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Erschienen in: Medical Oncology 6/2020

01.06.2020 | Review Article

A closer look to the new frontier of artificial intelligence in the percutaneous treatment of primary lesions of the liver

verfasst von: M. Citone, F. Fanelli, G. Falcone, F. Mondaini, D. Cozzi, V. Miele

Erschienen in: Medical Oncology | Ausgabe 6/2020

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Abstract

The purpose of thermal ablation is induction of tumor death by means of localized hyperthermia resulting in irreversible cellular damage. Ablative therapies are well-recognized treatment modalities for HCC lesions and are considered standard of care for HCC nodules < 3 cm in diameter in patients not suitable for surgery. Effective lesion treatment rely on complete target volume ablation. Technical limitations are represented by large (> 3 cm) or multicentric nodules as well as complex nodule location and poor lesion conspicuity. Artificial Intelligence (AI) is a general term referred to computational algorithms that can analyze data and perform complex tasks otherwise prerogative of Human Intelligence. AI has a variety of application in percutaneous ablation procedures such as Navigational software, Fusion Imaging, and robot-assisted ablation tools. Those instruments represent relative innovations in the field of Interventional Oncology and promising strategies to overcome actual limitations of ablative therapy in order to increase feasibility and technical results. This work aims to review the principal application of Artificial Intelligence in the percutaneous ablation of primary lesions of the liver with special focus on how AI can impact in the treatment of HCC especially on potential advantages on the drawbacks of the conventional technique.
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Metadaten
Titel
A closer look to the new frontier of artificial intelligence in the percutaneous treatment of primary lesions of the liver
verfasst von
M. Citone
F. Fanelli
G. Falcone
F. Mondaini
D. Cozzi
V. Miele
Publikationsdatum
01.06.2020
Verlag
Springer US
Erschienen in
Medical Oncology / Ausgabe 6/2020
Print ISSN: 1357-0560
Elektronische ISSN: 1559-131X
DOI
https://doi.org/10.1007/s12032-020-01380-y

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