Numerical study of microwave induced thermoacoustic imaging for initial detection of cancer of breast on anatomically realistic breast phantom

A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model

This study presented a novel approach for the precise ablation of breast tumors using focused ultrasound (FUS), leveraging a physics-informed neural network (PINN) integrated with a realistic breast model. FUS has shown significant promise in treating breast tumors by effectively targeting and ablating cancerous tissue. This technique employs concentrated ultrasonic waves to generate intense heat, effectively destroying cancerous tissue. In previous finite element method (FEM) models, the computational demands of handling extensive datasets, multiple dimensions, and discretization posed significant challenges. Our PINN-based solution operated efficiently in a mesh-free domain, achieving remarkable accuracy with significantly reduced computational demands, compared to conventional FEM techniques. Additionally, employing PINN for estimating partial differential equations (PDE) solutions can notably decrease the enormous number of discretized elements needed. The model employed a bowl-shaped acoustic transducer to focus ultrasound waves accurately on the tumor location. The simulation results offered detailed insights into each step of the FUS treatment process, including the generation of acoustic waves, the targeting of the tumor, and the subsequent heating and ablation of cancerous tissue. By applying a 3.8 nm displacement amplitude of transducer input pulse at a frequency of 1.1 MHz for 1 second, the temperature at the focal point elevated to 38.4 ℃, followed by another 90 seconds of cooling time, which resulted in significant necrosis of the tumor tissues. Validation of the PINN model's accuracy was conducted through FEM analysis, aligning closely with real-world FUS therapy scenarios. This innovative model provided physicians with a predictive tool to estimate the necrosis of tumor tissue, facilitating the customization of FUS treatment strategies for individual breast cancer patients.

A comprehensive numerical procedure for high-intensity focused ultrasound ablation of breast tumour on an anatomically realistic breast phantom

High-Intensity Focused Ultrasound (HIFU) as a promising and impactful modality for breast tumor ablation, entails the precise focalization of high-intensity ultrasonic waves onto the tumor site, culminating in the generation of extreme heat, thus ablation of malignant tissues. In this paper, a comprehensive three-dimensional (3D) Finite Element Method (FEM)-based numerical procedure is introduced, which provides exceptional capacity for simulating the intricate multiphysics phenomena associated with HIFU. Furthermore, the application of numerical procedures to an anatomically realistic breast phantom (ARBP) has not been explored before. The integrity of the present numerical procedure has been established through rigorous validation, incorporating comparative assessments with previous two-dimensional (2D) simulations and empirical data. For ARBP ablation, the administration of a 0.1 MPa pressure input pulse at a frequency of 1.5 MHz, sustained at the focal point for 10 seconds, manifests an ensuing temperature elevation to 80°C. It is noteworthy that, in contrast, the prior 2D simulation using a 2D phantom geometry reached just 72°C temperature under the identical treatment regimen, underscoring the insufficiency of 2D models, ascribed to their inherent limitations in spatially representing acoustic energy, which compromises their overall effectiveness. To underscore the versatility of this numerical platform, a simulation of a more clinically relevant HIFU therapy procedure has been conducted. This scenario involves the repositioning of the ultrasound focal point to three separate lesions, each spaced at 3 mm intervals, with ultrasound exposure durations of 6 seconds each and a 5-second interval for movement between focal points. This approach resulted in a more uniform high-temperature distribution at different areas of the tumour, leading to the ablation of almost all parts of the tumour, including its verges. In the end, the effects of different abnormal tissue shapes are investigated briefly as well. For solid mass tumors, 67.67% was successfully ablated with one lesion, while rim-enhancing tumors showed only 34.48% ablation and non-mass enhancement tumors exhibited 20.32% ablation, underscoring the need for multiple lesions and tailored treatment plans for more complex cases.

