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Deep Learning Diagnostic and Risk-stratification for IPF and COPD

Study Purpose

Idiopathic pulmonary fibrosis (IPF), non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive, irreversibly incapacitating pulmonary disorders with modest response to therapeutic interventions and poor prognosis. Prompt and accurate diagnosis is important to enable patients to receive appropriate care at the earliest possible stage to delay disease progression and prolong survival. Artificial intelligence (AI)-assisted digital lung auscultation could constitute an alternative to conventional subjective operator-related auscultation to accurately and earlier diagnose these diseases. Moreover, lung ultrasound (LUS), a relevant gold standard for lung pathology, could also benefit from automation by deep learning.

Recruitment Criteria

Accepts Healthy Volunteers Healthy volunteers are participants who do not have a disease or condition, or related conditions or symptoms	No
Study Type An interventional clinical study is where participants are assigned to receive one or more interventions (or no intervention) so that researchers can evaluate the effects of the interventions on biomedical or health-related outcomes. An observational clinical study is where participants identified as belonging to study groups are assessed for biomedical or health outcomes. Searching Both is inclusive of interventional and observational studies.	Observational
Eligible Ages	18 Years and Over
Gender	All

More Inclusion & Exclusion Criteria

Inclusion Criteria:

- Written informed consent.

- age > 18 years old.

- patients with already-diagnosed IPF (group 1) prior to the consultation (index) date.

- patients with already-diagnosed NSIP (group 2) prior to the consultation (index) date.

- patients with already-diagnosed COPD (group 3) prior to the consultation (index) date.

- Control subjects must be followed-up at the pulmonology outpatient clinic for: 1.

obstructive sleep apnoea. 2. occupational lung diseases (miners, chemical workers, etc.). 3. pulmonary nodules (considered benign after 2 years).

Exclusion Criteria:

- patients who cannot be mobilized for posterior auscultation.

- patients known for severe cardiovascular disease with pulmonary repercussion.

- patients known for a concurrent, acute, infectious pulmonary disease (e.g., pneumonia, bronchitis).

- patients known for asthma.

- patients known or suspected of immunodeficiency, alpha-1-antitrypsin deficit, and or under immunotherapy.

- patients with physical inability to follow procedures.

- patients with inability to give informed consent.

Trial Details

Trial ID: This trial id was obtained from ClinicalTrials.gov, a service of the U.S. National Institutes of Health, providing information on publicly and privately supported clinical studies of human participants with locations in all 50 States and in 196 countries.	NCT05318599
Phase Phase 1: Studies that emphasize safety and how the drug is metabolized and excreted in humans. Phase 2: Studies that gather preliminary data on effectiveness (whether the drug works in people who have a certain disease or condition) and additional safety data. Phase 3: Studies that gather more information about safety and effectiveness by studying different populations and different dosages and by using the drug in combination with other drugs. Phase 4: Studies occurring after FDA has approved a drug for marketing, efficacy, or optimal use.
Lead Sponsor The sponsor is the organization or person who oversees the clinical study and is responsible for analyzing the study data.	Pediatric Clinical Research Platform
Principal Investigator The person who is responsible for the scientific and technical direction of the entire clinical study.	Pierre-Olivier Bridevaux, Prof.Johan N. Siebert, MD
Principal Investigator Affiliation	Hôpital du Valais, SwitzerlandGeneva University Hospitals, Switzerland
Agency Class Category of organization(s) involved as sponsor (and collaborator) supporting the trial.	Other
Overall Status	Recruiting
Countries	Switzerland
Conditions The disease, disorder, syndrome, illness, or injury that is being studied.	Lung; Disease, Interstitial, With Fibrosis, Pulmonary Disease, Chronic Obstructive, Artificial Intelligence

Additional Details

Aim: To develop and determine the predictive power of an AI (deep learning) algorithm in identifying the acoustic and LUS signatures of IPF, NSIP and COPD in an adult population and discriminating them from age-matched, never smoker, control subjects with normal lung function. Methodology: A single-center, prospective, population-based case-control study that will be carried out in subjects with IPF, NSIP and COPD. A total of 120 consecutive patients aged ≥ 18 years and meeting IPF, NSIP or COPD international criteria, and 40 age-matched controls, will be recruited in a Swiss pulmonology outpatient clinic with a total of approximately 7000 specialized consultations per year, starting from August 2022. At inclusion, demographic and clinical data will be collected. Additionally, lung auscultation will be recorded with a digital stethoscope and LUS performed. A deep learning algorithm (DeepBreath) using various deep learning networks with aggregation strategies will be trained on these audio recordings and lung images to derive an automated prediction of diagnostic (i.e., positive vs.#46;negative) and risk stratification categories (mild to severe). Secondary outcomes will be to measures the association of analysed lung sounds with clinical, functional and radiological characteristics of IPF, NSIP and COPD diagnosis. Patients' quality of life will be measured with the standardized dedicated King's Brief Interstitial Lung Disease (K-BILD) and the COPD assessment test (CAT) questionnaires. Expected results: This study seeks to explore the synergistic value of several point-of-care-tests for the detection and differential diagnosis of ILD and COPD as well as estimate severity to better guide care management in adults

Arms & Interventions

Arms

: IPF patients (group 1)

Consenting adult patients >18 years old with with already-diagnosed IPF

: NSIP patients (group 2)

Consenting adult patients >18 years old with with already-diagnosed non-specific interstitial pneumonia (NSIP)

: COPD patients (group 3)

Consenting adult patients >18 years old with with already-diagnosed chronic obstructive pulmonary disease (COPD)

: Control subjects (group 4)

Consenting age-matched (+/- 2.5 years) never smokers patients with normal lung function (spirometry, lung volume and Transfer Factor for Carbon Monoxide (TLCO)) followed in the pulmonology outpatient clinic with similar quality of electronic medical records but for diseases other than the outcome of interest, namely: patients with obstructive sleep apnea. patients followed-up for occupational lung diseases (miners, chemical workers, etc.). patients followed-up for pulmonary nodules (considered benign after 2 years).

Interventions

Device: - Lung auscultation

Digital lung auscultation with the Eko core digital stethoscope (Eko Devices, Inc., CA, USA).

Device: - Lung ultrasound

Lung ultrasonography

Other: - Quality of Life's questionnaires

Impact of the diseases on subjects' health-related quality of life measured with standardized questionnaires (K-BILD, CAT)

Diagnostic Test: - Pulmonary functional tests

Spirometry, body-plethysmographic parameters and lung diffusion capacity for carbon monoxide will be measured.

Contact a Trial Team

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