A pharmacokinetic model for hyperpolarized ¹³C-pyruvate MRI when using metabolite-specific bSSFP sequences

Area of Science:

• Medical Imaging
• Biophysics
• Biochemistry

Background:

• Metabolite-specific balanced SSFP (MS-bSSFP) sequences enhance signal-to-noise ratio (SNR) in hyperpolarized [1-13C]Pyruvate (HP 13C) MRI.
• Existing pharmacokinetic models do not account for the unique signal evolution of MS-bSSFP data.
• Accurate estimation of metabolic conversion rate constants (kPL and kPB) is crucial for interpreting HP 13C MRI studies.

Purpose of the Study:

• To develop and validate a flexible GRE-bSSFP model for fitting metabolic conversion rate constants in HP 13C MRI.
• To address the limitations of current models in handling MS-bSSFP signal characteristics.
• To compare the performance of the new GRE-bSSFP model against a traditional GRE model.

Main Methods:

• A novel GRE-bSSFP model was constructed to analyze MS-bSSFP acquisitions.
• The model's accuracy was assessed using simulations and in vivo data from healthy rat kidneys, mouse prostate cancer, and human renal cell carcinoma.
• Results were compared with those obtained using a conventional GRE model and GRE acquisitions.

Main Results:

• The proposed GRE-bSSFP model accurately fits simulated data, while the GRE model shows bias due to model mismatch.
• In vivo studies demonstrated consistent conversion rate constant estimates between the GRE-bSSFP and GRE models.
• Simultaneous fitting of lactate T2 and kPL led to less precise kPL estimations.

Conclusions:

• The developed GRE-bSSFP model accurately estimates kPL and kPB for MS-bSSFP HP 13C experiments.
• This modeling approach offers improved accuracy for metabolic rate constant estimation in HP 13C MRI.
• The model framework is adaptable for other hyperpolarized agents and multi-echo bSSFP sequences.