Quantitative Interpretation of UWB Radar Images for Non-Invasive Tissue Temperature Estimation during Hyperthermia

Prokhorova, Alexandra; Ley, Sebastian; Helbig, Marko

doi:10.3390/diagnostics11050818

Cited by 11 publications

(7 citation statements)

References 29 publications

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“…The target was placed in the mold with the help of a holder, as shown in Figure 3 e. The 2 mL tumor-mimicking target consisted of 10% gelatin mixed with distilled water and an MNP concentration of 25 mg/mL, as illustrated in Figure 3 f. The surrounding medium was cream with a fat content of 32%, which represents healthy tissue (see Figure 3 b). The dielectric properties of the cream in the frequency range between 1 GHz and 5 GHz can be found in the literature [ 34 ].…”

Section: Methodsmentioning

confidence: 99%

MNP-Enhanced Microwave Medical Imaging by Means of Pseudo-Noise Sensing

Ley

Sachs

Faenger

et al. 2021

Sensors

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Magnetic nanoparticles have been investigated for microwave imaging over the last decade. The use of functionalized magnetic nanoparticles, which are able to accumulate selectively within tumorous tissue, can increase the diagnostic reliability. This paper deals with the detecting and imaging of magnetic nanoparticles by means of ultra-wideband microwave sensing via pseudo-noise technology. The investigations were based on phantom measurements. In the first experiment, we analyzed the detectability of magnetic nanoparticles depending on the magnetic field intensity of the polarizing magnetic field, as well as the viscosity of the target and the surrounding medium in which the particles were embedded, respectively. The results show a nonlinear behavior of the magnetic nanoparticle response depending on the magnetic field intensity for magnetic nanoparticles diluted in distilled water and for magnetic nanoparticles embedded in a solid medium. Furthermore, the maximum amplitude of the magnetic nanoparticles responses varies for the different surrounding materials of the magnetic nanoparticles. In the second experiment, we investigated the influence of the target position on the three-dimensional imaging of the magnetic nanoparticles in a realistic measurement setup for breast cancer imaging. The results show that the magnetic nanoparticles can be detected successfully. However, the intensity of the particles in the image depends on its position due to the path-dependent attenuation, the inhomogeneous microwave illumination of the breast, and the inhomogeneity of the magnetic field. Regarding the last point, we present an approach to compensate for the inhomogeneity of the magnetic field by computing a position-dependent correction factor based on the measured magnetic field intensity and the magnetic susceptibility of the magnetic particles. Moreover, the results indicate an influence of the polarizing magnetic field on the measured ultra-wideband signals even without magnetic nanoparticles. Such a disturbing influence of the polarizing magnetic field on the measurements should be reduced for a robust magnetic nanoparticles detection. Therefore, we analyzed the two-state (ON/OFF) and the sinusoidal modulation of the external magnetic field concerning the detectability of the magnetic nanoparticles with respect to these spurious effects, as well as their practical application.

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Section: Methodsmentioning

confidence: 99%

MNP-Enhanced Microwave Medical Imaging by Means of Pseudo-Noise Sensing

Ley

Sachs

Faenger

et al. 2021

Sensors

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“…There are many works in literature related with estimation of temperature variation on biological tissues via active microwave imaging techniques [31], [34], [35], [36], [37], [38]. Although there are some quantitative works, most of these methods provide qualitative information about the temperature.…”

Section: Monitoring Of Hyperthermia Treatmentmentioning

confidence: 99%

Continuous Monitoring of Hyperthermia Treatment of Breast Tumors With Singular Sources Method

et al. 2023

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Qualitative microwave imaging methods provide a fast and accurate reconstruction of the shapes of the targets from scattered electric field measurements. In this paper, a qualitative imaging method, the singular sources method (SSM), is analyzed for two-dimensional transverse magnetic electromagnetic (2D-TM EM) inverse scattering scenarios. The contribution of the paper can be briefly summarized as: (i) The SSM was previously proposed for the far-field scenario, here we extend the SSM in the near field -inhomogeneous background setup. While making the extension each step (which includes an integral equation) is explained by exploiting the linearity and reciprocity principles to give physical insights. (ii) The relation between the electrical parameters of the scatterers and the indicator of SSM is derived. (iii) To analyze the performance of SSM in real-world problems, the proposed method is tested for monitoring hyperthermia treatment problems with a realistic breast model. Obtained results show that the SSM can handle realistic breast phantoms for monitoring hyperthermia problems.INDEX TERMS Hyperthermia treatment, inverse scattering, microwave imaging, singular sources method, temperature monitoring.

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“…Medical MWI is enabled by the heterogeneous dielectric properties (relative permittivity and conductivity) that different human tissues exhibit at microwave frequencies, based on their typology and on their physio-pathological status [ 3 ]. More precisely, MWI has been mainly considered for breast cancer screening [ 4 ], the diagnosis of cerebrovascular diseases [ 1 ], treatment monitoring [ 5 , 6 , 7 , 8 , 9 ], and, more recently, Alzheimer’s disease monitoring [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

An Effective Framework for Deep-Learning-Enhanced Quantitative Microwave Imaging and Its Potential for Medical Applications

Ruiz

Cavagnaro

Crocco

2023

Sensors

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Microwave imaging is emerging as an alternative modality to conventional medical diagnostics technologies. However, its adoption is hindered by the intrinsic difficulties faced in the solution of the underlying inverse scattering problem, namely non-linearity and ill-posedness. In this paper, an innovative approach for a reliable and automated solution of the inverse scattering problem is presented, which combines a qualitative imaging technique and deep learning in a two-step framework. In the first step, the orthogonality sampling method is employed to process measurements of the scattered field into an image, which explicitly provides an estimate of the targets shapes and implicitly encodes information in their contrast values. In the second step, the images obtained in the previous step are fed into a neural network (U-Net), whose duty is retrieving the exact shape of the target and its contrast value. This task is cast as an image segmentation one, where each pixel is classified into a discrete set of permittivity values within a given range. The use of a reduced number of possible permittivities facilitates the training stage by limiting its scope. The approach was tested with synthetic data and validated with experimental data taken from the Fresnel database to allow a fair comparison with the literature. Finally, its potential for biomedical imaging is demonstrated with a numerical example related to microwave brain stroke diagnosis.

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Quantitative Interpretation of UWB Radar Images for Non-Invasive Tissue Temperature Estimation during Hyperthermia

Cited by 11 publications

References 29 publications

MNP-Enhanced Microwave Medical Imaging by Means of Pseudo-Noise Sensing

MNP-Enhanced Microwave Medical Imaging by Means of Pseudo-Noise Sensing

Continuous Monitoring of Hyperthermia Treatment of Breast Tumors With Singular Sources Method

An Effective Framework for Deep-Learning-Enhanced Quantitative Microwave Imaging and Its Potential for Medical Applications

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