Surgical Education and Anatomical Identification in Laparoscopic CholecystectomyNCT07188181
Using AI and Fluorescence Guidance to Enhance Extrahepatic Bile Duct Identification Among Junior Surgeons During Laparoscopic Cholecystectomy
An observational study of Surgical Education and Anatomical Identification in Laparoscopic Cholecystectomy, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
Trial summary
The present study evaluates whether PGY trainees and surgical residents, with or without AI assistance, could accurately identify the presence and anatomical location of the CBD, as well as delineate intraoperative danger zones during LC. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Surgical Education and Anatomical Identification in Laparoscopic Cholecystectomy
- How many people
- 8 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Aug 2024to 31 Jul 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Surgical trainees (postgraduate trainees, junior residents, and senior residents) recruited from a single tertiary academic medical center. Participants performed video-based assessments of indocyanine green-guided laparoscopic cholecystectomy recordings.
Who may be able to join
- Postgraduate-year (PGY) trainees with fewer than 20 laparoscopic cholecystectomy (LC) cases.
- Junior residents with 20-50 LC cases.
- Senior residents with more than 50 LC cases.
Who cannot join
- Participants not available for the one-week washout and repeat assessment.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: AI and Fluorescence Help Junior Surgeons Identify the Bile Duct During Laparoscopic Cholecystectomy
The present study evaluates whether PGY trainees and surgical residents, with or without AI assistance, could accurately identify the presence and anatomical location of the CBD, as well as delineate intraoperative danger zones during LC.
Read the detailed description
This retrospective cohort study evaluated the impact of artificial intelligence (AI) assistance on anatomical recognition during laparoscopic cholecystectomy (LC). Between June 2022 and December 2024, indocyanine green (ICG) fluorescence-guided LC videos were prospectively collected at a tertiary referral center. After excluding duplicate cases, 177 videos were used for model training, 15 for validation, and 15 for testing. Frames were extracted at 1 frame per second, and key structures including the common bile duct (CBD), cystic duct, cystic artery, liver, gallbladder, and surgical instruments were annotated by board-certified hepatobiliary surgeons to generate the ground truth dataset.
A YOLOv9 object detection model, incorporating Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN), was trained to recognize critical biliary anatomy. For the experimental phase, surgical trainees (postgraduate trainees, junior residents, and senior residents) reviewed condensed 2-3 minute surgical videos, segmented into 5-second clips. In the CBD recognition task, participants determined whether the CBD was visible in each clip. In the CBD annotation task, participants placed bounding boxes to indicate the CBD location on single frames, and additionally delineated a polygonal "dangerous zone" within Calot's triangle where further dissection is considered hazardous.
Each participant first performed both tasks without AI assistance. After a one-week washout, the same tasks were repeated with AI support, which displayed YOLOv9-generated bounding boxes to guide decision-making. The task order was randomized to minimize learning bias. Performance metrics included recognition accuracy, precision, recall, F1-score, and intersection over union (IoU).
This study was retrospectively registered after completion, as it used de-identified surgical videos and trainee assessments.
- Keywords
- Laparoscopic Cholecystectomy, Artificial Intelligence, Common Bile Duct Identification, Indocyanine Green Fluorescence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| PGY Trainees | Postgraduate-year trainees with limited experience in laparoscopic cholecystectomy (<20 cases). | |
| Junior Residents | Residents with moderate experience in laparoscopic cholecystectomy (20-50 cases) | |
| Senior Residents | Residents with advanced experience in laparoscopic cholecystectomy (>50 cases). |
What is being measured
The primary outcome is the main question the study is designed to answer.
CBD Recognition
identify the presence of the CBD
Measured: During a single video review session (approximately 30-60 minutes per participant)
Secondary outcomes (1)
CBD annotation
Identify the exact location of the CBD
Measured: During a single video review session (approximately 30-60 minutes per participant)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Sep 2025
- Study start1 Aug 2024
- Primary completion31 Jul 2025
- Study completion31 Jul 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Surgical Education and Anatomical Identification in Laparoscopic CholecystectomyStudies of the same condition, open and under way.
- More trials run by Chang Gung Memorial HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 8 participants (actual)
Sponsor and investigators
- Lead sponsor
- Chang Gung Memorial Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- National Science and Technology Council, Taiwan
- Responsible party
- Sponsor
- Investigators
- Shih Min Yin, Study director, Chang Gung Memorial Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07188181
- Sponsor's protocol ID
- 202301955B0
- Status last verified
- Jan 2024
- First submitted
- 17 Sep 2025
- Last updated
- 23 Sep 2025
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared because institutional policy prohibits release of de-identified surgical videos and trainee performance data outside the study team.
