Christoph Schildknecht, David Brunner, Thomas Schmid, Jonas Reber, Josip Marjanovic, Klaas Pruessmann

For robust and high-quality brain imaging rigid body motion correction plays an increasingly important role.

We propose a wireless motion tracking method based on short-wave RF signal transmission that does not require a direct line of sight and can penetrate tissue and plastics between detector and marker providing a unprecedented degree of freedom in marker placement and fixation. Single digit micrometer precision during an EPI sequence could be demonstrated even at high tracking bandwidth of 100 Hz with minimal latency and operating independently from the scanner.

Adam van Niekerk, Ernesta Meintjes, Andre van der Kouwe

Using external hardware to track patient motion allows for high frequency, accurate prospective motion correction that is robust to changes in coil set-up and subject anatomy. However, this typically comes at the expense of increased hardware complexity, difficulties in marker placement and in some cases cross-calibration. To address some of these challenges, we have developed a small, battery powered marker that uses the three-dimensional gradient spatial encoding, visible through Faraday induction, for vector-based position and orientation estimates. The device enables wireless, calibration-free prospective motion correction that can be used on an ad-hoc basis in an unmodified scanner.

Alexander Aranovitch, Maximilian Haeberlin, Simon Gross, Benjamin Dietrich, Jonas Reber, Thomas Schmid, Klaas Pruessmann

Tracking head mounted NMR markers enables to carry out prospective motion correction for brain MRI. In this work, a NMR marker tracking method that facilitates easy deployment is characterized with respect to tracking reliability in the presence of hardware drift and other imperfections. The method is then applied to a high-resolution in-vivo scan with long scan duration.

Xiang Gao, Patrick Hucker, Juergen Hennig, Maxim Zaitsev

Turbo spin echo (TSE) sequence is one of the “workhorses” used in routine clinical applications for MR imaging [1]. However, long scan time and segmented k-space acquisition make it particularly susceptible to artifacts due to motion, not only between echo trains but also during echo train. When correcting such motions prospectively, a signal loss might be induced due to noise in motion tracking data. In this work, we present an analysis linking tracking noise to the signal drop. A sequence optimization approach predicts that intra-echo train motion correction with the available optical tracking system should be feasible without signal loss.

Laurence Jackson, Anthony Price, Jana Hutter, Alison Ho, Thomas Roberts, Laura McCabe, Maria Deprez, Lucy Chappell, Mary Rutherford, Joseph Hajnal

Major obstetric complications such as pre-eclampsia and intrauterine growth restriction can result from malformations in the circulation of the fetus and placenta. Robust, high resolution in-utero MR angiography has the potential to be a valuable tool in identification and monitoring of these disorders but is hampered by the presence of complex motion, ineffective breath holds and lack of safe contrast agents. Here we present a motion compensated method for visualising the vascular networks in the fetus and placenta using respiration resolved 2D inflow angiography with efficient and dense spatiotemporal sampling and retrospective correction.

Merlin Fair, Fuyixue Wang, Zijing Dong, Berkin Bilgic, Timothy Reese, Kawin Setsompop

Echo-Planar Time-resolved Imaging (EPTI) is a recent multi-shot EPI-based approach that allows extremely rapid acquisition of distortion and blurring free multi-contrast imaging and mapping. In this work, a motion robust extension to EPTI, termed PEPTIDE, is presented. Combining Propeller-like rotations into the EPTI sampling strategy, this technique brings significant tolerance to shot-to-shot motion and B₀ phase variations, as well as opening up opportunities for further acceleration.

Jiaen Liu, Peter van Gelderen, Jacco de Zwart, Jeff Duyn

The ability of T₂*-weighted (or susceptibility-weighed) MRI to provide structural and functional information about the brain is affected by B₀ field fluctuations associated with head motion, which are inadequately accounted for in current correction approaches. Here, a 3D EPI navigator was developed to measure head motion, map the associated complex B₀ field changes and correct their effects in T₂*-weighted GRE MRI. Adequate temporal resolution of the navigator was achieved by implementing 2D parallel imaging with controlled aliasing. A fast reconstruction strategy is proposed to retrospectively correct the motion artifacts, overcoming limitations of prospective B₀ corrections inadequately dealing with the spatially complex B₀ changes.

Juliane Ludwig, Peter Speier, Frank Seifert, Tobias Schaeffter, Christoph Kolbitsch

Respiratory motion during data acquisition can introduce strong motion artefacts in 2D cine cardiac MR images. The commonly used breathhold method minimizes these artefacts, but also limits achievable image resolution and requires patient cooperation. Here we present a prospective motion correction technique using RF pilot tone signals with high temporal resolution. A calibration scan was carried out to convert signal intensity changes of the pilot tone to displacements of the heart due to breathing. The proposed approach was evaluated in four healthy volunteers and allowed for free-breathing 2D cine MR with high image quality.

Melissa Haskell, Stephen Cauley, Berkin Bilgic, Julian Hossbach, Josef Pfeuffer, Kawin Setsompop, Lawrence Wald

Retrospective motion correction techniques have the potential to improve clinical imaging without altering the workflow or acquisition sequence.  Yet, they suffer from long reconstruction times and poor conditioning. To address these problems, we developed a Network Accelerated Motion Estimation and Reduction method (NAMER) within a data-consistency based forward model approach to motion parameter estimation. The neural net accelerates convergence up to 15-fold as well as improving final image quality. The ML+MR physics motion correction method combines the speedup provided by fast convolutional neural networks with the robustness of a forward model-based data-consistency reconstruction.

Thomas Kuestner, Bin Yang, Fritz Schick, Sergios Gatidis, Karim Armanious

Motion is the main extrinsic source for imaging artifacts which can strongly deteriorate image quality and thus impair diagnostic accuracy. Numerous motion correction strategies have been proposed to mitigate or capture the artifacts. These methods have in common that they need to be applied during the actual measurement procedure with already a-priori knowledge about the expected motion type and appearance. We propose the usage of deep neural networks to perform retrospective motion correction in a reference-free setting, i.e. not requiring any a-priori motion information. Feasibility and influences of motion type and origin as well as optimal architecture are investigated.