The Role of Radiology in Bronchiectasis Evaluation: Insights from CT, MRI, and Emerging Technologies

Abstract

Bronchiectasis is a chronic lung condition characterized by abnormal dilatation and lack of tapering of the airways. Computed tomography (CT) and magnetic resonance imaging (MRI) have significantly advanced the detection and evaluation of bronchiectasis. CT imaging plays a central role in identifying key features of bronchiectasis, such as airway dilatation, lack of tapering, and the presence of mucus plugging. Visual CT scoring systems, while effective, are limited in their ability to comprehensively assess both the extent and severity of bronchiectasis. Computer-based image analysis, including deep learning techniques, shows promise in enhancing diagnostic precision, tracking disease progression, and predicting clinical outcomes. However, the development of reliable algorithms requires large and diverse datasets to ensure unbiased training data. Collaborative networks are expected to be valuable resources in developing bronchiectasis-specific computer algorithms. The primary value of computer analysis lies in tracking disease severity and changes over time, with a focus on measuring longitudinal disease progression. MRI, particularly with hyperpolarized noble gases, offers a sensitive alternative for detecting ventilatory defects, making it valuable for longitudinal monitoring of disease, especially in pediatric cases. The combination of quantitative CT analysis, improved MRI techniques, and computational tools holds great promise for revolutionizing the assessment of bronchiectasis, improving prognostic accuracy, and providing valuable insights for personalized treatment plans in the future.