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Quantitative MRI

Research group 8.13

Motion-compensated MRI

Physiological motion, such as the movement of the head, respiratory motion or the heart beat, is still a major challenge in magnetic resonance imaging (MRI), especially for high-resolution 3D imaging. Motion can strongly degrade image quality and can even lead to scan abortions.

The standard approach to compensate for periodic motion (i.e. respiratory or cardiac motion) is motion gating, which restricts MR data acquisition to a predefined motion state (e.g. end-expiration for respiration). Data obtained in any other motion state is discarded and reacquired. This is a simple and robust approach which significantly improves image quality in a wide range of applications. Nevertheless, only a small section of the actual scan time is used for data acquisition, meaning scan times are not being utilised as efficiently as they could be.

Respiratory Gating. In order to minimise artefacts due to respiratory motion, the interface between the lung and the liver (diaphragm) is monitored during the MR data acquisition (white dot). MR data (k-space data) is only obtained if this reference point is within a predefined gating window (green rectangle). This ensures that all acquired data is obtained during the same respiratory motion state.
Respiratory Gating. Respiratory motion can blur MR images, resulting, for example, in a poor visualisation of vessels in the liver in this contrast-enhanced high-resolution 3D MR scan (Ungated). Respiratory gating leads to longer scan times, but significantly improves image quality (Gated).

Prospective motion correction

Prospective motion correction updates MR sequence parameters based on a motion surrogate to compensate for physiological motion during data acquisition. Although in principle this allows for full affine motion correction, commonly only the translational “through-plane” motion component is corrected for. The correction is applied globally and affects the entire FOV. Correcting for the affine component of the heart’s respiratory motion, for example, will lead to artefacts caused by the “wrongly corrected” static tissue of the back.

Motion-compensated image reconstruction

Motion-compensated image reconstruction acquires data in all motion states and uses additional motion information during the image reconstruction to transform all this data to the same reference motion state. This yields one high quality image without any motion artefacts. The main advantage of this approach is that data can be acquired continuously, leading to a high scan efficiency. Furthermore, it allows for the correction of complex non-rigid physiological motion (e.g. the respiratory motion of the abdomen, cardiac motion of the heart etc.).

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Motion-compensated image reconstruction. This high-resolution 3D MR scan is acquired over multiple cardiac cycles. The cardiac motion of the heart impairs the visibility, especially of small features such as the wall of the right ventricle (Uncorrected). In order to compensate for the cardiac motion, time-resolved 3D images are obtained showing the heart at different positions in the cardiac cycle. Each image is reconstructed using very little k-space information, resulting in poor image quality when using direct reconstruction techniques. Advanced iterative reconstruction methods are required in order to ensure sufficient image quality to carry out accurate motion estimation. This motion information can then be used in a motion compensated image reconstruction to improve the image quality (Motion Corrected) without increasing scan time. (Data obtained in a canine study).

Accurate motion information

The image quality achieved with motion compensation depends on two main parameters. Firstly, a motion surrogate with high temporal resolution is required to identify different motion states. Secondly, accurate motion information is needed to transform all acquired data to a reference motion state. The most efficient approach for motion-compensated image reconstruction is to obtain the motion information from the data itself. Usually very little k-space information is available for each motion state, therefore advanced iterative image reconstruction algorithms are necessary.

Clinical applications

Motion-compensated MRI provides high image quality independent of physiological motion. This allows for short acquisition times which are not impaired by subject-specific parameters such as heart rate or breathing type. We are developing novel, more reliable and more robust techniques to ensure this promising technique can be translated to clinical practice.

The recent introduction of simultaneous PET-MR scanners also offers the exciting opportunity to use high-resolution MR motion information to strongly compensate for physiological motion during PET image reconstruction, improving PET image quality and PET tracer quantification.

Further information on PET-MR

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Current projects

Motion correction for 3D high resolution dynamic contrast enhanced MRI of the liver

Novel acquisition scheme which provide high temporal and high spatial resolution 3D dynamic contrast enhanced MR images of the liver during free-breathing are developed as part of the DFG research training group BIOQIC (BIOphysical Quantitative Imaging Towards Clinical Diagnosis) and in collaboration with Charité Berlin.

Cooperation with:
Prof. Dr. Marcus Makowski, Department of Radiology, Charité Berlin, Germany

Respiratory-resolved attenuation correction maps for motion-compensated PET reconstructions

Attenuation correction information required for quantitative PET imaging is commonly obtained with a multi-echo MR acquisition. We have developed an MR scan which yields both accurate attenuation correction information and respiratory motion information in one efficient MR acquisition. This scan allows for respiratory motion-compensated PET reconstructions strongly improving PET image quality and tracer uptake quantification in lesions. (Link to PET-MR project).

Cooperation with:
Division of Imaging Sciences and Biomedical Engineering, King’s College London, UK
Siemens Healthcare, Research Collaborations, Frimley, UK

Model-based image reconstruction for rapid and accurate T1-mapping of the heart

Development of novel motion-compensated T1-mapping approaches which utilise signal models during image reconstruction in order to provide accurate T1 maps in the shortest possible scan time (Link zu Bewegungskompensation).

