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Visualization and Quantification of 3-Dimensional Stereotactic Surface Projections for F-18-Flutemetamol PET Using Variable Depth
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. GE Healthcare, Uppsala, Sweden..
GE Healthcare, Uppsala, Sweden.;Univ Gothenburg, Sahlgrenska Acad, Inst Neurosci & Physiol, Gothenburg, Sweden..
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Clinical Physiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
2016 (English)In: Journal of Nuclear Medicine, ISSN 0161-5505, E-ISSN 1535-5667, Vol. 57, no 7, 1078-1083 p.Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

Three-dimensional stereotactic surface projection (3D-SSP) is a widely used method for the analysis of clinical F-18-FDG brain studies. However, for PET amyloid scans the use of 3D-SSP is challenging because of nonspecific uptake in white matter. Our objective was to implement a method for 3D-SSP quantification and visualization of F-18-flutemetamol images that avoids extraction of white matter signal. METHODS: Triangulated brain surface models were extracted from a T1-weighted MR template image. Using an F-18-flutemetamol-negative template, a maximum depth for each vertex on the surface models was calculated to avoid extraction of white matter. The method was evaluated using F-18-flutemetamol images from 2 cohorts. Cohort 1 consisted of 105 healthy volunteers and was used to create a normal database for each reference region. Cohort 2 consisted of 171 subjects including patients with Alzheimer disease and mild cognitive impairment and healthy volunteers. Images were spatially normalized using an adaptive template registration method, and SUV ratio 3D-SSP values were computed using the pons and cerebellar cortex as reference regions. Images from cohort 2 were then compared with the normal database and classified into negatives and positives, based on a calculated z score threshold. The results were compared with consensus visual interpretation results from 5 trained interpreters blinded to clinical data. RESULTS: With the pons as the reference region, the optimal z score threshold was 1.97, resulting in an overall agreement with visual interpretation results in 170 of 171 images (99.42%). With the cerebellar cortex as the reference region, the optimal z score threshold was 2.41, with an overall agreement with visual interpretation in 168 of 171 images (98.25%). CONCLUSION: Variable-depth 3D-SSP allows computation and visualization of F-18-flutemetamol 3D-SSP maps, with minimized contribution from white matter signal while retaining sensitivity in detecting gray matter signal.

Place, publisher, year, edition, pages
2016. Vol. 57, no 7, 1078-1083 p.
Keyword [en]
Alzheimer's disease, positron emission tomography, brain mapping, stereotactic surface projections, flutemetamol, amyloid
National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
URN: urn:nbn:se:uu:diva-300057DOI: 10.2967/jnumed.115.169169ISI: 000378979200017PubMedID: 26912445OAI: oai:DiVA.org:uu-300057DiVA: diva2:950763
Available from: 2016-08-02 Created: 2016-08-02 Last updated: 2017-03-18Bibliographically approved
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

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