Shape-based motion correction in dynamic contrast-enhanced MRI for quantitative assessment of renal function

Area of Science:

• Medical Imaging
• Biophysics
• Radiology

Background:

• Quantitative functional analysis in Magnetic Resonance Urography (MRU) is crucial for assessing kidney health.
• Respiratory motion artifacts can significantly compromise the accuracy of quantitative MRU measurements.
• Existing methods may struggle to adequately compensate for complex motion patterns during image acquisition.

Purpose of the Study:

• To integrate a novel shape-based motion estimation algorithm into MRU workflows.
• To validate the effectiveness of this motion compensation technique for quantitative functional analysis.
• To improve the precision of pharmacokinetic modeling and parameter estimation in MRU.

Main Methods:

• A three-module scheme was proposed: MRU image acquisition, motion compensation, and quantitative functional analysis.
• Experiments involved simulated respiratory motion on dynamic contrast-enhanced (DCE) MR images and real-time motion compensation on free-breathing noncontrast MR images.
• Performance was evaluated by comparing functional estimates (e.g., Patlak number, GFR) against ground truth and by analyzing the reduction in temporal intensity curve variations.

Main Results:

• Simulated motion caused significant underestimation of Patlak numbers (up to 35%); motion compensation reduced errors to within 3-4%.
• On free-breathing images, motion compensation drastically reduced temporal intensity curve variations (standard deviation decreased from ~30-38 to ~8-11).
• The developed method demonstrated substantial improvement in the accuracy of quantitative functional estimates.

Conclusions:

• The novel shape-based motion compensation method effectively enhances quantitative functional analysis in MRU.
• The technique improves the accuracy of pharmacokinetic modeling and quantitative parameter estimations, crucial for clinical diagnosis.
• Future research will focus on clinical validation and extending the method to other DCE-based quantitative analyses in different organs.