Biliary Tract Cancer (BTC)BTC-NCCT-AINCT07911397
Prospective AI-Assisted Screening of Biliary Tract Cancer Using Non-Contrast CT
A study testing AI-Assisted Biliary Tract Cancer Screening Using NCCT in people with Biliary Tract Cancer (BTC), run by Beijing Tsinghua Chang Gung Hospital at 1 site in China.
Trial summary
Biliary tract cancer is a group of malignant tumors involving the intrahepatic bile ducts, extrahepatic bile ducts, and gallbladder. Early detection can be challenging because non-contrast computed tomography (NCCT), which is commonly performed in routine clinical practice, may provide limited information for… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Biliary Tract Cancer (BTC)
- What is being tested?
- AI-Assisted Biliary Tract Cancer Screening Using NCCT
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 10,000 participants
- Where
- 1 siteChina
- Study dates
- 1 Oct 2026to 28 Feb 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Adults aged 18 years or older.
- Undergoing abdominal non-contrast computed tomography (NCCT) as part of routine clinical evaluation or health examination.
- NCCT examination provides adequate coverage of the liver and biliary tract.
- Complete NCCT imaging data with sufficient image quality for analysis by the artificial intelligence system.
- Sufficient clinical information and/or follow-up data are available to establish the predefined clinical reference standard.
Who cannot join
- Previous major hepatobiliary or pancreatic surgery that substantially alters the anatomy of the liver or biliary tract and may affect AI analysis.
- Recent major upper-abdominal surgery or hepatic trauma that may substantially affect evaluation of the liver or biliary tract.
- Poor image quality or severe image artifacts that preclude reliable AI analysis, including severe motion, metal, or noise artifacts.
- Inadequate scan coverage that does not include the liver and biliary tract.
- Duplicate examinations or repeated enrollment of the same participant.
- Insufficient clinical information or follow-up to establish the predefined clinical reference standard.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site
Beijing Tsinghua Changgung Hospital
Beijing, 102218
Jiaqi Dou, Dr., +86 17801066821, jiaqi_thu@163.com
About this study
Official title: Prospective Clinical Validation of an Artificial Intelligence System for Biliary Tract Cancer Screening Using Non-Contrast Computed Tomography
Biliary tract cancer is a group of malignant tumors involving the intrahepatic bile ducts, extrahepatic bile ducts, and gallbladder. Early detection can be challenging because non-contrast computed tomography (NCCT), which is commonly performed in routine clinical practice, may provide limited information for identifying biliary tract cancer. This prospective study aims to clinically validate an artificial intelligence (AI) system for screening and detecting biliary tract cancer on NCCT images. The AI system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. The study will evaluate the diagnostic performance of the AI system against a predefined clinical reference standard. The primary objective is to assess the ability of the AI system to distinguish patients with biliary tract cancer from those without biliary tract cancer using NCCT. Secondary objectives include evaluating sensitivity, specificity, positive predictive value, and negative predictive value. The study is designed to evaluate the clinical performance and potential screening value of AI-assisted analysis of NCCT. Routine clinical care and clinical decision-making will not be replaced by the AI system.
- Conditions
- Biliary Tract Cancer (BTC)
- Being tested
- AI-Assisted Biliary Tract Cancer Screening Using NCCT
- Medical subject headings
- Biliary Tract Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted Biliary Tract Cancer Screening Using NCCTDiagnostic test
An artificial intelligence system that analyzes non-contrast computed tomography (NCCT) examinations to screen for biliary tract cancer. The system independently processes eligible NCCT images and generates a patient-level risk score indicating the likelihood of biliary tract cancer. The AI output will be evaluated against a predefined clinical reference standard. The system is intended to support the detection of biliary tract cancer and does not replace routine clinical interpretation or independently determine patient management.
