Lung Regions Research Articles

Advancing lung ultrasound imaging: advanced pre-processing and neoteric segmentation for improved accuracy

Abstract Within the medical imaging domain, the segmentation of Lung Ultrasound (LUS) images is crucial for accurately defining regions of interest, particularly for lung health assessments. various techniques such as threshold-based, region-based, and edge-based methods have been employed to address this challenge, their accuracy and efficiency are often questioned. This highlights the need for an innovative approach. With this context in mind, this research introduces a novel preprocessing step using Optimized Gaussian Histogram Equalization (GHE) followed by a Neoteric Segmentation (NS) approach. This combination enhances the capability of segmenting specific regions within LUS images, regardless of the overarching medical scenario. The primary focus of this method is to understand, through a thorough evaluation, how neoteric segmentation compares with more conventional methods. By conducting an in-depth comparative analysis, valuable insights can be unearthed. The results demonstrate that the optimized GHE technique significantly enhances contrast and preserves visual quality, while the NS approach shows superior performance in accurately segmenting the lung regions. Initial findings suggest that the NS method, achieving an impressive 95% accuracy, holds significant promise and could influence the trajectory of healthcare practices. This research aims to advance the field of medical image analysis by highlighting the potential benefits of this cutting-edge segmentation technique. These advancements could positively impact healthcare outcomes, especially in contexts that leverage lung ultrasound imaging.

Landmark registration in CT for lung model approximation in EIT

Abstract For the visualization of pulmonary ventilation with Electrical Impedance Tomography (EIT), most devices rely on generalized reconstruction models. Yet, fixed thorax dimensions, predetermined electrode locations, and standard lung shapes lead to multiple sources of EIT imaging distortion. The following work compares reconstructions of a library model, a practical model based on landmark fitting, and a detailed model based on manual segmentation. CT images of five pigs were segmented into torso surface, electrode positions, and lung borders. Practical models were created with reduced data, registration, and fitting. Detailed models were created by using the complete segmentation data. After EIT reconstruction and tidal image calculation, the overlap of CT lung segmentation and ventilated voxel was calculated. Compared with the results of a standardized model, the practical model reached an average ventilation/segmentation-overlap difference of an additional 12 %, and the detailed model achieved an average difference of 10 %. In conclusion, the shift of reconstructed impedance towards the segmented lung region is similar in both models when compared to the standard model, while the practical model requires a considerably less amount of information.

Nonrigid registration method for longitudinal chest CT images in COVID-19

Rationale and objectivesTo analyze morphological changes in patients with COVID-19-associated pneumonia over time, a nonrigid registration technique is required that reduces differences in respiratory phase and imaging position and does not excessively deform the lesion region. A nonrigid registration method using deep learning was applied for lung field alignment, and its practicality was verified through quantitative evaluation, such as image similarity of whole lung region and image similarity of lesion region, as well as visual evaluation by a physician. Materials and methodsFirst, the lung field positions and sizes of the first and second CT images were roughly matched using a classical registration method based on iterative calculations as a preprocessing step. Then, voxel-by-voxel transformation was performed using VoxelMorph, a nonrigid deep learning registration method. As an objective evaluation, the similarity of the images was calculated. To evaluate the invariance of image features in the lesion site, primary statistics and 3D shape features were calculated and statistically analyzed. Furthermore, as a subjective evaluation, the similarity of images and whether nonrigid transformation caused unnatural changes in the shape and size of the lesion region were visually evaluated by a pulmonologist. ResultsThe proposed method was applied to 509 patient data points with high image similarity. The variances in histogram characteristics before and after image deformation were confirmed. Visual evaluation confirmed the agreement between the shape and internal structure of the lung field and the natural deformation of the lesion region. ConclusionThe developed nonrigid registration method was shown to be effective for quantitative time series analysis of the lungs.

