ClinicalTrials.gov
public full text
Public Domain
Early Detection of Liver Cancer by QUS
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 i
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- A Study of Imaging, Blood, and Tissue Samples to Guide Treatment of Colon Cancer and Related Liver Tumors#804491
- Integration of AI-driven ultrasound and molecular testing to improve diagnosis of indeterminate thyroid nodules.#1284721
- The AI Prognostic Assessment and Pathological Basis Research of Early HCC After Minimally Invasive Treatment#1163850
- Usefulness of Multi-parametric, Quantitative MR Imaging for Staging of Hepatic Fibrosis in the Patients With Chronic Hepatitis#1170779
- Improving Hepatocellular Carcinoma Screening#1059097
Record · ID 1196363
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive