title: Optimization of the parameters for diffusion tensor magnetic resonance imaging data acquisition for breast fiber tractography at 1.5 T.
abstract: BACKGROUND
  Diffusion tensor MRI has emerged as a promising tool for the analysis of the microscopic properties of tissues. Optimizing image acquisition parameters is essential for producing high-quality DTI. This study aimed to optimize the parameters for DTI data acquisition for breast fiber tractography at 1.5 T.
  
  
  METHODS
  A total of 21 healthy volunteers received breast DTI scanning using an ASSET-based EPI technique operated under different parameters including b value, the number of diffusion gradient directions, and spatial resolution. The images were analyzed for signal-to-noise, signal intensity ratio, mean number and length of reconstructive fiber tracts, and fractional anisotropy value.
  
  
  RESULTS
  The optimal acquisition parameters at 1.5 T for breast DT-MRI fiber tractography were determined as follows: axial 31 direction, b = 600 seconds per mm(2), matrix 128 × 128 with slice thickness of 3 mm.
  
  
  CONCLUSIONS
  The optimization of data acquisition parameters could improve the quality of breast DT-MRI images and assist fiber tractography at 1.5 T.
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Yuan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China. Electronic address: zxp@bjcancer.org.
authors.forename: Xiao-Peng
authors.initials: XP
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Yan-Ling
authors.initials: YL
authors.lastname: Li
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Xiao-Ting
authors.initials: XT
authors.lastname: Li
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Hu
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Cui
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Ying-Shi
authors.initials: YS
authors.lastname: Sun
authors.affiliation: Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China.
authors.forename: Xiao-Yan
authors.initials: XY
authors.lastname: Zhang
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000473:pathology*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*
keywords: Array spatial sensitivity encoding technique; B value; Diffusion gradient directions; Diffusion tensor imaging; Spatial resolution