Colorectal NeoplasmsNCT06335654
Real-time Artificial Intelligence-based Endocytoscopic Diagnosis of Colorectal Neoplasms
An observational study of Colorectal Neoplasms, run by The First Hospital of Jilin University at 1 site in China.
Trial summary
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide. Colonoscopy is considered the preferred method of screening for colorectal cancer, and resection of colorectal lesions can significantly reduce the incidence and mortality of colorectal cancer. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Colorectal Neoplasms
- What is being tested?
- artificial intelligence system
- How many people
- 680 participants
- Where
- 1 siteChina
- Study dates
- 1 Apr 2024to 19 Dec 2024
- 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: The investigators analyzed only endoscopically or surgically resected colorectal lesions that had been observed with EC-NBI and EC-stained by endoscopists and artificial intelligence system before treatment that were ultimately performed histopathologic examination.
Who may be able to join
- Those patients who, during the endoscopic examination, discovered at least one colorectal lesion and received treatment and obtained a pathological diagnosis
- consent obtained for the study
Who cannot join
- non-epithelial tumors
- a history of inflammatory bowel disease
- chemotherapy or radiation therapy for colorectal cancer
- lesions without clear EC images
- specific pathological types
- familial adenomatous polyposis
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Real-time Artificial Intelligence-based Endocytoscopic Diagnosis of Colorectal Neoplasms: a Single Center, Prospective Clinical Study
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide. Colonoscopy is considered the preferred method of screening for colorectal cancer, and resection of colorectal lesions can significantly reduce the incidence and mortality of colorectal cancer. In order to improve the qualitative and quantitative diagnosis of colorectal lesions, many endoscopic techniques, such as image-enhanced endoscopy (IEE), including narrowband imaging (NBI), magnifying endoscopy, pigment endoscopy, confocal laser endoscopy, and endocytoscopy (EC) are applied clinically. However, with the increasing number of endoscopic resection, the costs associated with the pathological diagnosis of endoscopic resection and resection specimens increase year by year. In clinical practice, some non-neoplastic colorectal lesions may not require resection, so it is important to distinguish neoplastic from non-neoplastic during colonoscopy. The application of EC is intended to achieve the purpose of real-time histopathological endoscopic diagnosis without biopsy. Several studies have shown that EC is effective in identifying the nature of colorectal lesions and judging the depth of invasion in CRC. Based on the endoscopic diagnosis, the endoscopist can determine the treatment plan for the colorectal lesions. The latest EC is an integrated endoscope with a contact light microscopy system with a maximum magnification of 520 x. EC can demonstrate the atypical of gland structure and cells after staining and display the super-amplified surface microvessels of the lesion under the EC-NBI mode. However, the judgment of endocytoscopic images needs a lot of experience to improve the diagnostic accuracy. Moreover, endoscopists have certain subjective judgments and errors in endocytoscopic diagnosis. There is an artificial intelligence system which has been developed to identify colorectal neoplasms. However, there is still a lack of prospective clinical verification based on Chinese population. In the study, the investigators performed a prospective clinical study to determine the diagnostic accuracy of artificial intelligence system.
Read the detailed description
Colonoscopy is currently the gold standard of screening for CRC. The endocytoscopy, due to its high magnification function, can achieve the purpose of optical biopsy. However, endoscopic doctors have certain difficulties in diagnosing with the endocytoscopy, especially for novice endoscopic doctors, whose diagnostic accuracy is often low.
Therefore, EndoBRAIN, as an artificial intelligence system for assisting in the diagnosis of the endocytoscopy, has the advantage of rapid diagnosis. In the EC-NBI mode, it predicts as "Non-neoplastic" or "Neoplastic", and in the EC-stained mode, its prediction result is "Non-neoplastic", "Adenoma" or "Invasive cancer".
