Nonrigid PET motion compensation in the lower abdomen using simultaneous tagged-MRI and PET imaging

Abstract

Purpose: We propose a novel approach for PET respiratory motion correction using tagged-MRI and simultaneous PET-MRI acquisitions. Methods: We use a tagged-MRI acquisition followed by motion tracking in the phase domain to estimate the nonrigid deformation of biological tissues during breathing. In order to accurately estimate motion even in the presence of noise and susceptibility artifacts, we regularize the traditional HARP tracking strategy using a quadratic roughness penalty on neighboring displacement vectors (R-HARP). We then incorporate the motion fields estimated with R-HARP in the system matrix of an MLEM PET reconstruction algorithm formulated both for sinogram and list-mode data representations. This approach allows reconstruction of all detected coincidences in a single image while modeling the effect of motion both in the emission and the attenuation maps. At present, tagged-MRI does not allow estimation of motion in the lungs and our approach is therefore limited to motion correction in soft tissues. Since it is difficult to assess the accuracy of motion correction approaches in vivo, we evaluated the proposed approach in numerical simulations of simultaneous PET-MRI acquisitions using the NCAT phantom. We also assessed its practical feasibility in PET-MRI acquisitions of a small deformable phantom that mimics the complex deformation pattern of a lung that we imaged on a combined PET-MRI brain scanner. Results: Simulations showed that the R-HARP tracking strategy accurately estimated realistic respiratory motion fields for different levels of noise in the tagged-MRI simulation. In simulations of tumors exhibiting increased uptake, contrast estimation was 20% more accurate with motion correction than without. Signal-to-noise ratio (SNR) was more than 100% greater when performing motion-corrected reconstruction which included all counts, compared to when reconstructing only coincidences detected in the first of eight gated frames. These results were confirmed in our proofof-principle PET-MRI acquisitions, indicating that our motion correction strategy is accurate, practically feasible, and is therefore ready to be tested in vivo. Conclusions: This work shows that PET motion correction using motion fields measured with tagged-MRI in simultaneous PET-MRI acquisitions can be made practical for clinical application and that doing so has the potential to remove motion blur in whole-body PET studies of the torso.

Reconstruction-Incorporated Respiratory Motion Correction in Clinical Simultaneous PET/MR Imaging for Oncology Applications

“…In the case of nonrigid respiratory motion, the use of 2-dimensional (2D) and 3-dimensional (3D) MR sequences for nonrigid motion compensation has been proposed and evaluated using simulated PET data (17,18), phantom studies (19,20), and rabbits and primates (21). To our knowledge, the only study for respiratory motion correction in clinical PET/ MR imaging using patient datasets was described by Wurslin et al (22).…”

The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction

“…Motion estimation from gated 4D CT was considered in [35,36], but radiation dose and motion mismatch due to sequential acquisition of CT and PET (or SPECT) were major concerns. Recent advances in simultaneous PET-MR showed potentials to estimate accurate motion from highresolution MR images without additional radiation dose and achieved substantial quantitative improvements in PET imaging [37][38][39][40]. Figure 2 shows a motion-corrected image reconstruction example using simultaneous PET-MR. A balloon phantom with attached radioactive spheres was in the gel with background activity and the motion of the balloon mimics a cardiac motion with a 1-s period.…”

“…More recently, using the fact that molecular and anatomical images are affected by the same motion, motion correction for emission tomography has been investigated. Motion information from high-resolution anatomical information such as CT [35,36] or MR [37][38][39][40] was incorporated into reconstruction for motion-corrected PET or SPECT. Ideas of using structural couplings between molecular and anatomical images for reconstruction have been studied a couple of decades ago [41][42][43].…”

Joint PET-MR respiratory motion models for clinical PET motion correction

“…To aid motion detection, MR tagging has been proposed, a technique that creates tags in MR images which can be tracked through respiration to provide the deformation information (Guerin et al 2011, Chun et al 2012. In these cases, motion tracking is done with fast dynamic MR sequences, but this means other clinical MR sequences cannot be acquired during this time.…”