T2′ mapping of the brain from water‐unsuppressed ¹H‐MRSI and turbo spin‐echo data

Abstract

Purpose To obtain high‐quality T2′$$ {\mathrm{T}}_2^{\prime } $$ maps of brain tissues from water‐unsuppressed magnetic resonance spectroscopic imaging (MRSI) and turbo spin‐echo (TSE) data. Methods T2′$$ {\mathrm{T}}_2^{\prime } $$ mapping can be achieved using T2*$$ {\mathrm{T}}_2^{\ast } $$ mapping from water‐unsuppressed MRSI data and T2$$ {\mathrm{T}}_2 $$ mapping from TSE data. However, T2*$$ {\mathrm{T}}_2^{\ast } $$ mapping often suffers from signal dephasing and distortions caused by B0$$ {\mathrm{B}}_0 $$ field inhomogeneity; T2$$ {\mathrm{T}}_2 $$ measurements may be biased due to system imperfections, especially for T2$$ {\mathrm{T}}_2 $$‐weighted image with small number of TEs. In this work, we corrected the B0$$ {\mathrm{B}}_0 $$ field inhomogeneity effect on T2*$$ {\mathrm{T}}_2^{\ast } $$ mapping using a subspace model‐based method, incorporating pre‐learned spectral basis functions of the water signals. T2$$ {\mathrm{T}}_2 $$ estimation bias was corrected using a TE‐adjustment method, which modeled the deviation between measured and reference T2$$ {\mathrm{T}}_2 $$ decays as TE shifts. Results In vivo experiments were performed to evaluate the performance of the proposed method. High‐quality T2*$$ {\mathrm{T}}_2^{\ast } $$ maps were obtained in the presence of large field inhomogeneity in the prefrontal cortex. Bias in T2$$ {\mathrm{T}}_2 $$ measurements obtained from TSE data was effectively reduced. Based on the T2*$$ {\mathrm{T}}_2^{\ast } $$ and T2$$ {\mathrm{T}}_2 $$ measurements produced by the proposed method, high‐quality T2′$$ {\mathrm{T}}_2^{\prime } $$ maps were obtained, along with neurometabolite maps, from MRSI and TSE data that were acquired in about 9 min. The results obtained from acute stroke and glioma patients demonstrated the feasibility of the proposed method in the clinical setting. Conclusions High‐quality T2′$$ {\mathrm{T}}_2^{\prime } $$ maps can be obtained from water‐unsuppressed 1H‐MRSI and TSE data using the proposed method. With further development, this method may lay a foundation for simultaneously imaging oxygenation and neurometabolic alterations of brain disorders.

Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping

“…As a result, the T2-weighted data obtained would not follow a simple exponential model of T2 relaxation and the T2 values estimated with only 3 TEs would contain significant errors. To address this problem, we corrected the estimation bias via a model-based approach incorporating a set of preacquired calibration data [26]. More specifically, we modelled the deviation between the measured and reference T2 decays as an echo time shift using the following model:…”