wall estimation and compared it with the traditional full-width at half maximum (FWHM) method. The phantom study shows that the developed scheme has an error ranging from 0.04 mm to 0.36 mm, which is much smaller than the FWHM method with an error ranging from 0.16 mm to 0.84 mm. Second, we compared the results obtained by the developed scheme with those manually delineated by an experienced (>30 years) radiologist on clinical chest CT examinations, showing a mean difference of 0.084 mm. In particular, the sensitivity of the scheme to different reconstruction kernels was evaluated on real chest CT examinations. For the ‘lung’, ‘bone’ and ‘standard’ kernels, the average airway wall thicknesses computed by the developed scheme were 1.302 mm, 1.333 mm and 1.339 mm, respectively. Our preliminary experiments showed that the scheme had a reasonable accuracy in airway wall estimation. For a clinical chest CT examination, it took around 4 min for this scheme to identify the inner and outer airway walls on a modern PC.     

Computed tomography findings of complications resulting from cardiopulmonary resuscitation

IntroductionThis retrospective study was conducted to evaluate injuries related to cardiopulmonary resuscitation (CPR) and their associated factors using postmortem computed tomography (PMCT) and whole body CT after successful resuscitation.MethodsThe inclusion criteria were adult, non-traumatic, out-of-hospital cardiac arrest patients who were transported to our emergency room between April 1, 2008 and March 31, 2013. Following CPR, PMCT was performed in patients who died without return of spontaneous circulation (ROSC). Similarly, CT scans were performed in patients who were successfully resuscitated within 72 h after ROSC. The injuries associated with CPR were analysed retrospectively on CT images.ResultsDuring the study period, 309 patients who suffered out-of hospital cardiac arrest were transported to our emergency room and received CPR; 223 were enrolled in the study.The CT images showed that 156 patients (70.0%) had rib fractures, and 18 patients (8.1%) had sternal fractures. Rib fractures were associated with older age (78.0 years vs. 66.0 years, p < 0.01), longer duration of CPR (41 min vs. 33 min, p < 0.01), and lower rate of ROSC (26.3% vs. 55.3%, p < 0.01). All sternal fractures occurred with rib fractures and were associated with a greater number of rib fractures, higher age, and a lower rate of ROSC than rib fractures only cases. Bilateral pneumothorax was observed in two patients with rib fractures.ConclusionsPMCT is useful for evaluating complications related to chest compression. Further investigations with PMCT are needed to reduce complications and improve the quality of CPR.     

Automatic multimodal 2D/3D breast image registration using biomechanical FEM models and intensity-based optimization

Due to their different physical origin, X-ray mammography and Magnetic Resonance Imaging (MRI) provide complementary diagnostic information. However, the correlation of their images is challenging due to differences in dimensionality, patient positioning and compression state of the breast. Our automated registration takes over part of the correlation task. The registration method is based on a biomechanical finite element model, which is used to simulate mammographic compression. The deformed MRI volume can be compared directly with the corresponding mammogram. The registration accuracy is determined by a number of patient-specific parameters. We optimize these parameters – e.g. breast rotation – using image similarity measures. The method was evaluated on 79 datasets from clinical routine. The mean target registration error was 13.2 mm in a fully automated setting. On basis of our results, we conclude that a completely automated registration of volume images with 2D mammograms is feasible. The registration accuracy is within the clinically relevant range and thus beneficial for multimodal diagnosis.     

Clavicle segmentation in chest radiographs

Automated delineation of anatomical structures in chest radiographs is difficult due to superimposition of multiple structures. In this work an automated technique to segment the clavicles in posterior-anterior chest radiographs is presented in which three methods are combined. Pixel classification is applied in two stages and separately for the interior, the border and the head of the clavicle. This is used as input for active shape model segmentation. Finally dynamic programming is employed with an optimized cost function that combines appearance information of the interior of the clavicle, the border, the head and shape information derived from the active shape model. The method is compared with a number of previously described methods and with independent human observers on a large database. This database contains both normal and abnormal images and will be made publicly available. The mean contour distance of the proposed method on 249 test images is 1.1 ± 1.6 mm and the intersection over union is 0.86 ± 0.10.     

