Machine learning CT may better predict death in IPF

The new technique could help doctors determine disease progression and ensure earlier timing of treatment, suggests international research

Quantitative CT powered by machine learning could help doctors better predict death and disease severity in patients with idiopathic pulmonary fibrosis, international researchers say.

Results from their registry-based study suggest that imaging using data-driven texture analysis (DTA) would also enable earlier initiation of anti-fibrotic therapy and better timing of lung transplant evaluation before “irreversible progression has occurred”.