DC Field | Value | Language |
---|---|---|
dc.contributor.author | Baik, Jinhwan | - |
dc.contributor.author | Lee, Sangyong | - |
dc.contributor.author | Yang, Sunchoel | - |
dc.contributor.author | Park, Sung-Min | - |
dc.date.accessioned | 2022-03-18T08:00:06Z | - |
dc.date.available | 2022-03-18T08:00:06Z | - |
dc.date.created | 2022-03-14 | - |
dc.date.issued | 2022-01 | - |
dc.identifier.issn | 0018-9456 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/110892 | - |
dc.description.abstract | Electrosurgery that ablates the target tissues such as tumor and nerve cells using radio-frequency (RF) heating has been widely employed in the medical industry. Although the thermal lesion plays a key role in the efficacy and safety for this method, it is still difficult to identify the depth and size of the lesion during the treatment using recent electrosurgical systems. Herein, we propose a novel electrosurgical instrument for real-time approximation of thermal lesions during RF ablation (RFA). Thermal lesions were numerically calculated based on theoretical thermal models using a hybrid central processing unit (CPU)-field-programmable gate array (FPGA) chip. Other functions such as RF control, voltage, and temperature measurements were implemented using RF components in a modular manner. It can solve voltage distribution in 6 ms by repeating the calculation 5000 times and can anticipate the thermal lesion in 15.6 ms within a time step in real-time simulations. As a real-world validation, the feasibility of the system was demonstrated through an animal study using a swine model. The system is modularly designed using off-the-shelf chips and RF components to improve flexibility and scalability. It can be easily compatible with existing RF surgical applications and medical imaging devices and can improve the efficacy of RFA therapy. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.isPartOf | IEEE Transactions on Instrumentation and Measurement | - |
dc.title | Modularized Electrosurgical System with a Hybrid CPU-FPGA Chip for Real-Time Thermal Lesion Approximation | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/tim.2022.3154817 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Instrumentation and Measurement, v.71, pp.1 - 1 | - |
dc.identifier.wosid | 000770005800018 | - |
dc.citation.endPage | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | IEEE Transactions on Instrumentation and Measurement | - |
dc.citation.volume | 71 | - |
dc.contributor.affiliatedAuthor | Park, Sung-Min | - |
dc.identifier.scopusid | 2-s2.0-85125339011 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | RADIOFREQUENCY ABLATION | - |
dc.subject.keywordPlus | PRINCIPLES | - |
dc.subject.keywordPlus | EMULATION | - |
dc.subject.keywordAuthor | Field-programmable-gate-array (FPGA) | - |
dc.subject.keywordAuthor | Finite-difference time domain (FDTD) | - |
dc.subject.keywordAuthor | Radiofrequency ablation | - |
dc.subject.keywordAuthor | Real-time numerical simulation | - |
dc.subject.keywordAuthor | Renal denervation | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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