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Tsai YJ, Liu C. Joint motion estimation and penalized image reconstruction algorithm with anatomical priors for gated TOF-PET/CT. Phys Med Biol 2023; 68. [PMID: 36549009 DOI: 10.1088/1361-6560/acae19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
The presence of respiratory motion not only degrades the reconstructed image but also limits the utilization of anatomical priors in emission tomography. In this study, we explore the potential application of a joint motion estimation and penalized image reconstruction algorithm using anatomical priors in gated time-of-flight positron emission tomography/computed tomography (PET/CT). The algorithm is able to warp both the activity image and the attenuation map to align them with the measured data with the facilitation of anatomical information contained in the attenuation map. Five patient datasets, three acquired in single-bed position and two acquired in whole-body continuous-bed-motion mode, are included. For each patient, the attenuation map is derived from a breath-hold CT. The Parallel Levels Sets (PLS) is chosen as a representative anatomical prior. In addition to demonstrating the reliability of the estimated motion and the benefits of incorporating anatomical prior, preliminary results also indicate that the algorithm shows the potential to reconstruct an activity image in the space corresponding to that of the attenuation map, which could be applied to address the potential misalignment issue in applications involving multiple PET acquisitions but a single CT.
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Affiliation(s)
- Yu-Jung Tsai
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, United States of America.,Canon Medical Research USA, Inc., Vernon Hills, IL 60061, United States of America
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, United States of America
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Lamare F, Bousse A, Thielemans K, Liu C, Merlin T, Fayad H, Visvikis D. PET respiratory motion correction: quo vadis? Phys Med Biol 2021; 67. [PMID: 34915465 DOI: 10.1088/1361-6560/ac43fc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 12/16/2021] [Indexed: 11/12/2022]
Abstract
Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.
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Affiliation(s)
- Frederic Lamare
- Nuclear Medicine Department, University Hospital Centre Bordeaux Hospital Group South, ., Bordeaux, Nouvelle-Aquitaine, 33604, FRANCE
| | - Alexandre Bousse
- LaTIM, INSERM UMR1101, Université de Bretagne Occidentale, ., Brest, Bretagne, 29285, FRANCE
| | - Kris Thielemans
- University College London Institute of Nuclear Medicine, UCL Hospital, Tower 5, 235 Euston Road, London, NW1 2BU, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Chi Liu
- Department of Diagnostic Radiology, Yale University School of Medicine Department of Radiology and Biomedical Imaging, PO Box 208048, 801 Howard Avenue, New Haven, Connecticut, 06520-8042, UNITED STATES
| | - Thibaut Merlin
- LaTIM, INSERM UMR1101, Universite de Bretagne Occidentale, ., Brest, Bretagne, 29285, FRANCE
| | - Hadi Fayad
- Weill Cornell Medicine - Qatar, ., Doha, ., QATAR
| | - Dimitris Visvikis
- LaTIM, UMR1101, Universite de Bretagne Occidentale, INSERM, Brest, Bretagne, 29285, FRANCE
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Abstract
PET/CT has become a preferred imaging modality over PET-only scanners in clinical practice. However, along with the significant improvement in diagnostic accuracy and patient throughput, pitfalls on PET/CT are reported as well. This review provides a general overview on the potential influence of the limitations with respect to PET/CT instrumentation and artifacts associated with the modality integration on the image appearance and quantitative accuracy of PET. Approaches proposed in literature to address the limitations or minimize the artifacts are discussed as well as their current challenges for clinical applications. Although the CT component can play an important role in assisting clinical diagnosis, we concentrate on the imaging scenarios where CT is used to provide auxiliary information for attenuation compensation and scatter correction in PET.
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Affiliation(s)
- Yu-Jung Tsai
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT
| | - Chi Liu
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT; Department of Biomedical Engineering, Yale University, New Haven, CT.
