Precise Non-invasive Liver Cirrhosis Quantification via Multimodal Stiffness-Structural Fusion Imaging

Area of Science:

• Medical Imaging
• Radiology
• Biophysics

Background:

• Conventional Magnetic Resonance Elastography (MRE) provides separate stiffness and structural images, necessitating manual region of interest (ROI) delineation for liver stiffness assessment.
• Manual ROI placement introduces observer variability and may lead to the omission of significant lesions, hindering accurate representation of whole-liver stiffness distribution.

Purpose of the Study:

• To implement and evaluate a multimodal image fusion technique integrating stiffness maps with structural images for enhanced liver stiffness assessment.
• To establish a standardized, quantitative framework for whole-liver stiffness analysis and disease monitoring in liver cirrhosis.

Main Methods:

• Acquisition using 3.0T MRI with optimized T1-weighted imaging and MRE (60 Hz vibrations).
• Computational preprocessing of DICOM data into 3D volumes, followed by precise co-registration and fusion calculation.
• Quantitative analysis of liver stiffness distribution across different cirrhosis stages using the fused images.

Main Results:

• The stiffness-structural fusion imaging technique successfully integrated anatomical structures with stiffness patterns into a single visualization.
• Comparative analysis demonstrated clear differentiation between cirrhotic patients and healthy controls, with cirrhotic livers showing higher proportions of advanced fibrosis.
• The technique eliminated observer variability associated with manual ROI placement, enabling standardized whole-liver assessment.

Conclusions:

• Stiffness-structural fusion imaging provides comprehensive visualization of liver stiffness with precise anatomical correlation, potentially improving diagnostic accuracy over conventional MRE.
• This approach offers a standardized framework for whole-liver assessment, disease progression monitoring, and treatment response evaluation.
• The technique facilitates improved clinician-patient communication and provides a foundation for advanced radiomics in liver cirrhosis staging.