Deep Learning Diagnostic and Risk-stratification for IPF and COPD

Summary

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.

Conditions

• Lung; Disease, Interstitial, With Fibrosis
• Pulmonary Disease, Chronic Obstructive
• Artificial Intelligence

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.

Sponsors & Collaborators

• University Hospital, Geneva

  collaborator OTHER

• Swiss Federal Institute of Technology

  collaborator OTHER

• Hôpital du Valais

  collaborator OTHER

• Pediatric Clinical Research Platform

  lead OTHER

Principal Investigators

• Pierre-Olivier Bridevaux, Prof. · Hôpital du Valais, Switzerland

• Johan N. Siebert, MD · Geneva University Hospitals, Switzerland

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2023-04-01

Primary Completion

2024-10-06

Completion

2024-10-31

Countries

• Switzerland

Study Locations