Magnetic resonance-based motion correction for positron emission tomography imaging

Abstract

Positron emission tomography (PET) image quality is limited by patient motion. Emission data are blurred owing to cardiac and/or respiratory motion. Although spatial resolution is 4 mm for standard clinical whole-body PET scanners, the effective resolution can be as low as 1 cm owing to motion. Additionally, the deformation of attenuation medium causes image artifacts. Previously, gating has been used to "freeze" the motion, but led to significantly increased noise level. Simultaneous PET/magnetic resonance (MR) modality offers a new way to perform PET motion correction. MR can be used to measure 3-dimensional motion fields, which can then be incorporated into the iterative PET reconstruction to obtain motion-corrected PET images. In this report, we present MR imaging techniques to acquire dynamic images, a nonrigid image registration algorithm to extract motion fields from acquired MR images, and a PET reconstruction algorithm with motion correction. We also present results from both phantom and in vivo animal PET/MR studies. We demonstrate that MR-based PET motion correction using simultaneous PET/MR improves image quality and lesion detectability compared with gating and no motion correction.

Figure 1

Compounded effect of motion and attenuation: The arrows show an apparent myocardial perfusion defect due to different motion patterns between sequential PET and CT, which, associated to substantial differences in attenuation between lungs and soft tissue, yields the severe apparent anterolateral “defect”. No stenosis was seen on subsequent catheterization nor repeated imaging.

Figure 2

The relationship between heart and diaphragm motion.

Figure 3

A matrix of combinations of cardiac and respiratory phases.

Figure 4

The MR sequence that is used to measure the cardiac motion and monitor the respiratory phase.

Figure 5

(A) Deformable cardiac phantom. (B) Coronal MR slice without and with tagging. (C) Coronal PET slices for Uncorrected, Gated, MR motion corrected with full k-space, and MR motion corrected with half k-space. Noise σ was computed over 15 noise realizations.

Figure 6

Contrast (1−defect/myocardium) and CHO SNR for each of the three defects placed in the cardiac phantom.

Figure 7

(A,B,C) PET images of a rabbit reconstructed from a 5-min scan using Uncorrected, Gated, and MR motion corrected methods. (D) PET image reconstructed from a 30-min scan using Gated method. (E) Tagged MR image with the estimated motion fields.

Figure 8

(A,B,C) PET images of a free-breathing monkey reconstructed from a 6-min scan using Uncorrected, Gated, and MR motion corrected methods. (D) PET image reconstructed from a 30-min scan using Gated method.