Correction for variations in MRI scanner sensitivity in brain studies with histogram matching

Area of Science:

• Medical Imaging
• Neuroimaging
• Quantitative MRI

Background:

• Quantitative analysis of MRI scans is crucial for tracking disease progression and treatment efficacy.
• Variations in Magnetic Resonance (MR) scanner performance introduce significant variability in image intensity, complicating comparisons.
• This variability affects the accuracy of abnormality quantification, particularly in conditions like multiple sclerosis (MS).

Purpose of the Study:

• To introduce and evaluate a histogram matching method for correcting scanner-induced variations in MRI.
• To assess the method's effectiveness in reducing intensity variations in normal subjects.
• To determine if the method improves lesion volume measurement accuracy in multiple sclerosis patients.

Main Methods:

• A histogram matching technique was developed to normalize MR image intensities.
• The method was applied to MRI scans from normal subjects to quantify its effect on white matter intensity variation.
• Its performance in lesion volume measurement using global thresholding was evaluated in patients with multiple sclerosis (MS).
• The histogram matching method was compared against three other correction techniques.

Main Results:

• Histogram matching reduced white matter intensity variation in normal subjects from 7.5% to 2.5%.
• The method effectively removed threshold dependency in lesion volume measurements for MS patients.
• Histogram matching proved to be 2 to 5 times more effective than alternative correction schemes.

Conclusions:

• Histogram matching is a robust and effective method for correcting scanner-related intensity variations in MRI.
• This technique enhances the reliability of quantitative MRI analysis, especially for longitudinal studies and lesion quantification in MS.
• The proposed method offers a significant improvement over existing correction strategies for quantitative MRI.