Assessment of MR‐based and quantitative susceptibility mapping for the quantification of liver iron concentration in a mouse model at 7T

Authors:
Publisher website
Google Scholar
Abstract
Purpose: To assess the feasibility of quantifying liver iron concentration (LIC) using and quantitative susceptibility mapping (QSM) at a high field strength of 7 Tesla (T).Methods: Five different concentrations of Fe‐dextran were injected into 12 mice to produce various degrees of liver iron overload. After mice were sacrificed, blood and liver samples were harvested. Ferritin enzyme‐linked immunosorbent assay (ELISA) and inductively coupled plasma mass spectrometry were performed to quantify serum ferritin concentration and LIC. Multiecho gradient echo MRI was conducted to estimate and the magnetic susceptibility of each liver sample through complex nonlinear least squares fitting and a morphology enabled dipole inversion method, respectively.Results: Average estimates of serum ferritin concentration, LIC, , and susceptibility all show good linear correlations with injected Fe‐dextran concentration; however, the standard deviations in the estimates of and susceptibility increase with injected Fe‐dextran concentration. Both and susceptibility measurements also show good linear correlations with LIC (R2 = 0.78 and R2 = 0.91, respectively), and a susceptibility‐to‐LIC conversion factor of 0.829 ppm/(mg/g wet) is derived.Conclusion: The feasibility of quantifying LIC using MR‐based and QSM at a high field strength of 7T is demonstrated. Susceptibility quantification, which is an intrinsic property of tissues and benefits from being field‐strength independent, is more robust than quantification in this ex vivo study. A susceptibility‐to‐LIC conversion factor is presented that agrees relatively well with previously published QSM derived results obtained at 1.5T and 3T.
Funding Information
  • NIH (R01DK099596, S10RR023706)
  • NIH
  • National Institutes of Health
  • National Center for Research Resources

This publication has 87 references indexed in Scilit: