Your browser doesn't support javascript.
loading
Real-Time Temperature Rise Estimation during Irreversible Electroporation Treatment through State-Space Modeling.
Campelo, Sabrina N; Jacobs, Edward J; Aycock, Kenneth N; Davalos, Rafael V.
Afiliação
  • Campelo SN; Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA.
  • Jacobs EJ; Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA.
  • Aycock KN; Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA.
  • Davalos RV; Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Virginia Tech Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA 24061, USA.
Bioengineering (Basel) ; 9(10)2022 Sep 23.
Article em En | MEDLINE | ID: mdl-36290467
ABSTRACT
To evaluate the feasibility of real-time temperature monitoring during an electroporation-based therapy procedure, a data-driven state-space model was developed. Agar phantoms mimicking low conductivity (LC) and high conductivity (HC) tissues were tested under the influences of high (HV) and low (LV) applied voltages. Real-time changes in impedance, measured by Fourier Analysis SpecTroscopy (FAST) along with the known tissue conductivity and applied voltages, were used to train the model. A theoretical finite element model was used for external validation of the model, producing model fits of 95.8, 88.4, 90.7, and 93.7% at 4 mm and 93.2, 58.9, 90.0, and 90.1% at 10 mm for the HV-HC, LV-LC, HV-LC, and LV-HC groups, respectively. The proposed model suggests that real-time temperature monitoring may be achieved with good accuracy through the use of real-time impedance monitoring.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioengineering (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Bioengineering (Basel) Ano de publicação: 2022 Tipo de documento: Article