1614: MRI V/Q for assessing radiation-induced changes in regional lung function in lung cancer patients

1614: MRI V/Q for assessing radiation-induced changes in regional lung function in lung cancer patients

Black carbon and particle lung-deposited surface area in residential wood combustion emissions: Effects of an electrostatic precipitator and photochemical aging

Residential wood combustion (RWC) remains a significant global source of particulate matter (PM) emissions with adverse impacts on regional air quality, climate, and human health. The lung-deposited surface area (LDSA) and equivalent black carbon (eBC) concentrations have emerged as important metrics to assess particulate pollution. In this study we estimated combustion phase-dependent emission factors of LDSA for alveolar, tracheobronchial, and head-airway regions of human lungs and explored the relationships between eBC and LDSA in fresh and photochemically aged RWC emissions. Photochemical aging was simulated in an oxidative flow reactor at OH• exposures equivalent to 1.4 or 3.4 days in the atmosphere. Further, the efficiency of a small-scale electrostatic precipitator (ESP) for reducing LDSA and eBC from the wood stove was determined. For fresh emission eBC correlated extremely well with LDSA, but the correlation decreased after aging. Soot-dominated flaming phase showed the highest eBC dependency of LDSA whereas for ignition and char burning phases non-BC particles contributed strongly the LDSA. Deposition to the alveolar region contributed around 60 % of the total lung-deposition. The ESP was found as an effective method to mitigate particulate mass, LDSA, as well as eBC emissions from wood stoves, as they were reduced on average by 72%, 71%, and 69%, respectively. The reduction efficiencies, however, consistently dropped over the span of an experiment, especially for eBC. Further, the ESP was found to increase the sub-30 nm ultrafine particle number emissions, with implications for LDSA. The results of this study can be used for assessing the contribution of RWC to LDSA concentrations in ambient air.

A novel positive end-expiratory pressure titration using electrical impedance tomography in spontaneously breathing acute respiratory distress syndrome patients on mechanical ventilation: an observational study from the MaastrICCht cohort.

There is no universally accepted method for positive end expiratory pressure (PEEP) titration approach for patients on spontaneous mechanical ventilation (SMV). Electrical impedance tomography (EIT) guided PEEP-titration has shown promising results in controlled mechanical ventilation (CMV), current implemented algorithm for PEEP titration (based on regional compliance measurements) is not applicable in SMV. Regional peak flow (RPF, defined as the highest inspiratory flow rate based on EIT at a certain PEEP level) is a new method for quantifying regional lung mechanics designed for SMV. The objective is to study whether RPF by EIT is a feasible method for PEEP titration during SMV. Single EIT measurements were performed in COVID-19 ARDS patients on SMV. Clinical (i.e., tidal volume, airway occlusion pressure, end-tidal CO2) and mechanical (cyclic alveolar recruitment, recruitment, cumulative overdistension (OD), cumulative collapse (CL), pendelluft, and PEEP) outcomes were determined by EIT at several pre-defined PEEP thresholds (1-10% CL and the intersection of the OD and CL curves) and outcomes at all thresholds were compared to the outcomes at baseline PEEP. In total, 25 patients were included. No significant and clinically relevant differences were found between thresholds for tidal volume, end-tidal CO2, and P0.1 compared to baseline PEEP; cyclic alveolar recruitment rates changed by -3.9% to -37.9% across thresholds; recruitment rates ranged from - 49.4% to + 79.2%; cumulative overdistension changed from - 75.9% to + 373.4% across thresholds; cumulative collapse changed from 0% to -94.3%; PEEP levels from 10 up to 14 cmH2O were observed across thresholds compared to baseline PEEP of 10 cmH2O. A threshold of approximately 5% cumulative collapse yields the optimum compromise between all clinical and mechanical outcomes. EIT-guided PEEP titration by the RPF approach is feasible and is linked to improved overall lung mechanics) during SMV using a threshold of approximately 5% CL. However, the long-term clinical safety and effect of this approach remain to be determined.

The relationship between lobar distribution and primary lung cancer histological types

Background: Lung cancer is the primary cause of cancer-related deaths globally. Accurate tumor location and subtype characterization are critical for optimizing treatment and predicting outcomes. This study aims to identify the relationship between lobar distribution and primary lung cancer histological types and describe the most recent patterns at the country-level origin. Methods: This cross-sectional study was conducted at a major tertiary care hospital in Bangladesh, including 165 patients recruited using purposive non-probability sampling. Data were collected using a semi-structured case record form and analyzed using SPSS version 28.0. Results: Tumors were most commonly found in the central area (58.2%). Squamous cell carcinoma was the most prevalent type (46.1%), followed by adenocarcinoma (38.8%), small cell carcinoma (13.9%), and large cell carcinoma (1.2%). The incidence of squamous cell carcinoma was significantly higher in the upper lobe of the right lung (55.9%) compared to other forms, particularly in the central region of the right lung (P < 0.001). Squamous cell carcinoma was more common in the lower part of the left lung (42.9%), while adenocarcinoma was exclusively observed in the lingular portion of the left lung (100%). The major bronchus of the left lung primarily exhibited squamous cell carcinoma (60%), but this finding was not statistically significant (p=0.899). Conclusion: The study highlights the significant association between lobar distribution and histological types of primary lung cancer, emphasizing the need for precise tumor characterization for better treatment strategies and prognostic evaluation.

