Imperial College London
Alternate

ProfessorRogerGunn

Faculty of Medicine, Department of Brain Sciences

Emeritus Professor of Molecular Neuroimaging
 
 
 
//

Contact

 

r.gunn

 
 
//

Location

 

Burlington DanesHammersmith Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Jovalekic:2023:10.1007/s00259-023-06279-0,
author = {Jovalekic, A and Roé-Vellvé, N and Koglin, N and Quintana, ML and Nelson, A and Diemling, M and Lilja, J and Gómez-González, JP and Doré, V and Bourgeat, P and Whittington, A and Gunn, R and Stephens, AW and Bullich, S},
doi = {10.1007/s00259-023-06279-0},
journal = {Eur J Nucl Med Mol Imaging},
pages = {3276--3289},
title = {Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods.},
url = {http://dx.doi.org/10.1007/s00259-023-06279-0},
volume = {50},
year = {2023}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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 d
AU  - Jovalekic,A
AU  - Roé-Vellvé,N
AU  - Koglin,N
AU  - Quintana,ML
AU  - Nelson,A
AU  - Diemling,M
AU  - Lilja,J
AU  - Gómez-González,JP
AU  - Doré,V
AU  - Bourgeat,P
AU  - Whittington,A
AU  - Gunn,R
AU  - Stephens,AW
AU  - Bullich,S
DO  - 10.1007/s00259-023-06279-0
EP  - 3289
PY  - 2023///
SP  - 3276
TI  - Validation of quantitative assessment of florbetaben PET scans as an adjunct to the visual assessment across 15 software methods.
T2  - Eur J Nucl Med Mol Imaging
UR  - http://dx.doi.org/10.1007/s00259-023-06279-0
UR  - https://www.ncbi.nlm.nih.gov/pubmed/37300571
VL  - 50
ER  -
Download