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Creation of a tumor-mimic model using a muscle paste for radiofrequency ablation of the lung.

作者信息

Kawai T, Kaminou T, Sugiura K, Hashimoto M, Ohuchi Y, Adachi A, Fujioka S, Ito H, Nakamura K, Ogawa T

机构信息

Department of Pathophysiological and Therapeutic Science, Division of Radiology, Faculty of Medicine, Tottori University, Yonago, Tottori, Japan.

出版信息

Cardiovasc Intervent Radiol. 2009 Mar;32(2):296-302. doi: 10.1007/s00270-008-9463-9. Epub 2008 Nov 11.

DOI:10.1007/s00270-008-9463-9
PMID:19002525
Abstract

The purpose of this study was to develop an easily created tumor-mimic model and evaluate its efficacy for radiofrequency ablation (RFA) of the lung. The bilateral lungs of eight living adult swine were used. A tumor-mimic model was made by percutaneous injection of 1.0 ml muscle paste through the bone biopsy needle into the lung. An RFA probe was then inserted into the tumor mimics immediately after tumor creation. Ablation time, tissue impedance, and temperature were recorded. The tumor mimics and their coagulated regions were evaluated microscopically and macroscopically. The muscle paste was easily injected into the lung parenchyma through the bone biopsy needle and well visualized under fluoroscopy. In 10 of 12 sites the tumor mimics were oval shaped, localized, and homogeneous on gross specimens. Ten tumor mimics were successfully ablated, and four locations were ablated in the normal lung parenchyma as controls. In the tumor and normal lung parenchyma, ablation times were 8.9 +/- 3.5 and 4.4 +/- 1.6 min, respectively; tissue impedances at the start of ablation were 100.6 +/- 16.6 and 145.8 +/- 26.8 Omega, respectively; and temperatures at the end of ablation were 66.0 +/- 7.9 and 57.5 +/- 7.6 degrees C, respectively. The mean size of tumor mimics was 13.9 x 8.2 mm, and their coagulated area was 18.8 x 13.1 mm. In the lung parenchyma, the coagulated area was 15.3 x 12.0 mm. In conclusion, our tumor-mimic model using muscle paste can be easily and safely created and can be ablated using the ablation algorithm in the clinical setting.

摘要

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