Post Market Study to Collect Data for Software Recognizing the Anatomical Structures During Bronchoscopy.

Completed

• Conditions: Tumor; Pulmonary Disease; Hemoptysis
• Interventions: Diagnostic Test: Bronchoscopy

• Registration Number: NCT04770675
• Lead Sponsor: Qmed Consulting A/S

Brief Summary

The primary aim is to develop a software algorithm that has the capacity to detect the normal 18 anatomical structures of the lung by using the position of the scope during the bronchoscopy procedure and using existing bronchoscopy technology.

Detailed Description

2.000 subjects, preferable 150-200 number of patients per site. The 2.000 videos will be divided into an 80%/20% split (training and testing). It is a wish to obtain a spread of videos coming from across Europe, preferable from Germany, France and Denmark, with up to 800 videos coming from Denmark

The patient population indicated are patients indicated for full airway bronchoscopy. Of this group it is the aim to enrol the following:

1. Patients with obstructing tumors (when tumor blocks the view of the camera) - no more than 5% (120 patients) of studies

2. Bronchoscopies on indication of haemoptysis (active bleeding) - no more than 5% (120 patients) of studies

3. Patients with stents or valves - no more than 5% (120 patients) of studies bronchoscopies.

4. Patients with former lung operations, partial or full resections - no more than 2% (48 patients).

Study Timeline

• Study Start: 2020-12-01
• Study First Submitted: 2021-02-12
• Study First Submitted QC: 2021-02-24
• Study First Posted: 2021-02-25
• Primary Completion: 2021-12-31
• Study Completion: 2021-12-31
• Status Verified: 2022-05
• Last Update Submitted: 2022-05-02
• Last Update Posted: 2022-05-03

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 833

Inclusion Criteria

1. Oral and written participant information has been given (NA for Denmark)
2. The subject has signed informed consent (NA for Denmark)
3. Patients indicated for full airway bronchoscopy (identifying all 18 anatomical segments)
4. Patients older than 18

Exclusion Criteria

1. Subject with serious lung disease which investigator considers not appropriate for this examination.
2. Lack of patient cooperation for bronchoscopy (patient with mental disorders, dysgnosia, psychological disorder...)
3. Subjects unable to give consent (NA for Denmark)

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Treatment group	Bronchoscopy	Any subject who is scheduled to undergo bronchoscopy as per routine clinical practice

Primary Outcome Measures

Name	Time	Method
Number of anatomical segments accessed during bronchoscopy	1 day	accurate photo documentation of all 18 anatomical segments +/- abnormalities

Secondary Outcome Measures

Name	Time	Method
Rate of total number of lesions detected	1 day	total lesions detected by the core lab/ total lesions detected by Machine Learning (after training, using the test videos).
Number of anatomical segments identified	1 day	Identified anatomical segments by the core lab/ Identified anatomical segments by the Machine Learning (after training, using the test videos).
Number of sections and lesions detected by core lab and machine learning	1 day	Anatomical sections + lesions detected by core lab versus anatomical sections + lesions detected by machine learning

Trial Locations

Locations (1)

Rigshospitalet; 🇩🇰 Copenhagen, Denmark