Advanced imaging in systemic sclerosis: distinguishing activity from damage across organ systems

A central challenge in systemic sclerosis (SSc) is the inability to distinguish active, potentially reversible disease, from damage, irreversible fibrosis. Current imaging modalities, including high-resolution computed tomography (HRCT) and echocardiography, predominantly capture structural damage and cannot resolve this distinction. This review outlines next generation imaging modalities for SSc with focus on quantitative machine learning algorithms and molecular imaging.

The unifying advance across organ systems is a shift from documenting damage to measuring disease activity directly. Machine-learning-derived quantitative HRCT detects radiological patterns of ILD sensitive to change in SSc-associated interstitial lung disease. Parametric cardiac magnetic resonance mapping resolves diffuse interstitial fibrosis missed by late gadolinium enhancement. Fibroblast activation protein inhibitor PET (FAPI-PET) visualizes active fibrogenesis in lung and myocardium, identifying biologically active disease even before structural distortion occurs. [18F]Sodium fluoride PET detects metabolically active calcinosis. High-frequency ultrasound, elastography, and optical coherence tomography (OCT)-angiography extend objective assessment of cutaneous and microvascular involvement.

Emerging imaging modalities in SSc may enable earlier detection of active disease amenable to treatment modification and yield more sensitive endpoints for SSc clinical trials.