Lorlatinib experience in a patient with ALK + non-small cell lung cancer on hemodialysis: A case report.

Lorlatinib is a potent third-generation anaplastic lymphoma kinase/c-ros oncogene 1 (ALK)/ROS1 oral tyrosine kinase inhibitor that has broad coverage of acquired resistance mutations and is currently indicated for the treatment of adult patients with metastatic non-small cell lung cancer (NSCLC) whose tumors are ALK-positive. In this case, we aimed to present the safety and effectiveness of lorlatinib use in a patient diagnosed with ALK-positive metastatic NSCLC who underwent hemodialysis 3 days a week. A 76-year-old female patient has been undergoing regular hemodialysis for about 2 years. A brain magnetic resonance imaging (MRI) was taken due to headache and a mass was detected. She was diagnosed with lung adenocarcinoma as a result of excisional biopsy. Positron emission tomography/ computed tomography (PET/CT) showed a mass in the hilar region of the left lung and multiple lymphadenopathy in the mediastinum. In February 2023, 100 mg lorlatinib was started daily. There was no significant regression in PET-CT and no brain MRI residue during follow-up. The patient has been continuing lorlatinib for approximately 1 year with almost complete response, with no side effects other than hypercholesterolemia. We presented our experience using lorlatinib in a patient with metastatic ALK + NSCLC undergoing hemodialysis. Although the dosage of lorlatinib in hemodialysis patients is still controversial, our case report indicates that 100 mg lorlatinib was safe in this patient.

Multi-modal evaluation of respiratory diaphragm motion in chronic obstructive pulmonary disease using MRI series and CT images.

Chronic obstructive pulmonary disease (COPD), characterized by airflow limitation and breathing difficulty, is usually caused by prolonged inhalation of toxic substances or long-term smoking habits. Some abnormal features of COPD can be observed using medical imaging methods, such as magnetic resonance imaging (MRI) and computed tomography (CT). This study aimed to conduct a multi-modal analysis of COPD, focusing on assessing respiratory diaphragm motion using MRI series in conjunction with low attenuation volume (LAV) data derived from CT images. This study utilized MRI series from 10 normal subjects and 24 COPD patients, along with thoracic CT images from the same patients. Diaphragm profiles in the sagittal thoracic MRI series were extracted using field segmentation, and diaphragm motion trajectories were generated from estimated diaphragm displacements via registration. Re-sliced sagittal CT images were used to calculate regional LAVs for four distinct lung regions. The similarities among diaphragm motion trajectories at various positions were assessed, and their correlations with regional LAVs were analyzed. Compared with the normal subjects, patients with COPD typically exhibited fewer similarities in diaphragm motion, as indicated by the mean normalized correlation coefficient of the vertical motion component (0.96 for normal subjects vs. 0.76 for severity COPD patients). This reduction was significantly correlated with the LAV% in the two lower lung regions with a regression coefficient of 0.81. Our proposed evaluation method may assist in the diagnosis and therapy planning for patients with COPD.

Development of a New Dry Powder Aerosol Synthetic Lung Surfactant Product for Neonatal Respiratory Distress Syndrome (RDS) – Part I: In Vitro Testing and Characterization

