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Angewandte Nuklearmedizin 2022; 45(04): 297-314
DOI: 10.1055/a-1712-6140
DOI: 10.1055/a-1712-6140
Nuklearmedizinische Hirnbildgebung
Übersicht
Update FDG-PET in der Demenzdiagnostik
Update FDG-PET for the etiological diagnosis of cognitive impairment
Zusammenfassung
Dieser Artikel soll ein Update zu unserem Übersichtsartikel „FDG-PET in der Differenzialdiagnostik neurodegenerativer Demenzerkrankungen“ aus 2016 geben. Seitdem wurden zahlreiche neue, technisch hochwertige Studien mit großen Patientenkollektiven sowie systematische Übersichtsarbeiten internationaler Expertengruppen veröffentlicht. Außer den aktualisierten Best-Practice-Empfehlungen dieser Expertengruppen sollen in diesem Update einige ausgewählte neue Entwicklungen vorgestellt und diskutiert werden, die aus unserer Sicht für den Einsatz der FDG-PET des Gehirns in der klinischen Routineversorgung von Patienten mit kognitiven Einschränkungen besonders relevant sind, oder in naher Zukunft besonders relevant werden könnten. Dazu gehören neue diagnostische Optionen durch die verbesserte räumliche Auflösung der klinischen Hirn-PET mit „extraschnellen“ Time-of-Flight Ganzkörper-PET/CT-Systemen und der Einsatz Künstlicher Intelligenz zur automatischen Klassifikation der FDG-PET des Gehirns basierend auf konventionellen Kovarianzanalysen oder Deep Learning mit künstlichen neuronalen Netzen.
Abstract
This article is intended to provide an update on our 2016 review article „FDG-PET in the differential diagnosis of neurodegenerative dementia“. Since then, numerous high-quality studies with large patient samples have been published and systematically reviewed by international expert groups. This update will present the best-practice recommendations devised by these expert groups. In addition, a few selected developments will be discussed which, in our view, are particularly relevant for FDG-PET of the brain in routine care of patients with cognitive impairment such as new diagnostic options made possible by the considerable improvement of the spatial resolution of clinical brain PET with „extra-fast“ time-of-flight whole-body PET/CT systems or the use of artificial intelligence for the automatic classification of brain FDG-PET images trained by conventional covariance analysis or deep learning with artificial neural networks.
Schlüsselwörter
[18F]Fluorodesoxyglukose - Alzheimer-Krankheit - neurodegenerative Erkrankungen - Differenzialdiagnose - Datenanalyse - Künstliche IntelligenzKeywords
Fluorodeoxyglucose F18 - Alzheimer disease - neurodegenerative diseases - diagnosis, differential - data analysis - artificial intelligencePublication History
Article published online:
02 December 2022
© 2022. Thieme. All rights reserved.
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