About this Research Topic
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.
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.
Keywords: predictive models, toxicity, quality of life, radiation therapy, genomic, radiomic
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
