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Diffusion tensor brain imaging at 0.55T: A feasibility study.
Kung, Hao-Ting; Cui, Sophia X; Kaplan, Jonas T; Joshi, Anand A; Leahy, Richard M; Nayak, Krishna S; Haldar, Justin P.
Afiliación
  • Kung HT; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
  • Cui SX; Siemens Medical Solutions USA, Los Angeles, California, USA.
  • Kaplan JT; Brain and Creativity Institute, University of Southern California, Los Angeles, California, USA.
  • Joshi AA; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
  • Leahy RM; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
  • Nayak KS; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
  • Haldar JP; Signal and Image Processing Institute, Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA.
Magn Reson Med ; 2024 May 09.
Article en En | MEDLINE | ID: mdl-38725132
ABSTRACT

PURPOSE:

To investigate the feasibility of diffusion tensor brain imaging at 0.55T with comparisons against 3T.

METHODS:

Diffusion tensor imaging data with 2 mm isotropic resolution was acquired on a cohort of five healthy subjects using both 0.55T and 3T scanners. The signal-to-noise ratio (SNR) of the 0.55T data was improved using a previous SNR-enhancing joint reconstruction method that jointly reconstructs the entire set of diffusion weighted images from k-space using shared-edge constraints. Quantitative diffusion tensor parameters were estimated and compared across field strengths. We also performed a test-retest assessment of repeatability at each field strength.

RESULTS:

After applying SNR-enhancing joint reconstruction, the diffusion tensor parameters obtained from 0.55T data were strongly correlated ( R 2 ≥ 0 . 70 $$ {R}^2\ge 0.70 $$ ) with those obtained from 3T data. Test-retest analysis showed that SNR-enhancing reconstruction improved the repeatability of the 0.55T diffusion tensor parameters.

CONCLUSION:

High-resolution in vivo diffusion MRI of the human brain is feasible at 0.55T when appropriate noise-mitigation strategies are applied.
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Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos