Artificial IntelligenceNCT03759756
Artificial Intelligence for Early Diagnosis of Esophageal Squamous Cell Carcinoma
An observational study of Artificial Intelligence and Optical Enhancement Endoscopy, run by Shandong University at 1 site in China.
Trial summary
Esophageal squamous cell carcinoma is one of the most common malignant tumor of upper digestive tract. However, the detection rate and diagnosis accuracy of early esophageal squamous cell cancer is low. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Artificial Intelligence, Optical Enhancement Endoscopy, Magnifying Endoscopy
- What is being tested?
- AI presentation and no AI presentation
- How many people
- 119 participants
- Where
- 1 siteChina
- Study dates
- 1 Dec 2018to 1 Apr 2020
- 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 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Consecutive patients who came to Qilu Hospital of Shandong University and received optical magnifying OE endoscopy examination
Who may be able to join
- high risk patients for esophageal cancer aged 18 years or older;
- Histologically verified early esophageal squamous cell cancer.
Who cannot join
- patients whose images of esophagus not suitable for the training, validation and testing the computer-assist diagnosis tool.
Trial locations and contacts
1 site in 1 country.
China1 site
Department of Gastroenterology, Qilu Hospital, Shandong University
Jinan, Shandong, 250012
About this study
Official title: Application of Artificial Intelligence for Early Diagnosis of Esophageal Squamous Cell Carcinoma During Optical Enhancement Magnifying Endoscopy
Esophageal squamous cell carcinoma is one of the most common malignant tumor of upper digestive tract. However, the detection rate and diagnosis accuracy of early esophageal squamous cell cancer is low. The aim of this study is to develop a computer-assisted diagnosis tool combining with optical magnifying endoscopy for early detection and accurate diagnosis of it.
- Being tested
- AI presentation, no AI presentation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI presentationOther
AI presentation means the automatic diagnosis information of AI and AI presentation means it is visible in the group.
no AI presentationOther
AI presentation means the automatic diagnosis information of AI and no AI presentation means it is invisible in the group.
| Study group | Role | What they receive |
|---|---|---|
| AI visible group | the endoscopic novices analyzing the images can see the automatic diagnosis of AI during the process Receives: Other: AI presentation | |
| AI invisible group | the endoscopic novice analyzing the images can not see the automatic diagnosis of AI during the process Receives: Other: no AI presentation |
What is being measured
The primary outcome is the main question the study is designed to answer.
the diagnosis efficiency of the AI model
the sensitivity, specificity and accuracy of the AI model
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted30 Nov 2018
- Study start1 Dec 2018
- Primary completion1 Mar 2020
- Study completion1 Apr 2020
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Artificial IntelligenceStudies of the same condition, open and under way.
- 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 119 participants (actual)
Sponsor and investigators
- Lead sponsor
- Shandong University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yanqing Li, Shandong University
- Investigators
- Yanqing Li, PHD, Principal investigator, Qilu Hospital of Shandong University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03759756
- Sponsor's protocol ID
- 2018SDU-QILU-2
- Status last verified
- Apr 2020
- First submitted
- 28 Nov 2018
- Last updated
- 28 Apr 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 28 Apr 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Application of Artificial Intelligence for Early Diagnosis of Esophageal Squamous Cell Carcinoma During Optical Enhancement Magnifying Endoscopy
- ClinicalTrials.gov ID
- NCT03759756
- Acronym / sponsor ID
- 2018SDU-QILU-2
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 119 participants (actual)
- Lead sponsor
- Shandong UniversityUniversity, hospital or other
- Study start
- 1 Dec 2018 (actual)
- Primary completion
- 1 Mar 2020 (actual)
- Study completion
- 1 Apr 2020 (actual)
- First posted
- 30 Nov 2018 (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.
Esophageal squamous cell carcinoma is one of the most common malignant tumor of upper digestive tract. However, the detection rate and diagnosis accuracy of early esophageal squamous cell cancer is low. The aim of this study is to develop a computer-assisted diagnosis tool combining with optical magnifying endoscopy for early detection and accurate diagnosis of it.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI visible group | – | Other: AI presentationthe endoscopic novices analyzing the images can see the automatic diagnosis of AI during the process |
| AI invisible group | – | Other: no AI presentationthe endoscopic novice analyzing the images can not see the automatic diagnosis of AI during the process |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Consecutive patients who came to Qilu Hospital of Shandong University and received optical magnifying OE endoscopy examination
Key inclusion criteria (2 listed)
- high risk patients for esophageal cancer aged 18 years or older;
- Histologically verified early esophageal squamous cell cancer.
Key exclusion criteria (1 listed)
- patients whose images of esophagus not suitable for the training, validation and testing the computer-assist diagnosis tool.
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 presentationAI presentation means the automatic diagnosis information of AI and AI presentation means it is visible in the group. | Other | AI visible group |
| no AI presentationAI presentation means the automatic diagnosis information of AI and no AI presentation means it is invisible in the group. | Other | AI invisible group |
Primary outcome
the diagnosis efficiency of the AI model
Time frame: 12 months
the sensitivity, specificity and accuracy of the AI model
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 28 Apr 2020.
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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. This study is not recruiting at the moment.
Yanqing Li, PHD principal investigator
Qilu Hospital of Shandong University
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 Artificial Intelligence and Optical Enhancement Endoscopy, run by Shandong University 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 2 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 28 Apr 2020. 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?
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?
the diagnosis efficiency of the AI model (time frame: 12 months). 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 28 Apr 2020.