François Laurent

Background: Asbestos, mineral wool (MW), refractory ceramic fibres (RCF) and silica are among the most common exposures to mineral particles in the workplace. Objective: To study the effect of coexposure to asbestos and MW, crystalline silica or RCFs and the risk of lung cancer and mesothelioma. Methods: The Asbestos-Related Diseases Cohort is a surveillance programme in retired workers exposed to asbestos during their working life. Complete job histories were collected and occupational exposure to asbestos was assessed by an expert, while occupational exposure to MW, RCFs and silica was assessed using French job-exposure matrices. Cox proportional hazards models were used to estimate HR and 95% CI for lung cancer mortality and lung cancer incidence and for mesothelioma mortality or mesothelioma incidence. Results: In this population of workers exposed to asbestos, in the mortality study, exposures to MW, crystalline silica and RCFs were not found to be associated with lung cancer after adjustment for smoking and asbestos, nor with mesothelioma after adjustment for asbestos. In the incidence study, there was an association between exposure to crystalline silica (ever exposed) and mesothelioma (HR _a =1.75, 95% CI 1.17 to 2.62). Conclusion: Crystalline silica is not known to induce mesothelioma but coexposure to asbestos could increase the effect of asbestos on the mesothelial cells.

We introduce a simulation-based, amortised Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method. In the first step a graph neural network is trained on simulated data to learn optimized low-dimensional summary statistics of the random walk. In the second step an invertible neural network generates the posterior distribution of the parameters from the learnt summary statistics using variational inference. We apply our method to infer the parameters of the fractional Brownian motion model from single trajectories. The computational complexity of the amortized inference procedure scales linearly with trajectory length, and its precision scales similarly to the Cram{\'e}r-Rao bound over a wide range of lengths. The approach is robust to positional noise, and generalizes well to trajectories longer than those seen during training. Finally, we adapt this scheme to show that a finite decorrelation time in the environment can furthermore be inferred from individual trajectories.

Background: The National Lung Screening Trial (NLST) and NELSON study opened the debate on the relevance of lung cancer (LC) screening in subjects exposed to occupational respiratory carcinogens. This analysis reported the incremental cost-effectiveness ratios (ICER) of an organized LC screening program for an asbestos-exposed population. Methods: Using Markov modelization, individuals with asbestos exposure were either monitored without intervention or annual low-dose thoracic computed-tomography (LDTCT) scan LC screening. LC incidence came from a prospective observational cohort of subjects with occupational asbestos exposure. The intervention parameters were those of the NLST study. Utilities and LC-management costs came from published reports. A sensitivity analysis evaluated different screening strategies. Results: The respective quality-adjusted life year (QALY) gain, supplementary costs and ICER [95% confidence interval] were: 0.040 [0.010–0.065] QALY, 6900 [3700–11,800] € and 170,000 [75,000–645,000] €/QALY for all asbestos-exposed subjects; and 0.144 [0.071–0.216] QALY, 13,000 [5700–26,800] € and 90,000 [35,000–276,000] €/QALY for smokers with high exposure. When screening was based on biennial LDTCT scans, the ICER was 45,000 [95% CI: 15,000–116,000] €/QALY. Conclusions: Compared to the usual ICER thresholds, biennial LDTCT scan LC screening for smokers with high occupational exposure to asbestos is acceptable and preferable to annual scans.

Objective: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. Methods: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques. Results: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes (p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years. Conclusions: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy.