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Tsai YJ, Bousse A, Arridge S, Stearns CW, Hutton BF, Thielemans K. Penalized PET/CT Reconstruction Algorithms With Automatic Realignment for Anatomical Priors. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2021. [DOI: 10.1109/trpms.2020.3025540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Emond EC, Bousse A, Brusaferri L, Hutton BF, Thielemans K. Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2020.3001094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Yang J, Liu J, Wiesinger F, Menini A, Zhu X, Hope TA, Seo Y, Larson PEZ. Developing an efficient phase-matched attenuation correction method for quiescent period PET in abdominal PET/MRI. Phys Med Biol 2018; 63:185002. [PMID: 30106008 DOI: 10.1088/1361-6560/aada26] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Respiratory motion causes misalignments between positron emission tomography (PET) and magnetic resonance (MR)-derived attenuation maps (µ-maps) in addition to artifacts on both PET and MR images in simultaneous PET/MRI for organs such as liver that can experience motion of several centimeters. To address this problem, we developed an efficient MR-based attenuation correction (MRAC) method to generate phase-matched µ-maps for quiescent period PET (PETQ) in abdominal PET/MRI. MRAC data was acquired with CIRcular Cartesian UnderSampling (CIRCUS) sampling during 100 s in free-breathing as an accelerated data acquisition strategy for phase-matched MRAC (MRACPM-CIRCUS). For comparison, MRAC data with raster (Default) k-space sampling was also acquired during 100 s in free-breathing (MRACPM-Default), and used to evaluate MRACPM-CIRCUS as well as un-matched MRAC (MRACUM) that was un-gated. We purposefully oversampled the MRACPM data to ensure we had enough information to capture all respiratory phases to make this comparison as robust as possible. The proposed MRACPM-CIRCUS was evaluated in 17 patients with 68Ga-DOTA-TOC PET/MRI exams, suspected of having neuroendocrine tumors or liver metastases. Effects of CIRCUS sampling for accelerating a data acquisition were evaluated by simulating the data acquisition time retrospectively in increments of 5 s. Effects of MRACPM-CIRCUS on PETQ were evaluated using uptake differences in the liver lesions (n = 35), compared to PETQ with MRACPM-Default and MRACUM. A Wilcoxon signed-rank test was performed to compare lesion uptakes between the MRAC methods. MRACPM-CIRCUS showed higher image quality compared to MRACPM-Default for the same acquisition times, demonstrating that a data acquisition time of 30 s was reasonable to achieve phase-matched µ-maps. Lesion update differences between MRACPM-CIRCUS (30 s) versus MRACPM-Default (reference, 100 s) were 0.1% ± 1.4% (range of -2.7% to 3.2%) and not significant (P > .05); while, the differences between MRACUM versus MRACPM-Default were 0.6% ± 11.4% with a large variation (range of -37% to 20%) and significant (P < .05). In conclusion, we demonstrated that a data acquisition of 30 s achieved phase-matched µ-maps when using specialized CIRCUS data sampling and phase-matched µ-maps improved PETQ quantification significantly.
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Affiliation(s)
- Jaewon Yang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States of America. UCSF Physics Research Laboratory, 185 Berry Street, Suite 350, San Francisco, CA 94143-0946, United States of America. Author to whom any correspondence should be addressed
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Cuplov V, Holman BF, McClelland J, Modat M, Hutton BF, Thielemans K. Issues in quantification of registered respiratory gated PET/CT in the lung. ACTA ACUST UNITED AC 2017; 63:015007. [DOI: 10.1088/1361-6560/aa950b] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Salvo K, Defrise M. sMLACF: a generalized expectation-maximization algorithm for TOF-PET to reconstruct the activity and attenuation simultaneously. ACTA ACUST UNITED AC 2017; 62:8283-8313. [DOI: 10.1088/1361-6560/aa82ea] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Bousse A, Manber R, Holman BF, Atkinson D, Arridge S, Ourselin S, Hutton BF, Thielemans K. Evaluation of a direct motion estimation/correction method in respiratory-gated PET/MRI with motion-adjusted attenuation. Med Phys 2017; 44:2379-2390. [DOI: 10.1002/mp.12253] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Revised: 03/01/2017] [Accepted: 03/21/2017] [Indexed: 11/10/2022] Open
Affiliation(s)
- Alexandre Bousse
- Institute of Nuclear Medicine; University College London; London NW1 2BU UK
| | - Richard Manber
- Institute of Nuclear Medicine; University College London; London NW1 2BU UK
| | - Beverley F. Holman
- Institute of Nuclear Medicine; University College London; London NW1 2BU UK
| | - David Atkinson
- Centre for Medical Imaging; University College London; London NW1 2PG UK
| | - Simon Arridge
- Centre for Medical Image Computing; University College London; London WC1E 7JE UK
| | - Sébastien Ourselin
- Centre for Medical Image Computing; University College London; London WC1E 7JE UK
| | - Brian F. Hutton
- Institute of Nuclear Medicine; University College London; London NW1 2BU UK
- Centre for Medical Radiation Physics; University of Wollongong; Wollongong NSW 2522 Australia
| | - Kris Thielemans
- Institute of Nuclear Medicine; University College London; London NW1 2BU UK
