Encoding capability prediction of acquisition schedules in CEST MR fingerprinting for pH quantification

Area of Science:

• Magnetic Resonance Imaging
• Quantitative MRI
• Biomedical Engineering

Background:

• Chemical Exchange Saturation Transfer (CEST) MRI is a promising technique for pH quantification.
• Optimizing acquisition schedules is crucial for improving the accuracy and reliability of CEST MRI.
• Current methods for evaluating acquisition schedules lack a universally accepted predictive metric.

Purpose of the Study:

• To identify a reliable metric for predicting the encoding capability of CEST MR fingerprinting acquisition schedules for pH quantification.
• To facilitate the optimization of CEST MR fingerprinting protocols.

Main Methods:

• Numerical simulations and phantom MRI experiments were conducted at 3 Tesla.
• CEST effects at 2 ppm were measured and matched to a dictionary for pH determination.
• pH quantification error (RMSE) was assessed, and three metrics (Cramer-Rao bound, dot product, Euclidean distance) were evaluated for their predictive power.

Main Results:

• The Cramer-Rao bound metric consistently showed superior performance in predicting pH quantification error across various sampling scenarios.
• The dot product metric showed good predictive capability but failed under specific conditions (varied B1 numbers).
• The Euclidean distance metric demonstrated the poorest performance in predicting pH quantification error.

Conclusions:

• The Cramer-Rao bound metric reliably predicts the encoding capability of CEST MR fingerprinting sampling strategies.
• This metric can guide the optimization of CEST MRI protocols for enhanced pH quantification.
• The Cramer-Rao bound offers a superior alternative to dot product and Euclidean distance for evaluating acquisition schedules.