| Autor: |
Wu Y; School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China., Liu X; Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China., Zhang X; School of Biomedical Engineering, Southern Medical University, Guangzhou, China., Huynh KM; Department of Radiology, University of North Carolina, Chapel Hill, NC, USA.; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA., Ahmad S; Department of Radiology, University of North Carolina, Chapel Hill, NC, USA.; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA., Yap PT; Department of Radiology, University of North Carolina, Chapel Hill, NC, USA.; Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA. |
| Abstrakt: |
Brain tissue microarchitecture is characterized by heterogeneous degrees of diffusivity and rates of transverse relaxation. Unlike standard diffusion MRI with a single echo time (TE), which provides information primarily on diffusivity, relaxation-diffusion MRI involves multiple TEs and multiple diffusion-weighting strengths for probing tissue-specific coupling between relaxation and diffusivity. Here, we introduce a relaxation-diffusion model that characterizes tissue apparent relaxation coefficients for a spectrum of diffusion length scales and at the same time factors out the effects of intra-voxel orientation heterogeneity. We examined the model with an in vivo dataset, acquired using a clinical scanner, involving different health conditions. Experimental results indicate that our model caters to heterogeneous tissue microstructure and can distinguish fiber bundles with similar diffusivities but different relaxation rates. Code with sample data is available at https://github.com/dryewu/RDSI. |