| Study group | Role | What they receive |
|---|---|---|
| AI-Assisted NCCT Screening | Experimental | Participants in this arm will undergo AI-assisted screening for biliary tract cancer using non-contrast computed tomography (NCCT). The artificial intelligence system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. The AI output will be evaluated against a predefined clinical reference standard. Routine clinical interpretation and patient management will not be replaced by the AI system. Receives: Diagnostic Test: AI-Assisted Biliary Tract Cancer Screening Using NCCT |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient-level area under the receiver operating characteristic curve (AUC) of the AI system for distinguishing biliary tract cancer from non-biliary-tract-cancer cases using non-contrast computed tomography (NCCT)
The primary outcome is the patient-level area under the receiver operating characteristic curve (AUC) for the AI system in distinguishing biliary tract cancer from non-biliary-tract-cancer cases using non-contrast computed tomography (NCCT). Biliary tract cancer includes intrahepatic cholangiocarcinoma, perihilar cholangiocarcinoma, distal cholangiocarcinoma, and gallbladder cancer. The reference diagnosis will be established using the predefined clinical reference standard.
Measured: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Secondary outcomes (4)
Sensitivity of the AI system for detecting biliary tract cancer
Sensitivity of the AI system for identifying patients with biliary tract cancer using non-contrast computed tomography (NCCT), based on the predefined clinical reference standard. Biliary tract cancer includes intrahepatic cholangiocarcinoma, perihilar cholangiocarcinoma, distal cholangiocarcinoma, and gallbladder cancer.
Measured: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Specificity of the AI system for identifying non-biliary-tract-cancer cases
Specificity of the AI system for identifying patients without biliary tract cancer using non-contrast computed tomography (NCCT), based on the predefined clinical reference standard.
Measured: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Positive predictive value of the AI system for biliary tract cancer
Positive predictive value of the AI system for identifying biliary tract cancer using non-contrast computed tomography (NCCT), based on the predefined clinical reference standard.
Measured: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Negative predictive value of the AI system for biliary tract cancer
Negative predictive value of the AI system for excluding biliary tract cancer using non-contrast computed tomography (NCCT), based on the predefined clinical reference standard.
Measured: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Nov 2026
- Study start1 Oct 2026 (estimated)
- Primary completion30 Nov 2026 (estimated)
- Study completion28 Feb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Biliary Tract Cancer (BTC)Studies of the same condition, open and under way.
- More trials run by Beijing Tsinghua Chang Gung 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- All eligible participants will undergo the same AI-assisted screening workflow using non-contrast computed tomography. The artificial intelligence system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. No parallel control or randomized comparison group is planned.
- Masking
- None (open label)
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Tsinghua Chang Gung Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Shuo Jin, Beijing Tsinghua Chang Gung Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07911397
- Sponsor's protocol ID
- BTC-NCCT-AI-001
- Acronym
- BTC-NCCT-AI
- Status last verified
- Oct 2026
- First submitted
- 13 Sep 2026
- Last updated
- 2 Nov 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Nov 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Clinical Validation of an Artificial Intelligence System for Biliary Tract Cancer Screening Using Non-Contrast Computed Tomography
- ClinicalTrials.gov ID
- NCT07911397
- Acronym / sponsor ID
- BTC-NCCT-AI / BTC-NCCT-AI-001
- Conditions
- Biliary Tract Cancer (BTC)
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Beijing Tsinghua Chang Gung HospitalUniversity, hospital or other
- Study start
- 1 Oct 2026 (estimated)
- Primary completion
- 30 Nov 2026 (estimated)
- Study completion
- 28 Feb 2027 (estimated)
- First posted
- 2 Nov 2026 (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.
Biliary tract cancer is a group of malignant tumors involving the intrahepatic bile ducts, extrahepatic bile ducts, and gallbladder. Early detection can be challenging because non-contrast computed tomography (NCCT), which is commonly performed in routine clinical practice, may provide limited information for identifying biliary tract cancer. This prospective study aims to clinically validate an artificial intelligence (AI) system for screening and detecting biliary tract cancer on NCCT images. The AI system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. The study will evaluate the diagnostic performance of the AI system against a predefined clinical reference standard. The primary objective is to assess the ability of the AI system to distinguish patients with biliary tract cancer from those without biliary tract cancer using NCCT. Secondary objectives include evaluating sensitivity, specificity, positive predictive value, and negative predictive value. The study is designed to evaluate the clinical performance and potential screening value of AI-assisted analysis of NCCT. Routine clinical care and clinical decision-making will not be replaced by the AI system.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- All eligible participants will undergo the same AI-assisted screening workflow using non-contrast computed tomography. The artificial intelligence system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. No parallel control or randomized comparison group is planned.
