OPTIMIZING ECHO TIME AND REPETITION TIME FOR TISSUE CONTRAST USING DIGITAL PHANTOMS

Abstract

Optimizing echo time (TE) and repetition time (TR) is crucial for enhancing tissue contrast in magnetic resonance imaging (MRI). Traditional approaches to TE/TR selection often rely on empirical methods or scanner-based adjustments, which can be limited by variability and lack of controlled conditions. This study leverages digital phantom simulations to systematically evaluate the effect of varying TE and TR on tissue contrast across common anatomical structures. A realistic digital phantom was constructed using established relaxation parameters for gray matter, white matter, cerebrospinal fluid (CSF), muscle, and fat. MRI signal evolution was simulated using Bloch equations, and contrast between tissue pairs was calculated across a wide TE/TR parameter space. The results demonstrate distinct contrast patterns for different tissue combinations, with optimal TE/TR regions identified for T1-weighted, T2-weighted, and proton-density-weighted imaging. Contrast maps and optimization tables derived from the simulations offer a structured, reproducible framework for protocol design, reducing reliance on empirical parameter selection. The findings validate known MRI contrast behaviors and provide scanner-agnostic TE/TR recommendations to accommodate practical clinical constraints. This work highlights the value of digital phantom-based modeling for enhancing MRI protocol development, enabling more consistent and contrast-efficient imaging outcomes. Future extensions, including advanced simulation platforms, experimental validation, and integration with emerging techniques, will further strengthen the translational potential of this approach.