Minimally invasive procedures are achieving better satisfaction for treating liver cancers. Energy-based techniques were studied as prospective alternatives to the gold standard of liver transplantation. Among these techniques, radiofrequency (RF) was investigated for the selective ablation of liver tissue. In addition to optimizing the RF settings for the purpose of overcoming tissue perforation or inadequate ablation, an instrument collecting quantitative data regarding the intraoperative tissue status can aid the treatment procedure. This study demonstrates an innovative noninvasive technique using hyperspectral imaging (HSI) for monitoring RF ablative therapy in ex-vivo liver tissue. The cubic data generated by HSI provides spectral as well as spatial properties of the liver tissue included in each pixel of the field of view. In our study, the applied statistical analysis saves the computational burdens of multivariate analysis techniques. For this purpose, spectral angle mapper, logistic regression algorithm, and principal component analysis were applied. Of all spectral bands captured by the HSI camera, bands centered at 760 and 960 nm were identified for predicting the ablated area. Based on statistical analysis, the threshold for predicting the ablated area of the liver samples was determined, provided that the specificity is kept at 90%.
Keywords: Hyperspectral imaging; Liver cancer; Medical imaging; RF ablation; Thermal ablation treatment.
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