Differences in the dielectric properties of various benign and malignant thyroid nodules

Model-Optimizing Radiofrequency Parameters of 3D Finite Element Analysis for Ablation of Benign Thyroid Nodules

Radiofrequency (RF) ablation represents an efficient strategy to reduce the volume of thyroid nodules. In this study, a finite element model was developed with the aim of optimizing RF parameters, e.g., input power and treatment duration, in order to achieve the target volume reduction rate (VRR) for a thyroid nodule. RF ablation is modelled as a coupled electro-thermal problem wherein the electric field is applied to induce tissue heating. The electric problem is solved with the Laplace equation, the temperature distribution is estimated with the Pennes bioheat equation, and the thermal damage is evaluated using the Arrhenius equation. The optimization model is applied to RF electrode with different active tip lengths in the interval from 5 mm to 40 mm at the 5 mm step. For each case, we also explored the influence of tumour blood perfusion rate on RF ablation outcomes. The model highlights that longer active tips are more efficient as they require lesser power and shorter treatment time to reach the target VRR. Moreover, this condition is characterized by a reduced transversal ablation zone. In addition, a higher blood perfusion increases the heat dispersion, requiring a different combination of RF power and time treatment to achieve the target VRR. The model may contribute to an improvement in patient-specific RF ablation treatment.

Hyperthermia Treatment Monitoring via Deep Learning Enhanced Microwave Imaging: A Numerical Assessment

The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation.

The distinguishing electrical properties of cancer cells

In recent decades, medical research has been primarily focused on the inherited aspect of cancers, despite the reality that only 5-10% of tumours discovered are derived from genetic causes. Cancer is a broad term, and therefore it is inaccurate to address it as a purely genetic disease. Understanding cancer cells' behaviour is the first step in countering them. Behind the scenes, there is a complicated network of environmental factors, DNA errors, metabolic shifts, and electrostatic alterations that build over time and lead to the illness's development. This latter aspect has been analyzed in previous studies, but how the different electrical changes integrate and affect each other is rarely examined. Every cell in the human body possesses electrical properties that are essential for proper behaviour both within and outside of the cell itself. It is not yet clear whether these changes correlate with cell mutation in cancer cells, or only with their subsequent development. Either way, these aspects merit further investigation, especially with regards to their causes and consequences. Trying to block changes at various levels of occurrence or assisting in their prevention could be the key to stopping cells from becoming cancerous. Therefore, a comprehensive understanding of the current knowledge regarding the electrical landscape of cells is much needed. We review four essential electrical characteristics of cells, providing a deep understanding of the electrostatic changes in cancer cells compared to their normal counterparts. In particular, we provide an overview of intracellular and extracellular pH modifications, differences in ionic concentrations in the cytoplasm, transmembrane potential variations, and changes within mitochondria. New therapies targeting or exploiting the electrical properties of cells are developed and tested every year, such as pH-dependent carriers and tumour-treating fields. A brief section regarding the state-of-the-art of these therapies can be found at the end of this review. Finally, we highlight how these alterations integrate and potentially yield indications of cells' malignancy or metastatic index.

Measurement and image-based estimation of dielectric properties of biological tissues —past, present, and future—

The dielectric properties of biological tissues are fundamental pararmeters that are essential for electromagnetic modeling of the human body. The primary database of dielectric properties compiled in 1996 on the basis of dielectric measurements at frequencies from 10 Hz to 20 GHz has attracted considerable attention in the research field of human protection from non-ionizing radiation. This review summarizes findings on the dielectric properties of biological tissues at frequencies up to 1 THz since the database was developed. Although the 1996 database covered general (normal) tissues, this review also covers malignant tissues that are of interest in the research field of medical applications. An intercomparison of dielectric properties based on reported data is presented for several tissue types. Dielectric properties derived from image-based estimation techniques developed as a result of recent advances in dielectric measurement are also included. Finally, research essential for future advances in human body modeling is discussed.

[Comparison of dielectric properties of normal human esophagus and esophageal cancer using an open-ended coaxial probe]

OBJECTIVE

To study the difference in dielectric properties (relative permittivity and electrical conductivity) between normal human esophageal tissues and esophageal cancer tissues resected in esophageal cancer surgery for rapid identification of esophageal cancer during surgery.

METHODS

An open- end coaxial probe in the frequency range of 50 MHz to 4 GHz was used for dielectric measurement of the normal tissues and tumor tissues immediately after resection in 51 esophageal cancer cases. The difference in dielectric characteristics of the tissues was analyzed in the full frequency range, and the measurement data at 6 specific frequencies (64, 128, 298, 433, 915, and 2450 MHz) were analyzed statistically. The Cole-Cole model was used for data fitting in the entire frequency band and the measured values were compared with reported values.

RESULTS

In the frequency range of 50 MHz- 4 GHz, the dielectric measurement values of esophageal cancer tissues were significantly higher than those of normal esophageal tissues. At the 6 specific frequencies, the dielectric properties also differed significantly between normal esophageal tissues and esophageal cancer tissues (P < 0.01). The Cole-Cole model achieved a good fitting result of the measured data. The measured values in this study were lower than the reported values.

CONCLUSION

There are significant differences in the dielectric properties between normal esophageal tissue and tumor tissue, which may provide a new theoretical basis for rapid identification of esophageal cancer during surgery.

Microwave ablation of lung tumors: A probabilistic approach for simulation-based treatment planning

PURPOSE

Microwave ablation (MWA) is a clinically established modality for treatment of lung tumors. A challenge with existing application of MWA, however, is local tumor progression, potentially due to failure to establish an adequate treatment margin. This study presents a robust simulation-based treatment planning methodology to assist operators in comparatively assessing thermal profiles and likelihood of achieving a specified minimum margin as a function of candidate applied energy parameters.

METHODS

We employed a biophysical simulation-based probabilistic treatment planning methodology to evaluate the likelihood of achieving a specified minimum margin for candidate treatment parameters (i.e., applied power and ablation duration for a given applicator position within a tumor). A set of simulations with varying tissue properties was evaluated for each considered combination of power and ablation duration, and for four different scenarios of contrast in tissue biophysical properties between tumor and normal lung. A treatment planning graph was then assembled, where distributions of achieved minimum ablation zone margins and collateral damage volumes can be assessed for candidate applied power and treatment duration combinations. For each chosen power and time combination, the operator can also visualize the histogram of ablation zone boundaries overlaid on the tumor and target volumes. We assembled treatment planning graphs for generic 1, 2, and 2.5 cm diameter spherically shaped tumors and also illustrated the impact of tissue heterogeneity on delivered treatment plans and resulting ablation histograms. Finally, we illustrated the treatment planning methodology on two example patient-specific cases of tumors with irregular shapes.

RESULTS

The assembled treatment planning graphs indicate that 30 W, 6 min ablations achieve a 5-mm minimum margin across all simulated cases for 1-cm diameter spherical tumors, and 70 W, 10 min ablations achieve a 3-mm minimum margin across 90% of simulations for a 2.5-cm diameter spherical tumor. Different scenarios of tissue heterogeneity between tumor and lung tissue revealed 2 min overall difference in ablation duration, in order to reliably achieve a 4-mm minimum margin or larger each time for 2-cm diameter spherical tumor.

CONCLUSIONS

An approach for simulation-based treatment planning for microwave ablation of lung tumors is illustrated to account for the impact of specific geometry of the treatment site, tissue property uncertainty, and heterogeneity between the tumor and normal lung.