Lung Cancer Clinical Trial
Official title:
Automatic Segmentation of Mediastinal Lymph Nodes and Blood Vessels in Endobronchial Ultrasound (EBUS) Images Using a Deep Neural Network
NCT number | NCT05739331 |
Other study ID # | 240245 |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | May 1, 2023 |
Est. completion date | December 1, 2025 |
To evaluate the usefulness of Deep neural network (DNN) in the evaluation of mediastinal and hilar lymph nodes with Endobronchial ultrasound (EBUS). The study will explore the feasibility of DNN to identify lymph nodes and blood vessel examined with EBUS.
Status | Recruiting |
Enrollment | 50 |
Est. completion date | December 1, 2025 |
Est. primary completion date | May 1, 2025 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | 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. |
Country | Name | City | State |
---|---|---|---|
Norway | Department of Pulmonology, Levanger Hospital, North Trøndelag Hospital Trust | Levanger | |
Norway | Department of Thoracic Medicine, St Olavs Hospital | Trondheim |
Lead Sponsor | Collaborator |
---|---|
Norwegian University of Science and Technology | Helse Nord-Trøndelag HF, SINTEF Health Research |
Norway,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Capability | To explore if Deep neural network (DNN) has capability to segment lymph nodes and blood vessels from EBUS images | 8 months | |
Secondary | Precision | 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). | 2 months | |
Secondary | Sensitivity | True positive rate. Correctly detected lymph nodes/blood vessel over total lymph nodes/blood vessel. Measured per pixel in the EBUS images | 2 months | |
Secondary | Specificity | Specificity = (True Negative)/(True Negative + False Positive). Measured per pixel in the EBUS images. | 2 months | |
Secondary | Dice similarity coefficient | Measures the similarity between two sets of data: Annotated by pulmonologist vs DNN. | 2 months | |
Secondary | Run-time | Is the run-time sufficiently low for real-time analysis during EBUS? | 2 months | |
Secondary | Adverse events | Procedure related adverse events or unexpected incidents registered | 48 hours |
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