eISSN: 2081-2841
ISSN: 1689-832X
Journal of Contemporary Brachytherapy
Current Issue Archive Supplements Articles in Press Journal Information Aims and Scope Editorial Office Editorial Board Register as Author Register as Reviewer Instructions for Authors Abstracting and indexing Subscription Advertising Information Links
Editorial System
Submit your Manuscript
SCImago Journal & Country Rank

5/2020
vol. 12
 
Share:
Share:
abstract:
Review paper

Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives

Bruno Fionda
1
,
Luca Boldrini
1, 2
,
Andrea D’Aviero
2
,
Valentina Lancellotta
1
,
Maria Antonietta Gambacorta
1, 2
,
György Kovács
3
,
Stefano Patarnello
1
,
Vincenzo Valentini
1, 2
,
Luca Tagliaferri
1

1.
UOC Radioterapia Oncologica, Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Roma, Italy
2.
Università Cattolica del Sacro Cuore, Roma, Italy
3.
Università Cattolica del Sacro Cuore, Educational Program Director Gemelli-INTERACTS, Roma, Italy
J Contemp Brachytherapy 2020; 12, 5: 497–500
Online publish date: 2020/10/29
View full text Get citation
 
Purpose
Artificial intelligence (AI) plays a central role in building decision supporting systems (DSS), and its application in healthcare is rapidly increasing. The aim of this study was to define the role of AI in healthcare, with main focus on radiation oncology (RO) and interventional radiotherapy (IRT, brachytherapy).

Artificial intelligence in interventional radiation therapy:
AI in RO has a large impact in providing clinical decision support, data mining and advanced imaging analysis, automating repetitive tasks, optimizing time, and modelling patients and physicians’ behaviors in heterogeneous contexts. Implementing AI and automation in RO and IRT can successfully facilitate all the steps of treatment workflow, such as patient consultation, target volume delineation, treatment planning, and treatment delivery.

Conclusions
AI may contribute to improve clinical outcomes through the application of predictive models and DSS optimization. This approach could lead to reducing time-consuming repetitive tasks, healthcare costs, and improving treatment quality assurance and patient’s assistance in IRT.

keywords:

artificial intelligence, interventional radiotherapy, brachytherapy, personalized medicine, machine learning, decision supporting system

 
Quick links
© 2024 Termedia Sp. z o.o.
Developed by Bentus.