Implementation of automatic plan optimization in Italy: Status and perspectives

2021 ◽  
Vol 92 ◽  
pp. 86-94
Author(s):  
Stefania Pallotta ◽  
Livia Marrazzo ◽  
Silvia Calusi ◽  
Roberta Castriconi ◽  
Claudio Fiorino ◽  
...  
Keyword(s):  
2021 ◽  
Vol 22 (10) ◽  
pp. 329-337
Author(s):  
Huaizhi Geng ◽  
Tawfik Giaddui ◽  
Chingyun Cheng ◽  
Haoyu Zhong ◽  
Samuel Ryu ◽  
...  

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

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.


2011 ◽  
Vol 81 (2) ◽  
pp. S801-S802
Author(s):  
A.F. Uribe-Sanchez ◽  
X. Jia ◽  
C. Men ◽  
S. Jiang
Keyword(s):  

2016 ◽  
Author(s):  
Mohammad Yunus Khan ◽  
Anupam Tiwari ◽  
Shuichiro Ikeda ◽  
Fahad I. Syed ◽  
Alunood K. Al Sowaidi ◽  
...  

2018 ◽  
Vol 129 (Suppl1) ◽  
pp. 118-124 ◽  
Author(s):  
Alexis Dimitriadis ◽  
Ian Paddick

OBJECTIVEStereotactic radiosurgery (SRS) is characterized by high levels of conformity and steep dose gradients from the periphery of the target to surrounding tissue. Clinical studies have backed up the importance of these factors through evidence of symptomatic complications. Available data suggest that there are threshold doses above which the risk of symptomatic radionecrosis increases with the volume irradiated. Therefore, radiosurgical treatment plans should be optimized by minimizing dose to the surrounding tissue while maximizing dose to the target volume. Several metrics have been proposed to quantify radiosurgical plan quality, but all present certain weaknesses. To overcome limitations of the currently used metrics, a novel metric is proposed, the efficiency index (η50%), which is based on the principle of calculating integral doses: η50% = integral doseTV/integral dosePIV50%.METHODSThe value of η50% can be easily calculated by dividing the integral dose (mean dose × volume) to the target volume (TV) by the integral dose to the volume of 50% of the prescription isodose (PIV50%). Alternatively, differential dose-volume histograms (DVHs) of the TV and PIV50% can be used. The resulting η50% value is effectively the proportion of energy within the PIV50% that falls into the target. This value has theoretical limits of 0 and 1, with 1 being perfect. The index combines conformity, gradient, and mean dose to the target into a single value. The value of η50% was retrospectively calculated for 100 clinical SRS plans.RESULTSThe value of η50% for the 100 clinical SRS plans ranged from 37.7% to 58.0% with a mean value of 49.0%. This study also showed that the same principles used for the calculation of η50% can be adapted to produce an index suitable for multiple-target plans (Gη12Gy). Furthermore, the authors present another adaptation of the index that may play a role in plan optimization by calculating and minimizing the proportion of energy delivered to surrounding organs at risk (OARη50%).CONCLUSIONSThe proposed efficiency index is a novel approach in quantifying plan quality by combining conformity, gradient, and mean dose into a single value. It quantifies the ratio of the dose “doing good” versus the dose “doing harm,” and its adaptations can be used for multiple-target plan optimization and OAR sparing.


2016 ◽  
Vol 1 (4) ◽  
pp. 281-289 ◽  
Author(s):  
Martha M. Matuszak ◽  
Charles Matrosic ◽  
David Jarema ◽  
Daniel L. McShan ◽  
Matthew H. Stenmark ◽  
...  

2018 ◽  
Vol 128 (2) ◽  
pp. 375-379 ◽  
Author(s):  
Camilla Kronborg ◽  
Eva Serup-Hansen ◽  
Anna Lefevre ◽  
Eva E. Wilken ◽  
Jørgen B. Petersen ◽  
...  

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