Tissue characterization utilizing hyperspectral imaging for liver thermal ablation.

Background: Thermal ablation is the dominant modality to treat liver tumors for patients who are not surgical candidates. . However, correctly predicting the volume of the subsequent tissue destruction during the Thermal Ablation technique is a difficult undertaking.

Objective: To examine the impacts of ablation zone volume following Radiofrequency ablation (RFA) of an ex-vivo bovine liver to correlate the impacts of thermal ablation with target organ perfusion; by exploiting the unique properties of Hyperspectral Imaging (HSI).

Materials And Methods: Radiofrequency ablation was perfused on ex-vivo bovine livers at peripheral and central‑vessel‑adjacent locations, and monitored by HSI with a spectral range from 400 to 1000 nm. The system contains k-means clustering (K = 8) algorithms combining spectral and spatial information. Labeled spectral signatures datasets were used as training data. Statistical analysis (10 samples) was computed to calculate the highest variance between six spectral images for determining the optimum wavelength for discrimination between the affected regions after thermal ablation (normal, thermal, and ablated liver tissue regions).

Results: The change of the optical properties ofex-vivo liver tissues provides different responses to light transmission, scattering, absorption and particularly the reflection over the spectrum range. The produced spectral image from reflection with the highest variance (358.07) empowered us to determine the optimum wavelength spectral image (720 ± 18.92 nm) to distinguish between the normal, ablated, and thermal categories.

Conclusion: Hyperspectral imaging is a powerful tool in monitoring tissue characterization, which is a useful technique for edge evaluation of liver thermal ablation ..