FRI and disease characterization: Idiopathic pulmonary fibrosis

A thorough understanding of a pharmaceutical company’s target disease is imperative when it wants to successfully develop and market its respiratory drug. Often, conventional lung function parameters lack the sensitivity and level of detail to fully capture a disease and this leads to very expensive developments in the respiratory field. This is especially the case in diseases with difficult treatments, where even governmental bodies recognize the fact that conventional lung function parameters have never been fully validated against disease progression .

Idiopathic pulmonary fibrosis (IPF) is such a disease. Patients with IPF develop a progressive scarring of the lung tissue, starting at the alveoli and moving more centrally over time. The scarring causes the lung tissue to become stiffer, which makes it more difficult for lungs to work properly. It becomes more difficult to take in a deep breath and eventually the lungs cannot take in enough oxygen. Although the scarring is associated with a multitude of factors, doctors cannot find what’s causing the fibrotic proliferation.

With progressing disease, the conventional spirometry tests show us that the forced vital capacity (FVC) decreases up until the point where the lungs become so stiff that the organ fails. However, FVC only starts to drop when the disease is already rather advanced. Recent expert statements point out the need for earlier detection and for endpoints that are closer linked to true, regional disease progression. The lack of information on disease progression through various stages leads to sub-optimal treatments simply because physicians and drug developers are at a loss about what’s really going on regionally. It is essential to find better ways of mapping the various stages of the disease in order to find more effective treatment paradigms and reduce mortality.

Quantitative CT imaging (QCT) can help the field move forward with giant strides. QCT provides a wealth of information about the organ and can accurately show what’s going on in the lungs from a physiological point of view. By quantifying various aspects (structural deformations, tissue alterations,…) of the lungs and following them up over time, one gets a good understanding of the physiological changes over time. This helps answering various questions on structural disease progression and often leads to earlier signs of change than the parameters doctors are used to seeing (e.g. FVC, currently the primary endpoint in clinical trials for IPF).

Functional Respiratory Imaging (FRI) goes a step further and combines lung structure with lung function. By looking at CT scans of a lung at both expiration and inspiration, FRI assesses flow dynamics and adds functionality to the analysis. This gives us the tools to describe the IPF lung accurately with progressing disease. Doing this in a population of IPF patients, we observe distinct structural changes over time that are also reflected in the functionality of the lung.

Figure 1 Illustration of the consequences of IPF lung disease (versus healthy on top, internal variation in IPF patients on the bottom).

By means of FRI, significant differences can be seen in the IPF lung when compared to a healthy lung. The lung lobes are smaller, fibrosis is present, and the airways are larger [Vos et al, ATS2015]. Within the IPF patients themselves FRI shows that the disease presence is stronger in the lower lobes as compared to the upper lobes [De Backer et al, ATS 2015]. This regional difference in disease presence causes the internal ventilation (which is lower lobe driven in healthy subjects) to be upper lobe predominant. The figure below shows that this shift in ventilation distribution is independent of the disease stage.

Figure 2 The internal airflow distribution (fraction of incoming air) in IPF patients for different degrees of severity (as expressed by FVC (%pred). In healthy subjects 60% of the inhaled air is going to the lower lobes.

Moreover, in the early disease stage where the FVC is near 100% predicted, FRI already shows other significant deviations from a healthy lung. The lower lung lobes already lose 40% of their volume before FVC is even showing any signal [De Backer et al, ATS 2017]. This loss in lung volume is combined with an increase in airway caliber in the same regions. This change in airway caliber can be explained by the scarring of the alveoli, causing them to be less elastic. Consequently, when breathing in, the volume increase of the thorax needs to be compensated elsewhere which will lead to stretching of the distal airways rather than the alveoli themselves (see video below).

Figure 3 In IPF patients lung lobes are smaller than in healthy subjects. For IPF patients with normal lung function already 40% of the lung volume in the lower lobes is lost (top image). In contrast with the decrease in lung volume, airways volumes keep increasing in IPF (bottom image).

Video 1 An infographic showing how the increase in fibrotic tissue (and stiffness) in the alveoli in IPF patients causes the airways to become overstretched when inhaling.

Measuring airway, lung and lobe volumes, and internal airflow distributions over time shows a clearer and more linear disease stage as compared to drops in FVC. In fact, the changes we observe in the lungs at each stage are considerably larger than the changes observed in FVC. These changes reflect a substantial potential for using the lung structures as biomarkers for disease stage and progression. As a result, when focusing on those signals with the largest change, sample size calculations are considerably reduced compared to FVC [De Backer et al, ATS 2017].

Figure 4 Possible reduction in sample size to show diseases progression in mild IPF patients by using regional (lower lobes only) FRI measures versus FVC.

The evidence of these findings has now been gathered, analyzed and presented to the FDA for which FLUIDDA has received a letter of support in 2016. Our conclusion is that disease characterization is of utter importance to understand disease and treatment paradigm. FRI has shown that with quantitative imaging we get a better handle on the various disease stages and its progression, ultimately giving the field better tools to treat IPF patients better. At FLUIDDA we know that we can change the lives of severe respiratory patients by looking at their disease in more detail, and hence gain a deeper understanding of the disease and treatment processes. Our FRI tools related to disease characterisation make it possible to support drug developers better than ever in providing better drugs to their target population, improving the lives of patients together.

Discover more about how FRI can be the answer to your research question here.

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