Cooperation with:
Prof. Dr. Jeanette Schulz-Menger, Experimental and Clinical Research Center, Charité Berlin, Germany

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Selected references

C. Kolbitsch, R. Neji, M. Fenchel, A. Mallia, P. Marsden, T. Schaeffter,
Respiratory-resolved MR-based attenuation correction for motion-compensated cardiac PET-MR
Opens external link in new window Physics in Medicine & Biology 63, 135008 (2018).

M. Ippoliti, M. Makowski, T. Schaeffter, C. Kolbitsch,
3D non-rigid motion-corrected dynamic contrast enhanced MRI of the liver with high isotropic resolution
Proceedings of Joint Annual Meeting ISMRM-ESMRMB, Paris, France, 476 (2018).

J. Ludwig, P. Speier, F. Seifert, T. Schaeffter, C. Kolbitsch,
Comparison of three surrogate-based respiratory motion correction methods for 3D high resolution cardiac MRI
Proceedings of Joint Annual Meeting ISMRM-ESMRMB, Paris, France, 4109 (2018).

C. Kolbitsch, R. Neji, M. Fenchel, A. Mallia, P. Marsden, T. Schaeffter,
Fully integrated 3D high-resolution multicontrast abdominal PET-MR with high scan efficiency
Opens external link in new window Magnetic Resonance in Medicine 79, 900-911 (2018).

C. Kolbitsch, M. Ahlman, C. Davies-Venn, R. Evers, M. Hansen, D. Peressutti, P. Marsden, P. Kellman, D. Bluemke, T. Schaeffter
Cardiac and Respiratory Motion Correction for Simultaneous Cardiac PET/MR
Opens external link in new window Journal of Nuclear Medicine 58, 846-852 (2017).

C. Baumgartner, C. Kolbitsch, J. McClelland, D. Rueckert, A. King
Autoadaptive motion modelling for MR-based respiratory motion estimation
Opens external link in new window Medical Image Analysis 35, 83-100 (2017).

N. Paschke, O. Doessel, T. Schaeffter, C. Prieto, C. Kolbitsch
Comparison of image-based and reconstruction-based respiratory motion correction for golden radial phase encoding coronary MR angiography
Opens external link in new window J Magn Reson Imaging 42, 964-71 (2015).

D. Balfour, P. Marsden, I. Polycarpou, C. Kolbitsch, A. King
Respiratory motion correction of PET using MR-constrained PET-PET registration
Opens external link in new window BioMedical Engineering OnLine 14, 85 (2015).

M. Usman, D. Atkinson, C. Kolbitsch, T. Schaeffter, C. Prieto
Manifold learning based ECG-free free-breathing cardiac CINE MRI
Opens external link in new window J Magn Reson Imaging 41, 1521-7 (2015).

C. Kolbitsch, C. Prieto, T. Schaeffter
Cardiac functional assessment without electrocardiogram using physiological self-navigation
Opens external link in new window Magn Reson Med 71, 942-54 (2014). 

C. Kolbitsch, C. Prieto, C. Tsoumpas, T. Schaeffter
A 3D MR-acquisition scheme for nonrigid bulk motion correction in simultaneous PET-MR
Opens external link in new window Medical Physics 41, 082304 (2014).

D. Peressutti, G. Penney, C. Kolbitsch, A. King
Personalising population-based respiratory motion models of the heart using neighbourhood approximation based on learnt anatomical features
Opens external link in new window Med Image Anal 18, 1015-25 (2014).

C. Baumgartner, C. Kolbitsch, D. Balfour, P. Marsden, J. McClelland, D. Rueckert, A. King
High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment
Opens external link in new window Med Image Anal 18, 939-52 (2014).

G. Vaillant, C. Prieto, C. Kolbitsch, G. Penney, T. Schaeffter
Retrospective Rigid Motion Correction in k-Space for Segmented Radial MRI
Opens external link in new window IEEE Trans Med Imaging 33, 1-10 (2014).

D. Peressutti, G. Penney, R. Housden, C. Kolbitsch, A. Gomez, E. Rijkhorst, D. Barratt, K. Rhode, A. King
A novel Bayesian respiratory motion model to estimate and resolve uncertainty in image-guided cardiac interventions
Opens external link in new window Med Image Anal 17, 488-502 (2013).

M. Usman, D. Atkinson, F. Odille, C. Kolbitsch, G. Vaillant, T. Schaeffter, P. Batchelor, C. Prieto
Motion corrected compressed sensing for free-breathing dynamic cardiac MRI
Opens external link in new window Magn Reson Med 70, 504-16 (2013).

C. Kolbitsch, C. Prieto, C. Buerger, J. Harrison, R. Razavi, J. Smink, T. Schaeffter
Prospective high-resolution respiratory-resolved whole-heart MRI for image-guided cardiovascular interventions
Opens external link in new window Magn Reson Med 68, 205-13 (2012).

Z. Chen, C. Kolbitsch, J. Smink, J. Harrison, V. Puntmann, E. Nagel, R. Razavi, A. Rinaldi, T. Schaeffter
Hybrid Phase ordering with Automatic Window Selection (HybridPAWS) improves respiratory-navigator efficiency during 3D late-gadolinium enhancement CMR in patients with chronic heart failure and irregular respiratory pattern
J Cardiovasc Magn Reson14, P256 (2012).

C. Kolbitsch, C. Prieto, J. Smink, T. Schaeffter
Highly efficient whole-heart imaging using radial phase encoding-phase ordering with automatic window selection
Opens external link in new window Magn Reson Med 66, 1008-18 (2011).

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