PurposeImproving the deep lung delivery of aerosol surfactant therapy (AST) with a dry powder formulation may enable significant reductions in dose while providing improved efficacy. The objective of Part I of this two-part study was to present the development of a new dry powder aerosol synthetic lung surfactant (SLS) product and to characterize performance based on aerosol formation and realistic in vitro airway testing leading to aerosol delivery recommendations for subsequent in vivo animal model experiments.MethodsA new micrometer-sized SLS excipient enhanced growth (EEG) dry powder formulation was produced via spray drying and aerosolized using a positive-pressure air-jet dry powder inhaler (DPI) intended for aerosol delivery directly to intubated infants with respiratory distress syndrome (RDS) or infant-size test animals.ResultsThe best-case design (D2) of the air-jet DPI was capable of high emitted dose (> 80% of loaded) and formed a < 2 µm mass median aerodynamic diameter (MMAD) aerosol, but was limited to ≤ 20 mg mass loadings. Testing with a realistic in vitro rabbit model indicated that over half of the loaded dose could penetrate into the lower lung regions. Using the characterization data, a dose delivery protocol was designed in which a 60 mg total loaded dose would be administered and deliver an approximate lung dose of 14.7–17.7 mg phospholipids/kg with a total aerosol delivery period < 5 min.ConclusionsA high-efficiency aerosol SLS product was designed and tested that may enable an order of magnitude reduction in administered phospholipid dose, and provide rapid aerosol administration to infants with RDS.

Inhaled Nanoparticulate Systems: Composition, Manufacture and Aerosol Delivery.

An increasing growth in nanotechnology is evident from the growing number of products approved in the past decade. Nanotechnology can be used in the effective treatment of several pulmonary diseases by developing therapies that are delivered in a targeted manner to select lung regions based on the disease state. Acute or chronic pulmonary disorders can benefit from this type of therapy, including respiratory distress syndrome (RDS), chronic obstructive pulmonary disease (COPD), asthma, pulmonary infections (e.g. tuberculosis, Yersinia pestis infection, fungal infections, bacterial infections, and viral infections), lung cancer, cystic fibrosis (CF), pulmonary fibrosis, and pulmonary arterial hypertension. Modification of size and surface property renders nanoparticles to be targeted to specific sites, which can serve a vital role in innovative pulmonary drug delivery. The nanocarrier type chosen depends on the intended purpose of the formulation and intended physiological target. Liquid nanocarriers and solid-state nanocarriers can carry hydrophilic and hydrophobic drugs (e.g. small molecular weight drug molecules, large molecular weight drugs, peptide drugs, and macromolecular biological drugs), while surface modification with polymer can provide cellular targeting, controlled drug release, and/or evasion of phagocytosis by immune cells, depending on the polymer type. Polymeric nanocarriers have versatile architectures, such as linear, branched, and dendritic forms. In addition to the colloidal dispersion liquid state, the various types of nanoparticles can be formulated into the solid state, offering important unique advantages in formulation versatility and enhanced stability of the final product. This chapter describes the different types of nanocarriers, types of inhalation aerosol device platforms, liquid aerosols, respirable powders, and particle engineering design technologies for inhalation aerosols.

Fully automated classification of pulmonary nodules in positron emission tomography-computed tomography imaging using a two-stage multimodal learning approach.

Lung cancer is a malignant tumor, for which pulmonary nodules are considered to be significant indicators. Early recognition and timely treatment of pulmonary nodules can contribute to improving the survival rate of patients with cancer. Positron emission tomography-computed tomography (PET/CT) is a noninvasive, fusion imaging technique that can obtain both functional and structural information of lung regions. However, studies of pulmonary nodules based on computer-aided diagnosis have primarily focused on the nodule level due to a reliance on the annotation of nodules, which is superficial and unable to contribute to the actual clinical diagnosis. The aim of this study was thus to develop a fully automated classification framework for a more comprehensive assessment of pulmonary nodules in PET/CT imaging data. We developed a two-stage multimodal learning framework for the diagnosis of pulmonary nodules in PET/CT imaging. In this framework, Stage I focuses on pulmonary parenchyma segmentation using a pretrained U-Net and PET/CT registration. Stage II aims to extract, integrate, and recognize image-level and feature-level features by employing the three-dimensional (3D) Inception-residual net (ResNet) convolutional block attention module architecture and a dense-voting fusion mechanism. In the experiments, the proposed model's performance was comprehensively validated using a set of real clinical data, achieving mean scores of 89.98%, 89.21%, 84.75%, 93.38%, 86.83%, and 0.9227 for accuracy, precision, recall, specificity, F1 score, and area under curve values, respectively. This paper presents a two-stage multimodal learning approach for the automatic diagnosis of pulmonary nodules. The findings reveal that the main reason for limiting model performance is the nonsolitary property of nodules in pulmonary nodule diagnosis, providing direction for future research.