Clinical value of relative quantification ultrasound elastography in characterizing breast tumors

ObjectivesTo evaluate ultrasound elastography (USE) using strain ratio (SR), a relative quantification approach for breast lesions characterization.MethodsOne hundred forty-seven consecutive patients with a total of 156 breast lesions underwent USE. Technical accuracy was assessed automatically. For SR evaluation a rounded ROI was depicted inside fat (F), glandular tissue (G) and inside the lesion (L), preferably at the same depth. R1, mean value of the G and F ratio, stands for in background tissue composition elasticity. R2; mean value of L/F stands for in lesion elasticity, both evaluated in arbitrary unit (au). Two-years follow-up and pathology results were standard of reference. Mann–Whitney test, ROC analysis and Chi-square with Yates correction were used.ResultsWith the exception of 27 cysts, 17 malignant and 112 benign lesions were found. R1 values were 1.6 ± 0.7 au and 1.2 ± 0.9 au (p = 0.015 NS); R2 values were 6.1 ± 2.5 au and 1.9 ± 1.3 au (p < 0.001) for malignant and benign lesions, respectively. A threshold of 3.3 au showed a sensitivity and specificity of 88% and 87%, respectively with an AUC of 93%. Fifteen false positive and two false negative were detected.ConclusionRelative quantification of ultrasound elastography allows to find high levels of diagnostic accuracy in characterizing breast tumors above all in downgrading BI-RADS 3 and 4 lesions.     

Cortical surface shift estimation using stereovision and optical flow motion tracking via projection image registration

Stereovision is an important intraoperative imaging technique that captures the exposed parenchymal surface noninvasively during open cranial surgery. Estimating cortical surface shift efficiently and accurately is critical to compensate for brain deformation in the operating room (OR). In this study, we present an automatic and robust registration technique based on optical flow (OF) motion tracking to compensate for cortical surface displacement throughout surgery. Stereo images of the cortical surface were acquired at multiple time points after dural opening to reconstruct three-dimensional (3D) texture intensity-encoded cortical surfaces. A local coordinate system was established with its z-axis parallel to the average surface normal direction of the reconstructed cortical surface immediately after dural opening in order to produce two-dimensional (2D) projection images. A dense displacement field between the two projection images was determined directly from OF motion tracking without the need for feature identification or tracking. The starting and end points of the displacement vectors on the two cortical surfaces were then obtained following spatial mapping inversion to produce the full 3D displacement of the exposed cortical surface. We evaluated the technique with images obtained from digital phantoms and 18 surgical cases – 10 of which involved independent measurements of feature locations acquired with a tracked stylus for accuracy comparisons, and 8 others of which 4 involved stereo image acquisitions at three or more time points during surgery to illustrate utility throughout a procedure. Results from the digital phantom images were very accurate (0.05 pixels). In the 10 surgical cases with independently digitized point locations, the average agreement between feature coordinates derived from the cortical surface reconstructions was 1.7–2.1 mm relative to those determined with the tracked stylus probe. The agreement in feature displacement tracking was also comparable to tracked probe data (difference in displacement magnitude was <1 mm on average). The average magnitude of cortical surface displacement was 7.9 ± 5.7 mm (range 0.3–24.4 mm) in all patient cases with the displacement components along gravity being 5.2 ± 6.0 mm relative to the lateral movement of 2.4 ± 1.6 mm. Thus, our technique appears to be sufficiently accurate and computationally efficiency (typically ∼15 s), for applications in the OR.     

Fast and robust 3D ultrasound registration – Block and game theoretic matching

Real-time 3D US has potential for image guidance in minimally invasive liver interventions. However, motion caused by patient breathing makes it hard to visualize a localized area, and to maintain alignment with pre-operative information. In this work we develop a fast affine registration framework to compensate in real-time for liver motion/displacement due to breathing. The affine registration of two consecutive ultrasound volumes in time is performed using block-matching. For a set of evenly distributed points in one volume and their correspondences in the other volume, we propose a robust outlier rejection method to reject false matches. The inliers are then used to determine the affine transformation. The approach is evaluated on 13 4D ultrasound sequences acquired from 8 subjects. For 91 pairs of 3D ultrasound volumes selected from these sequences, a mean registration error of 1.8 mm is achieved. A graphics processing unit (GPU) implementation runs the 3D US registration at 8 Hz.     

Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map

Optical coherence tomography (OCT) is a powerful and noninvasive method for retinal imaging. In this paper, we introduce a fast segmentation method based on a new variant of spectral graph theory named diffusion maps. The research is performed on spectral domain (SD) OCT images depicting macular and optic nerve head appearance. The presented approach does not require edge-based image information in localizing most of boundaries and relies on regional image texture. Consequently, the proposed method demonstrates robustness in situations of low image contrast or poor layer-to-layer image gradients. Diffusion mapping applied to 2D and 3D OCT datasets is composed of two steps, one for partitioning the data into important and less important sections, and another one for localization of internal layers. In the first step, the pixels/voxels are grouped in rectangular/cubic sets to form a graph node. The weights of the graph are calculated based on geometric distances between pixels/voxels and differences of their mean intensity. The first diffusion map clusters the data into three parts, the second of which is the area of interest. The other two sections are eliminated from the remaining calculations. In the second step, the remaining area is subjected to another diffusion map assessment and the internal layers are localized based on their textural similarities. The proposed method was tested on 23 datasets from two patient groups (glaucoma and normals). The mean unsigned border positioning errors (mean ± SD) was 8.52 ± 3.13 and 7.56 ± 2.95 μm for the 2D and 3D methods, respectively.     

A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images

Prostate segmentation aids in prostate volume estimation, multi-modal image registration, and to create patient specific anatomical models for surgical planning and image guided biopsies. However, manual segmentation is time consuming and suffers from inter-and intra-observer variabilities. Low contrast images of trans rectal ultrasound and presence of imaging artifacts like speckle, micro-calcifications, and shadow regions hinder computer aided automatic or semi-automatic prostate segmentation. In this paper, we propose a prostate segmentation approach based on building multiple mean parametric models derived from principal component analysis of shape and posterior probabilities in a multi-resolution framework. The model parameters are then modified with the prior knowledge of the optimization space to achieve optimal prostate segmentation. In contrast to traditional statistical models of shape and intensity priors, we use posterior probabilities of the prostate region determined from random forest classification to build our appearance model, initialize and propagate our model. Furthermore, multiple mean models derived from spectral clustering of combined shape and appearance parameters are applied in parallel to improve segmentation accuracies. The proposed method achieves mean Dice similarity coefficient value of 0.91 ± 0.09 for 126 images containing 40 images from the apex, 40 images from the base and 46 images from central regions in a leave-one-patient-out validation framework. The mean segmentation time of the procedure is 0.67 ± 0.02 s.     

A method of 2D/3D registration of a statistical mouse atlas with a planar X-ray projection and an optical photo

The development of sophisticated and high throughput whole body small animal imaging technologies has created a need for improved image analysis and increased automation. The registration of a digital mouse atlas to individual images is a prerequisite for automated organ segmentation and uptake quantification. This paper presents a fully-automatic method for registering a statistical mouse atlas with individual subjects based on an anterior–posterior X-ray projection and a lateral optical photo of the mouse silhouette. The mouse atlas was trained as a statistical shape model based on 83 organ-segmented micro-CT images. For registration, a hierarchical approach is applied which first registers high contrast organs, and then estimates low contrast organs based on the registered high contrast organs. To register the high contrast organs, a 2D-registration-back-projection strategy is used that deforms the 3D atlas based on the 2D registrations of the atlas projections. For validation, this method was evaluated using 55 subjects of preclinical mouse studies. The results showed that this method can compensate for moderate variations of animal postures and organ anatomy. Two different metrics, the Dice coefficient and the average surface distance, were used to assess the registration accuracy of major organs. The Dice coefficients vary from 0.31 ± 0.16 for the spleen to 0.88 ± 0.03 for the whole body, and the average surface distance varies from 0.54 ± 0.06 mm for the lungs to 0.85 ± 0.10 mm for the skin. The method was compared with a direct 3D deformation optimization (without 2D-registration-back-projection) and a single-subject atlas registration (instead of using the statistical atlas). The comparison revealed that the 2D-registration-back-projection strategy significantly improved the registration accuracy, and the use of the statistical mouse atlas led to more plausible organ shapes than the single-subject atlas. This method was also tested with shoulder xenograft tumor-bearing mice, and the results showed that the registration accuracy of most organs was not significantly affected by the presence of shoulder tumors, except for the lungs and the spleen.     

