scholarly journals Quantitative cone-beam CT imaging in radiation therapy using planning CT as a prior: First patient studies

2012 ◽  
Vol 39 (4) ◽  
pp. 1991-2000 ◽  
Author(s):  
Tianye Niu ◽  
Ahmad Al-Basheer ◽  
Lei Zhu
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Ct Imaging ◽  
Cone Beam ◽  
Planning Ct ◽  
Patient Studies

WE-C-WAB-07: Quantitative Cone-Beam CT Imaging in Radiation Therapy Using Planning CT as a Prior: Clinical Assessments

2013 ◽  
Vol 40 (6Part29) ◽  
pp. 479-479 ◽  
Author(s):  
HY Zhang ◽  
L Liu ◽  
H Wu ◽  
HZ Yue ◽  
TY Niu ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Ct Imaging ◽  
Cone Beam ◽  
Clinical Assessments ◽  
Planning Ct

4D cone-beam CT imaging for guidance in radiation therapy: setup verification by use of implanted fiducial markers

2016 ◽  
Author(s):  
Peng Jin ◽  
Niek van Wieringen ◽  
Maarten C. C. M. Hulshof ◽  
Arjan Bel ◽  
Tanja Alderliesten
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Ct Imaging ◽  
Cone Beam ◽  
Fiducial Markers ◽  
Setup Verification

SU-FF-T-86: Assessment of Carbon Fiber and Synthetic Fiber Radiation Therapy Tabletops for Kilovoltage Cone Beam CT Imaging

2007 ◽  
Vol 34 (6Part8) ◽  
pp. 2420-2420
Author(s):  
J Ye ◽  
T Wong ◽  
D Cao ◽  
M Afghan ◽  
J Riley ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Carbon Fiber ◽  
Cone Beam Ct ◽  
Ct Imaging ◽  
Synthetic Fiber ◽  
Cone Beam

Fast shading correction for cone beam CT in radiation therapy via sparse sampling on planning CT

2017 ◽  
Vol 44 (5) ◽  
pp. 1796-1808 ◽  
Author(s):  
Linxi Shi ◽  
Tiffany Tsui ◽  
Jikun Wei ◽  
Lei Zhu
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Sparse Sampling ◽  
Cone Beam ◽  
Planning Ct

Automated Liver Segmentation for Cone Beam CT Dataset by Probabilistic Atlas Construction

2012 ◽  
Vol 195-196 ◽  
pp. 583-588
Author(s):  
Deng Wang Li ◽  
Hong Jun Wang ◽  
Da Chen ◽  
Yong Yin
Keyword(s):  
Radiation Therapy ◽  
Cone Beam Ct ◽  
Ct Images ◽  
Cone Beam ◽  
Treatment Delivery ◽  
Low Contrast ◽  
Image Guided Radiation Therapy ◽  
Probabilistic Atlas ◽  
Atlas Construction ◽  
Planning Ct

Cone beam CT based image guided radiation therapy can be used to measure and correct positional errors for target and critical structures immediately prior to or during the treatment delivery. Data correlation between Planning CT images and daily CBCT images is the key issue for adaptive radiation therapy, including image registration and segmentation processing. In this paper, aiming for getting accurate liver contour structures automatically in daily CBCT images which is very low-contrast comparing the planning CT, probabilistic atlas is constructed from 50 high contrast planning CT images with manual delineation by oncologist. The incoming CBCT images are registered with the atlas using the deformable registration algorithm, and the liver contour structures are generated automatically by using the deformation map. The experiment results demonstrate the efficiency of our algorithm.

scholarly journals Analysis of local setup errors of sub-regions in cone-beam CT-guided post-mastectomy radiation therapy

2020 ◽  
Vol 61 (3) ◽  
pp. 457-463 ◽  
Author(s):  
Jidan Zhou ◽  
Shuai Li ◽  
Chengwei Ye ◽  
Konglong Shen ◽  
An Li ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Chest Wall ◽  
Cone Beam Ct ◽  
Target Volume ◽  
Cone Beam ◽  
Wall Region ◽  
Ct Guided ◽  
Setup Errors ◽  
Planning Ct ◽  
Anterior Posterior

ABSTRACT The purpose of the study was to quantify local setup errors and evaluate the planning target volume (PTV) margins for sub-regions in cone-beam computed tomography (CBCT)-guided post-mastectomy radiation therapy (PMRT). The local setup errors of 20 patients undergoing CBCT-guided PMRT were analysed retrospectively. Image registration between CBCT and planning CT was performed using four sub-regions of interest (ROIs): the supraclavicular area (SROI), ipsilateral chest wall region (CROI), ipsilateral chest wall plus supraclavicular region (SROI + CROI) and vertebral region (TROI). Bland–Altman analysis, correlation, local setup errors and PTV margins among these ROIs were evaluated. There was no significant consistency or correlation for registration results between the TROI and the CROI or SROI regions on any translational axis. When using the SROI + CROI as the ROI, the systematic error (Σ) and random error (σ) of the local setup errors for the CROI region were 1.81, 1.19 and 1.76 mm and 1.84, 2.64 and 3.00 mm along the medial–lateral (ML), superior–inferior (SI) and anterior–posterior (AP) directions, respectively. The PTV margins for the CROI region were 5.80, 4.82 and 6.50 mm. The Σ and σ of the local setup errors for the SROI region were 1.29, 1.15 and 0.77 mm and 1.96, 2.65 and 2.2 mm, respectively, and the PTV margins were 4.59, 4.73 and 3.47 mm. Large setup errors and local setup errors occur in PMRT. The vertebral body should not be a position surrogate for the supraclavicular region or chest wall. To compensate for the local setup errors, different PTV margins are required, even with CBCT guidance.

Sign in / Sign up

Export Citation Format

Share Document