The effects of laryngeal mask versus endotracheal tube on atelectasis after general anesthesia induction assessed by lung ultrasound: A randomized controlled trial

Study objectiveThis study aims to evaluate the impact of Supreme™ laryngeal masks versus endotracheal tubes on atelectasis during general anesthesia using lung ultrasound (LUS), and provide evidence for respiratory management. DesignA single-center, double-blind, randomized controlled trial was conducted. SettingThe study was conducted in both the operating room and the post-anesthesia care unit, with follow-up assessments performed in the ward. PatientsEnrollment included 180 cases undergoing non-laparoscopic surgeries in gynecology, urology, and orthopedic limb surgeries. InterventionsPatients were randomly assigned 1:1 to the endotracheal intubation or laryngeal mask group. MeasurementsLUS scores were recorded across 12 lung regions at baseline, 15 min after airway establishment, at the end of surgery, and 30 min following airway removal. Outcome measures encompassed the oxygenation index, dynamic lung compliance, incidence of postoperative pulmonary complications, throat pain, and other postoperative complications assessed at 24 and 48 h postoperatively. The primary outcome focused on the LUS score in all 12 lung regions at 15 min after airway establishment. Main resultsIntention-to-treat analysis of 177 subjects revealed endotracheal intubation led to significantly higher LUS scores at 15 min {P < 0.001, mean difference 4.15 ± 0.60, 95% CI [2.97, 5.33]}, end of surgery (P < 0.001, mean difference 3.37 ± 0.68, 95% CI [2.02, 4.72]), and 30 min post-removal (P < 0.001, mean difference 2.63 ± 0.48, 95% CI [1.68, 3.58]). No major complications occurred in the two groups. ConclusionsCompared to endotracheal intubation, laryngeal masks effectively reduce atelectasis formation and progression in gynecological, urological non-laparoscopic, and orthopedic limb surgeries. However, caution is warranted when generalizing these findings to surgeries with a higher risk of laryngeal mask leakage or obese patients. Additionally, the efficacy of laryngeal masks in reducing postoperative atelectasis remains uncertain when comprehensive monitoring of muscle relaxation and reversal therapy is employed.

Evaluation of Progressive Architectural Distortion in Idiopathic Pulmonary Fibrosis Using Deformable Registration of Sequential CT Images.

Monitoring the progression of idiopathic pulmonary fibrosis (IPF) using CT primarily focuses on assessing the extent of fibrotic lesions, without considering the distortion of lung architecture. To evaluate three-dimensional average displacement (3D-AD) quantification of lung structures using deformable registration of serial CT images as a parameter of local lung architectural distortion and predictor of IPF prognosis. Patients with IPF evaluated between January 2016 and March 2017 who had undergone CT at least twice were retrospectively included (n = 114). The 3D-AD was obtained by deformable registration of baseline and follow-up CT images. A computer-aided quantification software measured the fibrotic lesion volume. Cox regression analysis evaluated these variables to predict mortality. The 3D-AD and the fibrotic lesion volume change were significantly larger in the subpleural lung region (5.2 mm (interquartile range (IQR): 3.6-7.1 mm) and 0.70% (IQR: 0.22-1.60%), respectively) than those in the inner region (4.7 mm (IQR: 3.0-6.4 mm) and 0.21% (IQR: 0.004-1.12%), respectively). Multivariable logistic analysis revealed that subpleural region 3D-AD and fibrotic lesion volume change were independent predictors of mortality (hazard ratio: 1.12 and 1.23; 95% confidence interval: 1.02-1.22 and 1.10-1.38; p = 0.01 and p < 0.001, respectively). The 3D-AD quantification derived from deformable registration of serial CT images serves as a marker of lung architectural distortion and a prognostic predictor in patients with IPF.

