Synoptic Reporting of Focal Liver Masses in at Risk Patients: Algorithmic Diagnosis and CEUS LI-RADS.

OBJECTIVES: Reporting contrast-enhanced ultrasound (CEUS) for focal liver masses in at risk patients is a challenging task. Traditionally used prose reporting (PR) is inconsistent and lacks standardization. We propose synoptic reporting (SR), encompassing algorithmic interpretation and liver imaging and reporting data system (LI-RADS) categorization. METHODS: A software worksheet from Kailo Medical (Melbourne, AU), incorporates the CEUS algorithm for liver interpretation and CEUS LI-RADS categorization. Part 1. Feasibility of SR: twenty participants of varying experience were presented a brief lecture on SR, algorithmic approach to liver mass interpretation, and CEUS LI-RADS categorization. Ten representative liver masses were shown as unknown cases. Participants inputted data into SR worksheets. Results and LI-RADS category were generated solely by SR. Data were categorized as "correct" or "incorrect." Part 2. Prospective Analysis: Ninety-one patients for SR and 56 for PR, all were tested for completeness, efficiency, and user satisfaction. RESULTS: Part 1: Junior participants, pass rate 81.6%, and senior participants, pass rate 83.3% showed no difference in performance. Part 2: Completeness: SR 98.4% and PR 87.0%. Efficiency: Average total time to completion: SR 11 minutes and PR 20 minutes. User satisfaction: Ultrasound technologists, all referring physicians, and six out of seven radiologists preferred SR over PR. Major benefits cited were total time saved, consistency and accuracy in documentation, and report completeness. CONCLUSIONS: SR is a reliable and useful tool in clinical practice to report liver masses on ultrasound and assign an appropriate LI-RADS categorization and management pathway. This ultimately improves communication with referring clinicians and leads to better patient outcomes.