Respiratory motion correction of PET using MR-constrained PET-PET registration

BackgroundRespiratory motion in positron emission tomography (PET) is an unavoidable source of error in the measurement of tracer uptake, lesion position and lesion size. The introduction of PET-MR dual modality scanners opens a new avenue for addressing this issue. Motion models offer a way to estimate motion using a reduced number of parameters. This can be beneficial for estimating motion from PET, which can otherwise be difficult due to the high level of noise of the data.MethodWe propose a novel technique that makes use of a respiratory motion model, formed from initial MR scan data. The motion model is used to constrain PET-PET registrations between a reference PET gate and the gates to be corrected. For evaluation, PET with added FDG-avid lesions was simulated from real, segmented, ultrashort echo time MR data obtained from four volunteers. Respiratory motion was included in the simulations using motion fields derived from real dynamic 3D MR volumes obtained from the same volunteers.ResultsPerformance was compared to an MR-derived motion model driven method (which requires constant use of the MR scanner) and to unconstrained PET-PET registration of the PET gates. Without motion correction, a median drop in uncorrected lesion $${\mathrm {SUV}}_{\mathrm {peak}}$$SUVpeak intensity to $$78.4 \pm 18.6 \,\,\%$$78.4±18.6% and an increase in median head-foot lesion width, specified by a minimum bounding box, to $$179 \pm 63.7\,\, \%$$179±63.7% was observed relative to the corresponding measures in motion-free simulations. The proposed method corrected these values to $$86.9 \pm 13.6\,\, \%$$86.9±13.6% ($$p<0.001$$p<0.001) and $$100 \pm 29.12\,\, \%$$100±29.12% ($$p<0.001$$p<0.001) respectively, with notably improved performance close to the diaphragm and in the liver. Median lesion displacement across all lesions was observed to be $$6.6 \pm 5.4\,\mathrm {mm}$$6.6±5.4mm without motion correction, which was reduced to $$3.5 \pm 1.8\,\mathrm {mm}$$3.5±1.8mm ($$p<0.001$$p<0.001) with motion correction.DiscussionThis paper presents a novel technique for respiratory motion correction of PET data in PET-MR imaging. After an initial 30 second MR scan, the proposed technique does not require use of the MR scanner for motion correction purposes, making it suitable for MR-intensive studies or sequential PET-MR. The accuracy of the proposed technique was similar to both comparative methods, but robustness was improved compared to the PET-PET technique, particularly in regions with higher noise such as the liver.

[1]  D. Visvikis,et al.  A posteriori respiratory motion gating of dynamic PET images , 2003, 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515).

[2]  G. J. Klein,et al.  Four-dimensional affine registration models for respiratory-gated PET , 2001 .

[3]  Kris Thielemans,et al.  Device-less gating for PET/CT using PCA , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.

[4]  P. Marsden,et al.  Retrospective data-driven respiratory gating for PET/CT , 2008, Physics in medicine and biology.

[5]  David J. Hawkes,et al.  Respiratory motion models: a review. , 2013 .

[6]  Xiaoyi Jiang,et al.  Motion Correction of Whole-Body PET Data with a Joint PET-MRI Registration Functional , 2014, BioMedical Engineering OnLine.

[7]  Tobias Schaeffter,et al.  Hierarchical adaptive local affine registration for fast and robust respiratory motion estimation , 2011, Medical Image Anal..

[8]  John W. Clark,et al.  A motion-incorporated reconstruction method for gated PET studies , 2006, Physics in medicine and biology.

[9]  H. William Strauss,et al.  Recent Advances in the Molecular Imaging of Programmed Cell Death: Part II—Non–Probe-Based MRI, Ultrasound, and Optical Clinical Imaging Techniques , 2013, The Journal of Nuclear Medicine.

[10]  G Malandain,et al.  Model-based respiratory motion compensation for emission tomography image reconstruction , 2007, Physics in medicine and biology.

[11]  Kris Thielemans,et al.  Comparison of different methods for data-driven respiratory gating of PET data , 2013, 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC).

[12]  Holger Schmidt,et al.  Reconstruction-Incorporated Respiratory Motion Correction in Clinical Simultaneous PET/MR Imaging for Oncology Applications , 2015, The Journal of Nuclear Medicine.

[13]  Lei Xing,et al.  Model-based image reconstruction for four-dimensional PET. , 2006, Medical physics.

[14]  N. Schwenzer,et al.  Respiratory Motion Correction in Oncologic PET Using T1-Weighted MR Imaging on a Simultaneous Whole-Body PET/MR System , 2013, The Journal of Nuclear Medicine.