Model based deep learning method for focused ultrasound pathway scanning

The primary purpose of high-intensity focused ultrasound (HIFU), a non-invasive medical therapy, is to precisely target and ablate tumors by focusing high-frequency ultrasound from an external power source. A series of ablations must be performed in order to treat a big volume of tumors, as a single ablation can only remove a small amount of tissue. To maximize therapeutic efficacy while minimizing adverse side effects such as skin burns, preoperative treatment planning is essential in determining the focal site and sonication duration for each ablation. Here, we introduce a machine learning-based approach for designing HIFU treatment plans, which makes use of a map of the material characteristics unique to a patient alongside an accurate thermal simulation. A numerical model was employed to solve the governing equations of HIFU process and to simulate the HIFU absorption mechanism, including ensuing heat transfer process and the temperature rise during the sonication period. To validate the accuracy of this numerical model, a series of tests was conducted using ex vivo bovine liver. The findings indicate that the developed models properly represent the considerable variances observed in tumor geometrical shapes and proficiently generate well-defined closed treated regions based on imaging data. The proposed strategy facilitated the formulation of high-quality treatment plans, with an average tissue over- or under-treatment rate of less than 0.06%. The efficacy of the numerical model in accurately predicting the heating process of HIFU, when combined with machine learning techniques, was validated through quantitative comparison with experimental data. The proposed approach in cooperation with HIFU simulation holds the potential to enhance presurgical HIFU plan.

Spatiotemporal modeling of radiopharmaceutical transport in solid tumors: Application to 177Lu-PSMA therapy of prostate cancer

BACKGROUND AND OBJECTIVE

177Lu-labeled prostate-specific membrane antigen (PSMA) radiopharmaceutical therapy (RPT) represents a pivotal advancement in addressing prostate cancer. However, existing therapies, while promising, remain incompletely understood and optimized. Computational models offer potential insights into RPTs, aiding in clinical drug delivery enhancement. In this study, we investigate the impact of various physiological parameters on the delivery of 177Lu-PSMA-617 RPT using the convection-diffusion-reaction (CDR) model.

METHODS

Our investigation encompasses tumor geometry and surrounding tissue, characterized by well-defined boundaries and initial conditions. Utilizing the finite element method, we solve governing equations across a range of parameters: dissociation constant KD (1, 0.1, 0.01 [nM]), internalization rate (0.01-0.0001 [min-1]), diverse tumor shapes, and variable necrotic zone sizes. This model can provide an accurate analysis of radiopharmaceutical delivery from the injection site to the tumor cell, including drug transport in the vascular, interstitial, and intracellular spaces, and considering important parameters (e.g., drug extravasation from microvessels or to lymphatic vessels, the extracellular matrix, receptors, and intracellular space).

RESULTS

Our findings reveal significant enhancements in tumor-absorbed doses as KD decreases. This outcome can be attributed to the higher affinity of radiopharmaceuticals for PSMA receptors as KD diminishes, facilitating a more efficient binding and retention of the therapeutic agent within the tumor microenvironment. Additionally, tumor-absorbed doses for KD ∼ 1 [nM] show an upward trend with higher internalization rates. This observation can be rationalized by considering that a greater internalization rate would result in a higher proportion of radiopharmaceuticals being taken up by tumor cells after binding to receptors on the cell surface. Notably, tumor shape and necrotic zone size exhibit limited influence on tumor absorbed dose.

CONCLUSIONS

The present study employs the CDR model to explore the role of physiological parameters in shaping 177Lu-PSMA-617 RPT delivery. These findings provide insights for improving prostate cancer therapy by understanding radiopharmaceutical transport dynamics. This computational approach contributes to advancing our understanding of radiopharmaceutical delivery mechanisms and has implications for enhancing treatment efficacy.

MATLAB-based innovative 3D finite element method simulator for optimized real-time hyperthermia analysis

BACKGROUND AND OBJECTIVE

Owing to the significant role of hyperthermia in enhancing the efficacy of chemotherapy or radiotherapy for treating malignant tissues, this study introduces a real-time hyperthermia simulator (RTHS) based on the three-dimensional finite element method (FEM) developed using the MATLAB App Designer.

