Mathematical study of probe arrangement and nanoparticle injection effects on heat transfer during cryosurgery

Iceball growth 3D simulation model based on finite element method for hepatic cryoablation planning

BACKGROUND

Cryoablation simulation based on Finite Element Method (FEM) can facilitate preoperative planning for liver tumors. However, it has limited application in clinical practice due to its time-consuming process and improvable accuracy. We aimed to propose a FEM-based simulation model for rapid and accurate prediction of the iceball size during the hepatic cryofreezing cycle.

METHODS

A 3D simulation model was presented to predict the iceball size (frozen isotherm boundaries) in biological liver tissues undergoing cryofreezing based on the Pennes bioheat equation. The simulated results for three cryoprobe types were evaluated in the ex vivo porcine livers and clinical data. In ex vivo experiments, CT-based measurements of iceball size were fitted as growth curves and compared to the simulated results. Eight patient cases of CT-guided percutaneous hepatic cryoablation procedures were retrospectively collected for clinical validation. The Dice Score Coefficient (DSC) and Hausdorff distance (HD) were used to measure the similarity between simulation and ground truth segmentation.

RESULTS

The measurements in the ex vivo experiments showed a close similarity between the simulated and experimental iceball growth curves for three cryoprobe models, with all mean absolute error<2.9 mm and coefficient of determination>0.85. In the clinical validation, the simulation model achieved high accuracy with a DSC of 0.87 ± 0.03 and an HD of 2.0 ± 0.4 mm. The average computational time was 23.2 s for all simulations.

CONCLUSION

Our simulation model achieves accurate iceball size predictions within a short time during hepatic cryoablation and potentially allows for the implementation of the preoperative cryoablation planning system.

A Novel, Efficient, Unit Circle-Based, Method for Positioning and Operating Cryo-Surgical Probes in Convex Target Areas

A novel method for positioning and operating needle-like cryo-surgical probes in 2D convex target areas is presented. The method is based on the recorded dynamic performance of a single probe, termed "unit circle," (UC) embedded in a semi-infinite, tissue-like medium. Up to 15 cryo-probes, inserted into the same depth, are operated uniformly for 2-5 min. A predetermined number of probes are rearranged inside the target area until a "tight configuration" is obtained. The probes are initially arranged inside the target area such that the "lethal temperature" circles produced by them are tangent to its contour and to both adjacent lethal temperature circles. Subsequently, all probes are repositioned inwardly, each at a specific distance that depends on the local radius of curvature of the target area. Resulting total "defect areas"-internal and external-for a number of demonstrated cases, amounted to between 2.5% and 7.6% of the target area. The lower values of the defect areas were obtained with increasing numbers of inserted probes coupled with shorter operating times. Possible freezing damages to regions beyond the target area were reduced by up to about 30% for these cases. Similar results were obtained for a case of combined convex-concave target area, treated with additional, externally inserted, heating probes.

Selective nano-thermal therapy of human retinoblastoma in retinal laser surgery

In this research, an experimental validated predictive finite element model of a cancerous human eye is developed to investigate how the tumor cells in retinoblastoma can be selectively damaged in the course of laser irradiation. In the computational modeling, the tumor is assumed to be in the initial growth stages and located in the macular zone. The statistical calculations testify that an 8.5% improvement in our estimation of the experimental temperature inside the normal human eye compared to those provided by the previous model has been achieved. Under the surgical conditions, the at-risk regions are determined, and the thermal responses of the tissue to various intrinsic and operating factors are obtained and discussed. Our findings indicate that, in the same amount of exposure time, introducing biodegradable nanoparticles in a concentration of 0.2 into the tumor tissue can increase the lethal zone area by 51 percent, and could plays an effective role in surviving of corneal injury.

Numerical investigation of the effect of vessel size and distance on the cryosurgery of an adjacent tumor

Cryosurgery is an efficient cancer treatment which can be used for non-invasive ablation of some internal tumors such as liver and prostate. Tumors are usually located near the large blood vessels and the heat convection may affect the progression of the ice ball. Hence it is necessary to predict the surgery procedure and its consequences earlier. In spite of the recent studies it is still unclear that which arteries will significantly affect the freezing treatment of tumors and which can be ignored. Therefore a numerical model of a spherical 3 cm diameter liver tumor, subjected to cryosurgery was developed. The specific thermophysical properties were applied to the tumor and healthy tissues in frozen and unfrozen states. A simplified Hepatic artery with different anatomical diameters was placed in different positions relative to the tumor and energy and momentum equations were solved. The temperature distribution and the shape of the resultant ice ball were discussed. The results showed that a 4 mm diameter artery in the vicinity of a tumor will increase the minimum temperature achieved at the tumor boundary by 12.5 °C and therefore significantly affects the cryosurgery outcome. This may cause insufficient freezing which leads to incomplete death of tumor cells, failure of the surgery and tumor regenesis. Eventually it was shown that injection of gold and Fe₃O₄ nanoparticles to the surrounding tissue of the artery can enhance the heat transfer and progression of the ice ball, making temperature distribution similar to the no vessel state. Development of computational models can provide the physicians an applicable tool which helps them recognize how efficient a treatment method will be for a specific case and design a suitable cryosurgery plan.