Augmented Endobronchial Ultrasound (EBUS-TBNA) With Artificial Intelligence
Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using a Deep Neural Network
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Øyvind Ervik, MD
- Phone Number: +4791634595
- Email: oyvind.ervik@ntnu.no
Study Contact Backup
- Name: Hanne Sorger, MD,PhD
- Phone Number: +4791816787
- Email: hanne.sorger@ntnu.no
Study Locations
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-
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Levanger, Norway, 7600
- Recruiting
- Department of Pulmonology, Levanger Hospital, North Trøndelag Hospital Trust
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Contact:
- Øyvind Ervik, MD
- Phone Number: +4791634595
- Email: oyvind.ervik@ntnu.no
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Trondheim, Norway, 7030
- Recruiting
- Department of Thoracic Medicine, St Olavs Hospital
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Contact:
- Håkon O Leira, MD, PhD
- Phone Number: +4799014967
- Email: håkon.o.leira@ntnu.no
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Subjects referred to thoracic department in any of the participating hospitals with undiagnosed enlarged mediastinal and hilar lymph nodes.
- Subjects have to be ≥ 18 years of age
Exclusion Criteria:
- Pregnancy
- Any patient that the Investigator feels is not appropriate for this study for any reason.
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Capability
Time Frame: 8 months
|
To explore if Deep neural network (DNN) has capability to segment lymph nodes and blood vessels from EBUS images
|
8 months
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Precision
Time Frame: 2 months
|
The precision the DNN has for detecting lymph nodes and blood vessels.
Measured both per voxel in the EBUS images and per annotated structure (a structure is counted as detected if at least 50% of its annotated pixels are identified by the DNN).
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2 months
|
|
Sensitivity
Time Frame: 2 months
|
True positive rate.
Correctly detected lymph nodes/blood vessel over total lymph nodes/blood vessel.
Measured per pixel in the EBUS images
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2 months
|
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Specificity
Time Frame: 2 months
|
Specificity = (True Negative)/(True Negative + False Positive).
Measured per pixel in the EBUS images.
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2 months
|
|
Dice similarity coefficient
Time Frame: 2 months
|
Measures the similarity between two sets of data: Annotated by pulmonologist vs DNN.
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2 months
|
|
Run-time
Time Frame: 2 months
|
Is the run-time sufficiently low for real-time analysis during EBUS?
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2 months
|
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Adverse events
Time Frame: 48 hours
|
Procedure related adverse events or unexpected incidents registered
|
48 hours
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Study Director: Øivind Rognmo, Dr.philos, Norwegian University of Science and Technology
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 240245
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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