LI-RADS (2022)-W1-CGI09-2022

Video Transcription

Video Summary

The discussion focused on the Liver Imaging Reporting and Data System (LI-RADS) and its future directions, with emphasis on simplifying and optimizing the current system to improve clarity and diagnostic performance. The steering committee, led by Professor Victoria Cherniak, plans updates every few years based on accruing knowledge and user feedback. Current issues include complexity in the LI-RADS algorithm, causing challenges for new users, and variability in intermodality and inter-reader agreement, particularly between CT and MRI. These discrepancies can affect the categorization of liver lesions, with substantial consequences for patient management.<br /><br />Future updates aim to reduce ancillary features and optimize size thresholds to better classify indeterminate lesions, like LR3 and LR4, which currently pose treatment dilemmas. The presentation also highlighted efforts to expand LI-RADS beyond cirrhosis and ordinal categories into integrating quantitative imaging and patient-specific data for a more accurate probability of hepatocellular carcinoma (HCC) and prognosis predictions. Additionally, the talk introduced the potential role of imaging in predicting tumor aggressiveness and treatment response, potentially influencing treatment strategies through earlier interventions with systemic therapies. Such advancements aim to enhance precision and individualized care for patients with liver disease.

Keywords

LI-RADS

liver imaging

diagnostic performance

intermodality agreement

hepatocellular carcinoma

quantitative imaging

treatment strategies