Pathology Foundation ModelNCT07291362
AI-Assisted Pathologist Performance Improvement: A Multicenter, Prospective, Randomized Controlled Trial
A study testing AI pathology model in people with Pathology Foundation Model, run by Nanfang Hospital, Southern Medical University at 2 sites in China.
Trial summary
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pathology Foundation Model
- What is being tested?
- AI pathology model
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 1,000 participants
- Where
- 2 sitesChina
- Study dates
- 1 Nov 2025to Nov 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
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Sex: ≥ 18 years of age;
- Patients undergoing gastric mucosal biopsy or gastric cancer surgical resection, with available digital pathology images and clinical information.
Who cannot join
- 1.Missing data or data of insufficient quality for analysis
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
China2 sites
Nanfang Hospital, Southern Medical University
Guangzhou, Guangdong, 510515
The First Affiliated Hospital of Zhengzhou University
Zhengzhou, Henan
About this study
Official title: Artificial Intelligence Model-Assisted Improvement of Pathologists' Performance in Clinical Diagnostic Tasks: A Multicenter, Prospective, Randomized Controlled Trial
The investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. The study will focus on comparing AI-assisted platform interpretation with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., comparison of time to diagnosis), quality of diagnostic reports, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI models. The investigators will also assess superiority for less-experienced (junior) pathologists and noninferiority for more-experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support the standardized deployment, quality control, and broader application of pathology AI in the gastric cancer care pathway.
- Conditions
- Pathology Foundation Model
- Being tested
- AI pathology model, Control
- Keywords
- Randomized Controlled Trial
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI pathology modelOther
Doctors in this group are required to use the AI pathology model to assist their diagnoses. The AI pathology model will provide a predicted result for each case.
ControlOther
Pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence.
| Study group | Role | What they receive |
|---|---|---|
| AI-assisted group | Experimental | Doctors in this group are required to use the AI pathology diagnostic model to assist their diagnoses. The AI pathology model will provide a predicted result for each case. Receives: Other: AI pathology model |
| Independent Diagnosis Group (Control Group) | Placebo comparator | In this group, pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence. Receives: Other: Control |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under ROC curve (AUC)
Area under the curve
Measured: Assessments will be conducted within one week after the physicians' diagnoses.
Secondary outcomes (4)
Diagnostic time per case
Time required for the pathologist to complete the diagnosis of each case in the AI-assisted diagnosis group compared with the independent diagnosis group. Diagnostic time is defined as the duration (in minutes/seconds) from initiating case review to finalizing and submitting the diagnostic report in the study system
Measured: Measured immediately after the physician's diagnosis.
Diagnostic report quality score
Quality score of pathology diagnostic reports in the AI-assisted diagnosis group compared with the independent diagnosis group. Report quality will be evaluated by an independent panel of expert pathologists using a predefined scoring rubric (e.g., 0-100 scale), considering diagnostic accuracy, completeness, clarity, and structure of the report. Higher scores indicate better report quality.
Measured: Within 1 week after the initial diagnosis for each case.
Pathologists' diagnostic confidence
Self-reported diagnostic confidence of pathologists for each case in the AI-assisted diagnosis group compared with the independent diagnosis group. Diagnostic confidence will be rated by the reporting pathologist on a [5]-point Likert scale (e.g., 1 = very uncertain to 5 = very confident) immediately after completing the diagnosis. Higher scores indicate greater diagnostic confidence.
Measured: At the time of diagnosis for each case.
Pathologists' satisfaction with the AI pathology model
Overall satisfaction of pathologists with the AI pathology diagnostic model in terms of usability and perceived effectiveness. Satisfaction will be assessed using a structured questionnaire comprising Likert-scale items that evaluate ease of use, integration into workflow, clarity of AI outputs, perceived impact on diagnostic efficiency, and perceived impact on diagnostic accuracy and confidence. Higher scores indicate higher satisfaction, better usability, and greater perceived effectiveness.
