On Efficacy of Microwave Ablation in the Thermal Treatment of an Early-Stage Hepatocellular Carcinoma

Using Patient-Specific 3D Modeling and Simulations to Optimize Microwave Ablation Therapy for Liver Cancer

Microwave ablation (MWA) of liver tumors presents challenges like under- and over-ablation, potentially leading to inadequate tumor destruction and damage to healthy tissue. This study aims to develop personalized three-dimensional (3D) models to simulate MWA for liver tumors, incorporating patient-specific characteristics. The primary objective is to validate the predicted ablation zones compared to clinical outcomes, offering insights into MWA before therapy to facilitate accurate treatment planning. Contrast-enhanced CT images from three patients were used to create 3D models. The simulations used coupled electromagnetic wave propagation and bioheat transfer to estimate the temperature distribution, predicting tumor destruction and ablation margins. The findings indicate that prolonged ablation does not significantly improve tumor destruction once an adequate margin is achieved, although it increases tissue damage. There was a substantial overlap between the clinical ablation zones and the predicted ablation zones. For patient 1, the Dice score was 0.73, indicating high accuracy, with a sensitivity of 0.72 and a specificity of 0.76. For patient 2, the Dice score was 0.86, with a sensitivity of 0.79 and a specificity of 0.96. For patient 3, the Dice score was 0.8, with a sensitivity of 0.85 and a specificity of 0.74. Patient-specific 3D models demonstrate potential in accurately predicting ablation zones and optimizing MWA treatment strategies.

Imaging Delay Following Liver-Directed Therapy Increases Progression Risk in Early- to Intermediate-Stage Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related deaths in the world. Patients with early-stage HCC are treated with liver-directed therapies to bridge or downstage for liver transplantation (LT). In this study, the impact of HCC care delay on HCC progression among early-stage patients was investigated. Early-stage HCC patients undergoing their first cycle of liver-directed therapy (LDT) for bridge/downstaging to LT between 04/2016 and 04/2022 were retrospectively analyzed. Baseline variables were analyzed for risk of disease progression and time to progression (TTP). HCC care delay was determined by the number of rescheduled appointments related to HCC care. The study cohort consisted of 316 patients who received first-cycle LDT. The HCC care no-show rate was associated with TTP (p = 0.004), while the overall no-show rate was not (p = 0.242). The HCC care no-show rate and HCC care delay were further expanded as no-show rates and rescheduled appointments for imaging, laboratory, and office visits, respectively. More than 60% of patients experienced HCC care delay for imaging and laboratory appointments compared to just 8% for office visits. Multivariate analysis revealed that HCC-specific no-show rates and HCC care delay for imaging (p < 0.001) were both independently associated with TTP, highlighting the importance of minimizing delays in early-stage HCC imaging surveillance to reduce disease progression risk.

Simulation of Image-Guided Microwave Ablation Therapy Using a Digital Twin Computational Model

Emerging computational tools such as healthcare digital twin modeling are enabling the creation of patient-specific surgical planning, including microwave ablation to treat primary and secondary liver cancers. Healthcare digital twins (DTs) are anatomically one-to-one biophysical models constructed from structural, functional, and biomarker-based imaging data to simulate patient-specific therapies and guide clinical decision-making. In microwave ablation (MWA), tissue-specific factors including tissue perfusion, hepatic steatosis, and fibrosis affect therapeutic extent, but current thermal dosing guidelines do not account for these parameters. This study establishes an MR imaging framework to construct three-dimensional biophysical digital twins to predict ablation delivery in livers with 5 levels of fat content in the presence of a tumor. Four microwave antenna placement strategies were considered, and simulated microwave ablations were then performed using 915 MHz and 2450 MHz antennae in Tumor Naïve DTs (control), and Tumor Informed DTs at five grades of steatosis. Across the range of fatty liver steatosis grades, fat content was found to significantly increase ablation volumes by approximately 29-l42% in the Tumor Naïve and 55-60% in the Tumor Informed DTs in 915 MHz and 2450 MHz antenna simulations. The presence of tumor did not significantly affect ablation volumes within the same steatosis grade in 915 MHz simulations, but did significantly increase ablation volumes within mild-, moderate-, and high-fat steatosis grades in 2450 MHz simulations. An analysis of signed distance to agreement for placement strategies suggests that accounting for patient-specific tumor tissue properties significantly impacts ablation forecasting for the preoperative evaluation of ablation zone coverage.

