WFUMB Liver Ultrasound Fusion Imaging Technical Review and Position Statement: Focus on CT/MRI-Based Fusion

Ultrasound fusion imaging is a hybrid technique that combines real-time ultrasonography (US) with pre-acquired computed tomography (CT) or magnetic resonance imaging (MRI), using electromagnetic (EM) tracking to enable precise spatial correlation between modalities. This technology is increasingly used for liver imaging and interventions, especially when conventional B-mode US fails to provide adequate lesion visualization. The aim of this technical review and position statement is to evaluate the technical accuracy (target registration errors) and lesion visibility of ultrasound fusion imaging based on published evidence and expert consensus.

This manuscript was designed as the technical component of a two-part World Federation for Ultrasound in Medicine and Biology (WFUMB) position statement. A systematic review was conducted using a PICO framework focused on two core questions: (i) to evaluate EM-tracked fusion target registration errors (PICO T1), and (ii) whether fusion improves visibility of lesions in difficult-to-image liver lesions (PICO T2). Literature from January 2012 to January 2025 was searched across PubMed, Scopus, Embase, and IEEE Xplore, with manual citation tracking and AI-assisted query generation. Eligible studies included research on US/CEUS fusion with CT/MRI, reporting technical accuracy and lesion conspicuity.

The technical accuracy of fusion imaging was consistently high, with target registration errors (TRE) of ∼1-3 mm in ideal phantom settings and ∼4-14 mm in clinical studies. Automatic registration methods were faster and similarly accurate as manual registration, possibly reducing operator dependence. Fusion imaging improved the detectability of lesions not visible (occult) on conventional B-mode US, increasing the diagnostic yield and enabling successful interventions (e.g., ablation) in up to 90%-95% of cases. Safety profiles across studies were favorable, with major complication rates generally below 2%. Furthermore, fusion imaging might prove especially beneficial for treating tumors in difficult locations (e.g., caudate lobe, peribiliary lesions).

Ultrasound fusion imaging significantly enhances the spatial accuracy of liver interventions by aligning real-time US with CT/MRI datasets. It improves interventional procedures guidance and maintains a low complication profile as compared to conventional US alone. Advancements in artificial intelligence (AI) and augmented reality (AR) are expected to further optimize image co-registration workflows and clinical outcomes. This technical review supports the broader adoption of fusion imaging as a key tool in liver imaging and intervention.