Characterization complex collagen fiber architecture in knee joint using high-resolution diffusion imaging.

Published

Journal Article

PURPOSE: To evaluate the complex fiber orientations and 3D collagen fiber network of knee joint connective tissues, including ligaments, muscle, articular cartilage, and meniscus using high spatial and angular resolution diffusion imaging. METHODS: Two rat knee joints were scanned using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 μm at 9.4T. The b values varied from 250 to 1250 s/mm2 with 31 diffusion encoding directions for 1 rat knee. The b value was fixed to 1000 s/mm2 with 147 diffusion encoding directions for the second knee. Both the diffusion tensor imaging (DTI) model and generalized Q-sampling imaging (GQI) method were used to investigate the fiber orientation distributions and tractography with the validation of polarized light microscopy. RESULTS: To better resolve the crossing fibers, the b value should be great than or equal to 1000 s/mm2 . The tractography results were comparable between the DTI model and GQI method in ligament and muscle. However, the tractography exhibited apparent difference between DTI and GQI in connective tissues with more complex collagen fibers network, such as cartilage and meniscus. In articular cartilage, there were numerous crossing fibers found in superficial zone and transitional zone. Tractography generated with GQI also resulted in more intact tracts in articular cartilage than DTI. CONCLUSION: High-resolution diffusion imaging with GQI method can trace the complex collagen fiber orientations and architectures of the knee joint at microscopic resolution.

Full Text

Duke Authors

Cited Authors

  • Wang, N; Mirando, AJ; Cofer, G; Qi, Y; Hilton, MJ; Johnson, GA

Published Date

  • August 2020

Published In

Volume / Issue

  • 84 / 2

Start / End Page

  • 908 - 919

PubMed ID

  • 31962373

Pubmed Central ID

  • 31962373

Electronic International Standard Serial Number (EISSN)

  • 1522-2594

Digital Object Identifier (DOI)

  • 10.1002/mrm.28181

Language

  • eng

Conference Location

  • United States