Respirology最新文献

Background and objective: The diagnosis of interstitial lung diseases (ILDs) often relies on the integration of various clinical, radiological, and histopathological data. Achieving high diagnostic accuracy in ILDs, particularly for distinguishing usual interstitial pneumonia (UIP), is challenging and requires a multidisciplinary approach. Therefore, this study aimed to develop a multimodal artificial intelligence (AI) algorithm that combines computed tomography (CT) and histopathological images to improve the accuracy and consistency of UIP diagnosis.

Methods: A dataset of CT and pathological images from 324 patients with ILD between 2009 and 2021 was collected. The CT component of the model was trained to identify 28 different radiological features. The pathological counterpart was developed in our previous study. A total of 114 samples were selected and used for testing the multimodal AI model. The performance of the multimodal AI was assessed through comparisons with expert pathologists and general pathologists.

Results: The developed multimodal AI demonstrated a substantial improvement in distinguishing UIP from non-UIP, achieving an AUC of 0.92. When applied by general pathologists, the diagnostic agreement rate improved significantly, with a post-model κ score of 0.737 compared to 0.273 pre-model integration. Additionally, the diagnostic consensus rate with expert pulmonary pathologists increased from κ scores of 0.278-0.53 to 0.474-0.602 post-model integration. The model also increased diagnostic confidence among general pathologists.

Conclusion: Combining CT and histopathological images, the multimodal AI algorithm enhances pathologists' diagnostic accuracy, consistency, and confidence in identifying UIP, even in cases where specialised expertise is limited.

Background and objective: The evidence around occupation-related chronic cough is conflicting and current definitions of chronic cough cannot capture its heterogeneity. Using our recently characterised novel cough subclasses, we aimed to identify subclass-specific occupational risks.

Methods: Using data from the Tasmanian Longitudinal Health Study (TAHS), occupational exposures up to age 53 years were coded using the ALOHA+ Job Exposure Matrix, into ever-exposure (no, only-low, ever-high) and cumulative exposure. People belonging to six previously identified cough subclasses among 2213 current coughers at age 53 years were compared to non-coughers (n = 1396). Associations with occupational exposures were assessed using multinomial logistic regression for these cough subclasses and logistic regression for standard definitions (chronic cough, chronic phlegm, and chronic bronchitis) after adjusting for potential confounders.

Results: Biological dust was associated with "cough with allergies" (cumulative: adjusted multinomial odds ratio [aMOR] = 1.06, 95% CI: 1.02-1.10, per 10 exposure-year increase). Aromatic solvents were associated with "chronic dry cough" (cumulative: aMOR = 1.15, 95% CI: 1.02-1.29). Other solvents were associated with "chronic productive cough" (ever-high: aMOR = 2.81, 95% CI: 1.26-6.2); "intermittent productive cough" (cumulative: aMOR = 1.06, 95% CI: 0.98-1.16), chronic bronchitis (ever-high: aOR = 2.48, 95% CI: 1.01-6.06); and chronic phlegm (ever-high: aOR = 2.26, 95% CI: 1.14-4.51). Herbicides (cumulative) were also associated with "intermittent productive cough" (aOR = 1.09, 95% CI: 1.00-1.77) and chronic phlegm (aOR = 1.07, 95% CI: 1.00-1.15).

Conclusion: Novel cough subclasses had distinct associations with specific occupational exposures, suggesting different pathophysiology. Aromatic solvents were associated with dry cough; biological dust with allergic cough; herbicides and other solvents with productive cough. Using novel cough subclasses was superior to standard definitions in uncovering these associations.

Background and objective: β-ENaC-Tg mice serve as a relevant model of muco-obstructive lung disease and diffuse-type emphysema, with impaired mucociliary clearance, mucus obstruction, chronic airway inflammation, structural lung damage, and altered lung function. The aim of this study was to undertake a comprehensive analysis of lung function and mechanics of the adult β-ENaC-Tg model.

Methods: Adult β-ENaC-Tg and wild-type littermates underwent X-ray velocimetry (XV) scans using a Permetium XV scanner (4DMedical, Melbourne, Australia). For comparative lung mechanics, lung function assessments were conducted with a flexiVent system (SCIREQ, Montreal, Canada).

Results: XV imaging demonstrated elevated ventilation defect percentage, mean specific ventilation, and ventilation heterogeneity in β-ENaC-Tg mice. Spatial analysis of ventilation maps indicated increased ventilation variability in the peripheral lung regions, as well as an increased proportion of under-ventilated areas. The flexiVent analysis indicated that compared to wild types, β-ENaC-Tg mice have a significantly more compliant lungs with increased inspiratory capacity, reduced tissue elastance, and increased hysteresivity (heterogeneity), suggesting loss of parenchymal integrity.

Conclusion: This research highlights the utility of XV imaging in evaluating ventilation defects in the β-ENaC-Tg model and provides a comprehensive lung function analysis.

Background and objective: Asthma-COPD overlap (ACO) is characterized by patients exhibiting features of both asthma and COPD. Currently, there is no specific treatment for ACO. This study aimed to investigate the therapeutic potential of targeting CD131, a shared receptor subunit for IL-3, IL-5 and GM-CSF, in ACO development and in preventing acute viral exacerbations.

Methods: A two-hit mouse model of ACO was established by house dust mite (HDM) allergen sensitization to model asthma, and elastase treatment to model emphysema. In a separate model, human rhinovirus 1b (RV1b) was used to induce an acute asthma exacerbation. A neutralizing antibody against CD131 was used to block CD131 in vivo signalling.

Results: Mice exposed to HDM and elastase developed cardinal features for asthma and COPD, including airway hyperreactivity (AHR) and emphysema. A mixed granulocytic inflammatory profile was identified in the lungs, including expansion of monocyte-derived macrophages, neutrophils and eosinophils. RT-qPCR analysis detected heightened gene expression of Mmp12, Il5 and Il13. Transcriptomic analysis further revealed pathway enrichment for type 2 inflammation and macrophage activation. Blockade of CD131 effectively reduced the lung inflammation and prevented the development of AHR, airway fibrosis and emphysema. Interestingly, pathway enrichment for Th1 response and interferon production detected in the model was not affected by the treatment. Consistently, CD131 antagonism prevented RV1b-induced asthma exacerbation without compromising RV1b clearance.

Conclusion: CD131 signalling coordinates multiple pathological pathways that drive airway inflammation and lung remodelling in ACO. Hence, CD131 antagonism represents a novel approach to combating the immunopathology in the complex ACO setting.

Special Series: Leading Women in Respiratory Clinical Sciences Series Editors: Anne-Marie Russell and Kathleen O Lindell See related editorial.