uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Implementation and validation of an adaptive template registration method for 18F-flutemetamol imaging data.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
Show others and affiliations
2013 (English)In: Journal of Nuclear Medicine, ISSN 0161-5505, E-ISSN 1535-5667, Vol. 54, no 8, 1472-8 p.Article in journal (Refereed) Published
Abstract [en]

UNLABELLED: The spatial normalization of PET amyloid imaging data is challenging because different white and gray matter patterns of negative (Aβ-) and positive (Aβ+) uptake could lead to systematic bias if a standard method is used. In this study, we propose the use of an adaptive template registration method to overcome this problem.

METHODS: Data from a phase II study (n = 72) were used to model amyloid deposition with the investigational PET imaging agent (18)F-flutemetamol. Linear regression of voxel intensities on the standardized uptake value ratio (SUVR) in a neocortical composite region for all scans gave an intercept image and a slope image. We devised a method where an adaptive template image spanning the uptake range (the most Aβ- to the most Aβ+ image) can be generated through a linear combination of these 2 images and where the optimal template is selected as part of the registration process. We applied the method to the (18)F-flutemetamol phase II data using a fixed volume of interest atlas to compute SUVRs. Validation was performed in several steps. The PET-only adaptive template registration method and the MR imaging-based method used in statistical parametric mapping were applied to spatially normalize PET and MR scans, respectively. Resulting transformations were applied to coregistered gray matter probability maps, and the quality of the registrations was assessed visually and quantitatively. For comparison of quantification results with an independent patient-space method, FreeSurfer was used to segment each subject's MR scan and the parcellations were applied to the coregistered PET scans. We then correlated SUVRs for a composite neocortical region obtained with both methods. Furthermore, to investigate whether the (18)F-flutemetamol model could be generalized to (11)C-Pittsburgh compound B ((11)C-PIB), we applied the method to Australian Imaging, Biomarkers and Lifestyle (AIBL) (11)C-PIB scans (n = 285) and compared the PET-only neocortical composite score with the corresponding score obtained with a semimanual method that made use of the subject's MR images for the positioning of regions.

RESULTS: Spatial normalization was successful on all scans. Visual and quantitative comparison of the new PET-only method with the MR imaging-based method of statistical parametric mapping indicated that performance was similar in the cortical regions although the new PET-only method showed better registration in the cerebellum and pons reference region area. For the (18)F-flutemetamol quantification, there was a strong correlation between the PET-only and FreeSurfer SUVRs (Pearson r = 0.96). We obtained a similar correlation for the AIBL (11)C-PIB data (Pearson r = 0.94).

CONCLUSION: The derived adaptive template registration method allows for robust, accurate, and fully automated quantification of uptake for (18)F-flutemetamol and (11)C-PIB scans without the use of MR imaging data.

Place, publisher, year, edition, pages
2013. Vol. 54, no 8, 1472-8 p.
Keyword [en]
18F-flutemetamol, amyloid imaging, image registration
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-316798DOI: 10.2967/jnumed.112.115006PubMedID: 23740104OAI: oai:DiVA.org:uu-316798DiVA: diva2:1079043
Available from: 2017-03-07 Created: 2017-03-07 Last updated: 2017-11-29
In thesis
1. [18F]Flutemetamol PET image processing, visualization and quantification targeting clinical routine
Open this publication in new window or tab >>[18F]Flutemetamol PET image processing, visualization and quantification targeting clinical routine
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Alzheimer’s disease (AD) is the leading cause of dementia and is alone responsible for 60-70% of all cases of dementia. Though sharing clinical symptoms with other types of dementia, the hallmarks of AD are the abundance of extracellular depositions of β-amyloid (Aβ) plaques, intracellular neurofibrillary tangles of hyper phosphorylated tau proteins and synaptic depletion. The onset of the physiological hallmarks may precede clinical symptoms with a decade or more, and once clinical symptoms occur it may be difficult to separate AD from other types of dementia based on clinical symptoms alone. Since the introduction of radiolabeled Aβ tracer substances for positron emission tomography (PET) imaging it is possible to image the Aβ depositions in-vivo, strengthening the confidence in the diagnosis. Because the accumulation of Aβ may occur years before the first clinical symptoms are shown and even reach a plateau, Aβ PET imaging may not be feasible for disease progress monitoring. However, a negative scan may be used to rule out AD as the underlying cause to the clinical symptoms. It may also be used as a predictor to evaluate the risk of developing AD in patients with mild cognitive impairment (MCI) as well as monitoring potential effects of anti-amyloid drugs.Though currently validated for dichotomous visual assessment only, there is evidence to suggest that quantification of Aβ PET images may reduce inter-reader variability and aid in the monitoring of treatment effects from anti-amyloid drugs.The aim of this thesis was to refine existing methods and develop new ones for processing, quantification and visualization of Aβ PET images to aid in the diagnosis and monitoring of potential treatment of AD in clinical routine. Specifically, the focus for this thesis has been to find a way to fully automatically quantify and visualize a patient’s Aβ PET image in such way that it is presented in a uniform way and show how it relates to what is considered normal. To achieve the aim of the thesis registration algorithms, providing the means to register a patient’s Aβ PET image to a common stereotactic space avoiding the bias of different uptake patterns for Aβ- and Aβ+ images, a suitable region atlas and a 3-dimensional stereotactic surface projections (3D SSP) method, capable of projecting cortical activity onto the surface of a 3D model of the brain without sampling white matter, were developed and evaluated.The material for development and testing comprised 724 individual amyloid PET brain images from six distinct cohorts, ranging from healthy volunteers to definite AD. The new methods could be implemented in a fully automated workflow and were found to be highly accurate, when tested by comparisons to Standards of Truth, such as defining regional uptake from PET images co-registered to magnetic resonance images, post-mortem histopathology and the visual consensus diagnosis of imaging experts.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. 42 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1322
Keyword
quantification; flutemetamol; amyloid imaging; Alzheimer’s disease; positron emission tomography; brain mapping; stereotactic surface projections;image registration
National Category
Radiology, Nuclear Medicine and Medical Imaging Neurology
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-317688 (URN)978-91-554-9873-3 (ISBN)
Public defence
2017-05-05, Skoogsalen, Akademiska Sjukhuset, Ing 78/79 1tr, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2017-04-12 Created: 2017-03-18 Last updated: 2017-04-12

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Lilja, Johan
By organisation
Radiology
In the same journal
Journal of Nuclear Medicine
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 228 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf