Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/33062
Title: Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods.
Austin Authors: Jovalekic, Aleksandar;Roé-Vellvé, Núria;Koglin, Norman;Quintana, Mariana Lagos;Nelson, Aaron;Diemling, Markus;Lilja, Johan;Gómez-González, Juan Pablo;Doré, Vincent ;Bourgeat, Pierrick;Whittington, Alex;Gunn, Roger;Stephens, Andrew W;Bullich, Santiago
Affiliation: Life Molecular Imaging GmbH, Berlin, Germany.
MIM Software Inc., Cleveland, OH, USA.
Hermes Medical Solutions, Stockholm, Sweden.
Qubiotech Health Intelligence, A Coruña, Spain.
Molecular Imaging and Therapy
CSIRO, Brisbane, Australia.
Invicro, London, UK.
Issue Date: Sep-2023
Date: 2023
Publication information: European Journal of Nuclear Medicine and Molecular Imaging 2023-09; 50(11)
Abstract: Amyloid positron emission tomography (PET) with [18F]florbetaben (FBB) is an established tool for detecting Aβ deposition in the brain in vivo based on visual assessment of PET scans. Quantitative measures are commonly used in the research context and allow continuous measurement of amyloid burden. The aim of this study was to demonstrate the robustness of FBB PET quantification. This is a retrospective analysis of FBB PET images from 589 subjects. PET scans were quantified with 15 analytical methods using nine software packages (MIMneuro, Hermes BRASS, Neurocloud, Neurology Toolkit, statistical parametric mapping (SPM8), PMOD Neuro, CapAIBL, non-negative matrix factorization (NMF), AmyloidIQ) that used several metrics to estimate Aβ load (SUVR, centiloid, amyloid load, and amyloid index). Six analytical methods reported centiloid (MIMneuro, standard centiloid, Neurology Toolkit, SPM8 (PET only), CapAIBL, NMF). All results were quality controlled. The mean sensitivity, specificity, and accuracy were 96.1 ± 1.6%, 96.9 ± 1.0%, and 96.4 ± 1.1%, respectively, for all quantitative methods tested when compared to histopathology, where available. The mean percentage of agreement between binary quantitative assessment across all 15 methods and visual majority assessment was 92.4 ± 1.5%. Assessments of reliability, correlation analyses, and comparisons across software packages showed excellent performance and consistent results between analytical methods. This study demonstrated that quantitative methods using both CE marked software and other widely available processing tools provided comparable results to visual assessments of FBB PET scans. Software quantification methods, such as centiloid analysis, can complement visual assessment of FBB PET images and could be used in the future for identification of early amyloid deposition, monitoring disease progression and treatment effectiveness.
URI: https://ahro.austin.org.au/austinjspui/handle/1/33062
DOI: 10.1007/s00259-023-06279-0
ORCID: 0000-0001-9997-7409
Journal: European Journal of Nuclear Medicine and Molecular Imaging
PubMed URL: 37300571
ISSN: 1619-7089
Type: Journal Article
Subjects: Alzheimer’s disease
Amyloid-beta
Centiloid
Florbetaben
Mild cognitive impairment
Quantification
Appears in Collections:Journal articles

Show full item record

Page view(s)

38
checked on Oct 14, 2024

Google ScholarTM

Check


Items in AHRO are protected by copyright, with all rights reserved, unless otherwise indicated.