Novel tumor localization model and prediction of ablation zone using an intertwined helical antenna for the treatment of hepatocellular carcinoma

Hepatocellular carcinoma has been the leading cause of death in recent centuries and with the advent of newer technologies, several thermal and cryo-ablation techniques have been introduced in the recent past. In this regard, microwave ablation has developed into a promising method for thermal ablation technique. However, due to clinical obligations, in-vivo analysis is not feasible and ex-vivo analysis is inaccurate due to changes in the electrical and thermal properties of the tissue. Therefore, in this study, temperature-dependent permittivity, electrical conductivity, and thermal conductivity along with phase change effect due to temperature reaching above 100°C are incorporated using finite element method model. Further, using an intertwined normal mode helical antenna ablation probe, a change in resonant frequency (Δf) and reflection coefficient (ΔS₁₁ ) from the actual value (antenna parameter in the air at 5 GHz) is modeled using second-order polynomial curve fitting to predict the surrounding permittivity in the range of 30-70. A maximum deviation of 0.8 value in permittivity from the actual value is observed. However, to obtain a generalized methodology, XG Boost and CAT Boost algorithms are used. Further, since ablation diameter plays a crucial role in achieving optimal tumor ablation, an artificial neural network (ANN) algorithm with three different optimizers is incorporated to predict ablation diameter using five critical parameters. Such an ANN algorithm which can predict the transversal and axial ablation zone may provide optimal ablation outcomes.

Numerical Estimation of SAR and Temperature Distributions inside Differently Shaped Female Breast Tumors during Radio-Frequency Ablation

Radio-frequency (RF) ablation is a reliable technique for the treatment of deep-seated malignant tumors, including breast carcinoma, using high ablative temperatures. The paper aims at a comparative analysis of the specific absorption rate and temperature distribution during RF ablation with regard to different female breast tumors. In the study, four tumor models equivalent to an irregular tumor were considered, i.e., an equivalent sphere and ellipsoid with the same surfaces and volumes as the irregular tumor and an equivalent sphere and ellipsoid inscribed in the irregular tumor. An RF applicator with a specific voltage, operating at 100 kHz inserted into the anatomically correct female breast, was applied as a source of electromagnetically induced heat. A conjugated Laplace equation with the modified Pennes equation was used to obtain the appropriate temperature gradient in the treated area. The levels of power dissipation in terms of the specific absorption rate (SAR) inside the naturalistically shaped tumor, together with the temperature profiles of the four simplified tumor models equivalent to the irregular one, were determined. It was suggested that the equivalent tumor models might successfully replace a real, irregularly shaped tumor, and the presented numeric methodology may play an important role in the complex therapeutic RF ablation process of irregularly shaped female breast tumors.

The value of contrast-enhanced ultrasound quantitative parameters in the prognosis prediction of hepatocellular carcinoma after thermal ablation: a retrospective cohort study

BACKGROUND

The postoperative recurrence rate is the main factor affecting the prognosis of hepatocellular carcinoma (HCC) patients, this study sought to investigate the value of contrast-enhanced ultrasound (CEUS) quantitative parameters in predicting the recurrence and the survival of HCC patients after thermal ablation.

METHODS

The data of 97 patients with pathologically diagnosed HCC who underwent thermal ablation were retrospectively included in this study. The patients had an average age of 46.6 years (range, 23-79 years), and 79 were male and 18 were female. CEUS follow-up was performed at 1- and 3-month after thermal ablation, then at 6-month intervals thereafter for 5 years. CEUS was performed before thermal ablation, and the results were analyzed quantitatively using CEUS perfusion software (VueBox^®, Bracco, Italy). The ratios of the CEUS quantitative parameters between the HCC lesions and reference liver parenchyma were calculated. The parameters included the average contrast signal intensity (MeanLin), peak enhancement (PE), rising time (RT), fall time (FT), time to peak (TTP), mean transit time (mTT), perfusion index (PI), Wash-in Area Under the Curve (WiAUC), Wash-in Rate (WiR), Wash-in Perfusion Index (WiPI), Wash-out Area Under the Curve (WoAUC), Wash-out Rate (WoR), and WiAUC + WoAUC (WiWoAUC). The correlations between the preoperative CEUS quantitative parameter ratios, the blood laboratory indexes, postoperative recurrence, and survival were analyzed using log-rank tests and a Cox regression model.

RESULTS

The average follow-up duration period was 79 months (range, 5-145 months). The average recurrence time after ablation was 1-127 months, and the median disease-free survival time was 21 months. The 1-, 3- and 5-year survival rates were 96.9%, 92.3%, and 80.6%, respectively. The log-rank tests showed that tumor size, prothrombin time, and WiAUC, WoAUC, and WiWoAUC ratios were predictors of survival, and aspartate aminotransferase was a predictor of recurrence. The Cox regression analysis showed that tumor size [odds ratio (OR): 6.421; 95% CI: 1.434-28.761] and alanine transaminase (OR: 0.88; 95% CI: 0.010-0.742) were predictors of a poor prognosis.

CONCLUSIONS

CEUS quantitative parameters before thermal ablation and blood laboratory indexes provide potential clinical value for predicting the postoperative recurrence and survival of HCC patients.