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Kalantari F, Wang J. Attenuation correction in 4D-PET using a single-phase attenuation map and rigidity-adaptive deformable registration. Med Phys 2017; 44:522-532. [PMID: 27987223 DOI: 10.1002/mp.12063] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 12/03/2016] [Accepted: 12/05/2016] [Indexed: 11/11/2022] Open
Abstract
PURPOSE Four-dimensional positron emission tomography (4D-PET) imaging is a potential solution to the respiratory motion effect in the thoracic region. Computed tomography (CT)-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference between 4D-PET and a single attenuation map from CT, typically available in routine clinical scanning, motion artifacts are observed in the attenuation-corrected PET images, leading to errors in tumor shape and uptake. We introduced a practical method to align single-phase CT with all other 4D-PET phases for AC. METHODS A penalized non-rigid Demons registration between individual 4D-PET frames without AC provides the motion vectors to be used for warping single-phase attenuation map. The non-rigid Demons registration was used to derive deformation vector fields (DVFs) between PET matched with the CT phase and other 4D-PET images. While attenuated PET images provide useful data for organ borders such as those of the lung and the liver, tumors cannot be distinguished from the background due to loss of contrast. To preserve the tumor shape in different phases, an ROI-covering tumor was excluded from nonrigid transformation. Instead the mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of the tumor along with a nonrigid transformation of other organs. A 4D-XCAT phantom with spherical lung tumors, with diameters ranging from 10 to 40 mm, was used to evaluate the algorithm. The performance of the proposed hybrid method for attenuation map estimation was compared to (a) the Demons nonrigid registration only and (b) a single attenuation map based on quantitative parameters in individual PET frames. RESULTS Motion-related artifacts were significantly reduced in the attenuation-corrected 4D-PET images. When a single attenuation map was used for all individual PET frames, the normalized root-mean-square error (NRMSE) values in tumor region were 49.3% (STD: 8.3%), 50.5% (STD: 9.3%), 51.8% (STD: 10.8%) and 51.5% (STD: 12.1%) for 10-mm, 20-mm, 30-mm, and 40-mm tumors, respectively. These errors were reduced to 11.9% (STD: 2.9%), 13.6% (STD: 3.9%), 13.8% (STD: 4.8%), and 16.7% (STD: 9.3%) by our proposed method for deforming the attenuation map. The relative errors in total lesion glycolysis (TLG) values were -0.25% (STD: 2.87%) and 3.19% (STD: 2.35%) for 30-mm and 40-mm tumors, respectively, in proposed method. The corresponding values for Demons method were 25.22% (STD: 14.79%) and 18.42% (STD: 7.06%). Our proposed hybrid method outperforms the Demons method especially for larger tumors. For tumors smaller than 20 mm, nonrigid transformation could also provide quantitative results. CONCLUSION Although non-AC 4D-PET frames include insignificant anatomical information, they are still useful to estimate the DVFs to align the attenuation map for accurate AC. The proposed hybrid method can recover the AC-related artifacts and provide quantitative AC-PET images.
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Affiliation(s)
- Faraz Kalantari
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, 75235-8808, USA
| | - Jing Wang
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, 75235-8808, USA
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Gillam JE, Angelis GI, Meikle SR. List-mode image reconstruction for positron emission tomography using tetrahedral voxels. Phys Med Biol 2016; 61:N497-N513. [PMID: 27552113 DOI: 10.1088/0031-9155/61/18/n497] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Image space decomposition based on tetrahedral voxels are interesting candidates for use in emission tomography. Tetrahedral voxels provide many of the advantages of point clouds with irregular spacing, such as being intrinsically multi-resolution, yet they also serve as a volumetric partition of the image space and so are comparable to more standard cubic voxels. Additionally, non-rigid displacement fields can be applied to the tetrahedral mesh in a straight-forward manner. So far studies incorporating tetrahedral decomposition of the image space have concentrated on pre-calculated, node-based, system matrix elements which reduces the flexibility of the tetrahedral approach and the capacity to accurately define regions of interest. Here, a list-mode on-the-fly calculation of the system matrix elements is described using a tetrahedral decomposition of the image space and volumetric elements-voxels. The algorithm is demonstrated in the context of awake animal PET which may require both rigid and non-rigid motion compensation, as well as quantification within small regions of the brain. This approach allows accurate, event based, motion compensation including non-rigid deformations.
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Affiliation(s)
- John E Gillam
- Faculty of Health Sciences, University of Sydney, New South Wales 2006, Australia. Brain and Mind Centre, Camperdown, New South Wales 2050, Australia
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