This work proposes the quasi-distributed real-time monitoring and control of laser ablation (LA) of liver tissue. To confine the thermal damage, a pre-planning stage of the control strategy based on numerical simulations of the bioheat-transfer was developed to design the control parameters, then experimentally assessed. Fiber Bragg grating (FBG) sensors were employed to design the automatic thermometry system used for temperature feedback control for interstitial LA. The tissue temperature was maintained at a pre-set value, and the influence of different sensor locations (on the direction of the beam propagation and backward) on the thermal outcome was evaluated in comparison with the uncontrolled case. Results show that the implemented computational model was able to properly describe the temperature evolution of the irradiated tissue. Furthermore, the realized control strategy allowed for the accurate confinement of the laser-induced temperature increase, especially when the temperature control was actuated by sensors located in the direction of the beam propagation, as confirmed by the calculated fractions of necrotic tissues (e.g., 23 mm³ and 53 mm³ for the controlled and uncontrolled LA, respectively).

Laser ablation (LA) of cancer is a minimally invasive technique based on targeted heat release. Controlling tissue temperature during LA is crucial to achieve the desired therapeutic effect in the organs while preserving the healthy tissue around. Here, we report the design and implementation of a real-time monitoring system performing closed-loop temperature control, based on fiber Bragg grating (FBG) spatial measurements. Highly dense FBG arrays (1.19 mm length, 0.01 mm edge-to-edge distance) were inscribed in polyimide-coated fibers using the femtosecond point-by-point writing technology to obtain the spatial resolution needed for accurate reconstruction of high-gradient temperature profiles during LA. The zone control strategy was implemented such that the temperature in the laser-irradiated area was maintained at specific set values (43 and 55 °C), in correspondence to specific radii (2 and 6 mm) of the targeted zone. The developed control system was assessed in terms of measured temperature maps during an ex vivo liver LA. Results suggest that the temperature-feedback system provides several advantages, including controlling the margins of the ablated zone and keeping the maximum temperature below the critical values. Our strategy and resulting analysis go beyond the state-of-the-art LA regulation techniques, encouraging further investigation in the identification of the optimal control-loop.

In cancer treatment, laser ablation is a promising technique used to induce localized thermal damage. Different variables influence the temperature distribution in the tissue and the resulting therapy efficacy; thus, the optimal therapy settings are required for obtaining the desired clinical outcome. In this work, thermomechanical modeling of contactless laser ablation was implemented to analyze the sensitivity of independent variables on the optimal treatment conditions. The Finite Element Method was utilized to solve the governing equations, i.e., the bioheat, mechanical deformation, and the Navier-Stokes equations. Validation of the model was performed by comparing experimental and simulated temperatures, which indicated high accuracy for estimating temperature. In particular, the results showed that the model can estimate temperature with a good correlation factor (R = 0.98) and low Mean Absolute Error (3.9 °C). A sensitivity analysis based on laser irradiation time, power, beam distribution, and the blood vessel depth on temperature distribution and fraction of necrotic tissue was performed. An optimization process was performed based on the most significant variables, i.e., laser irradiation time and power. This resulted in an indication of the optimal therapy settings for achieving maximum procedure efficiency i.e., the required fraction of necrotic tissue within the target volume, constituted by tumor and safety margins around it.

The current challenge in the field of thermo-ablative treatments of tumors is to achieve a balance between complete destruction of malignant cells and safeguarding of the surrounding healthy tissue. Blood perfusion plays a key role for thermal ablation success, especially in the case of highly vascularized organs like liver. This work aims at monitoring the temperature within perfused swine liver undergoing laser ablation (LA). Temperature was measured through seven arrays of Fiber Bragg Grating sensors (FBGs) around the laser applicator. To mimic reality, blood perfusion within the ex-vivo liver was simulated using artificial vessels. The influence of blood perfusion on LA was carried out by comparing the temperature profiles in two different spatial configurations of vessels and fibers. The proposed setup permitted to accurately measure the heat propagation in real-time with a temperature resolution of 0.1 °C and to observe a relevant tissue cooling near to the vessel up to 65%.

Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safely destroy the tumor. Although temperature imaging techniques provide an indirect measurement of the thermal damage, a degree of uncertainty remains about the treatment effect. Optical techniques are currently emerging as tools to directly assess tissue thermal damage. Among them, hyperspectral imaging (HSI) has shown promising results in image-guided surgery and in the thermal ablation field. The highly informative data provided by HSI, associated with deep learning, enable the implementation of non-invasive prediction models to be used intraoperatively. Here we show a novel paradigm “peak temperature prediction model” (PTPM), convolutional neural network (CNN)-based, trained with HSI and infrared imaging to predict LA-induced damage in the liver. The PTPM demonstrated an optimal agreement with tissue damage classification providing a consistent threshold (50.6 ± 1.5 °C) for the damage margins with high accuracy (~0.90). The high correlation with the histology score (r = 0.9085) and the comparison with the measured peak temperature confirmed that PTPM preserves temperature information accordingly with the histopathological assessment.

This work presents the potential of hyperspectral imaging (HSI) to monitor the thermal outcome of laser ablation therapy used for minimally invasive tumor removal. Our main goal is the establishment of indicators of the thermal damage of living tissues, which can be used to assess the effect of the procedure. These indicators rely on the spectral variation of temperature-dependent tissue chromophores, i.e., oxyhemoglobin, deoxyhemoglobin, methemoglobin, and water. Laser treatment was performed at specific temperature thresholds (from 60 to 110 °C) on in-vivo animal liver and was assessed with a hyperspectral camera (500–995 nm) during and after the treatment. The indicators were extracted from the hyperspectral images after the following processing steps: the breathing motion compensation and the spectral and spatial filtering, the selection of spectral bands corresponding to specific tissue chromophores, and the analysis of the areas under the curves for each spectral band. Results show that properly combining spectral information related to deoxyhemoglobin, methemoglobin, lipids, and water allows for the segmenting of different zones of the laser-induced thermal damage. This preliminary investigation provides indicators for describing the thermal state of the liver, which can be employed in the future as clinical endpoints of the procedure outcome.