Enhanced IDEAL CSI in Hyperpolarized ¹³C MRI Using Single-Dataset K-Space Analysis for Metabolic Exchange Rate Estimation

Motivation: The rapid decay of clinical lactate signals compromises image quality and quantitative reliability, making traditional kinetic models that require multiple images impractical. Goal(s): To overcome signal decay limitations, we aim to analyze data using only a single set of metabolic images from IDEAL Chemical Shift Imaging (CSI). Approach: By acquiring one set of N metabolite images with echo time shifts, we leverage spectral and echo time information to extract metabolite signals and calculate exchange rates in the spatial frequency domain. Results: Our model successfully estimated metabolic signals and yielded consistent apparent exchange rate constants across three sequential datasets. Impact: This work introduces a single-dataset K-space analysis method enhancing IDEAL CSI in hyperpolarized ¹³C MRI, enabling accurate estimation of metabolic exchange rates, which simplifies data analysis and advances understanding of disease mechanisms and treatment responses.