Study at a glance
From the registry record, last updated by the sponsor on 23 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- AI and Fluorescence Help Junior Surgeons Identify the Bile Duct During Laparoscopic Cholecystectomy
- ClinicalTrials.gov ID
- NCT07188181
- Acronym / sponsor ID
- 202301955B0
- Keywords
- Laparoscopic Cholecystectomy, Artificial Intelligence, Common Bile Duct Identification, Indocyanine Green Fluorescence
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 8 participants (actual)
- Lead sponsor
- Chang Gung Memorial HospitalUniversity, hospital or other
- Collaborators
- National Science and Technology Council, Taiwan
- Study start
- 1 Aug 2024 (actual)
- Primary completion
- 31 Jul 2025 (actual)
- Study completion
- 31 Jul 2025 (actual)
- First posted
- 23 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The present study evaluates whether PGY trainees and surgical residents, with or without AI assistance, could accurately identify the presence and anatomical location of the CBD, as well as delineate intraoperative danger zones during LC.
Detailed description
This retrospective cohort study evaluated the impact of artificial intelligence (AI) assistance on anatomical recognition during laparoscopic cholecystectomy (LC). Between June 2022 and December 2024, indocyanine green (ICG) fluorescence-guided LC videos were prospectively collected at a tertiary referral center. After excluding duplicate cases, 177 videos were used for model training, 15 for validation, and 15 for testing. Frames were extracted at 1 frame per second, and key structures including the common bile duct (CBD), cystic duct, cystic artery, liver, gallbladder, and surgical instruments were annotated by board-certified hepatobiliary surgeons to generate the ground truth dataset.
A YOLOv9 object detection model, incorporating Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN), was trained to recognize critical biliary anatomy. For the experimental phase, surgical trainees (postgraduate trainees, junior residents, and senior residents) reviewed condensed 2-3 minute surgical videos, segmented into 5-second clips. In the CBD recognition task, participants determined whether the CBD was visible in each clip. In the CBD annotation task, participants placed bounding boxes to indicate the CBD location on single frames, and additionally delineated a polygonal "dangerous zone" within Calot's triangle where further dissection is considered hazardous.
Each participant first performed both tasks without AI assistance. After a one-week washout, the same tasks were repeated with AI support, which displayed YOLOv9-generated bounding boxes to guide decision-making. The task order was randomized to minimize learning bias. Performance metrics included recognition accuracy, precision, recall, F1-score, and intersection over union (IoU).
This study was retrospectively registered after completion, as it used de-identified surgical videos and trainee assessments.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| PGY Trainees | – | –Postgraduate-year trainees with limited experience in laparoscopic cholecystectomy (<20 cases). |
| Junior Residents | – | –Residents with moderate experience in laparoscopic cholecystectomy (20-50 cases) |
| Senior Residents | – | –Residents with advanced experience in laparoscopic cholecystectomy (>50 cases). |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Surgical trainees (postgraduate trainees, junior residents, and senior residents) recruited from a single tertiary academic medical center. Participants performed video-based assessments of indocyanine green-guided laparoscopic cholecystectomy recordings.
Key inclusion criteria (3 listed)
- Postgraduate-year (PGY) trainees with fewer than 20 laparoscopic cholecystectomy (LC) cases.
- Junior residents with 20-50 LC cases.
- Senior residents with more than 50 LC cases.
Key exclusion criteria (1 listed)
- Participants not available for the one-week washout and repeat assessment.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
CBD Recognition
Time frame: During a single video review session (approximately 30-60 minutes per participant)
identify the presence of the CBD
1 secondary outcome
CBD annotation
Time frame: During a single video review session (approximately 30-60 minutes per participant)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Sep 2025.
- Individual participant dataSharing planned: No. Individual participant data will not be shared because institutional policy prohibits release of de-identified surgical videos and trainee performance data outside the study team.
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Shih Min Yin study director
Chang Gung Memorial Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Surgical Education and Anatomical Identification in Laparoscopic Cholecystectomy, run by Chang Gung Memorial Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
CBD Recognition (time frame: During a single video review session (approximately 30-60 minutes per participant)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Sep 2025.