Imaging study puts LI-RADS under the microscope
The liver lesion reporting system LI-RADS is comparable to traditional non-standardized reporting methods in terms of interreader agreement and diagnostic accuracy, according to results of a new study recently published online in Academic Radiology.
The increased use of imaging in hepatocellular carcinoma surveillance has placed an emphasis on reliable liver lesion reporting as a cornerstone of communication and comparison of findings among individual institutions.
One possible solution is LI-RADS, a standardized reporting system that outlines terminology and criteria for the interpretation and reporting of cirrhotic liver observations, said Borna K. Barth, MD, of the University Hospital of Zürich in Switzerland, and his co-authors.
“LI-RADS bears the potential to become a widely accepted scoring system for standardized reporting of liver observations in patients at risk for hepatocellular carcinoma,” they wrote. “Although adopted by several institutions worldwide, there is still limited evidence if the elaborated LI-RADS improves interreader agreement.”
Barth and his team set out to compare the performance of LI-RADS to non-standardized reporting methods and to assess its level of acceptance in clinical routines.
To do so, they asked four readers to evaluate 104 liver observations in patients at risk for hepatocellular carcinoma using LI-RADS criteria as well as a 5-point Likert scale. Interreader agreement and diagnostic accuracy were analyzed, and reader acceptance was determined through a questionnaire.
Their results found that both methods showed similar overall interreader agreement, with LI-RADS trending slightly higher, as well as comparable diagnostic accuracy. Readers also were accepting of the LI-RADS criteria, with all four agreeing that a short version of LI-RADS would facilitate use in clinical routine.
“LI-RADS showed similar interreader agreement and diagnostic accuracy compared to nonstandardized reporting,” the authors concluded. “However, further reduction of complexity and refinement of imaging features may be needed.”
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