Contrastive learning with token projection for Omicron pneumonia identification from few-shot chest CT images.

Introduction: Deep learning-based methods can promote and save critical time for the diagnosis of pneumonia from computed tomography (CT) images of the chest, where the methods usually rely on large amounts of labeled data to learn good visual representations. However, medical images are difficult to obtain and need to be labeled by professional radiologists. Methods: To address this issue, a novel contrastive learning model with token projection, namely CoTP, is proposed for improving the diagnostic quality of few-shot chest CT images. Specifically, (1) we utilize solely unlabeled data for fitting CoTP, along with a small number of labeled samples for fine-tuning, (2) we present a new Omicron dataset and modify the data augmentation strategy, i.e., random Poisson noise perturbation for the CT interpretation task, and (3) token projection is utilized to further improve the quality of the global visual representations. Results: The ResNet50 pre-trained by CoTP attained accuracy (ACC) of 92.35%, sensitivity (SEN) of 92.96%, precision (PRE) of 91.54%, and the area under the receiver-operating characteristics curve (AUC) of 98.90% on the presented Omicron dataset. On the contrary, the ResNet50 without pre-training achieved ACC, SEN, PRE, and AUC of 77.61, 77.90, 76.69, and 85.66%, respectively. Conclusion: Extensive experiments reveal that a model pre-trained by CoTP greatly outperforms that without pre-training. The CoTP can improve the efficacy of diagnosis and reduce the heavy workload of radiologists for screening of Omicron pneumonia.

Internet of things-based management versus standard management of home noninvasive ventilation in COPD patients with hypercapnic chronic respiratory failure: a multicentre randomized controlled non-inferiority trial.

Background: Effective monitoring and management are crucial during long-term home noninvasive positive pressure ventilation (NPPV) in patients with hypercapnic chronic obstructive pulmonary disease (COPD). This study investigated the benefit of Internet of Things (IOT)-based management of home NPPV. Methods: This multicenter, prospective, parallel-group, randomized controlled non-inferiority trial enrolled patients requiring long-term home NPPV for hypercapnic COPD. Patients were randomly assigned (1:1), via a computer-generated randomization sequence, to standard home management or IOT management based on telemonitoring of clinical and ventilator parameters over 12 months. The intervention was unblinded, but outcome assessment was blinded to management assignment. The primary outcome was the between-group comparison of the change in health-related quality of life, based on severe respiratory insufficiency questionnaire scores with a non-inferiority margin of -5. This study is registered with Chinese Clinical Trials Registry (No. ChiCTR1800019536). Findings: Overall, 148 patients (age: 72.7 ± 6.8 years; male: 85.8%; forced expiratory volume in 1 s: 0.7 ± 0.3 L; PaCO2: 66.4 ± 12.0 mmHg), recruited from 11 Chinese hospitals between January 24, 2019, and June 28, 2021, were randomly allocated to the intervention group (n = 73) or the control group (n = 75). At 12 months, the mean severe respiratory insufficiency questionnaire score was 56.5 in the intervention group and 50.0 in the control group (adjusted between-group difference: 6.26 [95% CI, 3.71-8.80]; P < 0.001), satisfying the hypothesis of non-inferiority. The 12-month risk of readmission was 34.3% in intervention group compared with 56.0% in the control group, adjusted hazard ratio of 0.56 (95% CI, 0.34-0.92; P = 0.023). No severe adverse events were reported. Interpretation: Among stable patients with hypercapnic COPD, using IOT-based management for home NPPV improved health-related quality of life and prolonged the time to readmission. Funding: Air Liquide Healthcare (Beijing) Co., Ltd.

Mediating Effect of Tobacco Dependence on the Association Between Maternal Smoking During Pregnancy and Chronic Obstructive Pulmonary Disease: Case-Control Study.

BACKGROUND: Maternal smoking during pregnancy (MSDP) is a known risk factor for offspring developing chronic obstructive pulmonary disease (COPD), but the underlying mechanism remains unclear. OBJECTIVE: This study aimed to explore whether the increased COPD risk associated with MSDP could be attributed to tobacco dependence (TD). METHODS: This case-control study used data from the nationwide cross-sectional China Pulmonary Health study, with controls matched for age, sex, and smoking status. TD was defined as smoking within 30 minutes of waking, and the severity of TD was assessed using the Fagerstrom Test for Nicotine Dependence. COPD was diagnosed when the ratio of forced expiratory volume in 1 second to forced vital capacity was <0.7 in a postbronchodilator pulmonary function test according to the 2017 Global Initiative for Chronic Obstructive Lung Disease criteria. Logistic regression was used to examine the correlation between MSDP and COPD, adjusting for age, sex, BMI, educational attainment, place of residence, ethnic background, occupation, childhood passive smoking, residential fine particulate matter, history of childhood pneumonia or bronchitis, average annual household income, and medical history (coronary heart disease, hypertension, and diabetes). Mediation analysis examined TD as a potential mediator in the link between MSDP and COPD risk. The significance of the indirect effect was assessed through 1000 iterations of the "bootstrap" method. RESULTS: The study included 5943 participants (2991 with COPD and 2952 controls). Mothers of the COPD group had higher pregnancy smoking rates (COPD: n=305, 10.20%; controls: n=211, 7.10%; P<.001). TD was more prevalent in the COPD group (COPD: n=582, 40.40%; controls: n=478, 33.90%; P<.001). After adjusting for covariates, MSDP had a significant effect on COPD (ß=.097; P<.001). There was an association between MSDP and TD (ß=.074; P<.001) as well as between TD and COPD (ß=.048; P=.007). Mediation analysis of TD in the MSDP-COPD association showed significant direct and indirect effects (direct: ß=.094; P<.001 and indirect: ß=.004; P=.03). The indirect effect remains present in the smoking population (direct: ß=.120; P<.001 and indirect: ß=.002; P=.03). CONCLUSIONS: This study highlighted the potential association between MSDP and the risk of COPD in offspring, revealing the mediating role of TD in this association. These findings contribute to a deeper understanding of the impact of prenatal tobacco exposure on lung health, laying the groundwork for the development of relevant prevention and treatment strategies.

Spatial transcriptomics reveals heterogeneity of histological subtypes between lepidic and acinar lung adenocarcinoma.

BACKGROUND: Patients who possess various histological subtypes of early-stage lung adenocarcinoma (LUAD) have considerably diverse prognoses. The simultaneous existence of several histological subtypes reduces the clinical accuracy of the diagnosis and prognosis of early-stage LUAD due to intratumour intricacy. METHODS: We included 11 postoperative LUAD patients pathologically confirmed to be stage IA. Single-cell RNA sequencing (scRNA-seq) was carried out on matched tumour and normal tissue. Three formalin-fixed and paraffin-embedded cases were randomly selected for 10× Genomics Visium analysis, one of which was analysed by digital spatial profiler (DSP). RESULTS: Using DSP and 10× Genomics Visium analysis, signature gene profiles for lepidic and acinar histological subtypes were acquired. The percentage of histological subtypes predicted for the patients from samples of 11 LUAD fresh tissues by scRNA-seq showed a degree of concordance with the clinicopathologic findings assessed by visual examination. DSP proteomics and 10× Genomics Visium transcriptomics analyses revealed that a negative correlation (Spearman correlation analysis: r = -.886; p = .033) between the expression levels of CD8 and the expression trend of programmed cell death 1(PD-L1) on tumour endothelial cells. The percentage of CD8+ T cells in the acinar region was lower than in the lepidic region. CONCLUSIONS: These findings illustrate that assessing patient histological subtypes at the single-cell level is feasible. Additionally, tumour endothelial cells that express PD-L1 in stage IA LUAD suppress immune-responsive CD8+ T cells.

Heterogeneities and impact profiles of early chronic obstructive pulmonary disease status: findings from the China Pulmonary Health Study.