METHODS

The simulator consisted of operator-defined homogeneous and heterogeneous phantom models surrounded by an annular phased array (APA) of eight dipole antennas designed at 915 MHz. Electromagnetic and thermal analyses were conducted using the RTHS. To locally raise the target temperature according to the tumor's location, a convex optimization algorithm (COA) was employed to excite the antennas using optimal values of the phases to maximize the electric field at the tumor and amplitudes to achieve the required temperature at the target position. The performance of the proposed RTHS was validated by comparing it with similar hyperthermia setups in the FEM-based COMSOL software and finite-difference time-domain (FDTD)-based Sim4Life software.

RESULTS

The simulation results obtained using the RTHS were consistent, both for the homogeneous and heterogeneous models, with those obtained using commercially available tools, demonstrating the reliability of the proposed hyperthermia simulator. The effectiveness of the simulator was illustrated for target positions in five different regions for both homogeneous and heterogeneous phantom models. In addition, the RTHS was cost-effective and consumed less computational time than the available software. The proposed method achieved 94% and 96% accuracy for element sizes of λ/26 and λ/36, respectively, for the homogeneous model. For the heterogeneous model, the method demonstrated 93% and 95% accuracy for element sizes of λ/26 and λ/36, respectively. The accuracy can be further improved by using a more refined mesh at the cost of a higher computational time.

CONCLUSIONS

The proposed hyperthermia simulator demonstrated reliability, cost-effectiveness, and reduced computational time compared to commercial software, making it a potential tool for optimizing hyperthermia treatment.

Microwave-induced thermoacoustic microscopy based on short-pulse microwave and high-frequency point-focused ultrasonic transducer

BACKGROUND

As an emerging hybrid imaging modality, microwave-induced thermoacoustic imaging (MITAI) provides high contrast and deep tissue penetration, and has been extensively applied in cancer diagnosis, arthritis detection, and brain research. However, the previous studies had a limited spatial resolution of about 0.45-1.5 mm.

PURPOSE

Here, we describe a microwave-induced thermoacoustic microscopy (MITAM) system to help overcome the resolution limitation of current MITAI to image more subtle tissue features. On this basis, this paper applies MITAM to the thin skin and to demonstrate the potential of MITAM in detecting scleroderma.

METHODS

To achieve high resolution, short pulse width microwave (pulse width: 70 ns) and high-frequency ultrasonic point-focused transducer (center frequency: 25 MHz) were used to build the MITAM system. Two parallel copper wires with a diameter of 90 μm in the X/Y plane and Y/Z plane were imaged to estimate X/Y/Z resolution. Nine Balb/c mice were randomly divided into three groups and injected with different concentrations of bleomycin to induce scleroderma models. Their ex vivo skins were then imaged by our MITAM system. Visual observations were performed on the 3-dimensional skins MITAM images. And the mean value, Standard deviation, quartile distance, and signal-to-noise ratio were calculated to verify the results of the qualitative observations. Hematoxylin-Eosin (HE) and Masson staining were used to validate the findings of the MITAM.

RESULTS

The thickness of each imaged skin was measured to be about 450 μm. As an organ composed of multiple layers of tissues, the skin needs to be imaged at high resolution for the detection of related diseases. The results obtained showed that the improved resolution (68 μm in the Z-axis and 135 μm in the X-axis/Y-axis) of MITAM over conventional MITAI allowed us to differentiate scleroderma skins from normal skins and to identify the severity of scleroderma skins, consistent with the pathological findings of these skins.

CONCLUSIONS

The preliminary results obtained indicate that the MITAM can relieve the resolution limitation of traditional MITAI and has the potential to detection scleroderma. However, the transmission-type MITAM mentioned in this paper is difficult to image in vivo due to the narrow area between the antenna and the transducer. In the future, a reflective scanning MITAM will be constructed to detect scleroderma in vivo.