However, currently this artificial intelligence-assisted diagnostic system has not been applied in the Chinese population. The investigators plan to conduct a prospective clinical trial to validate the accuracy of EndoBRAIN for prediction of colorectal lesions histology in real-time endocytoscopy. This study will prospectively collect the lesions that meet the inclusion and exclusion criteria. After the endoscopic doctors make the diagnosis through endoscopic optics and EndoBRAIN, and then undergo endoscopic resection or surgical resection followed by pathological diagnosis, they will compare the doctor's diagnosis, the artificial intelligence diagnosis results with the gold standard pathological results, and summarize the diagnostic accuracy of this artificial intelligence-assisted diagnostic system for the colorectal lesions.
- Conditions
- Colorectal Neoplasms
- Being tested
- artificial intelligence system
- Keywords
- endocytoscopy, artificial intelligence
- Medical subject headings
- Colorectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
artificial intelligence systemDiagnostic test
Also called endocytoscopy
The colorectal lesions had been observed with EC-NBI and EC-stained by endoscopists before treatment that were ultimately performed histopathologic examination. The endocytoscopies (CF-H290ECI, Olympus, Tokyo, Japan) have a maximum magnification of ×520, focusing depth, 35 μm; field of view, 570 × 500μm. During EC-NBI , the endoscopist pushed the button of the endoscope to switch from white-light imaging to NBI and observed the lesion with full magnification. After endocytoscopic observation, the artificial intelligence system will be open and display the predictive result. Finally, the endoscopist performed EC-stained mode diagnosis after staining the lesion surface with 1.0% methylene blue. After endocytoscopic observation, the artificial intelligence system will be open again and display the predictive result.
| Study group | Role | What they receive |
|---|---|---|
| Patients with one or more colorectal lesions detected | During endocytoscopy, the Clinician inspect for the presence of colorectal lesions as per routine clinical practice with the EndoBRAIN turned off. When a colorectal lesion is encountered, the Clinician will make a prediction on the histology based on routine clinical practice. Following this, the EndoBRAIN function will be switched on and the Clinician will take note of the EndoBRAIN prediction for the every image of colorectal lesion.
In addition, other colorectal lesion features such as the size, location and shape will be recorded, which is similar to what is performed in routine clinical practice. The colorectal lesion will be resected and sent for pathological examination, which will form the "gold standard" for the diagnosis of colorectal lesion histology. Receives: Diagnostic Test: artificial intelligence system |
What is being measured
The primary outcome is the main question the study is designed to answer.
To evaluate the diagnostic performance and high confidence diagnosis rate of EndoBRAIN in diagnosing neoplastic lesions in a clinical setting.EndoBRAIN in diagnosing neoplastic lesions in a clinical setting.
The sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and high confidence diagnosis rate will be calculated for comparison with final histology as the gold standard for diagnosis
Measured: 8 months
Secondary outcomes (4)
To evaluate the performance and high-confidence diagnostic rate of EndoBRAIN in diagnosing adenomas of rectosigmoid colon ≤5 mm;
The sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and high confidence diagnosis rate will be calculated for comparison with final histology as the gold standard for diagnosis
Measured: 8 months
To evaluate the performance and high-confidence diagnostic rate of Endobrain under EC-stained mode in the diagnosis of invasive cancer;
The sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and high confidence diagnosis rate will be calculated for comparison with final histology as the gold standard for diagnosis
Measured: 8 months
To evaluate the Influencing factors on the diagnosis of colorectal lesions by EndoBRAIN.
The diagnostic performance of EndoBRAIN in different Influencing factors will be calculated for comparison with final histology as the gold standard for diagnosis
Measured: 8 months
To compare the diagnostic performance of diagnosing the histology of colorectal lesions by EndoBRAIN, by endoscopists, and by endoscopists combined with EndoBRAIN;
The diagnostic performance of diagnosing the histology of colorectal lesions by EndoBRAIN, by endoscopists, and by endoscopists combined with EndoBRAIN will be calculated for comparison with final histology as the gold standard for diagnosis
Measured: 8 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Mar 2024
- Study start1 Apr 2024
- Primary completion19 Dec 2024
- Study completion19 Dec 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal NeoplasmsStudies of the same condition, open and under way.
