Quantitative platform for accurate and reproducible assessment of transverse (T₂ ) relaxation time

MRI's transverse relaxation time (T₂ ) is sensitive to tissues' composition and pathological state. While variations in T₂ values can be used as clinical biomarkers, it is challenging to quantify this parameter in vivo due to the complexity of the MRI signal model, differences in protocol implementations, and hardware imperfections. Herein, we provide a detailed analysis of the echo modulation curve (EMC) platform, offering accurate and reproducible mapping of T₂ values, from 2D multi-slice multi-echo spin-echo (MESE) protocols. Computer simulations of the full Bloch equations are used to generate an advanced signal model, which accounts for stimulated echoes and transmit field (B₁⁺ ) inhomogeneities. In addition to quantifying T₂ values, the EMC platform also provides proton density (PD) maps, and fat-water fraction maps. The algorithm's accuracy, reproducibility, and insensitivity to T₁ values are validated on a phantom constructed by the National Institute of Standards and Technology and on in vivo human brains. EMC-derived T₂ maps show excellent agreement with ground truth values for both in vitro and in vivo models. Quantitative values are accurate and stable across scan settings and for the physiological range of T₂ values, while showing robustness to main field (B₀ ) inhomogeneities, to variations in T₁ relaxation time, and to magnetization transfer. Extension of the algorithm to two-component fitting yields accurate fat and water T₂ maps along with their relative fractions, similar to a reference three-point Dixon technique. Overall, the EMC platform allows to generate accurate and stable T₂ maps, with a full brain coverage using a standard MESE protocol and at feasible scan times. The utility of EMC-based T₂ maps was demonstrated on several clinical applications, showing robustness to variations in other magnetic properties. The algorithm is available online as a full stand-alone package, including an intuitive graphical user interface.