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DOI: 10.1055/a-2329-2866
Multiparametrischer Ultraschall von Schilddrüsenknoten
Article in several languages: English | deutsch
Zusammenfassung
Schilddrüsenknoten sind häufige Zufallsbefunde. Zwar sind die meisten Knoten gutartig, aber viele Feinnadel-Aspirationen, Kernbiopsien und sogar Thyreoidektomien oder nicht invasive Behandlungen werden unnötigerweise durchgeführt. Um die Charakterisierung von Schilddrüsenknoten zu verbessern, haben die meisten Experten und mehrere Gesellschaften den Einsatz multiparametrischer Ultraschalluntersuchungen empfohlen. Insbesondere die US-Elastografie zur Beurteilung der Gewebesteifigkeit und der CEUS zur Darstellung der Vaskularisation tragen zur besseren Charakterisierung bei. Darüber hinaus erhöht die Anwendung einer KI, insbesondere maschinelles Lernen und Deep Learning, die diagnostische Genauigkeit. Außerdem helfen KI-basierte computergestützte Diagnosesysteme (CAD), die in den Diagnoseprozess integriert sind, bei der Risikostratifizierung und verhindern unnötige Interventionen. Trotz dieser Fortschritte gibt es noch weitere Herausforderungen, darunter die Notwendigkeit standardisierter TIRADS, die Rolle der US-Elastografie in der Routinepraxis und die Integration von KI in klinische Protokolle. Die Integration klinischer Informationen, von Labordaten und multiparametrischen Ultraschallmerkmalen ist jedoch nach wie vor von entscheidender Bedeutung, um unnötige Eingriffe zu vermeiden und geeignete Behandlungen einzuleiten. Zusammenfassend lässt sich sagen, dass der Ultraschall bei der Behandlung von Schilddrüsenknoten eine zentrale Rolle spielt. Offene Fragen bezüglich der TIRADS-Auswahl, des konsequenten Einsatzes der US-Elastografie und der Rolle der KI-basierten Techniken unterstreichen den Bedarf an weitergehender Forschung. Jedenfalls wird ein umfassender Ansatz empfohlen, der klinische Informationen sowie Labor- und Ultraschalldaten kombiniert, um unnötige Eingriffe und Behandlungen zu minimieren.
Publication History
Article published online:
06 September 2024
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