Optimal control Magnetic Resonance Elastography : a non-invasive tool to characterize liver elasticity in the case of hemochromatosis.
Recrutement en cours/passé: 
Recrutement en cours
kevin.tsevekoon@creatis.univ-lyon1.fr olivier.beuf@creatis.insa-lyon.fr

Medical context : Magnetic Resonance Elastography (MRE) is a validated clinical tool to characterize damages to the liver [1]. To do so, MRE measures liver elasticity by imaging the propagation of a shear wave that is externally generated and propagates in the liver. Imaging requires the use of a particular phase contrast MRI sequence whose main characteristics is the application of Motion Encoding Gradients (MEG) placed between slice excitation and signal measurement thus increasing the echo time. Longer MEGs increase the phase encoding at the expense of lower signal magnitude so finding the right equilibrium is necessary. In the case of hemochromatosis, due to high iron content in the liver, T2 values are shortened causing a rapid lost of signal and the subsequent failure of MRE to produce conclusive results [2].

Aims : Optimal Control MRE is a novel concept proposed by our team. Its principles resides in designing a specific RF excitation pulse (through the optimal control algorithm) which simultaneously achieves slice selection and motion encoding [3]. The optimization procedure enables maximization of phase encoding and signal magnitude with respect to a given T2 value. Moreover, recent works have shown its compatibility with ultrashort echo time strategies [4]. Optimal control MRE is therefore an interesting candidate for liver elasticity measurement in the context of short T2 occurring during hemochromatosis. However, this new technique has yet to be applied and to demonstrate its superiority in an in vivo context.

Description of the project methodology:

  • The first step will consist in refining the design strategies of RF pulses so as to take into account short T2 values and maximum RF amplitudes as required by the in vivo context (SAR deposition for living organisms).

  • A secondary objective of the pulse design will be the possibility to acquire multiple frequencies MRE data in a single shot [5]. Multifrequency MRE is able to provide more details on the ongoing pathology and being able to acquire this data in less time is also mandatory for in vivo examination as well as in a clinical context.

  • The first experimental demonstration will be carried out on a preclinical MRI first on standard mice for instrumental development then on a Hfe-/- mouse model which develops hemochromatosis. Comparison with standard MRE sequences will be made to evaluate the performance of Optimal Control based strategies.

  • Finally, a proof on concept will also be sought on a clinical MRI on healthy volunteers.

Expected results:

  • Tackling short T2 tissues with optimal control will help get an insight on the best pulse sequence structure in this context.

  • Being able to characterize properly liver damages in the case of hemochromatosis will help to avoid liver biopsy which is an invasive procedure.

  • A successful application in a clinical context will further promote optimal control as a powerful tool for MRI as is already the case in parallel transmit or contrast preparation sequences.

Required skills : Physics, signal/data processing, instrumentation


  1. Yin M et al., Assessment of Hepatic Fibrosis With Magnetic Resonance Elastography. Clin. Gastr. and Hepat, Volume 5, Issue 10, 2007, Pages 1207-1213.

  2. Ghoz H.M et al. Hepatic iron overload identified by magnetic resonance imaging-based T2* is a predictor of non-diagnostic elastography. Quant. Imaging Med. Surgery, 2019;9(6):921-927

  3. Van-Reeth E et al. Constant Gradient Elastography with Optimal Control RF Pulses. Journal of Magnetic Resonance, Volume 294, 2018, Pages 153-161.

  4. Sango-Solanas P et al. Ultra-short echo time Magnetic Resonance Elastography. ISMRM 2020 28th Annual Meeting & Exhibition, Aug 2020

  5. Sango-Solanas P et al. Harmonic wideband simultaneous dual‐frequency MR Elastography. NMR in Biomedicine. 2020;e4442.