Literature DB >> 30622625

Prediction-Based Compensation for Gate On/Off Latency during Respiratory-Gated Radiotherapy.

Hisashi Johno1,2, Masahide Saito2, Hiroshi Onishi2.   

Abstract

During respiratory-gated radiotherapy (RGRT), gate on and off latencies cause deviations of gating windows, possibly leading to delivery of low- and high-dose radiations to tumors and normal tissues, respectively. Currently, there are no RGRT systems that have definite tools to compensate for the delays. To address the problem, we propose a framework consisting of two steps: (1) multistep-ahead prediction and (2) prediction-based gating. For each step, we have devised a specific algorithm to accomplish the task. Numerical experiments were performed using respiratory signals of a phantom and ten volunteers, and our prediction-based RGRT system exhibited superior performance in more than a few signal samples. In some, however, signal prediction and prediction-based gating did not work well, maybe due to signal irregularity and/or baseline drift. The proposed approach has potential applicability in RGRT, and further studies are needed to verify and refine the constituent algorithms.

Entities:  

Mesh:

Year:  2018        PMID: 30622625      PMCID: PMC6288586          DOI: 10.1155/2018/5919467

Source DB:  PubMed          Journal:  Comput Math Methods Med        ISSN: 1748-670X            Impact factor:   2.238


  2 in total

1.  Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

Authors:  Sangwoon Jeong; Wonjoong Cheon; Sungkoo Cho; Youngyih Han
Journal:  PLoS One       Date:  2022-10-18       Impact factor: 3.752

2.  Accuracy of real-time respiratory motion tracking and time delay of gating radiotherapy based on optical surface imaging technique.

Authors:  Li Chen; Sen Bai; Guangjun Li; Zhibin Li; Qing Xiao; Long Bai; Changhu Li; Lixun Xian; Zhenyao Hu; Guyu Dai; Guangyu Wang
Journal:  Radiat Oncol       Date:  2020-07-10       Impact factor: 3.481

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.