Model-Based Thermometry for Laser Ablation Procedure Using Kalman Filters and Sparse Temperature Measurements

The State-of-the-Art and Perspectives of Laser Ablation for Tumor Treatment

Tumors significantly impact individuals' physical well-being and quality of life. With the ongoing advancements in optical technology, information technology, robotic technology, etc., laser technology is being increasingly utilized in the field of tumor treatment, and laser ablation (LA) of tumors remains a prominent area of research interest. This paper presents an overview of the recent progress in tumor LA therapy, with a focus on the mechanisms and biological effects of LA, commonly used ablation lasers, image-guided LA, and robotic-assisted LA. Further insights and future prospects are discussed in relation to these aspects, and the paper proposed potential future directions for the development of tumor LA techniques.

Optimization of laser dosimetry based on patient-specific anatomical models for the ablation of pancreatic ductal adenocarcinoma tumor

Laser-induced thermotherapy has shown promising potential for the treatment of unresectable primary pancreatic ductal adenocarcinoma tumors. Nevertheless, heterogeneous tumor environment and complex thermal interaction phenomena that are established under hyperthermic conditions can lead to under/over estimation of laser thermotherapy efficacy. Using numerical modeling, this paper presents an optimized laser setting for Nd:YAG laser delivered by a bare optical fiber (300 µm in diameter) at 1064 nm working in continuous mode within a power range of 2-10 W. For the thermal analysis, patient-specific 3D models were used, consisting of tumors in different portions of the pancreas. The optimized laser power and time for ablating the tumor completely and producing thermal toxic effects on the possible residual tumor cells beyond the tumor margins were found to be 5 W for 550 s, 7 W for 550 s, and 8 W for 550 s for the pancreatic tail, body, and head tumors, respectively. Based on the results, during the laser irradiation at the optimized doses, thermal injury was not evident either in the 15 mm lateral distances from the optical fiber or in the nearby healthy organs. The present computational-based predictions are also in line with the previous ex vivo and in vivo studies, hence, they can assist in the estimation of the therapeutic outcome of laser ablation for pancreatic neoplasms prior to clinical trials.

Unscented Kalman Filtering for Real Time Thermometry During Laser Ablation Interventions

We present a data-assimilation Bayesian framework in the context of laser ablation for the treatment of cancer. For solving the nonlinear estimation of the tissue temperature evolving during the therapy, the Unscented Kalman Filter (UKF) predicts the next thermal status and controls the ablation process, based on sparse temperature information. The purpose of this paper is to study the outcome of the prediction model based on UKF and to assess the influence of different model settings on the framework performances. In particular, we analyze the effects of the time resolution of the filter and the number and the location of the observations. Clinical Relevance - The application of a data-assimilation approach based on limited temperature information allows to monitor and predict in real-time the thermal effects induced by thermal therapy for tumors.