AI-EBUS-Elastography for LN Staging (AI-EBUS-E)
Clinical Utility of Artificial Intelligence-Augmented Endobronchial Ultrasound-Elastography in Lymph Node Staging for Lung Cancer
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Ontario
-
Hamilton, Ontario, Canada, L8N 4A6
- St. Joseph's Healthcare Hamilton
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Patients that are diagnosed with suspected or confirmed NSCLC that have been referred to mediastinal staging through EBUS-TBNA at St. Joseph's Healthcare Hamilton will be eligible for this study.
Exclusion Criteria:
- No exclusion criteria will apply.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Experimental: EBUS-Elastography
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Patients undergoing LN staging for lung cancer with EBUS-TBNA will have digital images and biopsy of every LN obtained in accordance with standards of care.
Prior to the lymph node biopsy by EBUS-TBNA, elastography will be performed.
The relative strain of tissues in the scanned area of the LNs will be displayed as a colour map, with stiffer areas in blue and softer tissue in red.
Elastography and B-mode images will be displayed side by side and images recorded and saved onto an external drive for analysis.
Elastography images will be fed to the NeuralSeg algorithm which has a network architecture similar to the standard U-Net for image segmentation.
The automatically identified regions of interest will be overlaid onto the EBUS Elastography images to extract the LN stiffness measurements.
After overlaying, NeuralSeg will determine the proportion of the LN area within 9 previously defined stiffness thresholds.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Stiffness Area Ratio
Time Frame: 8 months
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Identifying whether the percent area of a lymph node above a defined blue colour threshold is independently associated with malignancy
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8 months
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
NeuralSeg's prediction of lymph node malignancy
Time Frame: 2 months
|
Determine whether NeuralSeg can accurately predict malignancy in lymph nodes when compared to biopsy results of the lymph nodes that were examined
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2 months
|
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The agreement between NeuralSeg's predictions and pathology results, as measured by diagnostic accuracy, sensitivity, specificity, positive and negative predictive values
Time Frame: 2 months
|
The agreement between NeuralSeg's predictions and pathology results, as measured by diagnostic accuracy, sensitivity, specificity, positive and negative predictive values
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2 months
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Waël C Hanna, MDCM, MBA, FRCSC, McMaster University
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
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
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- AI-EBUS-Elastography_19032021
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
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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