Exploring the Potential of Sensing for Breast Cancer Detection

Breast cancer is a generalized global problem. Biomarkers are the active substances that have been considered as the signature of the existence and evolution of cancer. Early screening of different biomarkers associated with breast cancer can help doctors to design a treatment plan. However, each screening technique for breast cancer has some limitations. In most cases, a single technique can detect a single biomarker at a specific time. In this study, we address different types of biomarkers associated with breast cancer. This review article presents a detailed picture of different techniques and each technique’s associated mechanism, sensitivity, limit of detection, and linear range for breast cancer detection at early stages. The limitations of existing approaches require researchers to modify and develop new methods to identify cancer biomarkers at early stages.

Microwave Imaging and Sensing Techniques for Breast Cancer Detection

Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.

A high-efficient excitation-detection thermoacoustic imaging probe for breast tumor detection

BACKGROUND

Microwave-induced thermoacoustic (TA) imaging (MTAI) is a promising alternative to biomedical imaging due to its high resolution, deep imaging depth, and minimal biohazard. To provide images of different anatomical regions and apply them to different clinical scenarios, the development of miniaturized portable TA probes is imperative.

PURPOSE

This study is aimed to propose a highly efficient handheld non-reflective microwave-acoustic coaxial TA probe to advance the translation of MTAI for the clinical use.

METHODS

The TA probe integrates a hollowed microwave antenna with a forward radiating uniform microwave field and a linear ultrasonic transducer array which is placed in the hole in the middle of the antenna that has almost no effect on the microwave distribution. The integrated probe was evaluated for properties, including the excitation efficiency of the microwave and the reception efficiency of the acoustic signal. Finally, an isolated EMT6 cell tumor was embedded in a sheep mammary gland to simulate the natural breast tumor environment, and the tumor was detected with the proposed MTAI probe to evaluate its practical feasibility.

RESULTS

Compared with the previous TA imaging probe, it has improved the detection efficiency of TA signals by up to 41%, contributing to an improved signal-to-noise ratio (SNR) of the image. The proposed TA probe successfully detected tumors embedded in the breast with a contrast ratio 3.27 times higher than the surrounding tissue in phantom experiments.

CONCLUSION

The proposed TA probe with the features of microwave illumination and ultrasonic detection of coaxial, avoiding TA signal attenuation due to reflection, enables high-efficient TA signal excitation and detection. The proposed TA probe is essential for improving the excitation and detection efficiency of TA signals, and increasing the flexibility of the probe, providing a bright future for the clinical application of MTAI technology.

Portable Microwave-Acoustic Coaxial Thermoacoustic Probe With Miniaturized Vivaldi Antennas for Breast Tumor Screening

Microwave-induced thermoacoustic (TA) imaging (MTAI), which exploits dielectric contrasts to provide images with high contrast and spatial resolution, holds the potential to serve as an additional means of clinical diagnosis and treatment. However, conventional MTAI usually uses large and heavy metal antennas to radiate pulsed microwaves, making it challenging to image different target areas flexibly. In this work, we presented the design and evaluation of a portable microwave-acoustic coaxial TA probe (51 mm × 63 mm × 138 mm) that can flexibly image the region of interest. The TA probe contains two miniaturized symmetrically distributed Vivaldi antennas (7.5 g) and a 128-element linear ultrasonic transducer. By adjusting the geometry of the antennas and the ultrasonic transducer, the TA probe's acoustic field and microwave field can be designed to be coaxial, which helps achieve homogeneous microwave illumination and high-sensitivity ultrasonic detection. The practical feasibility of the proposed probe was tested on an in vitro ewe breast and a healthy volunteer. The results demonstrate that the MTAI system with the proposed TA probe can visualize the anatomical structure of the breast tumor in ewe breast and a healthy volunteer breast with resolutions in hundreds of microns (transverse: 910 μm, axial: 780 μm) and an excellent signal-to-noise ratio can be obtained in deep adipose tissue (10 dB in 6 cm fat). The miniaturized portable TA probe takes a solid step forward in translating MTAI technology to clinical breast tumor diagnosis.

