MR-based motion correction for PET imaging using wired active MR microcoils in simultaneous PET-MR: phantom study.

PURPOSE Artifacts caused by head motion present a major challenge in brain positron emission tomography (PET) imaging. The authors investigated the feasibility of using wired active MR microcoils to track head motion and incorporate the measured rigid motion fields into iterative PET reconstruction. METHODS Several wired active MR microcoils and a dedicated MR coil-tracking sequence were developed. The microcoils were attached to the outer surface of an anthropomorphic(18)F-filled Hoffman phantom to mimic a brain PET scan. Complex rotation/translation motion of the phantom was induced by a balloon, which was connected to a ventilator. PET list-mode and MR tracking data were acquired simultaneously on a PET-MR scanner. The acquired dynamic PET data were reconstructed iteratively with and without motion correction. Additionally, static phantom data were acquired and used as the gold standard. RESULTS Motion artifacts in PET images were effectively removed by wired active MR microcoil based motion correction. Motion correction yielded an activity concentration bias ranging from -0.6% to 3.4% as compared to a bias ranging from -25.0% to 16.6% if no motion correction was applied. The contrast recovery values were improved by 37%-156% with motion correction as compared to no motion correction. The image correlation (mean ± standard deviation) between the motion corrected (uncorrected) images of 20 independent noise realizations and static reference was R(2) = 0.978 ± 0.007 (0.588 ± 0.010, respectively). CONCLUSIONS Wired active MR microcoil based motion correction significantly improves brain PET quantitative accuracy and image contrast.

[1]  Lutz Tellmann,et al.  Concepts of registration and correction of head motion in positron emission tomography. , 2006, Zeitschrift fur medizinische Physik.

[2]  L. Sokoloff,et al.  Effects of anesthesia on functional activation of cerebral blood flow and metabolism , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[3]  J. Mazziotta,et al.  Rapid Automated Algorithm for Aligning and Reslicing PET Images , 1992, Journal of computer assisted tomography.

[4]  Brian F. Hutton,et al.  Practical aspects of a data-driven motion correction approach for brain SPECT , 2003, IEEE Transactions on Medical Imaging.

[5]  Ciprian Catana,et al.  MRI-Assisted PET Motion Correction for Neurologic Studies in an Integrated MR-PET Scanner , 2011, The Journal of Nuclear Medicine.

[6]  Ciprian Catana,et al.  MRI-Based Nonrigid Motion Correction in Simultaneous PET/MRI , 2012, The Journal of Nuclear Medicine.

[7]  Dan Rettmann,et al.  PROMO: Real‐time prospective motion correction in MRI using image‐based tracking , 2010, Magnetic resonance in medicine.

[8]  Juha Koikkalainen,et al.  Combination of Biomarkers: PET [18F]Flutemetamol Imaging and Structural MRI in Dementia and Mild Cognitive Impairment , 2012, Neurodegenerative Diseases.

[9]  Saikat Sengupta,et al.  Prospective real‐time head motion correction using inductively coupled wireless NMR probes , 2014, Magnetic resonance in medicine.

[10]  R. Koeppe,et al.  A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[11]  Murat Aksoy,et al.  Prospective motion correction using inductively coupled wireless RF coils , 2013, Magnetic resonance in medicine.

[12]  André J W van der Kouwe,et al.  Real‐time rigid body motion correction and shimming using cloverleaf navigators , 2006, Magnetic resonance in medicine.

[13]  Quanzheng Li,et al.  Cardiac motion compensation and resolution modeling in simultaneous PET-MR: a cardiac lesion detection study , 2013, Physics in medicine and biology.

[14]  S J Riederer,et al.  Algorithms for extracting motion information from navigator echoes , 1996, Magnetic resonance in medicine.

[15]  Cornelis H. Slump,et al.  MRI modalitiy transformation in demon registration , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[16]  Jordan Muraskin,et al.  Echo‐planar imaging with prospective slice‐by‐slice motion correction using active markers , 2011, Magnetic resonance in medicine.

[17]  K. S. Arun,et al.  Least-Squares Fitting of Two 3-D Point Sets , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  A. Arnsten,et al.  Stress impairs prefrontal cortical function in rats and monkeys: role of dopamine D1 and norepinephrine α-1 receptor mechanisms , 2000 .

[19]  Karl J. Friston,et al.  Spatial registration and normalization of images , 1995 .

[20]  Margaret E. Daube-Witherspoon,et al.  A head motion measurement system suitable for emission computed tomography , 1997, IEEE Transactions on Medical Imaging.

[21]  Michael E Phelps,et al.  Impact of animal handling on the results of 18F-FDG PET studies in mice. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[22]  Donald S. Williams,et al.  Cerebral perfusion during anesthesia with fentanyl, isoflurane, or pentobarbital in normal rats studied by arterial spin‐labeled MRI , 2001, Magnetic resonance in medicine.

[23]  A Villringer,et al.  Characterization of CBF response to somatosensory stimulation: model and influence of anesthetics. , 1993, The American journal of physiology.

[24]  Sascha Krueger,et al.  Prospective real‐time correction for arbitrary head motion using active markers , 2009, Magnetic resonance in medicine.

[25]  J. Felmlee,et al.  Adaptive technique for high-definition MR imaging of moving structures. , 1989, Radiology.

[26]  D. Skerrett,et al.  A hybrid 3-D reconstruction/registration algorithm for correction of head motion in emission tomography , 2000 .

[27]  Zion Tsz Ho Tse,et al.  Prospective motion correction using tracking coils , 2013, Magnetic resonance in medicine.

[28]  R. Siddon Fast calculation of the exact radiological path for a three-dimensional CT array. , 1985, Medical physics.

[29]  William J. Jagust,et al.  The Use of MRI and PET for Clinical Diagnosis of Dementia and Investigation of Cognitive Impairment : A Consensus Report , 2004 .

[30]  Roger Fulton,et al.  The design and implementation of a motion correction scheme for neurological PET. , 2003, Physics in medicine and biology.

[31]  C. J. Thompson,et al.  Motion correction of PET images using multiple acquisition frames , 1997, IEEE Transactions on Medical Imaging.

[32]  Murat Aksoy,et al.  Prospective Rigid-Body Motion Correction Using Miniature Wireless RF-Coils as Position Tracking Probes , 2012 .

[33]  Derek A. Linkens,et al.  Estimation of Latency Changes and Relative Amplitudes in Somatosensory Evoked Potentials Using Wavelets and Regression , 1999, Comput. Biomed. Res..