Viscoelasticity Imaging to Assess Liver Cancer (VisCan)

Added Value of Shear Wave Viscoelasticity Imaging, Homodyned-K Tissue Imaging and Acoustic Attenuation to Assess Liver Cancer at Ultrasound: a Multiparametric Learning Approach

Ultrasound (US) used for hepatocellular carcinoma (HCC) surveillance suffers from low sensitivity (60-78%) due to fatty liver, obesity, and diffusely nodular appearance in cirrhosis. Once a suspicious malignant lesion is detected at US, guidelines recommend contrast-enhanced US, magnetic resonance imaging (MRI) or computed tomography (CT) scans to confirm suspicion. The investigators' team has developed innovative quantitative US (QUS) techniques that have a high potential to improve tissue characterization in terms of sensitivity and specificity. The investigators hypothesize that advanced QUS providing tumor viscoelasticity assessment, sub-resolution tissue structure characterization and US attenuation in the framework of a machine learning classification model can improve HCC diagnosis compared with standard US.

Early detection through systematic US surveillance translates into curative therapy in a higher proportion of patients and into improvements in survival rates. Thus, there is an urgent need to investigate innovative and cost-effective imaging techniques for improving detection and characterization of HCC. The proposed QUS methods are experimental and will be validated in this proof-of-concept clinical study. A major impact of this work, for patients and medical institutions, will be to improve early-stage detection and characterization of HCC, and offer alternatives in patients with negative or inconclusive conventional US. QUS are low-cost, non-invasive and non-irradiating imaging modalities available from a single exam (i.e., no additional imaging session is necessary).

Study Overview

Status

Recruiting

Conditions

Detailed Description

RESEARCH QUESTION AND BACKGROUND: Primary liver cancer or hepatocellular carcinoma (HCC) is the fifth most common cancer in men and the seventh in women and is the second cause of cancer mortality worldwide. In Canada, HCC is the only cancer for which mortality is increasing. More than 80% of HCC cases occur in individuals with advanced liver fibrosis (cirrhosis) due to viral hepatitis infection (B and C), non-alcoholic fatty liver disease (NAFLD), and alcoholic liver disease. Once cirrhosis is established, there is a significantly increased risk of developing HCC. Furthermore, HCC is observed in obese diabetic individuals without cirrhosis, increasing the population of patients at risk with a disease that has high fatality rate. HCC surveillance is associated with significantly prolonged survival. However, only 52% of patients undergoing surveillance have early HCCs that are eligible for curative treatment, whereas remainder of patients have intermediate- or advanced-stage disease eligible for bridge or palliative treatment only. HCC surveillance is also associated with significant improvements in early-stage detection, curative-treatment rates, and survival, even after adjusting for lead-time bias. North American guidelines recommend ultrasound (US) surveillance every 6 months in at-risk patients who are non-cirrhotic hepatitis B carriers and cirrhotic. However, a key challenge for US is the low sensitivity (60-78%) for identifying a lesion due to liver steatosis and cirrhosis. Once a suspicious malignant lesion is detected at US, current American Association for the Study of Liver Diseases (AASLD) guidelines recommend contrast-enhanced US, magnetic resonance imaging (MRI) or computed tomography (CT) scans to confirm suspicion.

GOAL: The long-term reaching goal is to develop US biomarkers of focal liver lesions and strategies to improve diagnostic sensitivity to HCC while maintaining a high specificity. This would constitute a major breakthrough because HCC diagnosis currently requires a combination of US for screening and confirmation using MRI, CT and less often biopsy.

OBJECTIVES: 1) Develop a machine learning model based on QUS for classification of solid hepatocellular carcinomas identified at US and diagnosed with MRI (or biopsy if required); 2) Determine if QUS maps can improve visual detection of suspected lesions at US; 3) Compare performance of QUS- versus MRI-based viscoelastography for lesion characterization.

Hypothesis: the investigators hypothesize that advanced QUS providing tumor viscoelasticity assessment, sub-resolution tissue structure characterization and US attenuation in the framework of a machine learning classification model can improve HCC diagnosis compared with standard US.

METHODOLOGY - Study design: This will be a 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.

Data analysis: Random forests machine learning to develop QUS classification models. Sensitivity and specificity to assess diagnostic accuracy, according to MRI and/or biopsy, with bootstrapping to obtain confidence intervals with training set. Confirmation of accuracy on test set. Inter-observer assessment of lesion detectability on clinical B-mode US versus QUS maps. Comparison of US- and MRI-based elasticity and viscosity according to diagnostic results.

Study Type

Observational

Enrollment (Estimated)

200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

    • Quebec
      • Montréal, Quebec, Canada, H2X 0A9
        • Recruiting
        • Centre Hospitalier de l'Université de Montréal (CHUM)
        • Sub-Investigator:
          • Jeanne-Marie Giard, MD
        • Sub-Investigator:
          • Bich Nguyen, MD
        • Contact:
        • Contact:
        • Sub-Investigator:
          • Marc Bilodeau, MD
        • Sub-Investigator:
          • Hélène Castel, MD
        • Sub-Investigator:
          • Marie-Pierre Sylvestre, PhD
        • Sub-Investigator:
          • Elijah Van Houten, PhD

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

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).

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Training cohort

All patients enrolled will undergo:

  • Magnetic Resonance Viscoelastography
  • Quantitative ultrasound (QUS)
Magnetic Resonance Viscoelastography
QUS
Validation cohort

All patients enrolled will undergo:

• Quantitative ultrasound (QUS)

QUS

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Liver viscoelastography determined by MRI
Time Frame: Within 6 weeks of liver echography
Measure of liver viscoelastography using magnetic resonance Imaging (MRI)
Within 6 weeks of liver echography
Liver viscoelastography determined by QUS
Time Frame: Within 6 weeks of liver echography
Measure of liver viscoelastography using quantitative ultrasound (QUS).
Within 6 weeks of liver echography
Detection of focal HCC lesions
Time Frame: Within 6 weeks of liver echography
Detection of focal HCC lesions using quantitative ultrasound (QUS).
Within 6 weeks of liver echography

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Guy Cloutier, PhD, Centre Hospitalier de l'Université de Montréal (CHUM)
  • Principal Investigator: An Tang, MD, MSc, Centre Hospitalier de l'Université de Montréal (CHUM)

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 5, 2020

Primary Completion (Estimated)

October 31, 2023

Study Completion (Estimated)

December 22, 2023

Study Registration Dates

First Submitted

May 27, 2020

First Submitted That Met QC Criteria

May 27, 2020

First Posted (Actual)

June 1, 2020

Study Record Updates

Last Update Posted (Actual)

October 2, 2023

Last Update Submitted That Met QC Criteria

September 29, 2023

Last Verified

September 1, 2023

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

plan undicided

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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