Quantitative Imaging Methods Lab
Departments of Radiology and Medical Physics

Diffusion MRI in the Body

(Top) The T2-weighted and DW images show the two cancerous lesions in the PCa patient. (Bottom) T1, T2 and ADC maps and ROI measurements of left PZ lesion, right PZ lesion and normal PZ tissue from the densely-sampled and the rapid STEM acquisitions. Zhang Y, et al. Magnetic Resonance in Medicine. 2018 (Accepted).
Axial diffusion-weighted images of a representative liver acquired with three different diffusion encoding waveforms (MONO, CODE-M2, and ODGD-M2) with a b-value of 500 s/mm2 (A). Corresponding ADC maps (B). MONO ADC maps have heterogeneous positive bias throughout the liver due to intravoxel signal dephasing produced by bulk motion. ODGD-M2 and CODE-M2 waveforms achieve more spatially homogeneous DW images and ADC maps than MONO, showing better motion robustness. Pena-Nogales O, et al. Magnetic Resonance in Medicine. 2018 (Accepted).

By sensitizing the MRI signal to the molecular diffusion within tissue, diffusion MRI provides a unique non-invasive probe into tissue microstructure. Using appropriate signal models, we can extract quantitative measures of tissue microstructure from diffusion MRI data. However, diffusion MRI is highly sensitive to distortions, noise and other imaging artifacts. These artifacts can introduce bias and variability in diffusion MRI measures, and preclude the reproducible application of diffusion MRI as a quantitative biomarker. We focus on the development and validation of diffusion MRI techniques that are accurate and reproducible. Our work includes the development and optimization of image acquisition and reconstruction techniques, as well as development of novel imaging phantoms, and validation in volunteers and patients.

Selected Publications

  • Geng R, Zhang Y, Starekova J, Rutkowski DR, Estkowski L, Roldán-Alzate A, Hernando D, Characterization and correction of cardiovascular motion artifacts in diffusion-weighted imaging of the pancreas, Magnetic Resonance in Medicine, 2021 DOI
  • Zhang Y, Wells SA, Triche BL, Kelcz F, and Hernando D. Stimulated-echo diffusion-weighted imaging with moderate b values for the detection of prostate cancer. European Radiology, 2020;  30:3236-3244. DOI PMID
  • Zhang Y, Peña-Nogales Ó, Holmes JH and Hernando D. Motion-robust and blood-suppressed M1-optimized diffusion MR imaging of the liver. Magnetic Resonance in Medicine. 2019 March DOI PMID
  • Zhang Y, Wells S and Hernando D. Stimulated echo based mapping (STEM) of T1, T2, and apparent diffusion coefficient: Validation and protocol optimization. Magnetic Resonance in Medicine. 2019 January;81(1):167-181. DOI PMID
  • Peña-Nogales Ó, Zhang Y, Wang X, de Luis-Garcia R, Aja-Fernández S, Holmes JH and Hernando D. Optimized Diffusion-Weighting Gradient Waveform Design (ODGD) formulation for motion compensation and concomitant gradient nulling. Magnetic Resonance in Medicine. 2018 nov;81(2):989-1003. DOI PMID
  • Zhang Y, Holmes J, Rabanillo I, Guidon A, Wells S and Hernando D. Quantitative diffusion MRI using reduced field-of-view and multi-shot acquisition techniques: Validation in phantoms and prostate imaging. Magnetic Resonance Imaging. 2018 Sep;51:173-181. DOI PMID