Novel MR imaging technologies

The study of brain disease with MRI requires images of the highest quality. However head motion, or physiological effects such as cardiac pulsation, lead to degradation of image quality. We develop technologies that enable the acquisition of high-quality MR images in non-compliant patient populations.

Correction of head motion effects

Motion artefacts may be present in MR images despite the use of motion correction techniques (left). The suspension technique developed in our laboratory allows for the acquisition of high quality MR images in non-compliant patient populations (right). Taken from Castella et al.

Prospective head motion correction during MRI examinations

Head motion during MRI examinations leads to a degradation of image quality. The LREN laboratory is equipped with an optical camera system (Kineticor) that allows the prospective correction of head motion, in real-time during MRI examinations. With this technology, the position of the head captured by the camera is passed on to the MRI scanner which is adjusted in real-time during the scans to account for the motion.

Despite this technology, strong motion artefacts may remain in MR images. In our laboratory, we address this by suspending the acquisition of data during periods of head motion. This approach is time-efficient: the suspension preferentially targets the most sensitive periods of data acquisition, to minimize the resulting prolongation of scan time. This approach is also flexible: the suspension of the acquisition is triggered above a threshold that can be adjusted by the user to accomodate patients' tolerance of scan duration.

Reference

Castella R, Arn L, Dupuis E, Callaghan MF, Draganski B, Lutti A. Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion. Magnetic Resonance in Medicine (2018) DOI: 10.1002/mrm.27214

In standard analyses, the loss of image quality due to head motion leads to a non-uniform distribution of image noise across datasets ('heteroscedasticity'), undermining the validity of statistical tests (figure A). The QUIQI method developed by our group restores homoscedasticity. With QUIQI, the strongest improvements lie in frontal regions consistently with the supine position of patients during MRI examination (figure B). Taken from Lutti et al. 2022

Retrospective correction of motion degradation in analyses of MRI data

The prospective correction technology introduced above is only available in a few research centres worldwide: most MRI examinations are conducted without motion correction technology. As a result, the data analysed in neuroscience studies likely exhibit a loss of quality due to head motion. In standard analyses, this results in a non-uniform distribution of image noise across datasets ('heteroscedasticity') which undermines the validity of statistical tests (figure A).

To address this issue, our group has developed a method that accounts for the loss of image quality in the analysis of the data. This technique, called QUIQI for ‘analysis of QUantitative Imaging data using a Quality Index’, restores the homoscedasticity assumption of statistical tests (figure A). This method performs optimally in all brain regions, although head motion effects are local. With QUIQI, the strongest improvements lie in frontal regions (figure B), consistently with the supine position of patients during MRI examination, with the back of the head resting on the scanner table.

Reference

Lutti A, Corbin N, Ashburner J, Ziegler G, Draganski B, Phillips C, Kherif F, Callaghan MF, Di Domenicantonio G. Restoring statistical validity in group analyses of motion-corrupted MRI data. Human Brain Mapping (2022). DOI: 10.1002/hbm.25767

Corbin N, Oliveira R, Raynaud R, Di Domenicantonio G, Draganski B, Kherif F, Callaghan MF, Lutti A. Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans. Journal of Neuroscience Methods. DOI: 10.1016/j.jneumeth.2023.109950

Correcting cardiac pulsation effects on brain MR images

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Changes in brain maps of the MRI parameter R2* across the cardiac cycle. Taken from Raynaud et al., 2023.

Cardiac pulsation enhances the noise level in MR images of the brain and hinders the use of MRI to study brain disease. We have conducted an extensive characterization of cardiac-induced noise in brain relaxometry images to assess its amplitude, spatial extent and timing. From this fingerprint, we now aim to design acquisition strategies that will mitigate cardiac-induced noise in brain relaxometry data.

Reference

Raynaud Q, Di Domenicantonio G, Yerly J, Dardano T, van Heeswijk R, Lutti A. A characterization of cardiac-induced noise in R2* maps of the brain. Magn. Reson. Med. In press (2023). DOI: 10.1002/mrm.29853

Raynaud Q, Dardano T, Roy CW, Yerly J, Kober T, van Heeswijk R, Lutti A. Data acquisition strategies to mitigate cardiac-induced noise in quantitative R2* maps of the brain. in 32nd Annual Meeting of the International Society for Magnetic Resonance in Medicine, Toronto, Canada 3945 (2023).

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