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WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion
Adrian Săftoiu1, Caroline Ewertsen2, Alina Popescu3
1Department of Gastroenterology and Hepatology, Elias Emergency University Hospital, Bucharest, Romania; Faculty of Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Ultrasound fusion imaging enhances liver interventions by improving spatial accuracy and lesion visibility, especially for difficult-to-image cases. This technique offers high accuracy and a favorable safety profile, supporting its wider clinical adoption.
Area of Science:
- Medical Imaging
- Interventional Radiology
- Diagnostic Ultrasound
Background:
- Ultrasound fusion imaging combines real-time ultrasonography (US) with pre-acquired CT/MRI for enhanced spatial correlation.
- It is crucial for liver imaging and interventions when conventional B-mode US has limitations in lesion visualization.
Purpose of the Study:
- To evaluate the technical accuracy (target registration errors) of ultrasound fusion imaging.
- To assess the improvement in lesion visibility using fusion imaging compared to conventional methods.
- To provide an expert consensus on its clinical utility in liver interventions.
Main Methods:
- Systematic review of literature from January 2012 to January 2025.
- PICO framework used to address target registration errors and lesion visibility.
- Searched PubMed, Scopus, Embase, and IEEE Xplore, including manual citation tracking and AI-assisted queries.
Main Results:
- Consistently high technical accuracy with target registration errors of ~1-3 mm (phantom) and ~4-14 mm (clinical).
- Fusion imaging significantly improved detection of occult liver lesions, increasing diagnostic yield and enabling successful interventions in up to 95% of cases.
- Favorable safety profile with major complication rates below 2%, particularly beneficial for tumors in challenging locations.
Conclusions:
- Ultrasound fusion imaging enhances spatial accuracy and guidance for liver interventions, maintaining a low complication rate.
- Advancements in AI and AR are expected to further optimize fusion imaging workflows and outcomes.
- Supports the broader adoption of fusion imaging as a vital tool in liver imaging and intervention.
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