Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing consistency, and improving dose-volumes parameters. Future developments include incorporating dose/outcome data to optimise dose distributions with optimal coverage of the high-risk areas, while at the same time limiting doses to low-risk areas. An infinite gradient of volumes and doses to deliver spatially-adjusted radiation can be generated, allowing to avoid unnecessary radiation to organs at risk. Therefore, data about patient-, tumour-, and treatment-related factors have to be combined with dose distributions and outcome-containing databases. (C) 2019 Published by Elsevier Ltd.

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer / Poortmans, Philip M P; Takanen, Silvia; Marta, Gustavo Nader; Meattini, Icro; Kaidar-Person, Orit. - In: THE BREAST. - ISSN 0960-9776. - STAMPA. - 49:(2020), pp. 194-200. [10.1016/j.breast.2019.11.011]

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer

Meattini, Icro;
2020

Abstract

Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing consistency, and improving dose-volumes parameters. Future developments include incorporating dose/outcome data to optimise dose distributions with optimal coverage of the high-risk areas, while at the same time limiting doses to low-risk areas. An infinite gradient of volumes and doses to deliver spatially-adjusted radiation can be generated, allowing to avoid unnecessary radiation to organs at risk. Therefore, data about patient-, tumour-, and treatment-related factors have to be combined with dose distributions and outcome-containing databases. (C) 2019 Published by Elsevier Ltd.
2020
49
194
200
Poortmans, Philip M P; Takanen, Silvia; Marta, Gustavo Nader; Meattini, Icro; Kaidar-Person, Orit
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0960977619311038-main.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Creative commons
Dimensione 1.13 MB
Formato Adobe PDF
1.13 MB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1196220
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 36
  • ???jsp.display-item.citation.isi??? 31
social impact