AI-Enhanced ultrasound aims to catch liver cancer earlier
NCT ID NCT04409340
First seen Sep 17, 2026 · Last updated Sep 18, 2026 · Updated 1 time
Summary
Researchers are testing whether advanced ultrasound techniques combined with machine learning can improve the detection and characterization of liver cancer compared to standard ultrasound. The study enrolls 200 adults who have a focal liver lesion visible on ultrasound or are in a monitoring program. Participants undergo quantitative ultrasound and magnetic resonance viscoelastography to measure tissue stiffness and structure, with the goal of developing a more accurate, low-cost, non-invasive diagnostic approach.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- advanced quantitative ultrasound and magnetic resonance viscoelastography imaging
- What this could lead to
- If it works, this could give doctors a low-cost, non-invasive way to spot liver cancer earlier, when curative treatment is more likely to succeed.
- What could go wrong
- This is an early proof-of-concept study with 200 participants, so the imaging methods may not prove accurate enough for routine use. Results might not apply to all patients, especially those with fatty liver or obesity.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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About 200 people
The number the study aims to enrol. It can still change while the study runs.
- Started
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Oct 2020
- Expected to finish
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Dec 2027
An estimate. End dates often move.
- Lead sponsor
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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 investigators propose a cross-sectional prospective clinical study with two sequential cohorts: 1) a training cohort of 100 patients at risk for HCC to optimize QUS biomarkers for classification of solid liver lesions using MRI and/or biopsy as gold standard clinical references; and 2) a validation cohort of 100 patients to confirm diagnostic performance. The investigators will recruit patients seen at the hepatology clinic of the University of Montreal Hospital (CHUM).
- Ages
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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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 Hide 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: * Are at least 18 years old at screening; * Able to comprehend and willingness to provide voluntary consent; * Are able to have a MRI; * Understand French or English; * Patients enrolled in a monitoring program or referred for the characterization of a focal liver lesion; * Focal liver lesion is visible during ultrasound screening in B-mode. Exclusion Criteria: * Are pregnant or trying to become pregnant; * Have a weight or girth preventing from entering the MR magnet bore; * Are unable to understand or unwilling to provide written informed consent for this study; * Have a contraindication to MRI (pacemaker, insurmountable claustrophobia); * Have chronic kidney disease preventing the injection of gadolinium-based contrast agent.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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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
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Centre hospitalier de l'Université de Montréal (CHUM)
RECRUITINGMontreal, Quebec, H2X 0A9, Canada
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