The Spanish Society of Rheumatology is currently conducting a research study to explore the prevalence and early diagnosis of interstitial lung disease (ILD) in individuals diagnosed with rheumatoid arthritis (RA). Fifteen rheumatology departments will work on the study together with the radiology departments in Spain in 2024 and 2025, and hereby make use of radiology AI in rheumatology.
This collaboration will address an important healthcare issue: the early detection of ILDs, which tend to go undetected until later stages. This, in turn, negatively impacts patient outcomes, particularly when a patient suffers from cardiovascular diseases.
Rheumatoid arthritis is a systemic autoimmune disease that predominately involves joints, but it can develop into inflammation in lungs, heart, eyes. The expectation is that approximately 30% of rheumatoid arthritis patients may develop diffuse ILDs, underscoring the need for effective screening criteria. Early diagnosis is hard due to the lack of standard. To achieve this goal, the research team has outlined specific criteria for participant selection, and the study aims to recruit over 450 patients across 15 hospital centers. The study results will hopefully help define strategies for early detection of ILD in patients with rheumatoid arthritis.
contextflow ADVANCE Chest CT as the AI solution will deliver automatic quantification regarding the extent of ILD in the study population, enabling detailed examination of the lung parenchyma. Furthermore, the study will compare the interstitial involvement of the lung parenchyma in chest CTs assessed by radiologists and compare them to the results from the automatic detection of ILD-associated patterns by contextflow’s AI software.
While specific lung patterns under assessment remain unclear, the integration of AI-driven analysis promises to enhance accuracy and efficiency of diagnosis.
Radiology AI solution for better diagnosis
This collaborative effort aims to improve early detection and management of ILDs in rheumatoid arthritis patients, potentially leading to better outcomes and quality of life for affected individuals. It is a great example of how radiology AI solution can be used in rheumatology.