Multiple regression method for pulmonary apparent diffusion coefficient measurement by hyperpolarized 3He MRI

Jiangsheng Yu, Masaru Ishii, Stephen Kadlecek, David A. Lipson, Kiarash Emami, Timothy W. Clark, Sheeva Rajaei, Rahim R. Rizi

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Purpose: To develop and validate a new multiple regression technique for the separation of flip angle effect in pulmonary apparent diffusion coefficient (ADC) measurement. Materials and Methods: Hyperpolarized 3He MRI (HP 3He MRI) ADC measurements were performed on phantom, pig, and human models. The diffusion-sensitization sequence is modified from a standard gradient echo (GRE) sequence with a nonlinear progression in the bipolar gradient amplitude with each image. In the self-diffusion phantom experiment, four images were acquired with base gradient factor b0 = 0.15 second/cm2; in the pig and human experiment, six images were acquired with base gradient factor b0 = 1.4 second/cm2. Results: The self-diffusion coefficient measured in the phantom experiment was 1.98 ± 0.16 cm2/second. The measured uncertainty curve was consistent with the theoretically predicted curve. The measured in vivo ADC values (three coronal slices in the supine direction) were 0.20/0.16/0.13 cm2/second and 0.20/0.18/0.16 cm2/second for pig and human experiments, respectively. Conclusion: With the introduction of a nonlinear progression in the diffusion-sensitization gradients, the multiple regression technique is capable of separating the flip angle effect in ADC measurement. In addition, this technique can perform a rigorous measurement uncertainty analysis and provide the optimal scan parameters that yield best noise performance.

Original languageEnglish (US)
Pages (from-to)982-991
Number of pages10
JournalJournal of Magnetic Resonance Imaging
Volume25
Issue number5
DOIs
StatePublished - May 2007

Keywords

  • Apparent diffusion coefficient
  • Diffusion sensitization
  • Hyperpolarized He MRI
  • Measurement uncertainty
  • Multiple regression method

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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