Particle swarm optimization solution for roll-off control in radiofrequency ablation of liver tumors: Optimal search for PID controller tuning
The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID par...
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| Veröffentlicht in: | PloS one 2024-06, Vol.19 (6), p.e0300445 |
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| creator | Faria, Rafael Mendes Rosa, Suélia de Siqueira Rodrigues Fleury Nunes, Gustavo Adolfo Marcelino de Almeida Santos, Klériston Silva de Souza, Rafael Pissinati Benavides, Angie Daniela Ibarra Alves, Angélica Kathariny de Oliveira da Silva, Ana Karoline Almeida Rosa, Mario Fabrício Cardoso, Antônio Aureliano de Anicêsio Faria, Sylvia de Sousa Berjano, Enrique da Rocha, Adson Ferreira Dos Santos, Ícaro González-Suárez, Ana |
| description | The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value ≪ 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques. |
| doi_str_mv | 10.1371/journal.pone.0300445 |
| format | Article |
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Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value ≪ 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0300445</identifier><identifier>PMID: 38924000</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Ablation ; Ablation (Surgery) ; Algorithms ; Animals ; Biology and Life Sciences ; Cancer therapies ; Carcinoma, Hepatocellular - surgery ; Catheter Ablation - methods ; Chemotherapy ; Computer and Information Sciences ; Computer Simulation ; Control algorithms ; Controllers ; Drug resistance ; Electrodes ; Heat ; Hepatocellular carcinoma ; Humans ; Hydration ; Immunotherapy ; Liver cancer ; Liver Neoplasms - surgery ; Liver tumors ; Mean ; Medicine and Health Sciences ; Optimization ; Particle swarm optimization ; Physical Sciences ; Proportional integral derivative ; Radio frequency ; Radiofrequency ablation ; Radiofrequency Ablation - methods ; Research and Analysis Methods ; Standard deviation ; Statistical analysis ; Temperature ; Thermal energy ; Transfer functions ; Tumors ; Tuning ; Variance ; Variance analysis ; Veins & arteries</subject><ispartof>PloS one, 2024-06, Vol.19 (6), p.e0300445</ispartof><rights>Copyright: © 2024 Faria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Faria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Faria et al 2024 Faria et al</rights><rights>2024 Faria et al. 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Faria, Rafael Mendes</au><au>Rosa, Suélia de Siqueira Rodrigues Fleury</au><au>Nunes, Gustavo Adolfo Marcelino de Almeida</au><au>Santos, Klériston Silva</au><au>de Souza, Rafael Pissinati</au><au>Benavides, Angie Daniela Ibarra</au><au>Alves, Angélica Kathariny de Oliveira</au><au>da Silva, Ana Karoline Almeida</au><au>Rosa, Mario Fabrício</au><au>Cardoso, Antônio Aureliano de Anicêsio</au><au>Faria, Sylvia de Sousa</au><au>Berjano, Enrique</au><au>da Rocha, Adson Ferreira</au><au>Dos Santos, Ícaro</au><au>González-Suárez, Ana</au><au>Heddam, Salim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Particle swarm optimization solution for roll-off control in radiofrequency ablation of liver tumors: Optimal search for PID controller tuning</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-06-26</date><risdate>2024</risdate><volume>19</volume><issue>6</issue><spage>e0300445</spage><pages>e0300445-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The study investigates the efficacy of a bioinspired Particle Swarm Optimization (PSO) approach for PID controller tuning in Radiofrequency Ablation (RFA) for liver tumors. Ex-vivo experiments were conducted, yielding a 9th order continuous-time transfer function. PSO was applied to optimize PID parameters, achieving outstanding simulation results: 0.605% overshoot, 0.314 seconds rise time, and 2.87 seconds settling time for a unit step input. Statistical analysis of 19 simulations revealed PID gains: Kp (mean: 5.86, variance: 4.22, standard deviation: 2.05), Ki (mean: 9.89, variance: 0.048, standard deviation: 0.22), Kd (mean: 0.57, variance: 0.021, standard deviation: 0.14) and ANOVA analysis for the 19 experiments yielded a p-value ≪ 0.05. The bioinspired PSO-based PID controller demonstrated remarkable potential in mitigating roll-off effects during RFA, reducing the risk of incomplete tumor ablation. These findings have significant implications for improving clinical outcomes in hepatocellular carcinoma management, including reduced recurrence rates and minimized collateral damage. The PSO-based PID tuning strategy offers a practical solution to enhance RFA effectiveness, contributing to the advancement of radiofrequency ablation techniques.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>38924000</pmid><doi>10.1371/journal.pone.0300445</doi><orcidid>https://orcid.org/0000-0002-0155-0392</orcidid><orcidid>https://orcid.org/0000-0001-9340-6568</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-06, Vol.19 (6), p.e0300445 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3072689268 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Ablation Ablation (Surgery) Algorithms Animals Biology and Life Sciences Cancer therapies Carcinoma, Hepatocellular - surgery Catheter Ablation - methods Chemotherapy Computer and Information Sciences Computer Simulation Control algorithms Controllers Drug resistance Electrodes Heat Hepatocellular carcinoma Humans Hydration Immunotherapy Liver cancer Liver Neoplasms - surgery Liver tumors Mean Medicine and Health Sciences Optimization Particle swarm optimization Physical Sciences Proportional integral derivative Radio frequency Radiofrequency ablation Radiofrequency Ablation - methods Research and Analysis Methods Standard deviation Statistical analysis Temperature Thermal energy Transfer functions Tumors Tuning Variance Variance analysis Veins & arteries |
| title | Particle swarm optimization solution for roll-off control in radiofrequency ablation of liver tumors: Optimal search for PID controller tuning |
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