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Title:

Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

Document type:
Journal Article
Author(s):
Zatcepin, Artem; Kopczak, Anna; Holzgreve, Adrien; Hein, Sandra; Schindler, Andreas; Duering, Marco; Kaiser, Lena; Lindner, Simon; Schidlowski, Martin; Bartenstein, Peter; Albert, Nathalie; Brendel, Matthias; Ziegler, Sibylle I
Abstract:
INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification...     »
Journal title abbreviation:
Z Med Phys
Year:
2024
Journal volume:
34
Journal issue:
2
Pages contribution:
218-230
Fulltext / DOI:
doi:10.1016/j.zemedi.2022.11.008
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/36682921
Print-ISSN:
0939-3889
TUM Institution:
657; Klinik und Poliklinik für Nuklearmedizin (Prof. Weber)
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