Update FDG-PET in der Demenzdiagnostik

Ralph Buchert; Stefan Förster

doi:10.1055/a-1712-6140

Angewandte Nuklearmedizin, Table of Contents

Angewandte Nuklearmedizin 2022; 45(04): 297-314
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

Ralph Buchert

¹Zentrum für Radiologie und Endoskopie, Klinik für diagnostische und interventionelle Radiologie und Nuklearmedizin, Abteilung für Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Deutschland (Ringgold ID: RIN37734)

,

Stefan Förster

²Klinik und Institut für Nuklearmedizin, Klinikum Bayreuth GmbH und Medizincampus Oberfranken der Friedrich-Alexander-Universität Erlangen, Bayreuth, Deutschland

³Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, München, Deutschland

› Author Affiliations

Abstract

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 Intelligenz

Keywords

Fluorodeoxyglucose F18 - Alzheimer disease - neurodegenerative diseases - diagnosis, differential - data analysis - artificial intelligence

Full Text

References

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