Brainomix e-Lung enables earlier detection of Progressive Pulmonary Fibrosis

Chicago, USA and Oxford, UK, 20 October 2025 – Brainomix, a global leader and pioneer of AI-powered imaging tools in lung fibrosis and stroke, presents new evidence at the CHEST Annual Meeting this week in Chicago showing its Brainomix 360 e-Lung technology could have significantly accelerated the diagnosis of Progressive Pulmonary Fibrosis (PPF) in over half of patients by up to almost two years.

Patients with Interstitial Lung Diseases (ILD) can develop PPF which causes irreversible lung damage and leads to early mortality. The key to the best outcome and survival for patients is early initiation of treatment. However, identifying patients eligible for treatment based on imaging can be challenging, even for experts.

Brainomix e-Lung is an FDA-cleared, AI-powered imaging software platform that automatically identifies and quantifies abnormalities on CT lung scans enabling clinicians to more easily identify changes including subtle deteriorations over multiple scan timepoints. Powered by novel, proprietary technology, e-Lung has been clinically validated to quantify lung features associated with ILD.

The results presented this week at CHEST – along with similarly notable results presented recently at the European Respiratory Society (ERS) Congress – stem from the REVISE PPF retrospective research study conducted with the University of Chicago, Weill Cornell Medical Center, and the University of Alabama at Birmingham, showing:

• e-Lung could have supported an earlier diagnosis of PPF in 62% of patients and up to 21 months earlier.
• e-Lung identified CT progression in 77% of patients deemed clinically stable.
• The earlier progression identified by e-Lung was clinically significant and was associated with survival, emphasising the value of earlier detection.
• e-Lung accurately identified patients at risk of developing future PPF from a single baseline scan.
• e-Lung metrics on the first patient scan are robust, independent predictors of mortality.

Dr Teja Kulkarni, Associate Professor and Director of the ILD Program at the University of Alabama at Birmingham, said:

AI-powered CT analysis has the potential to transform pulmonary fibrosis care. It can enhance early detection, precisely quantify disease, and track progression over time. The data we have shown for e-Lung is very promising, and the ability to objectively assess parenchymal changes to predict disease trajectory and treatment responses could really help us personalize treatment decisions and improve outcomes for patients living with pulmonary fibrosis.

Professor Peter George, Consultant Pulmonologist at the Royal Brompton Hospital, UK and Brainomix Senior Medical Director, said:

Early diagnosis of progressive pulmonary fibrosis is a key goal which is associated with improved patient outcomes. The evidence building around e-Lung points to a new tool that enables physicians and radiologists to more accurately identify subtle, but clinically meaningful disease progression on CT scans. Maximizing the data we can extract from routinely performed CT scans has the potential to identify progressive pulmonary fibrosis months and even years earlier than is currently possible; I look forward to seeing this scientific advancement translated into tangible benefits for patients ultimately improving their quality of life and long-term outcomes.

The two e-Lung studies will be presented as part of the CHEST Rapid Fire sessions on Tuesday, October 21st in Area 3A from 10:20 – 11:05AM CDT:

• Identification of Radiological Progressive Pulmonary Fibrosis in Clinically Stable Patients Using e-Lung Quantitative CT Algorithm: Results from REVISE PPF US Multicentre Study – Presented by Dr Teja Kulkarni
• The e-Lung Weighted Reticular Vascular Score Identifies Patients at Risk of Future Progressive Pulmonary Fibrosis: Results from the REVISE PPF Study – Presented by Professor Peter George