A simulation-based comparison of two methods for determining relaxation rates from relaxometry images

Area of Science:

• Medical Imaging
• Biophysics
• Radiology

Background:

• Liver iron content is crucial for diagnosing and managing various liver diseases.
• Relaxometry, particularly MRI-based methods, is a non-invasive technique for quantifying liver iron.
• Current methods often involve voxel-wise analysis of relaxation rates.

Purpose of the Study:

• To compare the precision and accuracy of voxel-wise fitting versus signal-averaging fitting for liver relaxometry.
• To determine which method provides more robust estimates of relaxation rates under various conditions.

Main Methods:

• Comparison of voxel-wise fitting and signal-averaging fitting on clinical MRI images.
• Mathematical simulations to assess the robustness of both fitting methods.
• Evaluation across a range of relaxation rate conditions, including those typical for high liver iron content.

Main Results:

• Systematic differences were observed between the two fitting methods in clinical images.
• Voxel-wise fitting was found to skew relaxation rate estimates and increase variance.
• These inaccuracies were more pronounced at moderate to fast relaxation rates, indicative of higher iron concentrations.

Conclusions:

• Signal-averaging fitting provides more robust and accurate relaxation rate estimates than voxel-wise fitting for liver iron assessment.
• The findings suggest potential impacts on clinical decisions due to inaccuracies in current voxel-wise methods.
• Further validation is recommended to refine non-invasive liver iron quantification techniques.