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Improved real-time tagged MRI using REALTAG.
Chen, Weiyi; Lee, Nam Gyun; Byrd, Dani; Narayanan, Shrikanth; Nayak, Krishna S.
  • Chen W; Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California.
  • Lee NG; Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California.
  • Byrd D; Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California.
  • Narayanan S; Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California.
  • Nayak KS; Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California.
Magn Reson Med ; 84(2): 838-846, 2020 08.
Article en En | MEDLINE | ID: mdl-31872918
ABSTRACT

OBJECTIVES:

To evaluate a novel method for real-time tagged MRI with increased tag persistence using phase sensitive tagging (REALTAG), demonstrated for speech imaging.

METHODS:

Tagging is applied as a brief interruption to a continuous real-time spiral acquisition. REALTAG is implemented using a total tagging flip angle of 180° and a novel frame-by-frame phase sensitive reconstruction to remove smooth background phase while preserving the sign of the tag lines. Tag contrast-to-noise ratio of REALTAG and conventional tagging (total flip angle of 90°) is simulated and evaluated in vivo. The ability to extend tag persistence is tested during the production of vowel-to-vowel transitions by American English speakers.

RESULTS:

REALTAG resulted in a doubling of contrast-to-noise ratio at each time point and increased tag persistence by more than 1.9-fold. The tag persistence was 1150 ms with contrast-to-noise ratio >6 at 1.5T, providing 2 mm in-plane resolution, 179 frames/s, with 72.6 ms temporal window width, and phase sensitive reconstruction. The new imaging window is able to capture internal tongue deformation over word-to-word transitions in natural speech production.

CONCLUSION:

Tag persistence is substantially increased in intermittently tagged real-time MRI by using the improved REALTAG method. This makes it possible to capture longer motion patterns in the tongue, such as cross-word vowel-to-vowel transitions, and provides a powerful new window to study tongue biomechanics.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Lenguaje Idioma: En Año: 2020 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Lenguaje Idioma: En Año: 2020 Tipo del documento: Article