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

Area of Science:

• Radiology and Medical Imaging
• Artificial Intelligence in Medicine
• Autoimmune Diseases

Background:

• Systemic sclerosis (SSc) is an autoimmune disease causing fibrosis in organs like the lungs.
• Interstitial lung disease (ILD) is a severe complication of SSc, impacting prognosis and quality of life.
• High-resolution computed tomography (HRCT) and PET/CT are crucial for diagnosing and assessing SSc-ILD.

Purpose of the Study:

• To review the applications of radiomics in SSc-ILD.
• To highlight AI's role in early ILD prediction and risk stratification.
• To explore radiomics' potential in complementing HRCT and PET/CT for personalized treatment.

Main Methods:

• Review of current literature on radiomics in SSc-ILD.
• Analysis of radiomics' integration with HRCT and PET/CT.
• Exploration of AI-driven radiomics for prediction and stratification.

Main Results:

• Radiomics improves diagnostic accuracy, staging, and prognosis in SSc-ILD.
• Radiomics effectively identifies usual interstitial pneumonia patterns and monitors disease progression.
• PET/CT combined with radiomics can reveal metabolic biomarkers of ILD activity.

Conclusions:

• Radiomics shows significant potential for managing SSc-ILD, offering enhanced precision beyond traditional methods.
• Standardization and validation are crucial for routine clinical implementation.
• Future research will focus on integrating radiomics with multi-omics data and AI for precision medicine in SSc-ILD.