Minimally Invasive Temperature Mapping for Laser Ablation: A Preliminary Study on Ex-vivo Livers

The optimization of laser ablation surgical procedures - specifically for the treatment of tumors - requires evaluating the temperature distribution across the entire area under treatment (e.g., the tumor volume). However, minimally invasive temperature sensors can only provide information in a limited number of points. Therefore, an effective prediction algorithm is required to reconstruct the temperature map for the entire heat affected tissue from as few temperature measurements as possible. This work presents an approach for predicting the temperature around the laser delivery fiber, based on the thermal Green's function, where patient-specific tissue thermal parameters are obtained through a fitting procedure using measurement of the temperature evolution at known locations. The proposed method is independent of the specific temperature sensor used; in the experiments reported, temperature was measured both at the prediction points and at validation points using quasi-distributed sensor composed of dense fiber Bragg grating (FBG) arrays, written with a femtosecond laser. A preliminary validation under ideal conditions, represented by ex-vivo cases, has been performed through a series of experiments on bovine liver samples. The obtained results demonstrate that it is possible to predict the temperature distribution across the entire ablated area, with errors well below the commonly accepted uncertainty for treatments of this type.