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AI reads biopsies to predict cancer spread

NCT ID NCT07660276

Knowledge-focused Sponsor: Xiangya Hospital of Central South University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only This study
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 24, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study is testing whether artificial intelligence can predict if prostate cancer has spread to lymph nodes or other parts of the body by analyzing biopsy tissue images. Researchers will use samples from 3,000 men to develop and validate the AI model. The goal is to help doctors make better decisions about treatment and surgery, but this is an observational study and does not test any new treatment.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this AI model could help doctors better predict if prostate cancer has spread, leading to more personalized treatment decisions.
What could go wrong
This is an observational study, not a treatment trial. The AI model may not be accurate enough for real-world use, and results may not apply to all patients.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 3,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Jan 2026

Expected to finish

Aug 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

The study population consists of patients with pathologically confirmed prostate cancer from multiple participating hospitals led by Xiangya Hospital. Eligible patients underwent prostate biopsy with available biopsy pathology specimens and relevant clinical and imaging data for assessment of lymph node and distant metastasis. Retrospective clinical and pathological data will be collected for development and validation of an artificial intelligence-based metastasis prediction model.

Ages

18 to 90 years

Sex

Male participants only

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: \- Male patients aged between 18 and 90 years; Patients who underwent prostate biopsy due to elevated prostate-specific antigen (PSA), abnormal digital rectal examination (DRE), or abnormal imaging findings, were pathologically diagnosed with prostate cancer, and had available prostate biopsy pathology specimens; Patients who underwent radical prostatectomy with extended pelvic lymph node dissection (ePLND) or pelvic lymph node dissection (PLND), with definitive pathological information regarding lymph node metastasis; Patients who underwent PSMA PET/CT, MRI, bone scintigraphy, or prostate MRI capable of identifying regional lymph node metastasis or distant metastasis; Adequate cardiac, pulmonary, hepatic, and renal function; Eastern Cooperative Oncology Group (ECOG) performance status of 0-1; Expected survival time greater than 1 year; Written informed consent signed by the patient or legally authorized representative. Exclusion Criteria: \- History of other malignancies; Severe dysfunction of major organs, including cardiac, pulmonary, hepatic, or renal insufficiency, or an expected survival time of less than 1 year; Prostate biopsy pathology specimens with inadequate whole-slide image scanning quality or failure of quality control assessment; Patients with prostate cancer diagnosed from transurethral resection specimens.

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Conditions

The condition(s) this trial relates to.

metastatic prostate carcinoma prostate cancer

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Prostate cancer metastatic

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    The full official record for this study. This one lists no contact details, but it is the first place any would appear.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Xiangya Hospital, Central South University

    Changsha, Hunan, 410008, China

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