Lung and Mediastinal Cancer

Computed tomography (CT) with iodine-based contrast medium and 18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography ( Artificial intelligence (AI) is a branch of computer science dedicated to the development of computer algorithms to accomplish tasks traditionally associated with human intelligence. A device mimics cognitive functions, i.e., learning and problem solving, is powered by AI. A popular form of AI is machine learning.18 F-FDG PET/CT) play a crucial role in the diagnosis and staging of lung cancer and mediastinal neoplasms. Magnetic resonance imaging (MRI) with gadolinium-based contrast medium is a complementary tool to CT in lung cancer staging and is extremely useful for the differential diagnosis of mediastinal malignancies. Multimodality imaging also provides key information to guiding interventional diagnostic and therapeutic procedures in the field of lung cancer. Percutaneous ablation therapies (radiofrequency ablation, microwaves and cryoablation) have been widely employed as effective and safe therapeutic options in patients not candidates or refusing surgery. In this context, CT and 18 F-FDG PET/CT are essential for the assessment of adequate tumour ablation, identification of complications, and timely detection of eventual recurrence. Furthermore, other new interventional techniques are emerging as promising options for the locoregional administration of chemotherapeutic agents. This chapter provides an overview of morphological and functional imaging features and applications in the diagnosis and staging of lung and mediastinal malignancies as well as in the assessment of lung cancer after interventional treatments. Interventional diagnostic and treatment options for lung cancer will be discussed, focusing on the multidisciplinary approach and novelties in the field.