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Spatial normalizati...
Spatial normalization of 18F-Flutemetamol PET images using an adaptive principal-component template
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- Lilja, Johan (författare)
- Uppsala universitet,Radiologi,Hermes Medical Solutions, Stockholm, Sweden
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Leuzy, Antoine (författare)
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- Chiotis, Konstantinos (författare)
- Karolinska Institutet
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Savitcheva, Irina (författare)
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- Sörensen, Jens (författare)
- Uppsala universitet,Radiologi
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- Nordberg, Agneta (författare)
- Karolinska Institutet
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(creator_code:org_t)
- 2018-06-14
- 2019
- Engelska.
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Ingår i: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 1535-5667 .- 2159-662X. ; 60:2, s. 285-291
- Relaterad länk:
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https://doi.org/10.2...
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https://uu.diva-port... (primary) (Raw object)
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http://jnm.snmjourna...
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https://urn.kb.se/re...
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https://doi.org/10.2...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- Though currently approved for visual assessment only, there is evidence to suggest that quantification of amyloid-β (Aβ) PET images may reduce interreader variability and aid in the monitoring of treatment effects in clinical trials. Quantification typically involves a regional atlas in standard space, requiring PET images to be spatially normalized. Different uptake patterns in Aβ-positive and Aβ-negative subjects, however, make spatial normalization challenging. In this study, we proposed a method to spatially normalize 18F-flutemetamol images using a synthetic template based on principal-component images to overcome these challenges.Methods: 18F-flutemetamol PET and corresponding MR images from a phase II trial (n = 70), including subjects ranging from Aβ-negative to Aβ-positive, were spatially normalized to standard space using an MR-driven registration method (SPM12). 18F-flutemetamol images were then intensity-normalized using the pons as a reference region. Principal-component images were calculated from the intensity-normalized images. A linear combination of the first 2 principal-component images was then used to model a synthetic template spanning the whole range from Aβ-negative to Aβ-positive. The synthetic template was then incorporated into our registration method, by which the optimal template was calculated as part of the registration process, providing a PET-only–driven registration method. Evaluation of the method was done in 2 steps. First, coregistered gray matter masks generated using SPM12 were spatially normalized using the PET- and MR-driven methods, respectively. The spatially normalized gray matter masks were then visually inspected and quantified. Second, to quantitatively compare the 2 registration methods, additional data from an ongoing study were spatially normalized using both methods, with correlation analysis done on the resulting cortical SUV ratios.Results: All scans were successfully spatially normalized using the proposed method with no manual adjustments performed. Both visual and quantitative comparison between the PET- and MR-driven methods showed high agreement in cortical regions. 18F-flutemetamol quantification showed strong agreement between the SUV ratios for the PET- and MR-driven methods (R2 = 0.996; pons reference region).Conclusion: The principal-component template registration method allows for robust and accurate registration of 18F-flutemetamol images to a standardized template space, without the need for an MR image.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
Nyckelord
- Alzheimer disease
- amyloid-beta
- PET
- F-18-flutemetamol
- adaptive template
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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