Onkologische Bildgebung mittels Spektral-CT

Zusammenfassung

Hintergrund Die Spektral-CT gewinnt mit vielfältigen Einsatzmöglichen zunehmend an klinischer Bedeutung, so auch im Rahmen der onkologischen Bildgebung. Die Spektral-CT-spezifischen Bilddaten bieten durch verschiedene Nachbearbeitungsalgorithmen vielfältige Vorteile gegenüber konventionellen CT-Bilddaten, was im folgenden Review genauer beleuchtet werden soll.

Methodik Der vorliegende Review-Artikel soll einen Überblick über die potenziell nützlichsten onkologischen Anwendungsgebiete der Spektral-CT geben und auf spezifische Spektral-CT-Fallstricke hinweisen. Hierbei werden sowohl technische Hintergründe als auch klinische Vorteile von onkologischen Primär- und Verlaufsuntersuchungen mittels Spektral-CT beleuchtet und die Anwendung entsprechender Spektral-Tools erläutert.

Ergebnisse/Schlussfolgerungen Die Spektral-CT-Bildgebung bietet vielfältige Vorteile gegenüber der konventionellen CT-Bildgebung, insbesondere auf dem Gebiet der Onkologie. Die Kombination von virtuell nativen und niedrigenergetischen Bildern führt zu einer verbesserten Detektion und Charakterisierung von Tumorläsionen. Jodkarten-Bilder bieten einen potenziellen Imaging-Biomarker zur Beurteilung des Therapieansprechens.

Kernaussagen 

• Die wichtigsten Spektral-CT-Rekonstruktionen für die onkologische Bildgebung sind die virtuell nativen, Jodkarten- und virtuelle monochromatische Rekonstruktionen.

• Die Kombination aus virtuell nativen und niedrigenergetischen Bildern führt zu einer verbesserten Detektion und Charakterisierung von vaskularisierten und nicht vaskularisierten Läsionen.

• Jodkarten können ein Surrogatparameter für die Tumorperfusion sein und potenziell als Therapie-Monitoring-Parameter verwendet werden.

• Für die Strahlentherapie-Planung lassen sich die relative Elektronendichte und die effektive Ordnungszahl eines Gewebes berechnen.

Zitierweise

• Sauerbeck J, Adam G, Meyer M. Spectral CT in Oncology. Fortschr Röntgenstr 2023; 195: 21 – 29

Key words

therapy planning - oncology imaging - lesion detection - review - CT - spectral CT

Publikationsverlauf

Eingereicht: 26. Oktober 2021

Angenommen: 03. Juli 2022

Artikel online veröffentlicht:
27. September 2022

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