Holographic Microwave Image Classification Using a Convolutional Neural Network

Holographic microwave imaging (HMI) has been proposed for early breast cancer diagnosis. Automatically classifying benign and malignant tumors in microwave images is challenging. Convolutional neural networks (CNN) have demonstrated excellent image classification and tumor detection performance. This study investigates the feasibility of using the CNN architecture to identify and classify HMI images. A modified AlexNet with transfer learning was investigated to automatically identify, classify, and quantify four and five different HMI breast images. Various pre-trained networks, including ResNet18, GoogLeNet, ResNet101, VGG19, ResNet50, DenseNet201, SqueezeNet, Inception v3, AlexNet, and Inception-ResNet-v2, were investigated to evaluate the proposed network. The proposed network achieved high classification accuracy using small training datasets (966 images) and fast training times.

Numerical study of magnetic hyperthermia ablation of breast tumor on an anatomically realistic breast phantom

Magnetic fluid hyperthermia (MFH) is a novel reliable technique with excellent potential for thermal therapies and treating breast tumours. This method involves injecting a magnetic nanofluid into the tumour and applying an external AC magnetic field to induce heat in the magnetic nanoparticles (MNPs) and raise the tumour temperature to ablation temperature ranges. Because of the complexity of considering and coupling all different physics involves in this phenomenon and also due to the intricacy of a thorough FEM numerical study, few FEM-based studies address the entire MFH process as similar to reality as possible. The current study investigates a FEM-based three-dimensional numerical simulation of MFH of breast tumours as a multi-physics problem. An anatomically realistic breast phantom (ARBP) is considered, some magnetic nanofluid is injected inside the tumour, and the diffusion phenomenon is simulated. Then, the amount of heat generated in the MNP-saturated tumour area due to an external AC magnetic field is simulated. In the end, the fraction of tumour tissue necrotized by this temperature rise is evaluated. The study's results demonstrate that by injecting nanofluid and utilizing seven circular copper windings with each coil carrying 400 A current with a frequency of 400 kHz for generating the external AC magnetic field, the temperature in tumour tissue can be raised to a maximum of about 51.4°C, which leads to necrosis of entire tumour tissue after 30 minutes of electromagnetic field (EMF) exposure. This numerical platform can depict all four various physics involved in the MFH of breast tumours by numerically solving all different equation sets coupled together with high precision. Thus, the proposed model can be utilized by clinicians as a reliable tool for predicting and identifying the approximate amount of temperature rise and the necrotic fraction of breast tumour, which can be very useful to opt for the best MFH therapeutic procedure and conditions based on various patients. In future works, this numerical platform's results should be compared with experimental in-vivo results to improve and modify this platform in order to be ready for clinical applications.

A Handheld Microwave Thermoacoustic Imaging System With an Impedance Matching Microwave-Sono Probe for Breast Tumor Screening

Microwave-induced thermoacoustic imaging (MTAI) is a promising alternative for breast tumor detection due to its deep imaging depth, high resolution, and minimal biological hazards. However, due to the bulky size and complicated system configuration of conventional benchtop MTAI, it is limited to imaging various anatomical sites and its application in different clinical scenarios. In this study, a handheld MTAI system equipped with a compact impedance matching microwave-sono and an ergonomically designed probe was presented and evaluated. The probe integrates a flexible coaxial cable for microwave delivery, a miniaturized microwave antenna, a linear transducer array, and wedge-shaped polystyrene blocks for efficient acoustic coupling, achieving microwave illumination and ultrasonic detection coaxially, and enabling high signal-to-noise ratio (SNR). Phantom experiments demonstrated that the maximum imaging depth is 5 cm (SNR = 8 dB), and the lateral and axial resolutions are 1.5 mm and 0.9 mm, respectively. Finally, three healthy female volunteers of different ages were subjected to breast thermoacoustic tomography and ultrasound imaging. The results showed that the h-MTAI data are correlated with the data of ultrasound imaging, indicating the safety and effectiveness of the system. Thus, the proposed h-MTAI system might contribute to breast tumor screening.

