Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era

154.4K

views

466

authors

35

articles

Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era

154.4K

views

466

authors

35

articles

Editorial

26 May 2021

Editorial: Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era

Tiziana Rancati

,

Claudio Fiorino

,

Giuseppe Sanguineti

,

Riccardo Valdagni

and

Ester Orlandi

1,874 views

3 citations

Editors

5

Ester Orlandi

National Cancer Institute Foundation (IRCCS)

Tiziana Rancati

National Cancer Institute Foundation (IRCCS)

Giuseppe Sanguineti

Regina Elena National Cancer Institute, Hospital Physiotherapy Institutes (IRCCS)

Claudio Fiorino

San Raffaele Hospital (IRCCS)

Riccardo Valdagni

University of Milan

Impact

Fetching...

About

So far, radiation therapy (RT) represents a mainstay of treatment for many cancer types, either as a single modality or within a multidisciplinary approach including surgery and systemic therapy. From a general perspective, when planning a course of curative radiotherapy, its potential benefits have to be weighed against the risk of acute and late tissue/organ damage. In other words, the main goal of RT is to improve the clinical outcome by increasing the therapeutic ratio, i.e. the ratio between tumor control probability (TCP) and normal tissue complication probability (NTCP). Although modern RT techniques, such as IMRT, SBRT, IGRT and protons, allow a better sparing of normal tissues due to their improved conformity and precision, radiation-induced toxicity is still a matter of concern. Indeed, dose tolerance of many healthy tissues, called organs at risk (OARs) is a little less than or equal to the dose needed to eradicate cancers.

It is acknowledged that the risk of some induced side effects during and after the first course of curative radiotherapy may be related to RT doses delivered to multiple OARs rather than to the dose received by a specific organ. Additionally, various patient-related factors, including comorbidities as well as genetic, genomic and biological/microenvironment features may act as modifiers of the dose-response curve. Thus, predicting toxicity by analyzing the relationship among all determinants of radiation response of healthy tissues could improve the therapeutic ratio as well as the management of side effects.

This Research Topic welcomes Original Research, Review, Mini Review, Perspective and Opinion articles focusing on:
1) The state-of-the-art of modelling approaches and their contribution towards personalized cancer treatment;
2) The improvements of knowledge on dose-volume relationships for different organs;
3) The integration of clinical/genetic/genomic/biological/microenvironment/imaging features in prediction models;
4) Pre-clinical research on radiation induced damage to normal tissues using animal models;
5) Voxel-based approaches to analysis of radiation induced toxicity.

Download ebook

PDF

EPUB

Share

Editors

Ester Orlandi

National Cancer Institute Foundation (IRCCS)

Tiziana Rancati

National Cancer Institute Foundation (IRCCS)

Giuseppe Sanguineti

Regina Elena National Cancer Institute, Hospital Physiotherapy Institutes (IRCCS)

Claudio Fiorino

San Raffaele Hospital (IRCCS)

Riccardo Valdagni

University of Milan

Impact

154,396 Total views

109,281 Article views

41,983 Article downloads

3,132 Topic views

Published In

Frontiers in Oncology

Radiation Oncology

About Frontiers Research Topics

With their unique mixes of varied contributions from Original Research to Review Articles, Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author.

Suggest a topic