Pulmonary Emphysema

The goal of this clinical trial is to identify correlations among data deriving from lung ultrasonographic (LUS) and tomographic evaluations of patients with panlobular or paraseptal emphysema, to improve the comprehension of acoustic information derived from ultrasound evaluation. The main question it aims to answer is: what are the correlations between thoracic ultrasonographic patterns and peripheral parenchymal changes evaluated by high resolution computed tomography (HRCT) of the chest, in patients affected with variable degree of panlobular or paraseptal emphysema? Researchers will compare LUS patterns observed in: 1) COPD patients with CT evidence of panlobular or paraseptal emphysema, 2) subjects participating in the screening program for lung cancer with CT evidence of panlobular or paraseptal emphysema, and 3) patients with suspected/known lung cancer undergoing with CT evidence of panlobular or paraseptal emphysema, with the ones obtained from healthy volunteers and subjects who participate in the screening program for lung cancer with no evidence of emphysema. Participants will undergo LUS evaluation with both clinical and research scanners. Patients will be assessed in supine position with the arms extended above the head. The position is the same in which chest CT scans will be performed. LUS assessment will be performed using commercially available linear probes. Finally, all COPD patients and subjects who participate in the screening program for lung cancer with CT evidence of paraseptal or panlobular emphysema will undergo respiratory oscillometry. Tidal breathing analysis with impulse oscillometry (IOS) has proven to be an informative and meaningful tool used in the early detection and follow up of pulmonary diseases like COPD.

PNEUMO-LIBS is a multicenter, non-interventional observational study designed to evaluate whether multi-element tissue imaging by Laser-Induced Breakdown Spectroscopy (LIBS), combined with an artificial intelligence-based analysis tool called Interesting Features Finder (IFF), may help physicians better understand the possible causes of chronic lung diseases. The study focuses on adult patients with chronic lung diseases for which a lung biopsy has already been performed as part of routine medical care. These diseases include diffuse interstitial lung diseases, pulmonary granulomatoses such as sarcoidosis, and emphysema, especially when an environmental or occupational exposure is suspected but not clearly demonstrated. Some chronic lung diseases may be influenced by inhaled mineral or metallic particles, such as silica, aluminum, titanium, or other metals. However, these exposures are often difficult to document at the individual patient level. Standard clinical, radiological, and pathological investigations do not usually provide direct information on the presence and distribution of such elements within lung tissue. LIBS is an imaging technique that can detect and map chemical elements directly in tissue samples, including archived formalin-fixed paraffin-embedded biopsy blocks. In this study, lung biopsy samples will be analyzed with LIBS to search for elemental signatures that may be compatible with occupational or environmental exposures. The IFF algorithm will then be used to help interpret the LIBS data and identify rare or unexpected elemental signals. The study does not require any additional biopsy, blood test, imaging examination, treatment, or hospital visit for participants. It uses tissue samples and medical data already collected during routine care. The results of LIBS and IFF analyses will be presented to the treating physician or investigator, who will complete standardized online questionnaires at three time points: before receiving the LIBS results, after receiving the LIBS report, and after receiving the IFF-assisted interpretation. The main objective is to assess the perceived clinical utility of LIBS imaging for physicians, particularly regarding etiological understanding, possible occupational disease recognition, and prevention-oriented reasoning. Secondary objectives include assessing the added value of the IFF algorithm and evaluating the feasibility of a centralized multicenter workflow for sample transfer, LIBS analysis, IFF processing, result reporting, and questionnaire completion. The study aims to include approximately 70 patients across several French hospital centers. Its results may support the development of future diagnostic, occupational health, and environmental medicine approaches, without modifying the medical care of participants during the study.