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@ARTICLE{Bischof:1030418,
author = {Bischof, Gérard N. and Brendel, Matthias and Barthel,
Henryk and Theis, Hendrik and Barbe, Michael and
Bartenstein, Peter and Claasen, Joseph and Danek, Adrian and
Höglinger, Günter and Levin, Johannes and Marek, Ken and
Neumaier, Bernd and Palleis, Carla and Patt, Marianne and
Rullmann, Michael and Saur, Dorothee and Schroeter, Matthias
L. and Seibyl, John and Song, Mengmeng and Stephens, Andrew
and Sabri, Osama and Drzezga, Alexander and van Eimeren,
Thilo},
title = {{I}mproved {T}au {PET} {SUVR} {Q}uantification in
4-{R}epeat {T}au {P}henotypes with [18{F}]{PI}-2620},
journal = {Journal of nuclear medicine},
volume = {65},
number = {6},
issn = {0097-9058},
address = {New York, NY},
publisher = {Soc.},
reportid = {FZJ-2024-05291},
pages = {952 - 955},
year = {2024},
abstract = {We used a new data-driven methodology to identify a set of
reference regions that enhanced the quantification of the
SUV ratio of the second-generation tau tracer
2-(2-([18F]fluoro)pyridin-4-yl)-9H-pyrrolo[2,3-b:4,5-c′]dipyridine
([18F]PI-2620) in a group of patients clinically diagnosed
with 4-repeat tauopathy, specifically progressive
supranuclear palsy or cortical basal syndrome. The study
found that SUV ratios calculated using the identified
reference regions (i.e., fusiform gyrus and crus-cerebellum)
were significantly associated with symptom severity and
disease duration. This establishes, for the first time to
our knowledge, the suitability of [18F]PI-2620 for tracking
disease progression in this 4-repeat disease population.
This is an important step toward increased clinical utility,
such as patient stratification and monitoring in
disease-modifying treatment trials. Additionally, the
applied methodology successfully optimized reference regions
for automated detection of brain imaging tracers. This
approach may also hold value for other brain imaging
tracers.},
cin = {INM-5 / INM-2},
ddc = {610},
cid = {I:(DE-Juel1)INM-5-20090406 / I:(DE-Juel1)INM-2-20090406},
pnm = {5253 - Neuroimaging (POF4-525) / 5254 - Neuroscientific
Data Analytics and AI (POF4-525)},
pid = {G:(DE-HGF)POF4-5253 / G:(DE-HGF)POF4-5254},
typ = {PUB:(DE-HGF)16},
pubmed = {38575191},
UT = {WOS:001251294600021},
doi = {10.2967/jnumed.123.265930},
url = {https://juser.fz-juelich.de/record/1030418},
}