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MR-PET head motion correction based on co-registration of multicontrast MR images

1 February 2020

Zhaolin Chen, Francesco Sforazzini, Jakub Baran, Thomas Close, Nadim Jon Shah, Gary F. Egan

When measurements using separate MRI and PET machines are taken, they are not taken under exactly the same physiological conditions. Therefore, the simultaneous acquisition of MR and PET images is highly valuable as it enables multi-parametric imaging at the same time-point and physiological condition. However, simultaneous acquisitions can be lengthy and subject head motion can cause image artefacts, leading to the degradation of the quantitative accuracy of the reconstructed images.

Although there are a number of techniques for motion correction, they are often time consuming, requiring expensive hardware, or inaccurate.

In this article, a fully automated PET motion correction method is introduced known as MR-guided MAF. The method is based on the co-registration of multi-contrast MR images and was evaluated using MR-PET data acquired from a cohort of ten healthy participants who received a slow infusion of fluorodeoxyglucose ([18-F]FDG).

In this collaborative study led by our colleagues at Monash University, Melbourne, Australia, it is shown that, compared with conventional methods, MR-guided PET image reconstruction can reduce artefacts introduced by head motion and improve the image sharpness and quantitative accuracy of PET images acquired using simultaneous MR-PET scanners.

The fully automated motion estimation method has been implemented as a publicly available web-service. relaxation times of water molecules are dependent on the microstructural environment and, as such, can provide vital information about tissue damage in various neurological pathologies, such as multiple sclerosis, epilepsy, psychotic disorders, dementia, and traumatic brain injury.

Comparison of the motion correction results between the MR‐guided MAF, fixed‐MAF and for the images without motion correction, for a dynamic PET reconstruction for one test subject.

Original publication:

MR-PET head motion correction based on co-registration of multicontrast MR images