Effects of starting one lung ventilation and applying individualized PEEP right after patients are placed in lateral decubitus position on intraoperative oxygenation for patients undergoing thoracoscopic pulmonary lobectomy: study protocol for a randomized controlled trial

BackgroundFor patients receiving one lung ventilation in thoracic surgery, numerous studies have proved the superiority of lung protective ventilation of low tidal volume combined with recruitment maneuvers (RM) and individualized PEEP. However, RM may lead to overinflation which aggravates lung injury and intrapulmonary shunt. According to CT results, atelectasis usually forms in gravity dependent lung regions, regardless of body position. So, during anesthesia induction in supine position, atelectasis usually forms in the dorsal parts of lungs, however, when patients are turned into lateral decubitus position, collapsed lung tissue in the dorsal parts would reexpand, while atelectasis would slowly reappear in the lower flank of the lung. We hypothesize that applying sufficient PEEP without RM before the formation of atelectasis in the lower flank of the lung may beas effective to prevent atelectasis and thus improve oxygenation as applying PEEP with RM.MethodsA total of 84 patients scheduled for elective pulmonary lobe resection necessitating one lung ventilation will be recruited and randomized totwo parallel groups. For all patients, one lung ventilation is initiated the right after patients are turned into lateral decubitus position. For patients in the study group, individualized PEEP titration is started the moment one lung ventilation is started, while patients in the control group will receive a recruitment maneuver followed by individualized PEEP titration after initiation of one lung ventilation. The primary endpoint will be oxygenation index measured at T4. Secondary endpoints will include intrapulmonary shunt, respiratory mechanics, PPCs, and hemodynamic indicators.DiscussionNumerous previous studies compared the effects of individualized PEEP applied alone with that applied in combination with RM on oxygenation index, PPCs, intrapulmonary shunt and respiratory mechanics after atelectasis was formed in patients receiving one lung ventilation during thoracoscopic surgery. In this study, we will apply individualized PEEP before the formation of atelectasis while not performing RM in patients allocated to the study group, and then we’re going to observe its effects on the aspects mentioned above. The results of this trial will provide a ventilation strategy that may be conductive to improving intraoperative oxygenation and avoiding the detrimental effects of RM for patients receiving one lung ventilation.Trial registrationwww.Chictr.org.cn ChiCTR2400080682. Registered on February 5, 2024.

Thoracic computed tomography (CT) image-based identification and severity classification of COVID-19 cases using vision transformer (ViT)

In this research, we developed a two-stage deep learning (DL) model using Vision Transformer (ViT) to detect COVID-19 and assess its severity from thoracic CT images. In the first stage, we utilized a pre-trained ViT model (ViT_B/32) and a custom CNN model to classify CT images as COVID-19 or non-COVID-19. The ViT model achieved superior performance with a fivefold cross-validated accuracy of 99.7%, compared to the custom CNN’s 98%. In the second stage, we employed a ViT-based U-Net model (Vision Transformer for Biomedical Image Segmentation, VITBIS) to segment lung and infection regions in COVID-19 positive CT images, determining the infection severity. This model uses transformers with attention mechanisms in both the encoder and decoder. The lung segmentation network achieved an Intersection Over Union (IOU) of 95.8% and a sensitivity of 99.67%, while the lesion segmentation network attained an IOU of 94% and a sensitivity of 98.3%.

The Impact of PEEP on Ventilation Distribution in ARDS.

The first aim of this study was to evaluate the capacity of electrical impedance tomography (EIT) to identify the effect of PEEP on regional ventilation distribution and the regional risk of collapse, overdistention, hypoventilation, and pendelluft in mechanically ventilated patients. The second aim was to evaluate the feasibility of EIT for estimating airway opening pressure (AOP). The EIT signal was recorded both during baseline cyclic ventilation and slow insufflation for one breath for 9 subjects with moderate-to-severe ARDS. From these data, the AOP and volumes insufflated to lung regions with or without the risk of either collapse, overdistention, hypoventilation, or pendelluft were assessed at 3 PEEP levels (5, 10, and 15 cm H2O). PEEP levels were compared by Friedman analysis of variance and the AOP measured by EIT evaluated using an F-test and the Bland and Altman method. The volume for which there was no specific risk significantly decreased at the highest PEEP from 55 ± 31% tidal volume (VT) at PEEP 5 or 82 ± 18% VT at PEEP 10 to 10 ± 30% VT at PEEP 15 (P = .038 between PEEP 5 vs PEEP 15; P = .01 between PEEP 10 vs PEEP 15). The volume associated with overdistention significantly increased with increasing PEEP, whereas that associated with atelectrauma significantly decreased. Pendelluft significantly decreased with increasing PEEP: VT of 8.9 ± 18.6%, 3.6 ± 7.0%, and 3.2 ± 7.1% for PEEP 5, PEEP 10, and PEEP 15, respectively. The center of ventilation tended to increase in the dependent direction with higher PEEP. The AOPs assessed by EIT and from the pressure-volume curve were in good agreement (bias 0.48 cm H2O). Our results suggest that EIT could aid clinicians in making personalized and reasoned choices in setting the PEEP for subjects with ARDS.