No difference in autopsy detected injuries in cardiac arrest patients treated with manual chest compressions compared with mechanical compressions with the LUCAS™ device—A pilot study

AimTo compare the variety and incidence of internal injuries after manual and mechanical chest compressions during CPR.MethodsIn a prospective pilot study conducted in two Swedish cities, 85 patients underwent autopsy after unsuccessful resuscitation attempts with manual or mechanical chest compressions, the latter with the LUCAS? device. Autopsy was performed and the results were evaluated according to a specified protocol.ResultsNo injuries were found in 26/47 patients in the manual group and in 16/38 patients in the LUCAS group (p = 0.28). Sternal fracture was present in 10/47 in the manual group and 11/38 in the LUCAS group (p = 0.46), and there were multiple rib fractures (≥3 fractures) in 13/47 in the manual group and in 17/38 in the LUCAS group (p = 0.12). Bleeding in the ventral mediastinum was noted in 2/47 and 3/38 in the manual and LUCAS groups respectively (p = 0.65), retrosternal bleeding in 1/47 and 3/38 (p = 0.32), epicardial bleeding in 1/47 and 4/38 (p = 0.17), and haemopericardium in 4/47 and 3/38 (p = 1.0) respectively. One patient in the LUCAS group had a small rift in the liver and one patient in the manual group had a rift in the spleen. These injuries were not considered to have contributed to the patient's death.ConclusionMechanical chest compressions with the LUCAS? device appear to be associated with the same variety and incidence of injuries as manual chest compressions.     

Can diaphragmatic breathing modify chest wall volumes during inspiratory loaded breathing in patients with heart failure?

Background

Some inspiratory muscle training protocols for patients with heart failure report the request of diaphragmatic breathing during inspiratory loaded breathing. However, it is unclear whether this condition modifies the chest wall volumes.

Effectiveness of simplified chest compression-only CPR training program with or without preparatory self-learning video: A randomized controlled trial

ObjectivesTo evaluate the effectiveness of 1-h practical chest compression-only cardiopulmonary resuscitation (CPR) training with or without a preparatory self-learning video.MethodsParticipants were randomly assigned to either a control group or a video group who received a self-learning video before attending the 1-h chest compression-only CPR training program. The primary outcome measure was the total number of chest compressions during a 2-min test period.Results214 participants were enrolled, 183 of whom completed this study. In a simulation test just before practical training began, 88 (92.6%) of the video group attempted chest compressions, while only 58 (64.4%) of the control group (p < 0.001) did so. The total number of chest compressions was significantly greater in the video group than in the control group (100.5 ± 61.5 versus 74.4 ± 55.5, p = 0.012). The proportion of those who attempted to use an automated external defibrillator (AED) was significantly greater in the video group (74.7% versus 28.7%, p < 0.001). After the 1-h practical training, the number of total chest compressions markedly increased regardless of the type of CPR training program and inter-group differences had almost disappeared (161.0 ± 31.8 in the video group and 159.0 ± 35.7 in the control group, p = 0.628).Conclusions1-h chest compression-only CPR training makes it possible for the general public to perform satisfactory chest compressions. Although a self-learning video encouraged people to perform CPR, their performance levels were not sufficient, confirming that practical training as well is essential. (UMIN000001046).     

