Beurteilung der Sakroiliitis mittels künstlicher Intelligenz – Fortschritte und Limitationen

Zusammenfassung

Die Sakroiliitis ist eine entzündliche Erkrankung des Sakroiliakalgelenks, die durch Faktoren wie Infektionen, Traumata und Autoimmunerkrankungen ausgelöst werden kann. Sie verursacht Schmerzen und Steifheit im unteren Rücken, weshalb eine frühzeitige Diagnose für eine optimale Behandlung entscheidend ist. Die Diagnose ist anspruchsvoll und erfordert klinische Beurteilung, Labortests und bildgebende Verfahren wie Röntgen, MRT oder CT. In den letzten Jahren hat sich die künstliche Intelligenz (KI) als vielversprechendes Instrument für die Beurteilung von Veränderungen im Rahmen der Sakroiliitis herausgestellt. KI-Algorithmen analysieren verschiedene bildgebende Verfahren, um strukturelle Veränderungen und Entzündungen im Sakroiliakalgelenk zu erkennen, zu quantifizieren und einzuordnen. Die Anwendung von KI kann die Diagnosegenauigkeit und Effizienz des Radiologen bzw. des Rheumatologen bei der Beurteilung von Sakroiliitis durch bildgebende Verfahren verbessern. KI-Algorithmen können strukturelle Veränderungen und Entzündungen im Sakroiliakalgelenk quantifizieren und Vorhersagemodelle für den Krankheitsverlauf erstellen. Herausforderungen wie der Bedarf an qualitativ hochwertigen Daten und die Minimierung von Verzerrungen und Fehlern in den Daten und Algorithmen müssen jedoch bewältigt werden. Weitere Studien sind erforderlich, um das volle Potenzial der KI bei der Beurteilung von Sakroiliitis auszuschöpfen. Der Einsatz von KI kann jedoch die Ergebnisse für Patienten verbessern, indem er eine frühzeitige Diagnose und Behandlung ermöglicht.

Abstract

Sacroiliitis is an inflammatory disease of the sacroiliac joint that can be triggered by factors such as infections, traumata, and autoimmune diseases. It causes pain and stiffness in the lower back, making early diagnosis crucial for optimal treatment. The diagnosis is challenging and requires clinical evaluation, laboratory tests, and imaging techniques such as X-ray, MRI, or CT. In recent years, artificial intelligence (AI) has emerged as a promising tool for assessing changes in sacroiliitis. AI algorithms analyse various imaging techniques to detect, quantify, and classify structural changes and inflammation in the sacroiliac joint. The application of AI can improve the accuracy and efficiency of radiologists or rheumatologists in assessing sacroiliitis through imaging techniques. AI algorithms can quantify structural changes and inflammation in the sacroiliac joint and create predictive models for the disease course. However, challenges such as the need for high-quality data and minimising biases and errors in the data and algorithms must be overcome. Further studies are required to fully exploit the potential of AI in assessing sacroiliitis through imaging techniques. Nevertheless, the use of AI can improve patient outcomes by enabling early diagnosis and treatment.

Schlüsselwörter

Sakroiliitis - Radiologie - Künstliche Intelligenz - Deep Learning

Key words

Sacroiliitis - Radiology - Artificial Intelligence - Deep Learning

Publication History

Article published online:
15 June 2023

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