Brief summary The goal of this Feasibility study is to capture bronchoscopy data from patients (Group1) and bronchoscopists (Group 2) over a period of three years. The investigators wish to collect the pre-procedure CT scans and endoscopy videos of 300 patients. Up to 20 bronchoscopists will take part in the study Primary outcomes 1. To collect imaging data from patients undergoing routine bronchoscopy procedures 2. To collect movement data from clinicians performing the routine bronchoscopy procedures using a sensory Glove Secondary outcomes 1. Integrate the data gathered with procedure guidelines to develop a representation of procedure success using machine learning algorithms. 2. Develop an actionable knowledge base for bronchoscopy skill transfer to novice/untrained medical staff. 3. Investigate the feasibility of developing models of bronchoscopy procedures to develop training tools in the future There are no additional samples or time commitments from the participants in Group 1. The participants in Group 2 will be asked to answer a short questionnaire about their experience in performing bronchoscopies and will be asked to wear a sensory glove during the bronchoscopy procedure to capture their hand movements.
Bronchoscopy is a procedure for visualising the inside of the lung and airways. During bronchoscopy, a thin tube is passed through the patient's mouth or nose, down the throat and into the lungs. This allows the practitioner to examine the patient's airways for abnormalities such as inflammation. Additionally, samples may be taken from inside the lungs. Success rate of bronchoscopy relies on the practitioners experience. Patients undergoing bronchoscopy performed by novice bronchoscopists have an increased complication rate. Data from clinical practice suggest that bronchoscopy has a prolonged learning curve and trainees should perform a number of procedures, under supervision, to learn the technique. In this study the investigators aim to capture bronchoscopy data from patients (Group1) and bronchoscopists (Group 2) over a period of 3 years. The investigators will collect the pre-procedure CT scans and endoscopy videos of 300 patients. Up to 20 bronchoscopists will take part in the study by answering a short questionnaire on their experience and wearing sensorized gloves which will record their hand movements during the procedure. the investigators aim to use this data to develop computer algorithms and simulators that will assist in the training of new bronchoscopists, decreasing the time required to learn the technique and improving patient safety.
Study Type
OBSERVATIONAL
Enrollment
320
Royal Infirmary of Edinburgh
Edinburgh, United Kingdom
RECRUITINGTo collect imaging data from patients undergoing routine bronchoscopy procedures
The bronchoscopy images will be recorded using a screen capture device
Time frame: up to 1 hour
to collect movement data from clinicians performing the routine bronchoscopy procedures
A sensory glove will be worn by the clinicians to capture their hand movements during the routine bronchoscopy
Time frame: up to 1 hour
Integrate the data gathered with procedure guidelines to develop a representation of procedure success using machine learning algorithms
Develop machine learning algorithms to
Time frame: 1 year after completion of data collection
Investigate the feasibility of developing models of bronchoscopy procedures to develop training tools in the future.
Once data has been analysed investigate whether this can be used to develop training tools for future clinicians
Time frame: 1 year after completion of data collection
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