DQF-MT MRI of connective tissues: Application to tendon and muscle

Slawomir Kusmia, Uzi Eliav, Gil Navon, Geneviève Guillot

Research output: Contribution to journalArticlepeer-review

Abstract

Object: The sequence combining DQF (double quantum filtering) with magnetisation transfer (DQF-MT) was tested as an alternative to the DQF sequence for characterising tendon and muscle by MR imaging. Materials and methods: DQF-MT images of tendon-muscle phantoms were obtained at 4.7 T using ultra-short time to echo (UTE) methods in order to alleviate the loss of SNR due to the short T2 of the tissues. Two different sampling schemes of the k-space, Cartesian or radial, were employed. In vivo images of the human ankle on a clinical 1.5 T scanner are also presented. Parameters providing optimal tendon signal as well as optimal contrast between this tissue and muscle were determined. Results: Two sets of parameters resulting in different contrasts between the tissues were found. For the first set (short creation time τ = 10 μs and magnetisation exchange time t LM = 100 ms), DQF-MT signals in muscle and tendon were detected, with that of the tendon being the larger one. For the second set (long creation time τ = 750 μs and magnetisation exchange time 10 μs < t LM < 100 ms), the DQF-MT signal was detected only in the tendon, and the decay of the double quantum coherence was slower than that observed for the first one, which allowed us to acquire DQF-MT MR images on a clinical 1.5 T MR scanner with minimal software interventions. In favourable conditions, the DQF-MT signal in the tendon could represent up to 10 % of the single-quantum signal. Conclusion: Dipolar interaction within macromolecules such as collagen and myosin is at the origin of the DQF-MT signal observed in the first parameter set. This should enable the detection of muscle fibrosis.

Original languageEnglish
Pages (from-to)203-214
Number of pages12
JournalMagnetic Resonance Materials in Physics, Biology, and Medicine
Volume26
Issue number2
DOIs
StatePublished - Apr 2013

Keywords

  • Contrast optimisation
  • DQF-MT MRI
  • Muscle
  • Tendon
  • UTE

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