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Related Experiment Video

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Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

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Free-Breathing 3D Liver Perfusion Quantification Using a Dual-Input Two-Compartment Model.

Satyam Ghodasara¹, Shivani Pahwa¹, Sara Dastmalchian¹

¹Department of Radiology, Case Western Reserve University, and University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.

Scientific Reports

|December 14, 2017

Summary

This summary is machine-generated.

This study shows a liver perfusion model can differentiate between healthy, metastatic, and hepatocellular carcinoma (HCC) tissues. The model aids in characterizing liver lesions and diffuse liver diseases.

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Author Spotlight: Investigating Hepatic Adaptations and Prediabetic Progression in Liver Diseases

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Area of Science:

Medical Imaging
Hepatology
Quantitative Perfusion Modeling

Background:

Liver pathologies like metastatic adenocarcinoma and hepatocellular carcinoma (HCC) require accurate characterization.
Quantitative perfusion modeling offers potential for non-invasive assessment of liver tissue hemodynamics.

Purpose of the Study:

To evaluate the feasibility of a dual-input two-compartment liver perfusion model.
To differentiate between healthy liver, metastatic lesions, and HCC using perfusion parameters.

Main Methods:

Applied a dual-input two-compartment liver perfusion model.
Acquired 3D free-breathing perfusion data.
Analyzed perfusion values in 7 healthy subjects, 6 patients with metastatic adenocarcinoma, and 5 patients with HCC.

Main Results:

Metastatic lesions showed higher arterial fraction and interstitial space volume, lower permeability-surface area product compared to healthy livers.
HCCs exhibited higher arterial fraction and lower vascular transit time than healthy livers.
Metastases differed from HCCs in arterial fraction, vascular transit time, and vascular/interstitial space volumes.
Cirrhotic livers demonstrated lower total perfusion, vascular space volume, and permeability-surface area product, with higher interstitial space volume than healthy livers.

Conclusions:

The dual-input two-compartment model is feasible for characterizing liver pathologies.
The model can distinguish between metastatic lesions, HCC, and cirrhotic tissue.
This approach supports non-invasive characterization of focal and diffuse liver diseases.