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AI reads tumor images to forecast bladder cancer treatment response

NCT ID NCT05825950

Knowledge-focused Sponsor: University of Texas Southwestern Medical Center Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now This study
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Aug 24, 2026 · Last updated Aug 25, 2026 · Updated 1 time

Summary

This study is testing whether an artificial intelligence (AI) tool can analyze digital images of bladder tumor tissue to predict how well patients will respond to standard treatments like BCG therapy or chemotherapy. The research involves 600 people with intermediate or high-risk non-muscle invasive bladder cancer, a type that has not spread into the muscle layer. The goal is to see if the AI can accurately forecast whether the cancer will come back after treatment, which could help doctors tailor treatment plans in the future.

What this could mean

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

Active substance
Artificial intelligence-based analysis of digital pathology data
What this could lead to
If successful, this AI tool could help doctors predict which bladder cancer patients will respond to standard treatments, potentially personalizing care and avoiding ineffective therapies.
What could go wrong
The tool is still in development and validation. It may not accurately predict outcomes in all patients, and its real-world usefulness remains uncertain until proven in larger, diverse populations.

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 600 people

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

Started

Jan 2024

Expected to finish

Sep 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

Subjects identified in urology clinics after a diagnosis of non-muscle invasive bladder cancer undergoing intravesical BCG therapy or chemotherapy

Ages

18 to 99 years

Sex

Anyone

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: * Diagnosis of intermediate or high-risk non-muscle invasive bladder cancer as defined by AUA/SUO criteria (Intermediate-risk: recurrence within 1 year low grade Ta, solitary low grade Ta \>3 cm, multifocal low grade Ta, high grade Ta ≤3 cm, low grade T1; High risk: high grade T1, recurrent high grade Ta, high grade Ta \>3 cm, multifocal high grade Ta, any CIS, any BCG failure in high grade disease, any variant histology, any lymphovascular invasion) following pathologic evaluation of tissue specimens from TURBT. * Intravesical therapy within 6 months from enrollment including patients treated with BCG, mitomycin C, or Gemcitabine/Docetaxel. * English or Spanish speakers * ≥ 18 years of age * Ability to understand and the willingness to provide an informed consent Exclusion Criteria: * Inadequate tissue from TURBT * ≥ T2 bladder cancer * Systemic therapy * Inability to read or write English or Spanish * Unwilling to sign written informed consent

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Conditions

The condition(s) this trial relates to.

non-invasive bladder urothelial carcinoma Non-Muscle Invasive Bladder Neoplasms superficial urinary bladder carcinoma Urinary Bladder Neoplasms

As listed by the trial registrant

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

Non muscle invasive bladder cancer

How to take part

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

  1. The places running it

    2 sites. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    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

  • University of Texas Health Science Center at San Antonio

    RECRUITING

    San Antonio, Texas, 78229, United States

  • University of Texas Southwestern Medical Center

    RECRUITING

    Dallas, Texas, 75390-9164, United States

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