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Stimulated echo based mapping (STEM) of T 1 , T 2 , and apparent diffusion coefficient: validation and protocol optimization
Author(s) -
Zhang Yuxin,
Wells Shane A.,
Hernando Diego
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27358
Subject(s) - effective diffusion coefficient , prostate cancer , prostate , nuclear medicine , stem cell , imaging phantom , medicine , magnetic resonance imaging , cancer , radiology , biology , genetics
Purpose To present a stimulated‐echo based mapping (STEM) approach for simultaneous T 1 , T 2 , and ADC mapping. Methods Diffusion‐weighted stimulated‐echo images with various combinations of mixing time (TM), TE, and b‐value were acquired to enable simultaneous mapping of T 1 , T 2 , and ADC. The proposed STEM method was performed by densely sampling the TM‐TE‐b space in a phantom and in brain and prostate of healthy volunteers. T 1 , T 2 , and ADC from STEM were compared to reference mapping methods. Additionally, protocol optimization was performed to enable rapid STEM acquisition within 2 min by sparsely sampling the TM‐TE‐b space. The T 1 , T 2 , and ADC measurements from rapid acquisitions were compared to the densely sampled STEM for evaluation. Finally, a patient with biopsy‐proven high‐risk prostate cancer was imaged to demonstrate the ability of STEM to differentiate cancer and healthy tissues. Results Relative to the reference measurements, densely sampled STEM provided accurate quantitative T 1 , T 2 , and ADC mapping in phantoms (R 2 = 0.999, slope between 0.97–1.03), as well as in brain and prostate. Further, the T 1 , T 2 , and ADC measurements from the optimized rapid STEM acquisitions agreed closely with densely sampled STEM. Finally, STEM showed decreased T 2 and ADC in prostate cancer compared to healthy prostate tissue. Conclusion STEM provides accurate simultaneous mapping of T 1 , T 2 , and ADC. This method may enable rapid and accurate multi‐parametric tissue characterization for clinical and research applications.