Artificial intelligence for the detection, quantification and characterization of metastatic prostate cancer in PSMA PET/CT - where are we now?
Publisher DOI
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.
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.
Date Issued
2019
Publication Type
Article
Subject(s)
Language(s)
de
Additional Credits
Journal
Der Nuklearmediziner
Publisher
Thieme
ISSN
0723-7065
Access(Rights)
restricted