Künstliche Intelligenz zur Detektion, Quantifizierung und Charakterisierung des metastasierten Prostatakarzinoms in der PSMA-PET/CT – Wo stehen wir?

Zusammenfassung

Das Prostatakarzinom (PCa) ist der weltweit häufigste maligne Tumor bei Männern. Seit ihrer klinischen Einführung im Jahr 2011 hat sich sowohl die PET/CT als auch die Radioligandentherapie mit PSMA-Liganden zur Diagnostik bzw. Therapie des PCa weltweit rasch ausgebreitet. Obwohl die PSMA-PET/CT als ein signifikanter Durchbruch in der Diagnostik des PCa gilt, stellt die Evaluation und Kontrolle aller Tumorherde inklusive ihrer Volumina und Charakteristiken bei fortgeschrittenem, multimetastatischem PCa nach wie vor eine große Herausforderung dar. Diese gilt es zu bewältigen, um beispielsweise eine Optimierung der Endoradiotherapie mit PSMA-Liganden zu erreichen. In diesem Kontext könnte die künstliche Intelligenz, die in den letzten Jahren signifikante Fortschritte erzielt hat, in der nahen Zukunft eine wichtige Rolle spielen. Die Artificial Intelligence (AI) hat bereits demonstriert, dass sie den menschlichen Fähigkeiten zur Datenverarbeitung überlegen sein kann und bietet damit großes Potenzial zur Verbesserung der Detektion, Quantifizierung und Charakterisierung von PCa-Herden in der PSMA-PET/CT.

Die hier vorliegende Schrift befasst sich mit den aktuellen Entwicklungen der künstlichen Intelligenz für den Einsatz in der PSMA-PET/CT und den sich daraus bietenden Möglichkeiten.

Abstract

Prostate cancer (PCa) is the most frequent tumor entity in men worldwide. Since their clinical introduction in 2011, PSMA-PET/CT and radionuclide therapy with PSMA-ligands have rapidly spread worldwide and are regarded as significant step forwards in the diagnosis and therapy of PCa. However, it is still an unmet challenge to evaluate and control all tumor lesions including their volume and characteristics in the complex context of advanced multimetastatic disease in PSMA-PET/CT. Such a control plays an important role, e. g. for the optimization of PSMA-ligandtherapy. In this context, artificial intelligence (AI) could play an important role in the near future. The rapid development of AI in the past few years has demonstrated its superiority in extending the human power of data processing and provides great potential to improve the detection, quantification and characterization of metastatic prostate cancer lesions in PSMA-PET/CT. This paper reviews the current progress of the development of artificial intelligence methods for PSMA-PET/CT and discusses the potential of clinical application.

Schlüsselwörter

PSMA - PET/CT - Prostatakarzinom - PSMA-Therapie - künstliche Intelligenz - Artificial Intelligence - Deep Learning

Key words

PSMA - PET/CT - prostate cancer - PSMA-therapy - artificial intelligence - deep learning

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