Lung segment anything model (LuSAM): a decoupled prompt-integrated framework for automated lung segmentation on chest x-Ray images

Accurate lung segmentation in chest x-ray images plays a pivotal role in early disease detection and clinical decision-making. In this study, we introduce an innovative approach to enhance the precision of lung segmentation using the Segment Anything Model (SAM). Despite its versatility, SAM faces the challenge of prompt decoupling, often resulting in misclassifications, especially with intricate structures like the clavicle. Our research focuses on the integration of spatial attention mechanisms within SAM. This approach enables the model to concentrate specifically on the lung region, fostering adaptability to image variations and reducing the likelihood of false positives. This work has the potential to significantly advance lung segmentation, improving the identification and quantification of lung anomalies across diverse clinical contexts.

Breath-by-breath assessment of acute pulmonary edema using electrical impedance tomography, spirometry and volumetric capnography in a sheep (Ovis Aries) model.

The bedside diagnosis of acute pulmonary edema is challenging. This study evaluated the breath-by-breath information from electrical impedance tomography (EIT), respiratory mechanics and volumetric capnography (VCap) to assess acute pulmonary edema induced by xylazine administration in anesthetized sheep. To determine the ability and efficiency of each monitoring modality in detecting changes in lung function associated with onset of pulmonary edema. Twenty healthy ewes were anesthetized, positioned in sternal (prone) recumbency and instrumented. Synchronized recordings of EIT, spirometry and VCap were performed for 60 s prior to start of injection, during xylazine injection over 60 s (0-60 s) and continuously for 1 min (60-120 s) after the end of injection. After visual assessment of the recorded mean variables, statistical analysis was performed using a mixed effect model for repeated measures with Bonferroni's correction for multiple comparisons, to determine at which breath after start of injection the variable was significantly different from baseline. A significant change over time was defined as an adjusted p < 0.05. All statistics were performed using GraphPad Prism 0.1.0. Electrical impedance tomography showed significant changes from baseline in all but two variables. These changes were observed simultaneously during xylazine injection at 48 s and were consistent with development of edema in dependent lung (decreased end-expiratory lung impedance, ventilation in centro-ventral and ventral lung region) and shift of ventilation into non-dependent lung (decreased non-dependent silent spaces and increased center of ventilation ventral to dorsal and increased ventilation in centro-dorsal and dorsal lung region). All changes in lung mechanics also occurred during injection, including decreased dynamic respiratory system compliance and increased peak expiratory flow, peak inspiratory pressure and airway resistance at 48, 54 and 60 s, respectively. Changes in VCap variables were delayed with all occurring after completion of the injection. In this model of pulmonary edema, EIT detected significant and rapid change in all assessed variables of lung function with changes in regional ventilation indicative of pulmonary edema. Volumetric capnography complemented the EIT findings, while respiratory mechanics were not specific to lung edema. Thus, EIT offers the most comprehensive method for pulmonary edema evaluation, including the assessment of ventilation distribution, thereby enhancing diagnostic capabilities.

Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning.

Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluated the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lipid distribution in the mouse lung that may contribute to ozone-induced exacerbations in asthma. Lung lobes from male and female BALB/c mice were cryosectioned and acquired by high resolution mass spectrometry imaging (MSI). Processed MSI peak annotations were validated by LC-MS/MS data from scraped tissue slides and microdissected lung tissue. Images were normalized and segmented into clusters. Interestingly, segmented clusters overlapped with stained serial tissue sections, enabling statistical analysis across biological replicates for morphologically relevant lung regions. Spatially distinct lipids had higher overall degree of unsaturated fatty acids in distal lung regions compared to proximal regions. Furthermore, the airway and alveolar epithelium exhibited significantly decreased sphingolipid and glycerophospholipid abundance in females, but not in males. We demonstrate the potential role of lipid saturation in healthy lung function and highlight sex differences in regional lung lipid distribution following ozone exposure. Our study provides a framework for future MSI experiments capable of relative quantification across biological replicates and expansion to multiple sample types, including human tissue.