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.
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Compare the sensitivity of QUS + B-mode US vs B-mode US alone for lesion detection, using MRI as the reference standard for detection
Timeframe: Within one month of the composite reference test (conventional MRI or pathology).