

Description:
Systemic sclerosis (SSc) is a rare autoimmune disease with significant morbidity and mortality, emphasizing the critical need for early and accurate diagnosis. Nailfold capillaroscopy (NFC) plays a pivotal role in detecting early microangiopathic changes before clinical symptoms manifest. It identifies characteristic patterns such as enlarged capillaries, capillary loss, and microhemorrhages, which help classify disease stages. Recent research also highlights NFC's predictive potential in anticipating complications like pulmonary and renal involvement, thus aiding clinical decision-making by identifying patients who require intensive monitoring due to high-risk factors.
Primary Users:
Rheumatologists and operators analyzing and interpreting NFC images.
Objectives:
At Digital Health Zurich, our initiative integrates Artificial Intelligence (AI) with NFC to enhance early diagnosis and predict disease progression in systemic sclerosis. This project aims to optimize care for SSc patients and assess the feasibility of implementing AI-enhanced NFC systems in clinical settings.
Project Partners:
Mike Oliver Becker, PD Dr. med., Senior Physician, Department of Rheumatology at USZ
Oliver Distler, Prof. Dr. med., Director, Department of Rheumatology
Funding:
Digital Health Zurich (DHZ)