Force and depth of mechanical chest compressions and their relation to chest height and gender in an out-of-hospital setting

IntroductionThe LUCAS 2 device stores technical data that documents the chest compression process. We analyzed chest wall dimensions and mechanics stored during chest compressions on humans using data gathered with the LUCAS 2 device.MethodsData from LUCAS 2 devices used in out-of-hospital cardiac arrest were downloaded with dedicated proprietary software and matched to the corresponding patient data. Cases were included only if the suction cup was placed correctly, if it was not realigned during the first 5 min of chest compressions, and if no other anomaly in device use was noted. Trauma cases were excluded.ResultsNinety-five patients were included. All patients received manual cardiopulmonary resuscitation prior to the application of the device. The mean (SD) chest height was 232 (25) mm for males and 209 (26) mm for females (P < 0.001). The mean (min–max) compression depth in patients with chest height >185 mm was 53 (50–55) mm, corresponding with 19–28% of the chest diameter. The mean force required to achieve the compression depth of 53 mm ranged between 219 and 568 N. No correlation was found between chest height and force to reach 53 mm depth (females: R² = 0.001, males: R² = 0.007).ConclusionThere was a large variation of the required force to achieve a compression depth of 53 mm. No correlation was seen between chest height and maximum force required to compress the chest 53 mm.     

Application of cabbage leaves compared to gel packs for mothers with breast engorgement: Randomised controlled trial

BackgroundThe effects of cold cabbage leaves and cold gel packs on breast engorgement management have been inconclusive. No studies have compared the effects of these methods on breast engorgement using a rigorous design.ObjectivesTo examine the effectiveness of cold cabbage leaves and cold gel packs application on pain, hardness, and temperature due to breast engorgement, the duration of breastfeeding and satisfaction.DesignA randomised controlled three-group pre-test and repeated post-test study.SettingA private maternal and children’s hospital in Singapore.ParticipantsMothers (n = 227) with breast engorgement within 14 days after delivery.MethodsThe mothers were randomly assigned into either cold cabbage leaves, cold gel packs, or the control group. Pain, hardness of breasts, and body temperature were measured before treatment. Two sets of post-test assessments were conducted at 30 min, 1 h, and 2 h after the first and second application. The duration of breastfeeding was measured up to 6 months. IBM SPSS 23.0 was used to analyse the data.ResultsMothers in the cabbage leaves and gel packs groups had significant reductions in pain at all post-intervention time points compared to the control group, starting from 30 min after the first application of cabbage leaves (mean difference = −0.38, p = 0.016) or gel packs (mean difference = −0.39, p = 0.013). When compared to the control group, mothers in the cabbage leaves group had significant reductions in the hardness of breasts at all post-intervention time points, and mothers in the gel packs group had significant reductions in the hardness of breasts at two time points (1 h and 2 h after the first and second application, respectively). Mothers in the cabbage leaves group had significant reductions in pain (mean difference = −0.53, p = 0.005) and hardness of breasts (mean difference = −0.35, p = 0.003) at 2 h after the second application compared to those in the gel packs group. Both interventions had no impact on body temperature. There was no significant difference in the durations of breastfeeding for mothers among the three groups at 3-month and 6-month follow-up. More mothers were very satisfied/satisfied with the breast engorgement care provided in the cabbage leaves group compared to the other groups.ConclusionWhile cold cabbage leaves and cold gel packs can relieve pain and hardness in breast engorgement, the former had better effect, which can be recommended to postnatal mothers to manage breast engorgement.     

MP2RAGE,a self bias-field corrected sequence for improved segmentation and T1-mapping at high field

The large spatial inhomogeneity in transmit B₁ field (B₁⁺) observable in human MR images at high static magnetic fields (B₀) severely impairs image quality. To overcome this effect in brain T₁-weighted images, the MPRAGE sequence was modified to generate two different images at different inversion times, MP2RAGE. By combining the two images in a novel fashion, it was possible to create T₁-weigthed images where the result image was free of proton density contrast, T₂? contrast, reception bias field, and, to first order, transmit field inhomogeneity.MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B₁⁺ variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T.From such T₁-weighted images, acquired within 12 min, high-resolution 3D T₁ maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65–0.85 mm isotropic). T₁ maps were validated in phantom experiments. In humans, the T₁ values obtained at 7 T were 1.15 ± 0.06 s for white matter (WM) and 1.92 ± 0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min, the T₁ values obtained (0.81 ± 0.03 s for WM and 1.35 ± 0.05 for GM) were once again found to be in very good agreement with values in the literature.