scholarly journals Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain

Diagnostics ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 299
Author(s):  
Iiro Ranta ◽  
Jarmo Teuho ◽  
Jani Linden ◽  
Riku Klén ◽  
Mika Teräs ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Attenuation Correction ◽  
Organs At Risk ◽  
External Beam Radiation ◽  
Dice Similarity Coefficient ◽  
Radiotherapy Treatment Planning ◽  
Beam Radiation ◽  
Dose Comparison ◽  
The Brain ◽  
Radiotherapy Treatment

Magnetic resonance imaging-only radiotherapy treatment planning (MRI-only RTP) and positron emission tomography (PET)–MRI imaging require generation of synthetic computed tomography (sCT) images from MRI images. In this study, initial dosimetric evaluation was performed for a previously developed MRI-based attenuation correction (MRAC) method for use in MRI-only RTP of the brain. MRAC-based sCT images were retrospectively generated from Dixon MR images of 20 patients who had previously received external beam radiation therapy (EBRT). Bone segmentation performance and Dice similarity coefficient of the sCT conversion method were evaluated for bone volumes on CT images. Dose calculation accuracy was assessed by recalculating the CT-based EBRT plans using the sCT images as the base attenuation data. Dose comparison was done for the sCT- and CT-based EBRT plans in planning target volume (PTV) and organs at risk (OAR). Parametric dose comparison showed mean relative differences of <0.4% for PTV and <1.0% for OARs. Mean gamma index pass rates of 95.7% with the 2%/2 mm agreement criterion and 96.5% with the 1%/1 mm agreement criterion were determined for glioma and metastasis patients, respectively. Based on the results, MRI-only RTP using sCT images generated from MRAC images can be a feasible alternative for radiotherapy of the brain.

scholarly journals Study Design: Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

2021 ◽  
Author(s):  
Aman Anand ◽  
Chris J. Beltran ◽  
Mark D. Brooke ◽  
Justine R. Buroker ◽  
Todd A. DeWees ◽  
...  
Keyword(s):  
At Risk ◽  
Deep Learning ◽  
Retrospective Study ◽  
Treatment Planning ◽  
Organs At Risk ◽  
Automated Segmentation ◽  
Radiotherapy Treatment Planning ◽  
Design Validation ◽  
Head And Neck Radiotherapy ◽  
Radiotherapy Treatment

AbstractThis document reports the design of a retrospective study to validate the clinical acceptability of a deep-learning-based model for the autosegmentation of organs-at-risk (OARs) for use in radiotherapy treatment planning for head & neck (H&N) cancer patients.

Delineation of organs at risk involved in swallowing for radiotherapy treatment planning

2011 ◽  
Vol 101 (3) ◽  
pp. 394-402 ◽  
Author(s):  
Miranda E.M.C. Christianen ◽  
Johannes A. Langendijk ◽  
Henriëtte E. Westerlaan ◽  
Tara A. van de Water ◽  
Hendrik P. Bijl
Keyword(s):  
At Risk ◽  
Treatment Planning ◽  
Organs At Risk ◽  
Radiotherapy Treatment Planning ◽  
Radiotherapy Treatment

scholarly journals Evaluation of a multi-atlas CT synthesis approach for MRI-only radiotherapy treatment planning

2017 ◽  
Vol 35 ◽  
pp. 7-17 ◽  
Author(s):  
F. Guerreiro ◽  
N. Burgos ◽  
A. Dunlop ◽  
K. Wong ◽  
I. Petkar ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Radiotherapy Treatment Planning ◽  
Synthesis Approach ◽  
Radiotherapy Treatment

EQUIVALENT UNIFORM DOSE SENSITIVITY TO CHANGES IN ABSORBED DOSE DISTRIBUTION

2013 ◽  
Vol 06 (01) ◽  
pp. 1250069
Author(s):  
FRANCISCO CUTANDA-HENRÍQUEZ ◽  
SILVIA VARGAS-CASTRILLÓN
Keyword(s):  
Treatment Planning ◽  
Dose Distribution ◽  
Absorbed Dose ◽  
Target Volume ◽  
Simple Expression ◽  
External Beam Radiation ◽  
Equivalent Uniform Dose ◽  
Beam Radiation ◽  
Dose Volume Histograms ◽  
Small Change

Treatment planning in external beam radiation therapy (EBRT) utilizes dose volume histograms (DVHs) as optimization and evaluation tools. They present the fraction of planning target volume (PTV) receiving more than a given absorbed dose, against the absorbed dose values, and a number of radiobiological indices can be computed with their help. Equivalent uniform dose (EUD) is the absorbed dose that, uniformly imparted, would yield the same biological effect on a tumor as the dose distribution described by the DVH. Uncertainty and missing information can affect the dose distribution, therefore DVHs can be modeled as samples from a set of possible outcomes. This work studies the sensitivity of the EUD index when a small change in absorbed dose distribution takes place. EUD is treated as a functional on the set of DVHs. Defining a Lévy distance on this set and using a suitable expansion of the functional, a very simple expression for a bound on the variation of EUD when the dose distribution changes is found. This bound is easily interpreted in terms of standard treatment planning practice.

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