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Miranda A, Bertoglio D, Stroobants S, Staelens S, Verhaeghe J. Translation of Preclinical PET Imaging Findings: Challenges and Motion Correction to Overcome the Confounding Effect of Anesthetics. Front Med (Lausanne) 2021; 8:753977. [PMID: 34746189 PMCID: PMC8569248 DOI: 10.3389/fmed.2021.753977] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 09/27/2021] [Indexed: 11/13/2022] Open
Abstract
Preclinical brain positron emission tomography (PET) in animals is performed using anesthesia to avoid movement during the PET scan. In contrast, brain PET scans in humans are typically performed in the awake subject. Anesthesia is therefore one of the principal limitations in the translation of preclinical brain PET to the clinic. This review summarizes the available literature supporting the confounding effect of anesthesia on several PET tracers for neuroscience in preclinical small animal scans. In a second part, we present the state-of-the-art methodologies to circumvent this limitation to increase the translational significance of preclinical research, with an emphasis on motion correction methods. Several motion tracking systems compatible with preclinical scanners have been developed, each one with its advantages and limitations. These systems and the novel experimental setups they can bring to preclinical brain PET research are reviewed here. While technical advances have been made in this field, and practical implementations have been demonstrated, the technique should become more readily available to research centers to allow for a wider adoption of the motion correction technique for brain research.
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Affiliation(s)
- Alan Miranda
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Daniele Bertoglio
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Sigrid Stroobants
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.,University Hospital Antwerp, Antwerp, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
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Kyme AZ, Fulton RR. Motion estimation and correction in SPECT, PET and CT. Phys Med Biol 2021; 66. [PMID: 34102630 DOI: 10.1088/1361-6560/ac093b] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 06/08/2021] [Indexed: 11/11/2022]
Abstract
Patient motion impacts single photon emission computed tomography (SPECT), positron emission tomography (PET) and X-ray computed tomography (CT) by giving rise to projection data inconsistencies that can manifest as reconstruction artifacts, thereby degrading image quality and compromising accurate image interpretation and quantification. Methods to estimate and correct for patient motion in SPECT, PET and CT have attracted considerable research effort over several decades. The aims of this effort have been two-fold: to estimate relevant motion fields characterizing the various forms of voluntary and involuntary motion; and to apply these motion fields within a modified reconstruction framework to obtain motion-corrected images. The aims of this review are to outline the motion problem in medical imaging and to critically review published methods for estimating and correcting for the relevant motion fields in clinical and preclinical SPECT, PET and CT. Despite many similarities in how motion is handled between these modalities, utility and applications vary based on differences in temporal and spatial resolution. Technical feasibility has been demonstrated in each modality for both rigid and non-rigid motion, but clinical feasibility remains an important target. There is considerable scope for further developments in motion estimation and correction, and particularly in data-driven methods that will aid clinical utility. State-of-the-art machine learning methods may have a unique role to play in this context.
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Affiliation(s)
- Andre Z Kyme
- School of Biomedical Engineering, The University of Sydney, Sydney, New South Wales, AUSTRALIA
| | - Roger R Fulton
- Sydney School of Health Sciences, The University of Sydney, Sydney, New South Wales, AUSTRALIA
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Miranda A, Staelens S, Stroobants S, Verhaeghe J. Motion Dependent and Spatially Variant Resolution Modeling for PET Rigid Motion Correction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:2518-2530. [PMID: 32070945 DOI: 10.1109/tmi.2019.2962237] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Recent advances in positron emission tomography (PET) have allowed to perform brain scans of freely moving animals by using rigid motion correction. One of the current challenges in these scans is that, due to the PET scanner spatially variant point spread function (SVPSF), motion corrected images have a motion dependent blurring since animals can move throughout the entire field of view (FOV). We developed a method to calculate the image-based resolution kernels of the motion dependent and spatially variant PSF (MD-SVPSF) to correct the loss of spatial resolution in motion corrected reconstructions. The resolution kernels are calculated for each voxel by sampling and averaging the SVPSF at all positions in the scanner FOV where the moving object was measured. In resolution phantom scans, the use of the MD-SVPSF resolution model improved the spatial resolution in motion corrected reconstructions and corrected the image deformation caused by the parallax effect consistently for all motion patterns, outperforming the use of a motion independent SVPSF or Gaussian kernels. Compared to motion correction in which the SVPSF is applied independently for every pose, our method performed similarly, but with more than two orders of magnitude faster computation time. Importantly, in scans of freely moving mice, brain regional quantification in motion-free and motion corrected images was better correlated when using the MD-SVPSF in comparison with motion independent SVPSF and a Gaussian kernel. The method developed here allows to obtain consistent spatial resolution and quantification in motion corrected images, independently of the motion pattern of the subject.
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Kyme AZ, Angelis GI, Eisenhuth J, Fulton RR, Zhou V, Hart G, Popovic K, Akhtar M, Ryder WJ, Clemens KJ, Balleine BW, Parmar A, Pascali G, Perkins G, Meikle SR. Open-field PET: Simultaneous brain functional imaging and behavioural response measurements in freely moving small animals. Neuroimage 2018; 188:92-101. [PMID: 30502443 DOI: 10.1016/j.neuroimage.2018.11.051] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 11/01/2018] [Accepted: 11/27/2018] [Indexed: 10/27/2022] Open
Abstract
A comprehensive understanding of how the brain responds to a changing environment requires techniques capable of recording functional outputs at the whole-brain level in response to external stimuli. Positron emission tomography (PET) is an exquisitely sensitive technique for imaging brain function but the need for anaesthesia to avoid motion artefacts precludes concurrent behavioural response studies. Here, we report a technique that combines motion-compensated PET with a robotically-controlled animal enclosure to enable simultaneous brain imaging and behavioural recordings in unrestrained small animals. The technique was used to measure in vivo displacement of [11C]raclopride from dopamine D2 receptors (D2R) concurrently with changes in the behaviour of awake, freely moving rats following administration of unlabelled raclopride or amphetamine. The timing and magnitude of [11C]raclopride displacement from D2R were reliably estimated and, in the case of amphetamine, these changes coincided with a marked increase in stereotyped behaviours and hyper-locomotion. The technique, therefore, allows simultaneous measurement of changes in brain function and behavioural responses to external stimuli in conscious unrestrained animals, giving rise to important applications in behavioural neuroscience.
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Affiliation(s)
- Andre Z Kyme
- Biomedical Engineering, School of Aerospace, Mechanical & Mechatronic Engineering, Faculty of Engineering and IT, The University of Sydney, Sydney, NSW, 2006, Australia; Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Georgios I Angelis
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
| | - John Eisenhuth
- Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Roger R Fulton
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia; Department of Medical Physics, Westmead Hospital, Sydney, NSW, 2145, Australia
| | - Victor Zhou
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Genevra Hart
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Kata Popovic
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Mahmood Akhtar
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
| | - William J Ryder
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Kelly J Clemens
- School of Psychology, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Bernard W Balleine
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Arvind Parmar
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Australian Nuclear Science and Technology Organisation, Sydney, NSW, 2234, Australia
| | - Giancarlo Pascali
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Australian Nuclear Science and Technology Organisation, Sydney, NSW, 2234, Australia
| | - Gary Perkins
- Australian Nuclear Science and Technology Organisation, Sydney, NSW, 2234, Australia
| | - Steven R Meikle
- Imaging Physics Laboratory, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2006, Australia; Faculty of Health Sciences, The University of Sydney, Sydney, NSW, 2006, Australia
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