Radiomics in PET/CT and HRCT for systemic sclerosis-associated interstitial lung disease: breakthroughs and future directions

Systemic sclerosis (SSc) is a multifaceted autoimmune condition that leads to fibrosis in the skin and various internal organs, including the lungs. One of its most serious complications is interstitial lung disease (ILD), which has a profound impact on the prognosis and on patient quality of life. High-resolution computed tomography (HRCT) plays a critical role by offering detailed structural information, whereas positron-emission tomography/CT (PET/CT) provides a deeper understanding of disease activity by combining metabolic and anatomical data. Radiomics expands on those modalities, extracting subtle imaging features undetectable by visual analysis, thereby enabling superior diagnostic accuracy, staging, and prognostic accuracy. This review explores the current applications of radiomics in SSc-ILD, highlighting breakthroughs such as the integration of artificial intelligence for early ILD prediction and risk stratification. Studies have demonstrated that radiomics is efficacious in overcoming traditional diagnostic limitations, enhancing precision in identifying the patterns of usual interstitial pneumonia and monitoring disease progression. When applied to PET/CT, especially that using advanced tracers, radiomics can complement HRCT by identifying metabolic biomarkers of ILD activity, thus supporting personalized treatment strategies. Although radiomics holds significant transformative potential, its routine use in clinical practice still faces several obstacles, such as the need for standardization, validation, and consistency across institutions. Future efforts will be focused on combining radiomics with genetic and molecular data, developing artificial intelligence-driven longitudinal models, and adopting multimodal approaches to improve the management of SSc-ILD. These advances promise to drive a shift toward precision medicine, ultimately improving outcomes for patients with this complex disease.