Objective: the aim of this study was to evaluate the association between interstitial lung abnormalities, asbestos exposure and age in a population of retired workers previously occupationally exposed to asbestos. Methods: previously occupationally exposed former workers to asbestos eligible for a survey conducted between 2003 and 2005 in four regions of France, underwent chest CT examinations and pulmonary function testing. Industrial hygienists evaluated asbestos exposure and calculated for each subject a cumulative exposure index (CEI) to asbestos. Smoking status information was also collected in this second round of screening. Expert radiologists performed blinded independent double reading of chest CT-scans and classified interstitial lung abnormalities into: no abnormality, minor interstitial findings, interstitial findings inconsistent with UIP, possible or definite UIP. In addition, emphysema was assessed visually (none, minor: emphysema 50% of the lung). Logistic regression models adjusted for age and smoking were used to assess the relationship between interstitial lung abnormalities and occupational asbestos exposure. Results: the study population consisted of 2157 male subjects. Interstitial lung abnormalities were present in 365 (16.7%) and emphysema in 444 (20.4%). Significant positive association was found between definite or possible UIP pattern and age (OR adjusted =1.08 (95% CI: 1.02–1.13)). No association was found between interstitial abnormalities and CEI or the level of asbestos exposure. Conclusion: presence of interstitial abnormalities at HRCT was associated to aging but not to cumulative exposure index in this cohort of former workers previously occupationally exposed to asbestos.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. It is a heterogeneous disease involving different components of the lung to varying extents. Developments in medical imaging and image analysis techniques provide new insights in the assessment of the structural and functional changes of the disease. This article reviews the leading imaging techniques: CT and MRI of the lung in research settings and clinical routine. Both visual and quantitative methods are reviewed, emphasizing their relevance to patient phenotyping and outcome prediction.

Introduction Guidelines concerning the follow-up of subjects occupationally exposed to lung carcinogens, published in France in 2015, recommended the setting up of a trial of low-dose chest CT lung cancer screening in subjects at high risk of lung cancer. Objective To evaluate the organisation of low-dose chest CT lung cancer screening in subjects occupationally exposed to lung carcinogens and at high risk of lung cancer. Methods and analysis This trial will be conducted in eight French departments by six specialised reference centres (SRCs) in occupational health. In view of the exploratory nature of this trial, it is proposed to test initially the feasibility and acceptability over the first 2 years in only two SRCs then in four other SRCs to evaluate the organisation. The target population is current or former smokers with more than 30 pack-years (who have quit smoking for less than 15 years), currently or previously exposed to International Agency for Research on Cancer group 1 lung carcinogens, and between the ages of 55 and 74 years. The trial will be conducted in the following steps: (1) identification of subjects by a screening invitation letter; (2) evaluation of occupational exposure to lung carcinogens; (3) evaluation of the lung cancer risk level and verification of eligibility; (4) screening procedure: annual chest CT scans performed by specialised centres and (5) follow-up of CT scan abnormalities. Ethics and dissemination This protocol study has been approved by the French Committee for the Protection of Persons. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings. Trial registration number NCT03562052; Pre-results.

A prospective multicenter phase II trial to evaluate the survival outcomes of percutaneous radiofrequency ablation (RFA) for patients with stage IA non-small cell lung cancer (NSCLC), ineligible for surgery. Patients with a biopsy-proven stage IA NSCLC, staging established by a positron emission tomography-computed tomography (PET-CT), were eligible. The primary objective was to evaluate the local control of RFA at 1-year. Secondary objectives were 1- and 3-year overall survival (OS), 3-year local control, lung function (prior to and 3 months after RFA) and quality of life (prior to and 1 month after RFA). Of the 42 patients (mean age 71.7 y) that were enrolled at six French cancer centers, 32 were eligible and assessable. Twenty-seven patients did not recur at 1 year corresponding to a local control rate of 84.38% (95% CI, [67.21–95.72]). The local control rate at 3 years was 81.25% (95% CI, [54.35–95.95]). The OS rate was 91.67% (95% CI, [77.53–98.25]) at 1 year and 58.33% (95% CI, [40.76–74.49]) at 3 years. The forced expiratory volume was stable in most patients apart from two, in whom we observed a 10% decrease. There was no significant change in the global health status or in the quality of life following RFA. RFA is an efficient treatment for medically inoperable stage IA NSCLC patients. RFA is well tolerated, does not adversely affect pulmonary function and the 3-year OS rate is comparable to that of stereotactic body radiotherapy, in similar patients. ClinicalTrials.gov Identifier NCT01841060 registered in November 2008.