Gating based on internal/external signals with dynamic correlation updates.
Precise localization of mobile tumor positions in real time is critical to the success of gated radiotherapy. Tumor positions are usually derived from either internal or external surrogates. Fluoroscopic gating based on internal surrogates, such as implanted fiducial markers, is accurate however requiring a large amount of imaging dose. Gating based on external surrogates, such as patient abdominal surface motion, is non-invasive however less accurate due to the uncertainty in the correlation between tumor location and external surrogates. To address these complications, we propose to investigate an approach based on hybrid gating with dynamic internal/external correlation updates. In this approach, the external signal is acquired at high frequency (such as 30 Hz) while the internal signal is sparsely acquired (such as 0.5 Hz or less). The internal signal is used to validate and update the internal/external correlation during treatment. Tumor positions are derived from the external signal based on the newly updated correlation. Two dynamic correlation updating algorithms are introduced. One is based on the motion amplitude and the other is based on the motion phase. Nine patients with synchronized internal/external motion signals are simulated retrospectively to evaluate the effectiveness of hybrid gating. The influences of different clinical conditions on hybrid gating, such as the size of gating windows, the optimal timing for internal signal acquisition and the acquisition frequency are investigated. The results demonstrate that dynamically updating the internal/external correlation in or around the gating window will reduce false positive with relatively diminished treatment efficiency. This improvement will benefit patients with mobile tumors, especially greater for early stage lung cancers, for which the tumors are less attached or freely floating in the lung.
Wu
Huanmei
H
Purdue School of Engineering and Technology, Indiana University School of Informatics, IUPUI, Indianapolis, IN, USA. hw9@iupui.edu
Zhao
Qingya
Q
Berbeco
Ross I
RI
Nishioka
Seiko
S
Shirato
Hiroki
H
Jiang
Steve B
SB
D000465:Algorithms; D003198:Computer Simulation; D005189:False Positive Reactions; D005471:Fluoroscopy / Q000379:methods; D006801:Humans; D015233:Models, Statistical; D009038:Motion; D009369:Neoplasms / Q000473:pathology* / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012189:Retrospective Studies; D013997:Time Factors