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

Abstract

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.

Quantification of Intra-Muscular Adipose Infiltration in Calf/Thigh MRI Using Fully and Weakly Supervised Semantic Segmentation

“…Thus, it is possible to synthesize any contrast level offline, greatly facilitating accurate prediction of the disease’s state. Furthermore, the EMC algorithm used to generate the T 2 and PD maps relies on precise Bloch simulations of the experimental protocol timing diagram, radiofrequency (RF) pulse shapes, and gradient pulses, thereby producing accurate values that are stable across vendors and scan setting [ 32 , 40 , 41 ].…”

“…Generation of T 2 and PD maps was conducted using the echo modulation curve ( EMC ) algorithm described in [ 29 , 32 ]. Reliable quantification of single T 2 values is a challenging task due to the contamination of fast multi-echo spin echo ( MESE ) protocols by stimulated echoes [ 33 ].…”

Correcting for imaging gradients–related bias of T2 relaxation times at high‐resolution MRI

“…The diffusion-corrected EMC algorithm is immune to these changes, as it incorporates the protocol timing diagram and exact experimental parameter values into its signal model. 28,29…”

Advanced Magnetic Resonance Imaging (MRI) Techniques: Technical Principles and Applications in Nanomedicine

“…Conventional (or standard) MRI imaging is based on longitudinal relaxation (T1), transverse relaxation (T2), and proton density (PD) sequences [ 64 ]. The technique for image intensity and contrast in standard MRI is based on the relaxation properties of water protons and total water content in tissues [ 80 , 81 ]. Free water shows a dark signal in T1-weighted (-W) images and a bright signal in T2-W images [ 64 , 70 ].…”