Background: The prevalence, epidemiological and clinical heterogeneities, and impact profiles of individuals with preserved ratio impaired spirometry (PRISm), pre-COPD, young COPD, and mild COPD in general Chinese population were not known yet. Methods: Data were obtained from the China Pulmonary Health study (2012-2015), a nationally representative cross-sectional survey that recruited 50,991 adults aged 20 years or older. Definitions of the four early disease status were consistent with the latest publications and the Global Initiative for Chronic Obstructive Lung Disease criteria. Findings: The age-standardised prevalences of PRISm, pre-COPD, young COPD, and mild COPD were 5.5% (95% confidence interval, 4.3-6.9), 7.2% (5.9-8.8), 1.1% (0.7-1.8), and 3.1% (2.5-3.8), respectively. In summary, mild COPD was under more direct or established impact factor exposures, such as older age, male gender, lower education level, lower family income, biomass use, air pollution, and more accumulative cigarette exposures; young COPD and pre-COPD experienced more personal and parents' events in earlier lives, such as history of bronchitis or pneumonia in childhood, frequent chronic cough in childhood, parental history of respiratory diseases, passive smoke exposure in childhood, and mother exposed to passive smoke while pregnant; pre-COPD coexisted with heavier symptoms and comorbidities burdens; young COPD exhibited worse airway obstruction; and most of the four early disease status harbored small airway dysfunction. Overall, older age, male gender, lower education level, living in the urban area, occupational exposure, frequent chronic cough in childhood, more accumulated cigarette exposure, comorbid with cardiovascular disease and gastroesophageal reflux disease were all associated with increased presence of the four early COPD status; different impact profiles were additionally observed with distinct entities. Over the four categories, less than 10% had ever taken pulmonary function test; less than 1% reported a previously diagnosed COPD; and no more than 13% had received pharmaceutical treatment. Interpretation: Significant heterogeneities in prevalence, epidemiological and clinical features, and impact profiles were noted under varied defining criteria of early COPD; a unified and validated definition for an early disease stage is warranted. Closer attention, better management, and further research need to be administrated to these population. Funding: Chinese Academy of Medical Sciences Institute of Respiratory Medicine Grant for Young Scholars (No. 2023-ZF-9); China International Medical Foundation (No. Z-2017-24-2301); Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences (No. 2021-I2M-1-049); National High Level Hospital Clinical Research Funding (No. 2022-NHLHCRF-LX-01); Major Program of National Natural Science Foundation of China (No. 82090011).

An artificial intelligence-assisted diagnostic system for the prediction of benignity and malignancy of pulmonary nodules and its practical value for patients with different clinical characteristics.

Objectives: This study aimed to explore the value of an artificial intelligence (AI)-assisted diagnostic system in the prediction of pulmonary nodules. Methods: The AI system was able to make predictions of benign or malignant nodules. 260 cases of solitary pulmonary nodules (SPNs) were divided into 173 malignant cases and 87 benign cases based on the surgical pathological diagnosis. A stratified data analysis was applied to compare the diagnostic effectiveness of the AI system to distinguish between the subgroups with different clinical characteristics. Results: The accuracy of AI system in judging benignity and malignancy of the nodules was 75.77% (p < 0.05). We created an ROC curve by calculating the true positive rate (TPR) and the false positive rate (FPR) at different threshold values, and the AUC was 0.755. Results of the stratified analysis were as follows. (1) By nodule position: the AUC was 0.677, 0.758, 0.744, 0.982, and 0.725, respectively, for the nodules in the left upper lobe, left lower lobe, right upper lobe, right middle lobe, and right lower lobe. (2) By nodule size: the AUC was 0.778, 0.771, and 0.686, respectively, for the nodules measuring 5-10, 10-20, and 20-30 mm in diameter. (3) The predictive accuracy was higher for the subsolid pulmonary nodules than for the solid ones (80.54 vs. 66.67%). Conclusion: The AI system can be applied to assist in the prediction of benign and malignant pulmonary nodules. It can provide a valuable reference, especially for the diagnosis of subsolid nodules and small nodules measuring 5-10 mm in diameter.