scholarly journals Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy

10.3791/52875 ◽  
2015 ◽  
Author(s):  
Charles A. Kunos ◽  
Jeffrey M. Fabien ◽  
John P. Shanahan ◽  
Christine Collen ◽  
Thierry Gevaert ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Lung Tumor ◽  
Tumor Tracking

Baseline Shift of Intrafractional Lung Tumor Motion in Real-Time Tumor-Tracking Radiation Therapy

2013 ◽  
Vol 87 (2) ◽  
pp. S67
Author(s):  
S. Takao ◽  
N. Miyamoto ◽  
T. Matsuura ◽  
S. Shimizu ◽  
R. Onimaru ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Real Time ◽  
Lung Tumor ◽  
Tumor Motion ◽  
Tumor Tracking ◽  
Baseline Shift

scholarly journals A Novel Markerless Lung Tumor-Tracking Method Using Treatment MV Beam Imaging

2018 ◽  
Vol 8 (12) ◽  
pp. 2525 ◽  
Author(s):  
Timothy Rozario ◽  
Tsuicheng Chiu ◽  
Mingli Chen ◽  
Xun Jia ◽  
Weiguo Lu ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Lung Tumor ◽  
Imaging Modality ◽  
Average Error ◽  
Lung Cancer Patients ◽  
Tumor Tracking ◽  
Novel Method ◽  
Projection Images ◽  
Phantom Studies ◽  
Maximum Average Error

A novel method was developed to track lung tumor motion in real time during radiation therapy with the purpose to allow target radiation dose escalation while simultaneously reducing the dose to sensitive structures, thereby increasing local control without increasing toxicity. This method analyzes beam’s eye view radiation therapy treatment megavoltage (MV) images with simulated digitally reconstructed radiographs (DRRs) as references. Instead of comparing global DRRs with projection images, this method incorporates a technique that divides the global composite DRR and the corresponding MV projection into sub-images called tiles. Registration is performed independently on tile pairs in order to reduce the effects of global discrepancies due to scattering or imaging modality differences. This algorithm was evaluated by phantom studies while simulated tumors were controlled to move with various patterns in a complex humanoid torso. Approximately 15,000 phantom MV images were acquired at nine gantry angles, with different tumors moving within ranges between 10 and 20 mm. Tumors were successfully identified on every projection with a total maximum/average error of 1.84/0.98 mm. This algorithm was also applied to over 5,000 frames of MV projections acquired during radiation therapy of five lung cancer patients. This tumor-tracking methodology is capable of accurately locating lung tumors during treatment without implanting any internal fiducial markers nor delivering extra imaging radiation doses.

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

scholarly journals Real-Time Lung Tumor Tracking Using a CUDA Enabled Nonrigid Registration Algorithm for MRI

2020 ◽  
Vol 8 ◽  
pp. 1-8
Author(s):  
Nazanin Tahmasebi ◽  
Pierre Boulanger ◽  
Jihyun Yun ◽  
Gino Fallone ◽  
Michelle Noga ◽  
...  
Keyword(s):  
Real Time ◽  
Lung Tumor ◽  
Nonrigid Registration ◽  
Registration Algorithm ◽  
Tumor Tracking

Fiducial-free Lung Tumor Tracking for CyberKnife Radiosurgery

2008 ◽  
Vol 72 (1) ◽  
pp. S608-S609 ◽  
Author(s):  
D. Fu ◽  
R. Kahn ◽  
B. Wang ◽  
H. Wang ◽  
Z. Mu ◽  
...  
Keyword(s):  
Lung Tumor ◽  
Tumor Tracking ◽  
Cyberknife Radiosurgery
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