80071872 - Fourth Minimally Invasive Lung Cancer and Pleural Disease Diagnostics and Treatment Conference

Monday, June 8, 2026, 8:00 AM - 5:00 PM, Palazzo Pucci, Florence Via de' Pucci, 2, 50122 Firenze FI, Italy, Florence, 00


This CME course provides a comprehensive, evidence based update in interventional pulmonology (IP), with a focused integration of artificial intelligence (AI) applications across lung nodule detection, lung cancer staging, pleural disease management, advanced bronchoscopic navigation, ablation therapies, imaging, and procedural safety. The program highlights both current literature and emerging AI enabled technologies that are reshaping diagnostic accuracy, procedural precision, and multidisciplinary thoracic oncology care. Led by nationally and internationally recognized experts, the course emphasizes practical implementation of AI enhanced tools in airway management, cytopathology, imaging interpretation, minimally invasive interventions, and COPD therapies. Through structured panels and discussion, participants will explore clinical integration, ethical and regulatory considerations, and future research priorities. The overall goal is to accelerate translation of innovation including AI driven advances into clinical practice to improve outcomes for patients with suspected or confirmed lung cancer, central airway disease, and pleural disorders.

1. Differentiate appropriate indications, contraindications, and patient selection criteria for advanced bronchoscopic and pleural interventions (e.g., navigational bronchoscopy, endobronchial ultrasound, pleural biopsy) in patients with suspected or confirmed thoracic malignancy.
2. Apply evidence based diagnostic algorithms to optimize tissue acquisition for molecular and next generation sequencing in non small cell lung cancer, with the goal of reducing time from presentation to treatment initiation.
3. Interpret bronchoscopic, imaging, and procedural findings to guide realtime clinical decisionmaking and multidisciplinary care planning in complex pulmonary and thoracic oncology cases.
4. Implement standardized peri procedural workflows and complication management strategies to improve procedural safety, diagnostic yield, and post procedure outcomes in interventional pulmonology practice.
5. Integrate emerging AI technologies and techniques in interventional pulmonology into clinical practice by evaluating their clinical utility, limitations, and impact on patient outcomes.

Mitigation of Relevant Financial Relationships

Johns Hopkins University adheres to the ACCME’s Standards for Integrity and Independence in Accredited Continuing Education. Any individuals in a position to control the content of a CE activity, including faculty, planners, reviewers or others are required to disclose all relevant financial relationships with ineligible entities (commercial interests). All relevant conflicts of interest have been mitigated prior to the commencement of the activity.

No faculty are available for this activity at this time.