Microwave Imaging for Early Breast Cancer Detection: Current State, Challenges, and Future Directions

Breast cancer is the most commonly diagnosed cancer type and is the leading cause of cancer-related death among females worldwide. Breast screening and early detection are currently the most successful approaches for the management and treatment of this disease. Several imaging modalities are currently utilized for detecting breast cancer, of which microwave imaging (MWI) is gaining quite a lot of attention as a promising diagnostic tool for early breast cancer detection. MWI is a noninvasive, relatively inexpensive, fast, convenient, and safe screening tool. The purpose of this paper is to provide an up-to-date survey of the principles, developments, and current research status of MWI for breast cancer detection. This paper is structured into two sections; the first is an overview of current MWI techniques used for detecting breast cancer, followed by an explanation of the working principle behind MWI and its various types, namely, microwave tomography and radar-based imaging. In the second section, a review of the initial experiments along with more recent studies on the use of MWI for breast cancer detection is presented. Furthermore, the paper summarizes the challenges facing MWI as a breast cancer detection tool and provides future research directions. On the whole, MWI has proven its potential as a screening tool for breast cancer detection, both as a standalone or complementary technique. However, there are a few challenges that need to be addressed to unlock the full potential of this imaging modality and translate it to clinical settings.

Drug delivery through nanoparticles in solid tumors: a mechanistic understanding

Aim: In this study, the main goal was to apply a multi-scale computational model in evaluating nano-sized drug-delivery systems, following extracellular drug release, into solid tumors in order to predict treatment efficacy. Methods: The impact of several parameters related to tumor (size, shape, vessel-wall pore size, and necrotic core size) and therapeutic agents (size of nanoparticles, binding affinity of drug, drug release rate from nanoparticles) are examined in detail. Results: This study illustrates that achieving a higher treatment efficacy requires smaller nanoparticles (NPs) or a low binding affinity and drug release rate. Long-term analysis finds that a slow release rate in extracellular space does not always improve treatment efficacy compared with a rapid release rate; NP size as well as binding affinity of drug are also highly influential. Conclusions: The presented methodology can be used as a step forward towards optimization of patient-specific nanomedicine plans.

An Excitation-Reception Collinear Probe for Ultrasonic, Photoacoustic, and Thermoacoustic Tri-Modal Volumetric Imaging

Imaging systems that integrate multiple modalities can reveal complementary anatomic and functional information as they exploit different contrast mechanisms, which have shown great application potential and advantages in preclinical studies. A portable and easy-to-use imaging probe will be more conducive to transfer to clinical practice. Here, we present a tri-modal ultrasonic (US), photoacoustic (PA), and thermoacoustic (TA) imaging system with an excitation-reception collinear probe. The acoustic field, light field, and electric field of the probe were designed to be coaxial, realizing homogeneous illumination and high-sensitivity detection at the same detection position. US images can provide detailed information about structures, PA images can delineate the morphology of blood vessels in tissues, and TA images can reveal dielectric properties of the tissues. Moreover, phantoms and in vivo human finger experiments were performed by the tri-modal imaging system to demonstrate its performance. The results show that the tri-modal imaging system with the proposed probe has the ability to detect small breast tumors with a radius of only 2.5 mm and visualize the anatomical structure of the finger in three dimensions. Our work confirms that the tri-modal imaging system equipped with a collinear probe can be applied to a variety of different scenarios, which lays a solid foundation for the application of the tri-modality system in clinical trials.

