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

Journal: Breast (Edinburgh, Scotland)
Published Date: Nov 26, 2019

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.

Authors

  • Philip M P Poortmans
    Paris Sciences & Lettres - PSL University, Paris, France. Electronic address: philip.poortmans@telenet.be.
  • Silvia Takanen
    Institut Curie, Department of Radiation Oncology, Paris, France.
  • Gustavo Nader Marta
    Department of Radiation Oncology - Hospital Sírio-Libanês, Brazil; Department of Radiology and Oncology - Radiation Oncology, Instituto Do Câncer Do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo, Brazil.
  • Icro Meattini
    Department of Experimental and Clinical Biomedical Sciences "M. Serio", University of Florence, Florence, Italy; Radiation Oncology Unit, Oncology Department, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
  • Orit Kaidar-Person
    Radiation Oncology Unit, Breast Radiation Unit, Sheba Tel Ha'shomer, Ramat Gan, Israel.

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