FRI Technology

The Functional Respiratory Imaging (FRI) technology is a novel image based diagnostic that combines imaging techniques such as High-Resolution CT scans (HRCT) and flow simulations (Computational Fluid Dynamics – CFD). Thanks to this combination, a 3D visualization and quantification of the patient’s lung structure and lung function can be provided.

1 Image Acquisition

To obtain this data about a patient, only two low dose HRCT scans taken during total inspiration (TLC) and normal expiration (FRC) are needed.

1 Image Acquisition

To obtain this data about a patient, only two low dose HRCT scans taken during total inspiration (TLC) and normal expiration (FRC) are needed.

2 Structure Segmentation

From the HRCT scans, the patient-specific airway and lung structures are segmented and 3D reconstructed. Several structural patient-specific parameters, such as lung and airway volumes, emphysema or air trapping can be obtained at this stage, at a lobar level. These 3D reconstructed structures from the CT scans form the basis for further functional analysis using CFD.

2 Structure Segmentation

From the HRCT scans, the patient-specific airway and lung structures are segmented and 3D reconstructed. Several structural patient-specific parameters, such as lung and airway volumes, emphysema or air trapping can be obtained at this stage, at a lobar level. These 3D reconstructed structures from the CT scans form the basis for further functional analysis using CFD.

3 Flow simulation

FRI technology combines CT images with an advanced Computational Fluid Dynamics (CFD) tool to provide both structural and functional parameters. CFD analyses the motion of fluids and their interaction with surfaces. This advanced technology in aerospace engineering can be applied to healthcare, accurately describing the patient’s “geometry” (lungs, arteries, heart, etc.) and “boundary” conditions (blood flow velocity, airflow pressures, etc.). This results in a detailed, functional imaging, allowing to provide patient-specific parameters such as airway resistance and aerosol deposition characteristics.

3 Flow simulation

FRI technology combines CT images with an advanced Computational Fluid Dynamics (CFD) tool to provide both structural and functional parameters. CFD analyses the motion of fluids and their interaction with surfaces. This advanced technology in aerospace engineering can be applied to healthcare, accurately describing the patient’s “geometry” (lungs, arteries, heart, etc.) and “boundary” conditions (blood flow velocity, airflow pressures, etc.). This results in a detailed, functional imaging, allowing to provide patient-specific parameters such as airway resistance and aerosol deposition characteristics.

Machine Learning

Machine Learning Algorithms can detect patterns in large amounts of data that are too complex to discern with the human eye. The low variability of the measurement and high quality of the FRI parameters makes them highly suited for Machine Learning and Artificial Intelligence. Initially applying this approach in clinical trials with FRI parameters obtained before and after a treatment creates a well controlled environment to validate the outcomes of the machine learning with known pathophysiology and treatment effect.

Read more...