LIRADS (2021)-S3-CGI02-2021

Video Transcription

Video Summary

The session focused on the advancements and components of the LI-RADS system over its 10-year evolution. Key aspects were the importance of a standardized lexicon for consistent reporting and data synthesis to improve patient care in liver imaging. Victoria Chernek emphasized the critical role of consistent language in research, education, and clinical care to enhance data analysis and patient outcomes. Dr. Claude Serlin highlighted different imaging algorithms within LI-RADS, including CT/MRI and contrast-enhanced ultrasound (CEUS), emphasizing CEUS's role as a safe, effective tool for liver imaging with high specificity for HCC diagnosis. Dr. David Fetzer discussed the CEUS algorithm as a complement to existing diagnostic modalities, showing its applicability in scenarios where CT or MRI might not be optimal or available. Professor Jianmin Li addressed the LI-RADS Treatment Response Algorithm (TRA), underscoring its relevance in evaluating tumor treatment responses post-locoregional therapies. He highlighted challenges and the potential improvement of TRA's diagnostic performance using ancillary features, particularly concerning therapies like TARE and radiation. Overall, the session underscored LI-RADS' function as a comprehensive framework for liver imaging that supports improved diagnostic accuracy and treatment assessments.

Keywords

LI-RADS

liver imaging

standardized lexicon

CEUS

HCC diagnosis

treatment response

diagnostic accuracy

imaging algorithms