- More trials run by The First Hospital of Jilin UniversityThe 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
- Case only
- Time perspective
- Prospective
- Enrolment
- 680 participants (actual)
Sponsor and investigators
- Lead sponsor
- The First Hospital of Jilin University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Hong Xu, The First Hospital of Jilin University
- Investigators
- Hong Xu, PHD, Principal investigator, The First Hospital of Jilin University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06335654
- Sponsor's protocol ID
- 24K056-001
- Status last verified
- Dec 2025
- First submitted
- 22 Mar 2024
- Last updated
- 9 Dec 2025
- Results posted
- 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 9 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Real-time Artificial Intelligence-based Endocytoscopic Diagnosis of Colorectal Neoplasms: a Single Center, Prospective Clinical Study
- ClinicalTrials.gov ID
- NCT06335654
- Acronym / sponsor ID
- 24K056-001
- Conditions
- Colorectal Neoplasms
- Keywords
- endocytoscopy, artificial intelligence
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 680 participants (actual)
- Lead sponsor
- The First Hospital of Jilin UniversityUniversity, hospital or other
- Study start
- 1 Apr 2024 (actual)
- Primary completion
- 19 Dec 2024 (actual)
- Study completion
- 19 Dec 2024 (actual)
- First posted
- 28 Mar 2024 (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.
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death worldwide. Colonoscopy is considered the preferred method of screening for colorectal cancer, and resection of colorectal lesions can significantly reduce the incidence and mortality of colorectal cancer. In order to improve the qualitative and quantitative diagnosis of colorectal lesions, many endoscopic techniques, such as image-enhanced endoscopy (IEE), including narrowband imaging (NBI), magnifying endoscopy, pigment endoscopy, confocal laser endoscopy, and endocytoscopy (EC) are applied clinically. However, with the increasing number of endoscopic resection, the costs associated with the pathological diagnosis of endoscopic resection and resection specimens increase year by year. In clinical practice, some non-neoplastic colorectal lesions may not require resection, so it is important to distinguish neoplastic from non-neoplastic during colonoscopy. The application of EC is intended to achieve the purpose of real-time histopathological endoscopic diagnosis without biopsy. Several studies have shown that EC is effective in identifying the nature of colorectal lesions and judging the depth of invasion in CRC. Based on the endoscopic diagnosis, the endoscopist can determine the treatment plan for the colorectal lesions. The latest EC is an integrated endoscope with a contact light microscopy system with a maximum magnification of 520 x. EC can demonstrate the atypical of gland structure and cells after staining and display the super-amplified surface microvessels of the lesion under the EC-NBI mode. However, the judgment of endocytoscopic images needs a lot of experience to improve the diagnostic accuracy. Moreover, endoscopists have certain subjective judgments and errors in endocytoscopic diagnosis. There is an artificial intelligence system which has been developed to identify colorectal neoplasms. However, there is still a lack of prospective clinical verification based on Chinese population. In the study, the investigators performed a prospective clinical study to determine the diagnostic accuracy of artificial intelligence system.
Detailed description
Colonoscopy is currently the gold standard of screening for CRC. The endocytoscopy, due to its high magnification function, can achieve the purpose of optical biopsy. However, endoscopic doctors have certain difficulties in diagnosing with the endocytoscopy, especially for novice endoscopic doctors, whose diagnostic accuracy is often low.
Therefore, EndoBRAIN, as an artificial intelligence system for assisting in the diagnosis of the endocytoscopy, has the advantage of rapid diagnosis. In the EC-NBI mode, it predicts as "Non-neoplastic" or "Neoplastic", and in the EC-stained mode, its prediction result is "Non-neoplastic", "Adenoma" or "Invasive cancer".
However, currently this artificial intelligence-assisted diagnostic system has not been applied in the Chinese population. The investigators plan to conduct a prospective clinical trial to validate the accuracy of EndoBRAIN for prediction of colorectal lesions histology in real-time endocytoscopy. This study will prospectively collect the lesions that meet the inclusion and exclusion criteria. After the endoscopic doctors make the diagnosis through endoscopic optics and EndoBRAIN, and then undergo endoscopic resection or surgical resection followed by pathological diagnosis, they will compare the doctor's diagnosis, the artificial intelligence diagnosis results with the gold standard pathological results, and summarize the diagnostic accuracy of this artificial intelligence-assisted diagnostic system for the colorectal lesions.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients with one or more colorectal lesions detected | – | Diagnostic Test: artificial intelligence systemDuring endocytoscopy, the Clinician inspect for the presence of colorectal lesions as per routine clinical practice with the EndoBRAIN turned off. When a colorectal lesion is encountered, the Clinician will make a prediction on the histology based on routine clinical practice. Following this, the EndoBRAIN function will be switched on and the Clinician will take note of the EndoBRAIN prediction for the every image of colorectal lesion. In addition, other colorectal lesion features such as the size, location and shape will be recorded, which is similar to what is performed in routine clinical practice. The colorectal lesion will be resected and sent for pathological examination, which will form the "gold standard" for the diagnosis of colorectal lesion histology. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- The investigators analyzed only endoscopically or surgically resected colorectal lesions that had been observed with EC-NBI and EC-stained by endoscopists and artificial intelligence system before treatment that were ultimately performed histopathologic examination.
Key inclusion criteria (2 listed)
- Those patients who, during the endoscopic examination, discovered at least one colorectal lesion and received treatment and obtained a pathological diagnosis
- consent obtained for the study
Key exclusion criteria (6 listed)
- non-epithelial tumors
- a history of inflammatory bowel disease
- chemotherapy or radiation therapy for colorectal cancer
- lesions without clear EC images
- specific pathological types
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 |
|---|---|---|
| artificial intelligence systemAlso: endocytoscopyThe colorectal lesions had been observed with EC-NBI and EC-stained by endoscopists before treatment that were ultimately performed histopathologic examination. The endocytoscopies (CF-H290ECI, Olympus, Tokyo, Japan) have a maximum magnification of ×520, focusing depth, 35 μm; field of view, 570 × 500μm. During EC-NBI , the endoscopist pushed the button of the endoscope to switch from white-light imaging to NBI and observed the lesion with full magnification. After endocytoscopic observation, the artificial intelligence system will be open and display the predictive result. Finally, the endoscopist performed EC-stained mode diagnosis after staining the lesion surface with 1.0% methylene blue. After endocytoscopic observation, the artificial intelligence system will be open again and display the predictive result. | Diagnostic test | Patients with one or more colorectal lesions detected |
Primary outcome
To evaluate the diagnostic performance and high confidence diagnosis rate of EndoBRAIN in diagnosing neoplastic lesions in a clinical setting.EndoBRAIN in diagnosing neoplastic lesions in a clinical setting.
Time frame: 8 months
The sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and high confidence diagnosis rate will be calculated for comparison with final histology as the gold standard for diagnosis
4 secondary outcomes
To evaluate the performance and high-confidence diagnostic rate of EndoBRAIN in diagnosing adenomas of rectosigmoid colon ≤5 mm;
Time frame: 8 months
To evaluate the performance and high-confidence diagnostic rate of Endobrain under EC-stained mode in the diagnosis of invasive cancer;
Time frame: 8 months
To evaluate the Influencing factors on the diagnosis of colorectal lesions by EndoBRAIN.
Time frame: 8 months
To compare the diagnostic performance of diagnosing the histology of colorectal lesions by EndoBRAIN, by endoscopists, and by endoscopists combined with EndoBRAIN;
Time frame: 8 months
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 9 Dec 2025.
- 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. This study is not recruiting at the moment.
Hong Xu, PHD principal investigator
The First Hospital of Jilin 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 Colorectal Neoplasms, run by The First Hospital of Jilin 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 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: finished, as of the sponsor's last update on 9 Dec 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 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?
To evaluate the diagnostic performance and high confidence diagnosis rate of EndoBRAIN in diagnosing neoplastic lesions in a clinical setting.EndoBRAIN in diagnosing neoplastic lesions in a clinical setting. (time frame: 8 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 9 Dec 2025.