Measured: Assessed once at the end of the AI-assisted reading period for each pathologist.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Dec 2025
- Study start1 Nov 2025
- Primary completionJun 2027 (estimated)
- Study completionNov 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pathology Foundation ModelStudies 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 1,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Nanfang Hospital, Southern Medical University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Li Liang, Study director, Nanfang Hospital, Southern Medical University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07291362
- Sponsor's protocol ID
- NFEC-2025-653
- Status last verified
- Feb 2026
- First submitted
- 5 Dec 2025
- Last updated
- 10 Feb 2026
- 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 10 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence Model-Assisted Improvement of Pathologists' Performance in Clinical Diagnostic Tasks: A Multicenter, Prospective, Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07291362
- Acronym / sponsor ID
- NFEC-2025-653
- Conditions
- Pathology Foundation Model
- Keywords
- Randomized Controlled Trial
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 1,000 participants (estimated)
- Lead sponsor
- Nanfang Hospital, Southern Medical UniversityUniversity, hospital or other
- Study start
- 1 Nov 2025 (actual)
- Primary completion
- Jun 2027 (estimated)
- Study completion
- Nov 2027 (estimated)
- First posted
- 18 Dec 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 investigators plan to conduct a multicenter, prospective, randomized controlled trial to systematically evaluate the added value of pathology-based AI models in the gastric cancer diagnostic workflow. The study will focus on comparing AI-assisted platform interpretation with conventional independent slide reading in terms of diagnostic accuracy (e.g., AUC), reading efficiency (e.g., comparison of time to diagnosis), quality of diagnostic reports, diagnostic confidence (Likert scale), and pathologists' satisfaction with the AI models. The investigators will also assess superiority for less-experienced (junior) pathologists and noninferiority for more-experienced (senior) pathologists. Successful completion of this project will provide high-level prospective evidence to support the standardized deployment, quality control, and broader application of pathology AI in the gastric cancer care pathway.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-assisted group | Experimental | Other: AI pathology modelDoctors in this group are required to use the AI pathology diagnostic model to assist their diagnoses. The AI pathology model will provide a predicted result for each case. |
| Independent Diagnosis Group (Control Group) | Placebo comparator | Other: ControlIn this group, pathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Sex: ≥ 18 years of age;
- Patients undergoing gastric mucosal biopsy or gastric cancer surgical resection, with available digital pathology images and clinical information.
Key exclusion criteria (1 listed)
- 1.Missing data or data of insufficient quality for analysis
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 pathology modelDoctors in this group are required to use the AI pathology model to assist their diagnoses. The AI pathology model will provide a predicted result for each case. | Other | AI-assisted group |
| ControlPathologists will independently diagnose each case based on their own clinical experience, and will record both their time to diagnosis and their diagnostic confidence. | Other | Independent Diagnosis Group (Control Group) |
Primary outcome
Area under ROC curve (AUC)
Time frame: Assessments will be conducted within one week after the physicians' diagnoses.
Area under the curve
4 secondary outcomes
Diagnostic time per case
Time frame: Measured immediately after the physician's diagnosis.
Diagnostic report quality score
Time frame: Within 1 week after the initial diagnosis for each case.
Pathologists' diagnostic confidence
Time frame: At the time of diagnosis for each case.
Pathologists' satisfaction with the AI pathology model
Time frame: Assessed once at the end of the AI-assisted reading period for each pathologist.
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 10 Feb 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.
Li Liang study director
Nanfang Hospital, Southern Medical University
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI pathology model in people with Pathology Foundation Model, run by Nanfang Hospital, Southern Medical University at 2 sites 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: enrolling by invitation, as of the sponsor's last update on 10 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites 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. Some participants in this study may receive a placebo. 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?
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?
Area under ROC curve (AUC) (time frame: Assessments will be conducted within one week after the physicians' diagnoses.). 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 10 Feb 2026.