[15]  Jinhua Long,et al.  Investigations of the functional states of dendritic cells under different conditioned microenvironments by Fourier transformed infrared spectroscopy , 2014, Biomedical engineering online.

[16]  C Tsoumpas,et al.  Analysis and comparison of two methods for motion correction in PET imaging. , 2012, Medical physics.

[17]  Michael Brady,et al.  Regularized B-spline deformable registration for respiratory motion correction in PET images , 2008, 2008 IEEE Nuclear Science Symposium Conference Record.

[18]  Joachim Hornegger,et al.  Self-gated MRI motion modeling for respiratory motion compensation in integrated PET/MRI , 2015, Medical Image Anal..

[19]  Jeffrey A. Fessler,et al.  Noise Properties of Motion-Compensated Tomographic Image Reconstruction Methods , 2013, IEEE Transactions on Medical Imaging.

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

[21]  S. Nekolla,et al.  Postacquisition Detection of Tumor Motion in the Lung and Upper Abdomen Using List-Mode PET Data: A Feasibility Study , 2007, Journal of Nuclear Medicine.

[22]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[23]  R. Lecomte,et al.  Respiratory gating for 3-dimensional PET of the thorax: feasibility and initial results. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[24]  K Thielemans,et al.  The effect of regularization in motion compensated PET image reconstruction: a realistic numerical 4D simulation study , 2013, Physics in medicine and biology.

[25]  T Schaeffter,et al.  Thoracic respiratory motion estimation from MRI using a statistical model and a 2-D image navigator , 2012, Medical Image Anal..

[26]  Paul E Kinahan,et al.  The impact of respiratory motion on tumor quantification and delineation in static PET/CT imaging , 2009, Physics in medicine and biology.

[27]  Xiaoyi Jiang,et al.  Lung motion correction on respiratory gated 3-D PET/CT images , 2006, IEEE Transactions on Medical Imaging.

[28]  A. Pevsner,et al.  The CT motion quantitation of lung lesions and its impact on PET-measured SUVs. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[29]  Daniel Rueckert,et al.  High-resolution dynamic MR imaging of the thorax for respiratory motion correction of PET using groupwise manifold alignment , 2014, Medical Image Anal..

[30]  C. Tsoumpas,et al.  STIR: software for tomographic image reconstruction release 2 , 2012, 2006 IEEE Nuclear Science Symposium Conference Record.

[31]  S. Nehmeh,et al.  Respiratory motion in positron emission tomography/computed tomography: a review. , 2008, Seminars in nuclear medicine.

[32]  Simon Ameer-Beg,et al.  Biomedical Imaging: From Nano to Macro , 2008 .

[33]  P. K. Marsden,et al.  Investigation of MR-Based Attenuation Correction and Motion Compensation for Hybrid PET/MR , 2012, IEEE Transactions on Nuclear Science.

[34]  Rongping Zeng,et al.  Iterative sorting for four-dimensional CT images based on internal anatomy motion. , 2008, Medical physics.

[35]  G Starkschall,et al.  Respiratory-driven lung tumor motion is independent of tumor size, tumor location, and pulmonary function. , 2001, International journal of radiation oncology, biology, physics.

[36]  M. V. van Herk,et al.  Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. , 2002, International journal of radiation oncology, biology, physics.

[37]  Balraj Naren,et al.  Medical Image Registration , 2022 .

[38]  C. Tsoumpas,et al.  Real-time respiratory motion correction for simultaneous PET-MR using an MR-derived motion model , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.

[39]  T Schaeffter,et al.  Fast generation of 4D PET-MR data from real dynamic MR acquisitions , 2011, Physics in medicine and biology.

[40]  R. Mohan,et al.  Motion adaptive x-ray therapy: a feasibility study , 2001, Physics in medicine and biology.

[41]  Thomas Beyer,et al.  Dual-modality PET/CT imaging: the effect of respiratory motion on combined image quality in clinical oncology , 2003, European Journal of Nuclear Medicine and Molecular Imaging.

[42]  David Atkinson,et al.  Practical PET Respiratory Motion Correction in Clinical PET/MR , 2015, The Journal of Nuclear Medicine.

[43]  Tobias Schaeffter,et al.  Assessment of input signal positioning for cardiac respiratory motion models during different breathing patterns , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[44]  Brian F. Hutton,et al.  4-D Generative Model for PET/MRI Reconstruction , 2011, MICCAI.