Quantifying Liver Heterogeneity via R2*-MRI with Super-Paramagnetic Iron Oxide Nanoparticles (SPION) to Characterize

Danny Lee1,2, Jason Sohn1,2, Alexander Kirichenko1,2

  • 1Radiation Oncology, Allegheny Health Network, Pittsburgh, PA 15012, USA.

Cancers
|November 11, 2022
PubMed

Insights

Super-paramagnetic iron oxide nanoparticles (SPIONs) improve liver MRI heterogeneity, enabling accurate characterization of functional liver parenchyma (FLP) and aiding radiation treatment planning for liver cancer.

Area of Science:

  • Medical Imaging
  • Nanotechnology
  • Hepatology

Background:

  • Super-paramagnetic iron oxide nanoparticles (SPIONs) serve as MRI contrast agents, safely labeling hepatic macrophages.
  • SPIONs localize within hepatic parenchyma, facilitating T2*- and R2*-MRI of the liver.
  • Quantifying liver heterogeneity using R2*-MRI with SPIONs for functional liver parenchyma (FLP) characterization remains unexplored.

Purpose of the Study:

  • To investigate SPIONs' ability to enhance liver heterogeneity for an auto-contouring tool.
  • To identify voxel-wise functional liver parenchyma volume (FLPV) using SPION-enhanced R2*-MRI.
  • To evaluate the impact of SPIONs on FLPV in liver cancer patients.

Main Methods:

  • SPIONs were administered to 12 liver cancer patients prior to R2*-MRI.
  • An auto-contouring tool was developed to identify FLPV based on R2* values.
  • Liver heterogeneity was compared between pre- and post-SPION MRI sessions.

Main Results:

  • SPIONs significantly improved liver heterogeneity across MRI sessions.
  • The auto-contouring tool identified an average of 60% FLPV (range 40-78%) using a threshold based on mean R2*.
  • The method was successful in 10 out of 12 patients, with two requiring adjusted echo times.

Conclusions:

  • SPION-enhanced R2*-MRI facilitates automatic characterization of FLP by leveraging increased liver heterogeneity.
  • The developed auto-contouring tool shows promise for accurate FLPV determination.
  • This technique is valuable for improving liver radiation treatment planning accuracy.