Prostatic NeoplasmsNCT06253065
Prospective Validation of Pathology-based Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in Prostate Cancer
An observational study of Prostatic Neoplasms and Lymphatic Metastasis, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University at 1 site in China.
Trial summary
The goal of this diagnostic test is to prospectively test the performance of pre-developed artificial intelligence (AI) diagnostic model for detecting pathological lymph node metastasis (LNM) of prostate cancer. Read more about this study
- Who is it for?
- Any age, men only
- Conditions the study is for
- Prostatic Neoplasms, Lymphatic Metastasis
- What is being tested?
- Artificial intelligence (AI)-based diagnostic model (developed)
- How many people
- 225 participants
- Where
- 1 siteChina
- Study dates
- 12 Jan 2024to 31 Dec 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
- Men only
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients with prostate cancer, (will) undergo radical prostatectomy and pelvic lymph node dissection between Jan, 2024 and Dec 2025 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University are planned to be enrolled in this prospective diagnostic test. Histopathological slides of resected pelvic lymph nodes of enrolled patients will be collected and digitised as whole-slide images (WSIs) for prospective validation of the AI model.
Who may be able to join
- Patients with prostate cancer, undergoing radical prostatectomy and pelvic lymph node dissection.
- Patients with complete clinical and pathological information.
Who cannot join
- Patients with other tumors that metastasized to pelvic lymph nodes.
- The patient refused to participate in this diagnostic test.
Trial locations and contacts
1 site in 1 country.
China1 site
Sun Yat-sen Memorial Hospital of Sun Yat-sen University
Guangzhou, Guangdong, 510120
About this study
The goal of this diagnostic test is to prospectively test the performance of pre-developed artificial intelligence (AI) diagnostic model for detecting pathological lymph node metastasis (LNM) of prostate cancer. Investigators had developed this AI model based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.
Investigators will compare the diagnostic performance (sensitivity, specificity, etc.) of the AI model and routine pathological report issued by pathologists, to see if the AI model can improve the clinical workflow of pathological evaluation of LNM in prostate cancer in the real world.
Read the detailed description
Lymph node metastasis (LNM) is a common mode of metastasis in prostate cancer, and accurate postoperative pathological lymph node staging is of great significance for further treatment and prognosis assessment. However, the current pathological evaluation of lymph nodes relies on manual examination by pathologists, which has a relatively low diagnostic efficiency and is prone to missed-diagnosis for micro metastatic lesions. Therefore, investigators developed an AI diagnostic model for detecting pathological lymph node metastasis of prostate cancer based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.
This study is a diagnostic test with no intervention measures, planning to collect pathological slides of formalin-fixed, paraffin-embedded lymph nodes resected from the enrolled patients and digitise them into whole-slide images (WSIs). The AI model will analyse the WSIs and generate pixel-level heatmaps and slide-level diagnostic results (with or without LNM). The routine pathological examination will be performed as usual. These two processes will not interfere with each other. And if there are inconsistency in slide-level classification between AI and routine pathological examination, investigators would convene senior pathologists for discussion to make the final decision (immunohistochemistry would be performed if necessary). The final result will be presented to the patient in the form of a pathological report.
- Conditions
- Prostatic Neoplasms, Lymphatic Metastasis
- Being tested
- Artificial intelligence (AI)-based diagnostic model (developed)
- Keywords
- artificial intelligence, lymph node metastasis, prostate cancer, whole slide image
- Medical subject headings
- Prostatic Neoplasms, Lymphatic Metastasis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence (AI)-based diagnostic model (developed)Diagnostic test
Collect pathological slides of resected lymph nodes of the enrolled patients. Digitise these slides into whole-slide images (WSIs). Analyze the WSIs using the AI model to generate diagnostic results (with or without lymphatic metastasis). No intervention to patients would be performed in this diagnostic test study.
| Study group | Role | What they receive |
|---|---|---|
| Patients undergoing PLND | Patients (will) undergo radical prostatectomy and pelvic lymph node dissection Receives: Diagnostic Test: Artificial intelligence (AI)-based diagnostic model (developed) |
What is being measured
The primary outcome is the main question the study is designed to answer.
sensitivity
the number of correctly diagnosed positive slides (with lymphatic metastasis), to be divided by the number of positive slides in total
Measured: For each enrolled patient, the diagnosis results of AI model will be obtained in not long after pelvic lymph node dissection, and the sensitivity of the AI model will be evaluated through study completion, an average of 2 year.
Secondary outcomes (1)
specificity
the number of correctly diagnosed negative slides (without lymphatic metastasis), to be divided by the number of negative slides in total
Measured: For each enrolled patient, the diagnosis results of AI model will be obtained in not long after pelvic lymph node dissection, and the specificity of the AI model will be evaluated through study completion, an average of 2 year.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted12 Feb 2024
- Study start12 Jan 2024
- Primary completion31 Dec 2025
- Study completion31 Dec 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Prostatic NeoplasmsStudies 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
- Cohort
- Time perspective
- Prospective
- Enrolment
- 225 participants (actual)
Sponsor and investigators
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Tianxin Lin, Ph.D, Study chair, Department of Urology of Sun Yat-sen Memorial Hospital of Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06253065
- Sponsor's protocol ID
- SYSKY-2023-1281
- Status last verified
- Feb 2026
- First submitted
- 24 Jan 2024
- Last updated
- 11 Feb 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: To protect patient privacy, pathological slide images and other patient-related data are not publicly accessible.
