Dosimetric investigation of lung tumor motion compensation with a robotic respiratory tracking system: An experimental study

2008 ◽  
Vol 35 (4) ◽  
pp. 1232-1240 ◽  
Author(s):  
Elena Nioutsikou ◽  
Yvette Seppenwoolde ◽  
J. Richard N. Symonds-Tayler ◽  
Ben Heijmen ◽  
Phil Evans ◽  
...  
Keyword(s):  
Experimental Study ◽  
Motion Compensation ◽  
Lung Tumor ◽  
Tracking System ◽  
Tumor Motion ◽  
Respiratory Tracking

Lung Tumor Motion Compensation during Real Time Respiratory Tracking using Gold Fiducial Markers

2008 ◽  
Vol 72 (1) ◽  
pp. S464-S465 ◽  
Author(s):  
K. Huang ◽  
S. Hossain ◽  
C. Chuang ◽  
M. Descovich ◽  
A. Gottschalk ◽  
...  
Keyword(s):  
Real Time ◽  
Motion Compensation ◽  
Lung Tumor ◽  
Fiducial Markers ◽  
Tumor Motion ◽  
Respiratory Tracking

Accuracy of tumor motion compensation algorithm from a robotic respiratory tracking system: A simulation study

2007 ◽  
Vol 34 (7) ◽  
pp. 2774-2784 ◽  
Author(s):  
Yvette Seppenwoolde ◽  
Ross I. Berbeco ◽  
Seiko Nishioka ◽  
Hiroki Shirato ◽  
Ben Heijmen
Keyword(s):  
Simulation Study ◽  
Motion Compensation ◽  
Tracking System ◽  
Tumor Motion ◽  
Compensation Algorithm ◽  
System A ◽  
Respiratory Tracking

scholarly journals Design and validation of a MV / kV imaging‐based markerless tracking system for assessing real‐time lung tumor motion

2018 ◽  
Vol 45 (12) ◽  
pp. 5555-5563 ◽  
Author(s):  
Pengpeng Zhang ◽  
Margie Hunt ◽  
Arina B. Telles ◽  
Hai Pham ◽  
Michael Lovelock ◽  
...  
Keyword(s):  
Real Time ◽  
Lung Tumor ◽  
Tracking System ◽  
Tumor Motion ◽  
Markerless Tracking

scholarly journals Study on Motion Management of Lung Cancer Treated by CyberKnife: Based on Tumor Position

2022 ◽  
Author(s):  
Shenghua Jing ◽  
Zhen Wang ◽  
Changchen Jiang ◽  
Xiangnan Qiu ◽  
Taincong Wu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Tumor ◽  
Tracking System ◽  
Lung Tumors ◽  
Prediction Errors ◽  
Baseline Drift ◽  
Anatomical Position ◽  
Standard Deviations ◽  
Respiratory Tracking ◽  
Motion Amplitude

Abstract Purpose: We investigated the movement characteristics of lung cancers and the clinical accuracy of tracking lung tumors with Synchrony Respiratory Tracking System (SRTs) during the CyberKnife treatment. We also explored the influencing factors of accuracy. These data provided the appropriate expansion margins of patients with different respiratory characteristics, which was helpful to realize the personalized design of treatment plans of CyberKnife. Methods and Materials: 73 patients with lung cancer treated with CyberKnife SRTs were selected retrospectively for this study. The patient's age, gender, respiratory characteristics and tumor datas (tumor size, anatomical position and geometric position) were recorded. During treatment, the deviation was checked every 45 s and compensated by the synchronous respiratory tracking system.Results: The total mean motion amplitudes and standard deviations of lung tumors in superior-inferior (SI), left-right (LR), and anterior-posterior (AP) directions were 4.15 ± 3.47 mm, 3.98 ± 3.21 mm and 3.79 ± 2.73 mm, respectively. The overall mean correlation errors and standard deviations were 0.86 ± 0.45 mm, 1.04 ± 0.76 mm and 0.70 ± 0.47 mm, respectively. The overall mean prediction errors and standard deviations were 0.18 ± 0.17 mm, 0.35 ± 0.39 mm and 0.35 ± 0.42 mm, respectively. The correlation errors of LR direction were less correlated with the geometric position of the tumor (r = 0.38), and not correlated with the anatomical position of the tumor (r < 0.3). The prediction errors were moderately correlated with the respiratory amplitude (r = 0.588), and less correlated with the baseline drift and the motion amplitude of the tumor (r = 0.407 and 0.365, respectively).Conclusions: The patient’s respiratory amplitude, the tumor motion amplitude, the tumor baseline drift and geometric position were the main factors affecting the tracking accuracy. Tumors at different geometric positions should be treated differently to ensure sufficient dose coverage of the lung tumor target.

SU-FF-J-109: Comparison of Lung Tumor Motion Profiles From 4D CT and a Treatment Tracking System

2009 ◽  
Vol 36 (6Part7) ◽  
pp. 2501-2501
Author(s):  
N Yu ◽  
C Chuang ◽  
A Gottschalk ◽  
S Yom ◽  
P Xia
Keyword(s):  
Lung Tumor ◽  
Tracking System ◽  
Tumor Motion ◽  
4D Ct

Intrafractional Baseline Shift or Drift of Lung Tumor Motion During Gated Radiation Therapy With a Real-Time Tumor-Tracking System

2016 ◽  
Vol 94 (1) ◽  
pp. 172-180 ◽  
Author(s):  
Seishin Takao ◽  
Naoki Miyamoto ◽  
Taeko Matsuura ◽  
Rikiya Onimaru ◽  
Norio Katoh ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Real Time ◽  
Lung Tumor ◽  
Tracking System ◽  
Tumor Motion ◽  
Tumor Tracking ◽  
Baseline Shift

Quantification of the geometric uncertainty when using implanted markers as a surrogate for lung tumor motion

2021 ◽  
Author(s):  
Nicholas Hardcastle ◽  
Adam Briggs ◽  
Vincent Caillet ◽  
Giorgios Angelis ◽  
Danielle Chrystall ◽  
...  
Keyword(s):  
Lung Tumor ◽  
Tumor Motion ◽  
Geometric Uncertainty

On using an adaptive neural network to predict lung tumor motion during respiration for radiotherapy applications

2005 ◽  
Vol 32 (12) ◽  
pp. 3801-3809 ◽  
Author(s):  
Marcus Isaksson ◽  
Joakim Jalden ◽  
Martin J. Murphy
Keyword(s):  
Neural Network ◽  
Lung Tumor ◽  
Tumor Motion ◽  
Adaptive Neural Network
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