Cystic lung diseases (CLDs) encompass a heterogeneous group of rare pulmonary disorders that are characterized by the presence of air-filled spaces within the lung parenchyma. CLDs often manifest with a wide range of clinical symptoms, including recurrent pneumothorax, dyspnea, constitutional symptoms such as fever, as well as symptoms associated with autoimmune conditions.
The potential diagnoses of CLDs are vast and they can be classified based on pathophysiologic mechanisms, including neoplastic, congenital, genetic, developmental, lymphoproliferative, infectious, inflammatory, or smoking-related diseases. Therefore, a multidisciplinary approach is often necessary for achieving a conclusive diagnosis. Radiologists play a vital role in unraveling complex presentations through CT imaging and refining the list of differential diagnoses.
Leading authors have proposed algorithmic approaches to help radiologists accurately diagnose CLDs by focusing on HRCT key features, including cyst characteristics such as shape, size, wall thickness, and distribution, as well as the presence or not of accompanying radiological features.
Our approach relies on these step-by-step algorithmic approaches to dissect the morphological and distribution of cyst lesions and try to define a radiological pattern on HRCT that matches a specific diagnosis
We will focus on the four main CLDs that can be encountered in clinical practice: Pulmonary Langerhans Cells Histiocytosis disease (PLCH), lymphangioleiomyomatosis (LAM), Birt-Hogg Dubé syndrome (BHD) and lymphoid interstitial pneumonia/follicular bronchiolitis (LIP/FB).