A Computational Study on the Role of Parameters for Identification of Thyroid Nodules by Infrared Images (and Comparison with Real Data)

According to experts and medical literature, healthy thyroids and thyroids containing benign nodules tend to be less inflamed and less active than those with malignant nodules. It seems to be a consensus that malignant nodules have more blood veins and more blood circulation. This may be related to the maintenance of the nodule's heat at a higher level compared with neighboring tissues. If the internal heat modifies the skin radiation, then it could be detected by infrared sensors. The goal of this work is the investigation of the factors that allow this detection, and the possible relation with any pattern referent to nodule malignancy. We aim to consider a wide range of factors, so a great number of numerical simulations of the heat transfer in the region under analysis, based on the Finite Element method, are performed to study the influence of each nodule and patient characteristics on the infrared sensor acquisition. To do so, the protocol for infrared thyroid examination used in our university's hospital is simulated in the numerical study. This protocol presents two phases. In the first one, the body under observation is in steady state. In the second one, it is submitted to thermal stress (transient state). Both are simulated in order to verify if it is possible (by infrared sensors) to identify different behavior referent to malignant nodules. Moreover, when the simulation indicates possible important aspects, patients with and without similar characteristics are examined to confirm such influences. The results show that the tissues between skin and thyroid, as well as the nodule size, have an influence on superficial temperatures. Other thermal parameters of thyroid nodules show little influence on surface infrared emissions, for instance, those related to the vascularization of the nodule. All details of the physical parameters used in the simulations, characteristics of the real nodules and thermal examinations are publicly available, allowing these simulations to be compared with other types of heat transfer solutions and infrared examination protocols. Among the main contributions of this work, we highlight the simulation of the possible range of parameters, and definition of the simulation approach for mapping the used infrared protocol, promoting the investigation of a possible relation between the heat transfer process and the data obtained by infrared acquisitions.

In Silico Study on Tumor-Size-Dependent Thermal Profiles inside an Anthropomorphic Female Breast Phantom Subjected to Multi-Dipole Antenna Array

Electromagnetic hyperthermia as a potent adjuvant for conventional cancer therapies can be considered valuable in modern oncology, as its task is to thermally destroy cancer cells exposed to high-frequency electromagnetic fields. Hyperthermia treatment planning based on computer in silico simulations has the potential to improve the localized heating of breast tissues through the use of the phased-array dipole applicators. Herein, we intended to improve our understanding of temperature estimation in an anatomically accurate female breast phantom embedded with a tumor, particularly when it is exposed to an eight-element dipole antenna matrix surrounding the breast tissues. The Maxwell equations coupled with the modified Pennes' bioheat equation was solved in the modelled breast tissues using the finite-difference time-domain (FDTD) engine. The microwave (MW) applicators around the object were modelled with shortened half-wavelength dipole antennas operating at the same 1 GHz frequency, but with different input power and phases for the dipole sources. The total input power of an eight-dipole antenna matrix was set at 8 W so that the temperature in the breast tumor did not exceed 42 °C. Finding the optimal setting for each dipole antenna from the matrix was our primary objective. Such a procedure should form the basis of any successful hyperthermia treatment planning. We applied the algorithm of multi for multi-objective optimization for the power and phases for the dipole sources in terms of maximizing the specific absorption rate (SAR) parameter inside the breast tumor while minimizing this parameter in the healthy tissues. Electro-thermal simulations were performed for tumors of different radii to confirm the reliable operation of the given optimization procedure. In the next step, thermal profiles for tumors of various sizes were calculated for the optimal parameters of dipole sources. The computed results showed that larger tumors heated better than smaller tumors; however, the procedure worked well regardless of the tumor size. This verifies the effectiveness of the applied optimization method, regardless of the various stages of breast tumor development.