Study at a glance
From the registry record, last updated by the sponsor on 11 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Validation of Pathology-based Artificial Intelligence Diagnostic Model for Lymph Node Metastasis in Prostate Cancer
- ClinicalTrials.gov ID
- NCT06253065
- Acronym / sponsor ID
- SYSKY-2023-1281
- Conditions
- Prostatic Neoplasms, Lymphatic Metastasis
- Keywords
- artificial intelligence, lymph node metastasis, prostate cancer, whole slide image
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 225 participants (actual)
- Lead sponsor
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityUniversity, hospital or other
- Study start
- 12 Jan 2024 (actual)
- Primary completion
- 31 Dec 2025 (actual)
- Study completion
- 31 Dec 2025 (actual)
- First posted
- 12 Feb 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.
The goal of this diagnostic test is to prospectively test the performance of pre-developed artificial intelligence (AI) diagnostic model for detecting pathological lymph node metastasis (LNM) of prostate cancer. Investigators had developed this AI model based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.
Investigators will compare the diagnostic performance (sensitivity, specificity, etc.) of the AI model and routine pathological report issued by pathologists, to see if the AI model can improve the clinical workflow of pathological evaluation of LNM in prostate cancer in the real world.
Detailed description
Lymph node metastasis (LNM) is a common mode of metastasis in prostate cancer, and accurate postoperative pathological lymph node staging is of great significance for further treatment and prognosis assessment. However, the current pathological evaluation of lymph nodes relies on manual examination by pathologists, which has a relatively low diagnostic efficiency and is prone to missed-diagnosis for micro metastatic lesions. Therefore, investigators developed an AI diagnostic model for detecting pathological lymph node metastasis of prostate cancer based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.
This study is a diagnostic test with no intervention measures, planning to collect pathological slides of formalin-fixed, paraffin-embedded lymph nodes resected from the enrolled patients and digitise them into whole-slide images (WSIs). The AI model will analyse the WSIs and generate pixel-level heatmaps and slide-level diagnostic results (with or without LNM). The routine pathological examination will be performed as usual. These two processes will not interfere with each other. And if there are inconsistency in slide-level classification between AI and routine pathological examination, investigators would convene senior pathologists for discussion to make the final decision (immunohistochemistry would be performed if necessary). The final result will be presented to the patient in the form of a pathological report.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients undergoing PLND | – | Diagnostic Test: Artificial intelligence (AI)-based diagnostic model (developed)Patients (will) undergo radical prostatectomy and pelvic lymph node dissection |
Who may qualify
- Sex
- Male only
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients with prostate cancer, (will) undergo radical prostatectomy and pelvic lymph node dissection between Jan, 2024 and Dec 2025 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University are planned to be enrolled in this prospective diagnostic test. Histopathological slides of resected pelvic lymph nodes of enrolled patients will be collected and digitised as whole-slide images (WSIs) for prospective validation of the AI model.
Key inclusion criteria (2 listed)
- Patients with prostate cancer, undergoing radical prostatectomy and pelvic lymph node dissection.
- Patients with complete clinical and pathological information.
Key exclusion criteria (2 listed)
- Patients with other tumors that metastasized to pelvic lymph nodes.
- The patient refused to participate in this diagnostic test.
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 (AI)-based diagnostic model (developed)Collect pathological slides of resected lymph nodes of the enrolled patients. Digitise these slides into whole-slide images (WSIs). Analyze the WSIs using the AI model to generate diagnostic results (with or without lymphatic metastasis). No intervention to patients would be performed in this diagnostic test study. | Diagnostic test | Patients undergoing PLND |
Primary outcome
sensitivity
Time frame: For each enrolled patient, the diagnosis results of AI model will be obtained in not long after pelvic lymph node dissection, and the sensitivity of the AI model will be evaluated through study completion, an average of 2 year.
the number of correctly diagnosed positive slides (with lymphatic metastasis), to be divided by the number of positive slides in total
1 secondary outcome
specificity
Time frame: For each enrolled patient, the diagnosis results of AI model will be obtained in not long after pelvic lymph node dissection, and the specificity of the AI model will be evaluated through study completion, an average of 2 year.
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 11 Feb 2026.
- Individual participant dataSharing planned: No. To protect patient privacy, pathological slide images and other patient-related data are not publicly accessible.
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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.
Tianxin Lin, Ph.D study chair
Department of Urology of Sun Yat-sen Memorial Hospital of Sun Yat-sen 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 Prostatic Neoplasms and Lymphatic Metastasis, run by Sun Yat-Sen Memorial Hospital of Sun Yat-Sen 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 2 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 11 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 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?
sensitivity (time frame: For each enrolled patient, the diagnosis results of AI model will be obtained in not long after pelvic lymph node dissection, and the sensitivity of the AI model will be evaluated through study completion, an average of 2 year.). 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 11 Feb 2026.