The current landscape
Currently, PPF diagnosis hinges on a combination of CT scans, patient narratives, and, in some cases, histological examination. Dr. Wijsenbeek stressed the need to transition to novel diagnostic modalities, including tools that can be readily employed by GPs in their practices.
“GPs have to care about a lot of different diseases, and it makes it more complicated to be aware of conditions like PPF: Symptoms are in fact extremely unspecific” Dr. Kreuter told this news organization. “My suggestion to GPs is to pay attention to the so-called inspiratory crackles because they represent a very early and specific sign of lung fibrosis. This sound does not resemble any other sound that you can hear with your stethoscope: It is like the sound you make walking on fresh snow,” he added, recommending a referral to the pulmonologist in case of identification of inspiratory crackles.
Additionally, several biomarkers can contribute to early PPF diagnosis, including the identification of the usual interstitial pneumonia (UIP) pattern through biopsy or imaging. “We know that this pattern predicts poor outcomes regardless of ILD type,” Dr. Podolanczuk explained, underlining the possibility of using a molecular classifier to identify a UIP pattern on transbronchial lung biopsy. “This is an already existing technology used to identify a gene expression pattern that is strongly predictive of a UIP pattern,” she said.
Furthermore, blood biomarkers, such as high peripheral blood monocyte count and telomere length, hold promise for early PPF detection and prognosis assessment.
The road ahead
The diagnostic landscape for PPF is evolving rapidly, with various emerging biomarkers and tools showing promise. Proteomics, alongside home spirometry as a digital biomarker for frequent FVC monitoring, have demonstrated potential for identifying patients who may benefit from early treatment. A 2022 study defined a 12-proteomic biomarkers signature of progressive fibrosing ILD that can identify patients who may benefit from early treatment and is predictive of outcomes regardless of the underlying CT pattern.
The integration of artificial intelligence into the interpretation of CT and x-ray images represents another avenue of advancement in PPF diagnosis. Dr. Podolanczuk highlighted the role of AI and quantitative CTs in enhancing diagnostic accuracy. She also mentioned innovative imaging methods, such as hyperpolarized gas MRI and endobronchial optical coherence tomography (EB-OCT), which offer new insights into disease progression and treatment response.
Beyond imaging and AI, various research tools are entering the diagnostic arena, including real-time breath analysis for distinguishing between different respiratory conditions. These tools collectively promise to shorten the time from symptom presentation to PPF diagnosis, a vital step in improving patient outcomes. In the words of Dr. Podolanczuk, “How early is too early to identify these patients? Let me say that there’s no such thing as ‘too early’ in the diagnosis of PPF!”
Dr. Podolanczuk disclosed grant funding from NHLBI, ALA, and Three Lakes Foundation; consulting fees from Regeneron, Roche, Imvaria, Boehringer Ingelheim, Veracyte, United Therapeutics, and Eisai; and honoraria from NACE and EBSCO/DynaMed. Ms. Robertson disclosed having no conflict.
A version of this article first appeared on Medscape.com.