| Arm | Type | Receives |
|---|---|---|
| AI-Assisted NCCT Screening | Experimental | Diagnostic Test: AI-Assisted Biliary Tract Cancer Screening Using NCCTParticipants in this arm will undergo AI-assisted screening for biliary tract cancer using non-contrast computed tomography (NCCT). The artificial intelligence system will independently analyze eligible NCCT examinations and generate a patient-level risk score for biliary tract cancer. The AI output will be evaluated against a predefined clinical reference standard. Routine clinical interpretation and patient management will not be replaced by the AI system. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Adults aged 18 years or older.
- Undergoing abdominal non-contrast computed tomography (NCCT) as part of routine clinical evaluation or health examination.
- NCCT examination provides adequate coverage of the liver and biliary tract.
- Complete NCCT imaging data with sufficient image quality for analysis by the artificial intelligence system.
- Sufficient clinical information and/or follow-up data are available to establish the predefined clinical reference standard.
Key exclusion criteria (6 listed)
- Previous major hepatobiliary or pancreatic surgery that substantially alters the anatomy of the liver or biliary tract and may affect AI analysis.
- Recent major upper-abdominal surgery or hepatic trauma that may substantially affect evaluation of the liver or biliary tract.
- Poor image quality or severe image artifacts that preclude reliable AI analysis, including severe motion, metal, or noise artifacts.
- Inadequate scan coverage that does not include the liver and biliary tract.
- Duplicate examinations or repeated enrollment of the same participant.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted Biliary Tract Cancer Screening Using NCCTAn artificial intelligence system that analyzes non-contrast computed tomography (NCCT) examinations to screen for biliary tract cancer. The system independently processes eligible NCCT images and generates a patient-level risk score indicating the likelihood of biliary tract cancer. The AI output will be evaluated against a predefined clinical reference standard. The system is intended to support the detection of biliary tract cancer and does not replace routine clinical interpretation or independently determine patient management. | Diagnostic test | AI-Assisted NCCT Screening |
Primary outcome
Patient-level area under the receiver operating characteristic curve (AUC) of the AI system for distinguishing biliary tract cancer from non-biliary-tract-cancer cases using non-contrast computed tomography (NCCT)
Time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
The primary outcome is the patient-level area under the receiver operating characteristic curve (AUC) for the AI system in distinguishing biliary tract cancer from non-biliary-tract-cancer cases using non-contrast computed tomography (NCCT). Biliary tract cancer includes intrahepatic cholangiocarcinoma, perihilar cholangiocarcinoma, distal cholangiocarcinoma, and gallbladder cancer. The reference diagnosis will be established using the predefined clinical reference standard.
4 secondary outcomes
Sensitivity of the AI system for detecting biliary tract cancer
Time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Specificity of the AI system for identifying non-biliary-tract-cancer cases
Time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Positive predictive value of the AI system for biliary tract cancer
Time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Negative predictive value of the AI system for biliary tract cancer
Time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Nov 2026.
- Individual participant dataSharing planned: No
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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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted Biliary Tract Cancer Screening Using NCCT in people with Biliary Tract Cancer (BTC), run by Beijing Tsinghua Chang Gung Hospital at 1 site in China.
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 5 inclusion and 6 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: opening soon, as of the sponsor's last update on 2 Nov 2026. 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 China. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Jiaqi Dou, Dr. (17801066821, jiaqi_thu@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Patient-level area under the receiver operating characteristic curve (AUC) of the AI system for distinguishing biliary tract cancer from non-biliary-tract-cancer cases using non-contrast computed tomography (NCCT) (time frame: From the index NCCT examination to completion of the reference standard assessment, up to 30 days). 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 2 Nov 2026.