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AI could catch returning cancer months earlier than current tests

NCT ID NCT07189520

Diagnosis Sponsor: Università Politecnica delle Marche 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 This study
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 Jun 26, 2026 · Last updated Jun 26, 2026 · Updated 1 time

Summary

This study will test whether an artificial intelligence system can detect minimal residual disease—tiny amounts of cancer left after surgery—and predict recurrence in 700 people with rectal cancer. The AI combines blood tests, genetic data, and scans to create a more complete picture than standard methods. If it works, it could lead to earlier, more personalized treatment decisions.

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 (AI) software
What this could lead to
If successful, this AI could help doctors detect leftover cancer cells and predict return of rectal cancer much earlier than standard tests, potentially guiding more timely treatment.
What could go wrong
This is an early-stage study that hasn't started recruiting yet. The AI may not perform better than existing methods in real-world settings, 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 700 people

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

Expected to start

Jun 2026

An estimate. Start dates often move.

Expected to finish

Jun 2030

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

Cancer patients

Ages

18 years and older

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 (Justification in parenthesis): * Age ≥18 years (RC and EC are primarily adult-onset cancers, and adult inclusion aligns with ethical biospecimen collection and consent processes.) * Histologically confirmed diagnosis of rectal or esophageal cancer (Confirms clinical relevance and eligibility for standard treatment pathways.) * Treatment plan includes surgical resection with curative intent (Ensures applicability to MRD and outcome prediction tasks.) * Undergoing standard-of-care neo-adjuvant or perioperative therapy (Ensures data consistency and relevance to response modelling.) * Ability and willingness to provide informed consent for biospecimen and clinical data use (Meets ethical requirements for participation.) * Availability for longitudinal blood sampling at T0 (baseline), T1 (3 months post-treatment), and T2 (6 months post-treatment) (Critical for temporal biomarker analysis.) * Optional Inclusion: Access to tumor tissue (archival or fresh) for multi-omic profiling (Supports deep integrative biomarker discovery.) Exclusion Criteria: * Diagnosis of non-resectable or metastatic disease at enrollment (Excludes non-curative settings where the longitudinal biomarker protocol may not be feasible.) * Emergency surgeries or treatment plans that deviate from standard protocols (To maintain data comparability.) * Inability or refusal to provide informed consent (Essential for ethical compliance.) * Failure to complete biospecimen donation or key follow-up timepoints (Maintains data integrity and model reliability.)

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Conditions

The condition(s) this trial relates to.

esophageal cancer rectal cancer rectal neoplasm

As listed by the trial registrant

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

Rectal cancer

How to take part

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  1. 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 ↗

  2. A doctor treating you

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