Revisiting signal intensity ratios for extending the dynamic range for iron overload estimation

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Medical Diagnostics
• Biophysics

Background:

• Liver iron concentration (LIC) is crucial for diagnosing and managing iron overload disorders.
• Current MRI techniques like R2* estimation have limitations in dynamic range and accuracy at high iron levels.

Purpose of the Study:

• To derive generalizable equations for quantifying liver iron concentration (LIC) using signal-intensity-ratio (SIR) estimation.
• To extend the dynamic range of LIC estimation and identify limitations of R2* methods.

Main Methods:

• Developed LIC equations for multi-echo gradient echo relaxometry and single-echo SIR of liver and muscle tissue.
• Conducted MRI at 1.5T and 3T on human subjects with varying liver iron burdens.
• Compared SIR-LIC and R2*-LIC estimates for concordance and high LIC performance.

Main Results:

• Linear regression of Log(SIR) by LIC showed similar slopes at 1.5T and 3T.
• SIR-LIC and R2*-LIC estimates were concordant until R2* saturation occurred.
• SIR-LIC estimates continued to increase beyond R2* saturation, indicating a wider dynamic range.
• Spatial intensity correction reduced bias and variance in LIC estimates.

Conclusions:

• LIC-SIR measurements provide a viable alternative for estimating liver iron concentration when R2* acquisitions are unavailable or protocols are exceeded.
• Spatial intensity correction enhances the accuracy of SIR-LIC estimates.