Advances in Radiological Imaging for Thoracic Oncology: A 20-Year Perspective.

Lung cancer remains the leading cause of cancer-related mortality worldwide, underscoring the critical role of imaging in early detection, staging, and treatment planning. In the past 2 decades, thoracic imaging has evolved from anatomical visualization to multiparametric assessment integrating functional, quantitative, and artificial intelligence-driven applications. Advances in computed tomography (CT), including multidetector arrays, dual-energy CT, and photon-counting CT, have improved spatial resolution, reduced radiation dose, and enabled functional evaluation through iodine mapping. Positron emission tomography/CT (PET/CT), particularly with Fluorine-18 fluorodeoxyglucose-PET/CT, has become indispensable for staging, radiotherapy planning, and response assessment, whereas novel tracers targeting hypoxia, proliferation, and immune biomarkers expand its clinical utility. Magnetic resonance imaging inherently offers superior soft tissue contrast, with new imaging sequences improving prior limited temporal resolution, and more recent functional techniques such as diffusion-weighted imaging and dynamic contrast enhancement, supporting early response evaluation and radiogenomic exploration. Hybrid modalities such as PET/magnetic resonance imaging and theranostic platforms exemplify the convergence of diagnosis and therapy, enabling personalized oncology. Radiomics and radiogenomics extract high-dimensional imaging features to predict prognosis, treatment response, and molecular profiles, whereas artificial intelligence accelerates detection, segmentation, and risk stratification with performance metrics rivaling expert interpretation. Despite challenges in standardization and validation, these innovations position imaging as a cornerstone of precision medicine in thoracic oncology. Continued multidisciplinary collaboration and rigorous methodological frameworks will be essential to translate these advances into routine clinical practice.

Copyright © 2026. Published by Elsevier Inc.