Important steps towards a big change for lung health: a joint approach by the European Respiratory Society, the European Society of Radiology and their partners to facilitate implementation of the European Union's new recommendations on lung cancer screening

Complications during chest tube drainage for iatrogenic pneumothorax

Background

Iatrogenic pneumothorax is a common complication of diagnostic and therapeutic pulmonary procedures. New guidelines on primary spontaneous pneumothorax suggest ambulatory approaches may be suitable. However, guidance on iatrogenic pneumothorax occurring in patients with impaired lung function, increased age, comorbidity and frailty is lacking, and the safety profile of ambulatory management is not known. The objective was to study the safety of iatrogenic pneumothorax treated with chest tubes and to identify the risks of life-threatening events.

Methods

In a retrospective cohort of patients admitted and treated with an adhesive valve-integrated chest tube system, we recorded the incidence of complications. The primary outcome was the incidence of life-threatening events that required urgent medical action. Incidences of serious adverse events, adverse events, serious device-related events and whether outpatient ambulatory treatment would be safe were recorded based on the review of the medical charts.

Results

In 97 patients, 6 (6%) life-threatening events occurred, including episodes of respiratory failure and an urgent need for new chest tube insertion. The event incidence was 21% in patients with pre-biopsy saturation below 95% and 1% in patients with saturation above 95%, p = 0.003, and greater if the lung had not expanded on the first radiograph, 25%, after insertion of the chest tube, than if the lung had fully expanded, 4%, or partially expanded, 2%, p = 0.009.

Conclusions

The incidence of life-threatening events during chest tube-treated iatrogenic pneumothorax is significant, but acceptable in patients without impaired lung function prior to the procedure and early response to treatment.

An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images

INTRODUCTION

Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for physicians and ensure timely pathological or etiological examinations for patients. Improving the diagnostic accuracy of the algorithms remains the key to this technology.

OBJECTIVES

To deal with the problem, we proposed a multiscale attention residual network (MARN) for diagnosing lung conditions through bronchoscopic images. The multiscale convolutional block attention module (MCBAM) was designed to enable accurate focus on lesion regions by enhancing spatial and channel features. Gradient-weighted Class Activation Map (Grad-CAM) was provided to increase the interpretability of diagnostic results.

METHODS

We collected 615 cases from Harbin Medical University Cancer Hospital, including 2900 images. The dataset was partitioned randomly into training sets, validation sets and test sets to update model parameters, evaluate the model's training performance, select network architecture and parameters, and estimate the final model. In addition, we compared MARN with other algorithms. Furthermore, three physicians with different qualifications were invited to diagnose the same test images, and the results were compared to those of the model.

RESULTS

In the dataset of normal and lesion images, our model displayed an accuracy of 97.76% and an AUC of 99.79%. The model recorded 92.26% accuracy and 96.82% AUC for datasets of benign and malignant lesion images, while it achieved 93.10% accuracy and 99.02% AUC for normal, benign, and malignant lesion images.

CONCLUSION

These results demonstrated that our network outperforms other methods in diagnostic performance. The accuracy of our model is roughly the same as that of experienced physicians and the efficiency is much higher than doctors. MARN has great potential for assisting physicians with assessing the bronchoscopic images precisely.

Strengthening lung cancer screening in Europe: fostering participation, improving outcomes, and addressing health inequalities through collaborative initiatives in the SOLACE consortium

The Strengthening the Screening of Lung Cancer in Europe (SOLACE) initiative, supported by Europe's Beating Cancer Plan, is dedicated to advancing lung cancer screening. This initiative brings together the most extensive pan-European network of respiratory and radiology experts, involving 37 partners from 15 countries. SOLACE aims to enhance equitable access to lung cancer screening by developing targeted recruitment strategies for underrepresented and high-risk populations. Through comprehensive work packages, SOLACE integrates scientific research, pilot studies, and sustainability efforts to bolster regional and national screening efforts across EU member states. CRITICAL RELEVANCE STATEMENT: The SOLACE project aims to facilitate the optimization and implementation of equitable lung cancer screening programs across the heterogeneous healthcare landscape in EU member states. KEY POINTS: The effectiveness of lung cancer screening is supported by both scientific evidence and now increasing legislative support. SOLACE aims to develop, test, and disseminate tools to facilitate the realization of lung cancer screening at both a national and regional level. Previously underrepresented populations in lung cancer screening will be targeted by tailored recruitment strategies. SOLACE forms the first pan-European network of experts poised to drive real-world implementation of lung cancer screening.

Study rationale and design of the PEOPLHE trial

PURPOSE

Lung cancer screening (LCS) by low-dose computed tomography (LDCT) demonstrated a 20-40% reduction in lung cancer mortality. National stakeholders and international scientific societies are increasingly endorsing LCS programs, but translating their benefits into practice is rather challenging. The "Model for Optimized Implementation of Early Lung Cancer Detection: Prospective Evaluation Of Preventive Lung HEalth" (PEOPLHE) is an Italian multicentric LCS program aiming at testing LCS feasibility and implementation within the national healthcare system. PEOPLHE is intended to assess (i) strategies to optimize LCS workflow, (ii) radiological quality assurance, and (iii) the need for dedicated resources, including smoking cessation facilities.

METHODS

PEOPLHE aims to recruit 1.500 high-risk individuals across three tertiary general hospitals in three different Italian regions that provide comprehensive services to large populations to explore geographic, demographic, and socioeconomic diversities. Screening by LDCT will target current or former (quitting < 10 years) smokers (> 15 cigarettes/day for > 25 years, or > 10 cigarettes/day for > 30 years) aged 50-75 years. Lung nodules will be volumetric measured and classified by a modified PEOPLHE Lung-RADS 1.1 system. Current smokers will be offered smoking cessation support.

CONCLUSION

The PEOPLHE program will provide information on strategies for screening enrollment and smoking cessation interventions; administrative, organizational, and radiological needs for performing a state-of-the-art LCS; collateral and incidental findings (both pulmonary and extrapulmonary), contributing to the LCS implementation within national healthcare systems.

Lung Cancer Screening in People With COPD: The Pamplona-IELCAP Experience

INTRODUCTION

The Global Initiative for Obstructive Lung Disease (GOLD) recommends lung cancer screening for patients with Chronic Obstructive Pulmonary Disease (COPD), but data is lacking regarding results of screening in this high-risk population. The main goal of the present work is to explore if lung cancer screening with Low Dose Chest Tomography (LDCT) in people with COPD, allows lung cancer (LC) diagnosis in early stages with survival compatible with curative state.

METHODS

This is a post hoc exploratory analysis. Pamplona International Early Lung Cancer Action Program (P-IELCAP) participants with a GOLD defined obstructive pattern (post bronchodilator FEV1/FVC<0.70) were selected for analysis. The characteristics of those who developed LC and their survival are described. A Cox proportional analysis explored the factors associated with LC diagnosis.

RESULTS

Eight hundred and sixty-five patients (77% male, 93% in spirometric GOLD stage 1+2) were followed for 102±63 months. LC prevalence was 2.6% at baseline, with an annual LC diagnosis rate of 0.68%. Early-stage tumors predominated (74%) with a median survival (25-75th percentiles) of 139 (76-185) months. Cumulative tobacco exposure, FEV1%, and emphysema were the main predictors of an LC diagnosis. Eight (11%) patients with COPD had a second LC, most of them in early stage (92%), and 6 (8%) had recurrence. Median survival (25-75th percentiles) in these patients was 168 (108-191) months.

CONCLUSIONS

Lung cancer screening of selected high-risk participants with COPD allowed the LC diagnosis in early stages with survival compatible with curative state.