Functional Respiratory Imaging (FRI)- A Novel Approach To Assess Lung Health

Respiratory health is deteriorating day by day globally due to an increased exposure to certain risk factors such as pollution, smoking and passive lifestyle. Although in general the respiratory diseases can be kept under control, there is still a need for better phenotyping and management of lung diseases such as COPD and Asthma. The conventional Lung Function Tests like spirometry don’t provide any regional information and have limited sensitivity to detect changes in pulmonary function in an early stage because the healthy areas in the lung compensate for a progressive disease making it undetectable. There is a need to shift to a better technology which can look at the overall lung health.

FRI Technology: How it works.

FRI provides a unique way to assess the ventilation-perfusion ratio in patients suffering from lung diseases like Asthma, COPD, Idiopathic Pulmonary Fibrosis, Cystic Fibrosis etc. It is a combination of conventional high resolution CT Scans and flow simulations (Computational Fluid Dynamics). It provides regional information about the lung structure as well as the lung function. It’s a sensitive biomarker that can help in conducting smaller and cheaper clinic trials and selecting the most suitable combination of treatments for individual patients.

Benefits of FRI

FRI can produce highly clinical relevant patient specific biomarkers, presenting 3D visualization of the patient’s airway and lung geometry, regional airway resistance and aerosol deposition patterns. Through the online platform Broncholab , FRI can help to better diagnose and phenotype respiratory patients, as it provides visual and regional quantified information that allows:

  • Early detection of disease progression
  • Early detection of therapy effects
  • Better understanding of underlying mechanisms of disease
  • Visualization of deposition characteristics of inhaled compounds

The use of FRI in clinical trials can have a major positive impact on cost and patient treatment such as:

  • It identifies the most promising respiratory drugs in a cost and time-effective way.
  • It reduces the number of patients in the clinical trial by a factor 3-8 while preserving statistical significance.
  • It helps to identify ineffective therapies sooner (fail fast – fail often).
  • It speeds up the registration process of compounds in the therapeutic area of respiratory diseases.




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