Neoplasms

Digestive System Diseases

All Conditions

Liver Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Liver Diseases

Hematinics

All Drugs and Chemicals

Liver Extracts

All patients enrolled will undergo:

* Magnetic Resonance Viscoelastography
* Quantitative ultrasound (QUS)

All patients enrolled will undergo:

• Quantitative ultrasound (QUS)

Magnetic Resonance Viscoelastography

Guy Cloutier, PhD

Louise Allard, PhD

Marc Bilodeau, MD

Hélène Castel, MD

Jeanne-Marie Giard, MD

Bich Nguyen, MD

Marie-Pierre Sylvestre, PhD

Elijah Van Houten, PhD

An Tang, MD, MSc

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).

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.

Viscoelasticity Imaging to Assess Liver Cancer

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

Measure of liver viscoelastography using magnetic resonance Imaging (MRI)

Measure of liver viscoelastography using quantitative ultrasound (QUS).

Detection of focal HCC lesions using quantitative ultrasound (QUS).

Siemens Corporation, Corporate Technology

Fonds de la Recherche en Santé du Québec

Centre de Recherche du Centre Hospitalier de l'Université de Montréal

Centre hospitalier de l'Université de Montréal (CHUM)

Carcinoma

Carcinoma, Hepatocellular

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Adenocarcinoma

Quantitative Ultrasound

B-mode US performed according to the clinical standard of care.

B-mode Ultrasound

The composite reference standard includes MRI performed according to the clinical standard of care or histopathology when available.

Magnetic Resonance Imaging

Liver Biopsy

Casey Bourdeau Caporuscio, MSc

Worldwide, liver cancers are the third most common cause of cancer mortality. Even when liver cancer is suspected by blood tests, imaging is required to determine the location, size, and extent of disease. Medical societies therefore recommend surveillance with ultrasound every 6 months in at-risk patients. However, a key challenge to improving the survival is that ultrasound may miss half of early-stage liver cancers, thus diagnosis must rely on additional tests such as computed tomography (CT), magnetic resonance imaging (MRI), or biopsy. Hence, there is a clear need to improve the ability to detect liver cancers, especially with ultrasound. The investigator's team proposes novel ultrasound approaches to detect cancer nodules invisible on conventional ultrasound based on differences in mechanical and structural properties between liver and tumor. Improving detection is critical because liver cancer can be cured only if detected at an early stage, as shown by improvements in survival rates in patients enrolled in surveillance programs. The investigator's multi-disciplinary, national, and international team includes experts in clinical fields (hepatology, oncology, radiology, pathology), basic sciences (engineering, medical physics, machine learning, biostatistics), and patient partnership. The investirgator will apply the methodology of patient partner recruitment and collaborate with the Centre of Excellence on Partnership with Patients and the Public to select potential new collaborators. This will permit this project to be informed at every stage by patient and family perspectives, ensuring that the results of this project will be more robust, impactful, and aligned with the priorities, needs and experiences of those who live with liver cancer. The investigator submits a research proposal focused on advanced imaging techniques because imaging constitutes a foundation for surveillance, diagnosis, staging, treatment selection and assessment of treatment response in patients with liver cancer.

BACKGROUND Worldwide, liver cancers are the third most common cause of cancer mortality. In Canada, hepatocellular carcinoma (HCC) is one of the few cancers for which mortality is increasing. Early detection of HCC improves the likelihood of curative treatment and survival. Systematic HCC surveillance with ultrasound (US) is recommended by practice guidelines. However, conventional (B-mode) US suffers from low sensitivity (47%) for detecting early-stage HCC due to fatty liver, obesity, and cirrhosis. Once a suspicious nodule is detected by US, guidelines recommend contrast-enhanced computed tomography (CT) or magnetic resonance imaging (MRI) to confirm cancer. Hence, there is an urgent need to improve the ability to detect and diagnose HCC early. Members of the investigator's team have developed innovative quantitative ultrasound (QUS) techniques (including shear wave viscoelastography \[SWV\] and sub-resolution cellular imaging) that have a high diagnostic potential. The investirgator hypothesizes that a combination of QUS techniques offering complementary assessment of tissue characteristics will improve our ability to detect liver nodules and diagnose HCC.

METHODOLOGY Design: Prospective, cross-sectional imaging trial comparing head-to-head B-mode US and research QUS acquired within one month to the composite reference standard. Reference standard: MRI will be used as the non-invasive ground truth for liver nodules detection and classification except when biopsy is available. Data analysis: Lesion detectability will be measured by contrast-to-noise ratio on US and QUS maps for different size thresholds (\<10 mm, 10-20 mm, \>20 mm) used in diagnostic algorithms. Diagnostic performance will be measured by receiver operating characteristic curve analysis on the training and test sets for different size thresholds. The diagnostic accuracy of US and QUS + B-mode US will be compared by using the DeLong method.

RATIONALE AND IMPACT Early detection through systematic US surveillance translates into curative therapy in a higher proportion of patients and into improvements in survival rates. This imaging trial will provide a low-cost imaging technique to identify liver cancers earlier and from a single exam. Unlike some other imaging techniques, US is widely available throughout Canada. A major impact of this work, for patients and medical institutions, will be to lower the need for liver biopsy, the risk of complications and the cost for HCC diagnosis. This trial will position Canada as a leader in HCC diagnosis as new QUS and SWV biomarkers will be tested.

Early Detection of Liver Cancer by QUS

Quantitative Ultrasound to Improve Detection and Diagnosis of Liver Cancer

Lesion detectability will be measured by contrast-to-noise ratio on US and QUS maps for different size thresholds (\<10 mm, 10-20 mm, \>20 mm) used in diagnostic algorithms

Diagnostic performance will be measured by receiver operating characteristic curve analysis on the training and test sets for different size thresholds

The diagnostic accuracy of US and QUS + B-mode US will be compared by using the DeLong method

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Viscoelasticity Imaging to Assess Liver Cancer	NCT04409340	Liver Cancer	Magnetic Resona... QUS	18 Years -	Centre hospitalier de l'Université de Montréal (CHUM)
Viscoelasticity Imaging to Assess Liver Cancer	NCT04409340	Liver Cancer	Magnetic Resona... QUS	18 Years -	Centre hospitalier de l'Université de Montréal (CHUM)
Early Detection of Liver Cancer by QUS	NCT06345508	Hepatocellular ... Liver Cancer	Quantitative Ul... B-mode Ultrasou... Magnetic Resona... Liver Biopsy	18 Years -	Centre hospitalier de l'Université de Montréal (CHUM)
Viscoelasticity Imaging to Assess Liver Cancer	NCT04409340	Liver Cancer	Magnetic Resona... QUS	18 Years -	Centre hospitalier de l'Université de Montréal (CHUM)

Spots Global Cancer Trial Database for viscoelastography