Feasibility of a Novel In-situ Local Tumor Ablation and Recycling Machine Based on Radiofrequency Dielectric Heating: In-depth Review on Research Background and Preliminary Report of an Experimental Study.

Abstract

Background: In bone sarcomas, chemotherapy has improved the prognosis with advances in diagnostic and surgical technologies, which has led to attempts to save limbs. As early detection and multidisciplinary treatment have improved the survival rate, curative surgery is considered for selected patients with metastatic bone carcinomas. Limb salvage procedures may vary in relation to the reconstruction method, which is accompanied by different complications. To overcome them, we devised a novel concept, in-situ local tumor ablation and recycling machine based on radiofrequency (RF)-induced heating and intended experiments to demonstrate its feasibility.

Methods: The fresh femurs of 6-month-old pigs were used after removing the epiphyses; the distal parts were placed in a heating chamber. Fiber-optic temperature sensors were inserted in the metaphysis, meta-diaphysis, and diaphysis. Temperatures were measured six times each during heating at 27.12 MHz at various powers. Additionally, the compressive and bending stiffnesses were measured six times each for the unprocessed, RF-treated, and pasteurized bones, and the results were compared.

Results: Under 200 W power output, the temperatures at all measurement sites reached 70 ℃ or higher in 6 minutes, and the temperatures were maintained. The median compressive stiffness of RF-heated bones was 79.2% higher than that of pasteurized bones, but the difference was statistically insignificant. The median bending stiffness of RF-heated bones was approximately 66.3% of that of unprocessed bones, which was 20% higher than that of pasteurized bones.

Conclusions: The feasibility to rapidly attain and maintain temperatures for tumor ablation is shown, which favorably preserves bone stiffness through the in-situ local tumor ablation and recycling based on RF heating. The problem of nonuniform temperature distribution might be solved by an optimal design determined from simulation research and additional experiments.