Aim: Development of bidirectional non-monotonic segmented leaf sequence (nsls) MLC delivery technique compatible with Varian MLC for non-split IMRT fields reducing total monitor units (TotaIMU) and the number of segme...
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Aim: Development of bidirectional non-monotonic segmented leaf sequence (nsls) MLC delivery technique compatible with Varian MLC for non-split IMRT fields reducing total monitor units (TotaIMU) and the number of segments (NS) simultaneously and assessment of its efficiency using a plan scoring index (PSI). Materials and methods: The optimal fluence of IMRT plans of ten patients of lung carcinoma, calculated using Eclipse TPS version 11.0 (Varian Medical Systems, Palo Alto, CA, USA), was used to generate the segmented MLC fields using our newly developed equally spaced (ES) reducing level and nsls algorithms in MATLAB (R) version 2011b for 6-10 intensity levels. These MLC fields were imported into the plans with the same field setup and the final dose was recalculated. The results were compared with those of commercially available multiple static segments (MSS) leaf motion calculation (LMC) algorithm and few previously published algorithms. Plan scoring index (PSI) and degree of modulation (DoM) was calculated to compare the quality of different plans for the same patient. Results: The average differences in TotaIMU and NS with respect to MSS algorithm are -3.80% and -14.28% for the nsls algorithm, respectively. The calculated average PSI and DoM is 0.75, 2.51 and 0.91, 2.41 for the MSS and nsls algorithms, respectively. Conclusions: IMRT plans generated using the nsls algorithm resulted in the best PSI, DoM values among all the leaf sequencing algorithms. Our proposed nsls algorithm allows bidirectional delivery in Varian medical linear accelerator which is not commercially available. nsls algorithm is efficient in reducing the TotaIMU and NS with equivalent plan quality as that of MSS. (C) 2020 Greater Poland Cancer Centre. Published by Elsevier B.V. All rights reserved.
A new multi-objective optimisation algorithm called non-dominated sorting and local search (nsls) algorithm is proposed for uniformly excited aperiodic array synthesis here. Two design cases of uniformly excited linea...
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A new multi-objective optimisation algorithm called non-dominated sorting and local search (nsls) algorithm is proposed for uniformly excited aperiodic array synthesis here. Two design cases of uniformly excited linear and planar array synthesis are conducted to verify the outperformance of nsls. Synthesis results indicate that nsls is able to obtain the lowest maximum sidelobe level (MSLL) and the deepest null depth level in linear array design case, along with the lowest MSLLs in two planes of radiation pattern in planar array design case compared with the other latest algorithms. In addition, the convergence performance and computational costs of nsls in the design cases are investigated. The synthesis results combined with excellent convergence performance and low computational costs of nsls make it a reliable and promising optimisation algorithm for uniformly excited aperiodic array synthesis.
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