eNose technology, a promising diagnostic tool for ILD

Dec 16, 2020

Interstitial lung diseases (ILD) are a diverse group of over 200 different lung diseases that are classified together because of their similarities in e.g. clinical, radiological and pathological features [i]. Since the course of the disease, treatment choices and prognosis vary for different subtypes, an early and correct diagnosis is highly important [i, ii].

In patients with ILD, the tissue and space around the air sacs of the lungs (a.k.a. alveoli) are affected, causing shortness of breath and persistent dry cough which might even worsen during exercise or sleep. Although there is still no cure for ILD, symptoms can be treated depending on the cause of the ILD. Known causes can vary from ILDs associated with connective tissue diseases, to environmental exposures and drugs [i]. Also, a large group of ILDs is idiopathic, so without a known cause. Unfortunately, diagnosis of this disease and specifically classification of a subtype of ILD, requires a multidisciplinary approach and still remains difficult [iii]. For the majority of patients, the period between initial presentation of symptoms and the diagnosis can take more than a year [iv].

Current diagnostic procedures

Because ILDs are rare and the symptoms are non-specific, they are often not early recognized. Once an ILD is suspected, the evaluation of patients starts with the identification of the underlying cause and severity of the ILD. Multiple diagnostic tests are performed, varying from non-invasive (e.g. radiology and pulmonary function testing) to very invasive diagnostic procedures (e.g. lung biopsy) [i]. Due to this excessive and time-consuming diagnostic process, clinicians and researchers are continuously searching for new methods to enable early and accurate diagnosis of these patients.

Exhaled breath analysis for ILD diagnosis

One of those new methods that has been recently studied is exhaled breath analysis using electronic nose (eNose) technology [v, vi]. The volatile organic compounds (VOCs) in the exhaled breath generate a characteristic “breathprint” that is unique for each person and the complete VOC mixture provides insights into the metabolic state of a patient. This non-invasive way of diagnosing different diseases (e.g. asthma, COPD, lung cancer, infectious diseases etc.) has already been shown useful in a large number of studies [vii].

In order to answer the question whether ILD and preferably ILD subtypes can be detected using exhaled breath analysis, a cross-sectional study was performed at the Erasmus hospital, Rotterdam, the Netherlands. Breathprints of study participants were collected by performing a breath manoeuvre using a cloud connected eNose, the SpiroNose. The SpiroNose completely distinguished ILD patients from healthy controls (100% accuracy) and these results were confirmed in a separate group of patients [v].

“Exhaled breath analysis using eNose technology can completely distinguish ILD patients from healthy controls and can accurately discriminate between different ILD subgroups”

Furthermore, in their study, Moor et al showed the potential of eNose technology for the discrimination of different ILD subtypes. Their next step is to conduct a large multi-centre study to further investigate this in a larger patient group. Additionally, they will investigate the accuracy of eNose technology for prediction of disease progression and treatment response [viii].

The take home message of this study is strongly positive about the future of eNose technology as a diagnostic method for ILD. The results of this study showed that the technology has the potential to provide guidance during the multidisciplinary diagnostic approach and enhance certainty in clinical practice. Furthermore, it would reduce the burden of going through multiple diagnostic tests, reduce the delay in the diagnostic process, and improve care and treatment for patients with ILD [v].

This conclusion is in line with our goal to revolutionise diagnostic procedures, to help the patient and the health care system by providing a fast, non-invasive, easy to implement and cost-effective diagnostic tool.

 

References

[i] King, T. E. Approach to the adult with interstitial lung disease: Diagnostic testing. UpToDate. 2017. Waltham, MA. Accessed on: March25.

[ii] Antoniou, K. M. et al. Interstitial lung disease. European Respiratory Review. 2014.

[iii] Cottin V et al. Presentation, diagnosis and clinical course of the spectrum of progressive-fibrosing interstitial lung diseases. European Respiratory Review. 2018 December.

[iv] Wijsenbeek M et al. Progressive fibrosing interstitial lung diseases: current practice in diagnosis and management. Current Medical Research and Opinion. 2019 November.

[v] Moor, C. C. et al. Exhaled breath analysis by use of eNose technology: a novel diagnostic tool for interstitial lung disease. European Respiratory Journal. 2020.

[vi] Dragonieri, S. et al. Exhaled volatile organic compounds analysis by e-nose can detect idiopathic pulmonary fibrosis. Journal Breath Res. 2020.

[vii] Pereira, J. et al. Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview. Metabolites. 2015.

[viii] Skolnik, K. et al. Unclassifiable interstitial lung disease: a review. Respirology. 2016.

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Finance Manager Breathomix is a fast-growing, internationally operating Medical Tech Scale-Up. Our core business is breath analysis for diagnosing a multitude of conditions (Asthma, COPD, lung cancer, and many more) and enabling precision medicine.  Our team is...

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Front-end Developer Breathomix is a fast-growing, internationally operating Medical Tech Scale-Up. Our core business is breath analysis for diagnosing a multitude of conditions (Asthma, COPD, lung cancer, and many more) and enabling precision medicine. Our team is...

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Functional Designer Breathomix is a fast-growing, internationally operating Medical Tech Scale-Up. Our core business is breath analysis for diagnosing a multitude of conditions (Asthma, COPD, lung cancer, and many more) and enabling precision medicine. Our team is...