| Title: |
Adaptive proton therapy |
| Authors: |
Paganetti, Harald; Botas, Pablo; Sharp, Gregory C; Winey, Brian |
| Contributors: |
National Cancer Institute |
| Source: |
Physics in Medicine & Biology ; volume 66, issue 22, page 22TR01 ; ISSN 0031-9155 1361-6560 |
| Publisher Information: |
IOP Publishing |
| Publication Year: |
2021 |
| Description: |
Radiation therapy treatments are typically planned based on a single image set, assuming that the patient’s anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research. |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| DOI: |
10.1088/1361-6560/ac344f |
| DOI: |
10.1088/1361-6560/ac344f/pdf |
| Availability: |
https://doi.org/10.1088/1361-6560/ac344f; https://iopscience.iop.org/article/10.1088/1361-6560/ac344f; https://iopscience.iop.org/article/10.1088/1361-6560/ac344f/pdf |
| Rights: |
https://publishingsupport.iopscience.iop.org/iop-standard/v1 ; https://iopscience.iop.org/info/page/text-and-data-mining |
| Accession Number: |
edsbas.159CA300 |
| Database: |
BASE |