scholarly journals Inverse plan optimization accounting for random geometric uncertainties with a multiple instance geometry approximation (MIGA)

2006 ◽  
Vol 33 (5) ◽  
pp. 1510-1521 ◽  
Author(s):  
D. L. McShan ◽  
M. L. Kessler ◽  
K. Vineberg ◽  
B. A. Fraass
2021 ◽  
Vol 22 (10) ◽  
pp. 329-337
Author(s):  
Huaizhi Geng ◽  
Tawfik Giaddui ◽  
Chingyun Cheng ◽  
Haoyu Zhong ◽  
Samuel Ryu ◽  
...  

2006 ◽  
Vol 13 (3) ◽  
pp. 108-115 ◽  
Author(s):  
O. Ballivy ◽  
W. Parker ◽  
T. Vuong ◽  
G. Shenouda ◽  
H. Patrocinio

We assessed the effect of geometric uncertainties on target coverage and on dose to the organs at risk (OARS) during intensity-modulated radiotherapy (IMRT) for head-and-neck cancer, and we estimated the required margins for the planning target volume (PTV) and the planning organ-at-risk volume (PRV). For eight headand- neck cancer patients, we generated IMRT plans with localization uncertainty margins of 0 mm, 2.5 mm, and 5.0 mm. The beam intensities were then applied on repeat computed tomography (CT) scans obtained weekly during treatment, and dose distributions were recalculated. The dose–volume histogram analysis for the repeat CT scans showed that target coverage was adequate (V100 ≥ 95%) for only 12.5% of the gross tumour volumes, 54.3% of the upper-neck clinical target volumes (CTVS), and 27.4% of the lower-neck CTVS when no margins were added for PTV. The use of 2.5-mm and 5.0-mm margins significantly improved target coverage, but the mean dose to the contralateral parotid increased from 25.9 Gy to 29.2 Gy. Maximum dose to the spinal cord was above limit in 57.7%, 34.6%, and 15.4% of cases when 0-mm, 2.5-mm, and 5.0-mm margins (respectively) were used for PRV. Significant deviations from the prescribed dose can occur during IMRT treatment delivery for headand- neck cancer. The use of 2.5-mm to 5.0-mm margins for PTV and PRV greatly reduces the risk of underdosing targets and of overdosing the spinal cord.


2020 ◽  
Vol 152 ◽  
pp. S51-S52
Author(s):  
H. Langendijk ◽  
L. Van den Bosch ◽  
A. Van den Hoek ◽  
E. Oldehinkel ◽  
T. Meijer ◽  
...  

Author(s):  
Recep M. Gorguluarslan ◽  
O. Utku Gungor

Abstract In this study, the influence of the spatial variability of geometric uncertainties on the strut members of the lattice structures fabricated by additive manufacturing is investigated. Individual struts are fabricated with various printing angles and diameters using a material extrusion process and PLA material. The diameter values of the fabricated samples are measured along the printing and radial directions at each layer under an optical microscope. Spatial correlations are characterized based on the measurements using the experimental autocorrelation function. Candidate autocorrelation functions are fitted to the measured data to identify the best fitted one for each diameter parameter and the corresponding correlation lengths are evaluated for random field. The applicability of the Karhunen-Loeve expansion (KLE) is investigated to reduce the dimensionality of the random field discretization. The results show that the diameters of the strut members at each layer are spatially dependent and the KLE method was found to give a good representation of the random field.


2018 ◽  
Vol 3 (3) ◽  
pp. 32 ◽  
Author(s):  
Shane Haladuick ◽  
Markus Dann

For engineering systems, decision analysis can be used to determine the optimal decision from a set of options via utility maximization. Applied to inspection and maintenance planning, decision analysis can determine the best inspection and maintenance plan to follow. Decision analysis is relatively straightforward for simple systems. However, for more complex systems with many components or defects, the set of all possible inspection and maintenance plans can be very large. This paper presents the use of a genetic algorithm to perform inspection and maintenance plan optimization for complex systems. The performance of the genetic algorithm is compared to optimization by exhaustive search. A numerical example of life cycle maintenance planning for a corroding pressure vessel is used to illustrate the method. Genetic algorithms are found to be an effective approach to reduce the computational demand of solving complex inspection and maintenance optimizations.


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