Close

eNose technology helps to diagnose interstitial lung disease

Note* - All images used are for editorial and illustrative purposes only and may not originate from the original news provider or associated company.

Subscribe

- Never miss a story with notifications

- Gain full access to our premium content

- Browse free from any location or device.

Media Packs

Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

– Access the Media Pack Now

– Book a Conference Call

– Leave Message for Us to Get Back

Related stories

CMS in US Launches WISeR Model to Enhance Original Medicare

The Centers for Medicare & Medicaid Services (CMS) is...

England GP IT Market Witnesses Shake-Up Unseen in 25 Years

England’s National Health Service, which is popularly known as...

Label Expansion In Alzheimers Gives GE HealthCare An Edge

The US Food and Drug Administration (FDA) has gone...

US Health Systems Accelerating AI Collaborations

US Health systems are speeding up their collaborations with...

Analysing exhaled breath using an artificial sensory system, the electronic nose (eNose), has enabled researchers to accurately differentiate between those interstitial lung disease (ILD) and healthy controls.

The eNose compares exhaled breath to previously obtained specific breath ‘signature’ for a particular condition held in a database.

Researchers from the Erasmus Medical Centre, The Netherlands, undertook a cross-sectional study in 322 patients with a diagnosis of ILD patients and 48 healthy controls with a mean age of 61.6 years (59.9% male), of whom, 5.3% were current smokers.

The eNose is first ‘trained’ to recognise ILD breath signatures of those with the condition the ILD subgroups, for example, idiopathic pulmonary fibrosis (IPF), sarcoidosis, connective-tissue related ILD etc. Researchers then compared the area under the curves (AUCs) results obtained from the training phase to the breath samples obtained from the study patients. The results showed a high level of comparability between the study patients and the breath signatures obtained through training the eNose. For example, in the training phase, the AUC for patients with IPF was 0.91 compared to other subtypes and 0.87 (95% CI 0.77–0.96) in the testing phase.

The authors concluded that using the eNose represents a potentially novel biomarker in ILD, which enables diagnosis of the condition and the different ILD subgroups.

 

Latest stories

Related stories

CMS in US Launches WISeR Model to Enhance Original Medicare

The Centers for Medicare & Medicaid Services (CMS) is...

England GP IT Market Witnesses Shake-Up Unseen in 25 Years

England’s National Health Service, which is popularly known as...

Label Expansion In Alzheimers Gives GE HealthCare An Edge

The US Food and Drug Administration (FDA) has gone...

US Health Systems Accelerating AI Collaborations

US Health systems are speeding up their collaborations with...

Subscribe

- Never miss a story with notifications

- Gain full access to our premium content

- Browse free from any location or device.

Media Packs

Expand Your Reach With Our Customized Solutions Empowering Your Campaigns To Maximize Your Reach & Drive Real Results!

– Access the Media Pack Now

– Book a Conference Call

– Leave Message for Us to Get Back