Early-stage treatment improves prognosis of lung cancer and two large randomized controlled trials have shown that early detection with low-dose computed tomography (LDCT) reduces mortality. Despite this, lung cancer screening (LCS) remains challenging. In the context of a global shortage of radiologists, the high rate of false-positive LDCT results in overloading of existing lung cancer clinics and multidisciplinary teams. Thus, to provide patients with earlier access to life-saving surgical interventions, there is an urgent need to improve LDCT-based LCS and especially to reduce the false-positive rate that plagues the current detection technology. In this context, LCS can be improved in three ways: (1) by refining selection criteria (risk factor assessment), (2) by using Computer Aided Diagnosis (CAD) to make it easier to interpret chest CTs, and (3) by using biological blood signatures for early cancer detection, to both spot the optimal target population and help classify lung nodules. These three main ways of improving LCS are discussed in this review.

Tracheobronchial injury is a heterogeneous entity comprising multiple rare and potentially life-threatening scenarios. We performed a systematic literature review focusing on post-intubation tracheal injuries (PiTIs) and post-traumatic tracheobronchial injuries (PTTBIs).PiTIs are often longitudinal lacerations of the middle third of the membranous trachea. Subcutaneous emphysema of the face and trunk following tracheal intubation should immediately trigger the diagnosis. Diagnosis may be suspected on the chest computed tomography (CT) and should be confirmed by bronchoscopic examination. Conservative management is encouraged for a spontaneously breathing or stable patient on noninvasive ventilation. Surgical repair is mandatory when mechanical ventilation is required and if bridging of the injury is impossible.PTTBIs are often associated with other severe injuries. Patients often present with massive subcutaneous emphysema and intractable pneumothorax. Diagnosis may be suspected on the chest CT and should be confirmed by bronchoscopic examination. Early surgical repair is indicated. In selected patients, conservative management can be considered.

Background: Bronchoscopic lung volume reduction using endobronchial coils is a new treatment for patients with severe emphysema. To date, the benefits have been modest and have been suggested to be much larger in patients with severe hyperinflation and nonmulti-comorbidity. Objective: We aimed to evaluate the efficacy and safety of endobronchial coil treatment in a randomized multicenter clinical trial using optimized patient selection. Method: Patients with severe emphysema on HRCT scan with severe hyperinflation (residual volume [RV] ≥200% predicted and RV/total lung capacity [TLC] >55%) were randomized to coil treatment or control. Primary outcome measures were differences in the forced expiratory volume in 1 s (FEV1) and St George’s Respiratory Questionnaire (SGRQ) total score at 6 months. Results: Due to premature study termination, a total of 120 patients (age 63 ± 7 years, FEV1 29 ± 7% predicted, RV 251 ± 41% predicted, RV/TLC 67 ± 6%, and SGRQ 58 ± 13 points), instead of 210 patients, were randomized. At study termination, 91 patients (57 coil and 34 control) had 6-month results available. Analyses showed significantly greater improvements in favor of the coil group. The increase in FEV1 was greater in the coil group than that in the control group by + 10.3 [+4.7 to +16.0] % and in SGRQ by −10.6 [−15.9 to −5.4] points. At study termination, there were 5 (6.8%) deaths in the coil cohort reported. Conclusion: Despite early study termination, coil treatment compared to control results in a significant improvement in the lung function and quality of life benefits for up to 6 months in patients with emphysema and severe hyperinflation. These improvements were of clinical importance but were associated with a higher likelihood of serious adverse events.

Background: Assessment of actionable EGFR mutations is mandatory for treatment-naïve advanced or metastatic non-squamous lung carcinoma (NSLC), but the results need to be obtained in less than 10 working days. For rapid EGFR testing, an EGFR-specific polymerase chain reaction (PCR) assay is an alternative and simple approach compared to next generation sequencing (NGS). Here, we describe how a rapid EGFR-specific PCR assay can be implemented in a single laboratory center (LPCE, Nice, France) as reflex testing in treatment-naïve NSLC. Methods: A total of 901 biopsies from NSLC with more than 10% of tumor cells were prospectively and consecutively evaluated for EGFR mutation status between November 2017 and December 2019 using the Idylla system (Biocartis NV, Mechelen, Belgium). NGS was performed for nonsmokers with NSLC wild type for EGFR, ALK, ROS1, and BRAF and with less than 50% PD-L1 positive cells using the Hotspot panel (Thermo Fisher Scientific, Waltham, MA, USA). Results: Results were obtained from 889/901 (97%) biopsies with detection of EGFR mutations in 114/889 (13%) cases using the Idylla system. Among the 562 EGFR wild type tumors identified with Idylla, NGS detected one actionable and one nonactionable EGFR mutation. Conclusions: Rapid and targeted assessment of EGFR mutations in treatment-naïve NSLC can be implemented in routine clinical practice. However, it is mandatory to integrate this approach into a molecular algorithm that allows evaluation of potentially actionable genomic alterations other than EGFR mutations.

Introduction Lung cancer (LC) is the most common cause of cancer-related deaths worldwide. Its early detection can be achieved with a CT scan. Two large randomised trials proved the efficacy of low-dose CT (LDCT)-based lung cancer screening (LCS) in high-risk populations. The decrease in specific mortality is 20%–25%. Nonetheless, implementing LCS on a large scale faces obstacles due to the low number of thoracic radiologists and CT scans available for the eligible population and the high frequency of false-positive screening results and the long period of indeterminacy of nodules that can reach up to 24 months, which is a source of prolonged anxiety and multiple costly examinations with possible side effects. Deep learning, an artificial intelligence solution has shown promising results in retrospective trials detecting lung nodules and characterising them. However, until now no prospective studies have demonstrated their importance in a real-life setting. Methods and analysis This open-label randomised controlled study focuses on LCS for patients aged 50–80 years, who smoked more than 20 pack-years, whether active or quit smoking less than 15 years ago. Its objective is to determine whether assisting a multidisciplinary team (MDT) with a 3D convolutional network-based analysis of screening chest CT scans accelerates the definitive classification of nodules into malignant or benign. 2722 patients will be included with the aim to demonstrate a 3-month reduction in the delay between lung nodule detection and its definitive classification into benign or malignant. Ethics and dissemination The sponsor of this study is the University Hospital of Nice. The study was approved for France by the ethical committee CPP (Comités de Protection des Personnes) Sud-Ouest et outre-mer III (No. 2022-A01543-40) and the Agence Nationale du Medicament et des produits de Santé (Ministry of Health) in December 2023. The findings of the trial will be disseminated through peer-reviewed journals and national and international conference presentations. Trial registration number NCT05704920.