An Analysis of Microwave Ablation Parameters for Treatment of Liver Tumors from the 3D-IRCADb-01 Database

Simulation techniques are powerful tools for determining the optimal conditions necessary for microwave ablation to be efficient and safe for treating liver tumors. Owing to the complexity and computational resource consumption, most of the existing numerical models are two-dimensional axisymmetric models that emulate actual three-dimensional cancers and the surrounding tissue, which is often far from reality. Different tumor shapes and sizes require different input powers and ablation times to ensure the preservation of healthy tissues that can be determined only by the full three-dimensional simulations. This study aimed to tailor microwave ablation therapeutic conditions for complete tumor ablation with an adequate safety margin, while avoiding injury to the surrounding healthy tissue. Three-dimensional simulations were performed for a multi-slot microwave antenna immersed in two tumors obtained from the 3D-IRCADb-01 liver tumors database. The temperature dependence of the dielectric and thermal properties of healthy and tumoral liver tissues, blood perfusion, and water content are crucial for calculating the correct ablation time and, thereby, the correct ablation process. The developed three-dimensional simulation model may help practitioners in planning patient-individual procedures by determining the optimal input power and duration of the ablation process for the actual shape of the tumor. With proper input power, necrotic tissue is placed mainly in the tumor, and only a small amount of surrounding tissue is damaged.

Liver Resection Using Saline-Linked Radiofrequency Technology in an Infant with Congenital Hepatoblastoma

We herein report a case of giant congenital hepatoblastoma in a 3-month-old male treated with neoadjuvant chemotherapy and hepatic resection. After considerable reduction of the tumor with chemotherapy, a right bloodless hemihepatectomy using saline-linked radiofrequency technology (SLRT) and without clamping of the hepatic pedicle was performed. Intraoperative blood loss was minimal, and consequently, no blood transfusions were required. The surgery lasted 140 min, and SLRT was used for a total of 60 min. No complications were observed during or after the surgery. In conclusion, congenital hepatoblastoma is a very rare cancer for which surgery is an essential therapeutic step, and in our presented case, we showed that SLRT allowed for a safe and effective bloodless liver resection.

Fat Quantification Imaging and Biophysical Modeling for Patient-Specific Forecasting of Microwave Ablation Therapy

Computational tools are beginning to enable patient-specific surgical planning to localize and prescribe thermal dosing for liver cancer ablation therapy. Tissue-specific factors (e.g., tissue perfusion, material properties, disease state, etc.) have been found to affect ablative therapies, but current thermal dosing guidance practices do not account for these differences. Computational modeling of ablation procedures can integrate these sources of patient specificity to guide therapy planning and delivery. This paper establishes an imaging-data-driven framework for patient-specific biophysical modeling to predict ablation extents in livers with varying fat content in the context of microwave ablation (MWA) therapy. Patient anatomic scans were segmented to develop customized three-dimensional computational biophysical models and mDIXON fat-quantification images were acquired and analyzed to establish fat content and determine biophysical properties. Simulated patient-specific microwave ablations of tumor and healthy tissue were performed at four levels of fatty liver disease. Ablation models with greater fat content demonstrated significantly larger treatment volumes compared to livers with less severe disease states. More specifically, the results indicated an eightfold larger difference in necrotic volumes with fatty livers vs. the effects from the presence of more conductive tumor tissue. Additionally, the evolution of necrotic volume formation as a function of the thermal dose was influenced by the presence of a tumor. Fat quantification imaging showed multi-valued spatially heterogeneous distributions of fat deposition, even within their respective disease classifications (e.g., low, mild, moderate, high-fat). Altogether, the results suggest that clinical fatty liver disease levels can affect MWA, and that fat-quantitative imaging data may improve patient specificity for this treatment modality.

A New Thermal Damage-Controlled Protocol for Thermal Ablation Modeled with Modified Porous Media-Based Bioheat Equation with Variable Porosity

Thermal ablation of tumors is a minimally invasive technique more and more employed in cancer treatments. The main shortcomings of this technique are, on the one hand, the risk of an incomplete ablation, and on the other hand, the destruction of the surrounding healthy tissue. In this work, thermal ablation of a spherical hepatocellular carcinoma tumor (HCC) surrounded by healthy tissue is modeled. A modified porous media-based bioheat model is employed, including porosity variability from tumor core to healthy tissue, following experimental in vivo measures. Moreover, three different protocols are investigated: a constant heating protocol, a pulsating protocol, and a new developed damage-controlled protocol. The proposed damage-controlled protocol changes the heating source from constant to pulsating according to the thermal damage probability on the tumor rim. The equations are numerically solved by means of the commercial software COMSOL Multiphysics, and the outcomes show that the new proposed protocol is able to achieve the complete ablation in less time than the completely pulsating protocol, and to reach tissue temperature on the tumor rim 10 °C smaller than the constant protocol. These results are relevant to develop and improve different patient-based and automated protocols which can be embedded in medical devices’ software or in mobile applications, supporting medical staff with innovative technical solutions.