Pub Date : 2024-08-22DOI: 10.1109/JERM.2024.3442073
{"title":"IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal","authors":"","doi":"10.1109/JERM.2024.3442073","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442073","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C3-C3"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-22DOI: 10.1109/JERM.2024.3442071
{"title":"IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information","authors":"","doi":"10.1109/JERM.2024.3442071","DOIUrl":"https://doi.org/10.1109/JERM.2024.3442071","url":null,"abstract":"","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"C2-C2"},"PeriodicalIF":3.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10643733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-19DOI: 10.1109/JERM.2024.3433008
Rakesh Singh;Dharmendra Singh;Manoj Gupta
Breast cancer imaging technology requires the artificial breast phantom for early-stage breast cancer testing. The creation of a breast phantom that can replicate the dielectric properties found in real breast tissue holds significant importance in the optimization of the imaging system where computation of the effective dielectric properties of the breast, with and without the tumor needs more attention. Therefore, in this paper, an attempt has been made to develop the dielectric mixing model approach which may represent the real scenario of breast cancer like breast with different size of the tumor. This paper is also proposed to fabricate the phantom using gelatin and water and different size of tumor such as 2 mm, 4 mm, 6 mm, 8 mm and 10 mm which has been inserted in the phantom, and obtained result were compared with dielectric mixing model approach. The dielectric properties of a fabricated phantom, and phantom embedded with different sizes of tumor, were obtained using an open-ended coaxial probe method and computed the effective dielectric properties using dielectric mixing model approach spanning the frequency range from 1 GHz to 10 GHz. It is observed that the measurement results are in quite good agreement with the result of the dielectric mixing model. The main aim of the paper is to observe the change in dielectric properties when the tumor sizes are changing and it is found that there are considerable changes in dielectric with different dimension of the tumor in the frequency range 1 GHz to 10 GHz.
{"title":"Computation of Effective Dielectric Properties Using Dielectric Mixing Model Approach for Breast Cancer Detection","authors":"Rakesh Singh;Dharmendra Singh;Manoj Gupta","doi":"10.1109/JERM.2024.3433008","DOIUrl":"https://doi.org/10.1109/JERM.2024.3433008","url":null,"abstract":"Breast cancer imaging technology requires the artificial breast phantom for early-stage breast cancer testing. The creation of a breast phantom that can replicate the dielectric properties found in real breast tissue holds significant importance in the optimization of the imaging system where computation of the effective dielectric properties of the breast, with and without the tumor needs more attention. Therefore, in this paper, an attempt has been made to develop the dielectric mixing model approach which may represent the real scenario of breast cancer like breast with different size of the tumor. This paper is also proposed to fabricate the phantom using gelatin and water and different size of tumor such as 2 mm, 4 mm, 6 mm, 8 mm and 10 mm which has been inserted in the phantom, and obtained result were compared with dielectric mixing model approach. The dielectric properties of a fabricated phantom, and phantom embedded with different sizes of tumor, were obtained using an open-ended coaxial probe method and computed the effective dielectric properties using dielectric mixing model approach spanning the frequency range from 1 GHz to 10 GHz. It is observed that the measurement results are in quite good agreement with the result of the dielectric mixing model. The main aim of the paper is to observe the change in dielectric properties when the tumor sizes are changing and it is found that there are considerable changes in dielectric with different dimension of the tumor in the frequency range 1 GHz to 10 GHz.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"42-48"},"PeriodicalIF":3.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1109/JERM.2024.3434519
Robert Streeter;Jooeun Lee;Gabriel Santamaria Botello;Zorana Popović
Determination of the thickness, permittivity, and conductivity of tissue layers in the microwave region of the electromagnetic spectrum is relevant to a number of applications, such as breast-cancer imaging and non-invasive subcutaneous tissue thermometry. Many current characterization approaches are limited to one or two layers, often required to be aqueous. This paper presents simplified modeling of a stack of tissue layers as a series of complex impedance transmission lines in the 2–20 GHz decade. A near-field, broadband interrogation antenna designed for this frequency range and placed on the skin is validated with complex reflection coefficient measurements on seventeen different stacks of materials. Initial measurements are used to build a lookup table of features that are then used to classify three independent sets of follow-up measurements on the same stacks. After processing and consideration of very thin and very low loss materials, the error rates for classification are found to be between 5.9% and 14.7%. This confirms that features extracted from a simple, calibrated one-port broadband reflection coefficient measurement provide sufficient information to identify the composition of a layered stack, modeling tissue layers.
{"title":"Classification of Multi-Layer Tissue-Mimicking Dielectric Stacks From 2 to 20 GHz","authors":"Robert Streeter;Jooeun Lee;Gabriel Santamaria Botello;Zorana Popović","doi":"10.1109/JERM.2024.3434519","DOIUrl":"https://doi.org/10.1109/JERM.2024.3434519","url":null,"abstract":"Determination of the thickness, permittivity, and conductivity of tissue layers in the microwave region of the electromagnetic spectrum is relevant to a number of applications, such as breast-cancer imaging and non-invasive subcutaneous tissue thermometry. Many current characterization approaches are limited to one or two layers, often required to be aqueous. This paper presents simplified modeling of a stack of tissue layers as a series of complex impedance transmission lines in the 2–20 GHz decade. A near-field, broadband interrogation antenna designed for this frequency range and placed on the skin is validated with complex reflection coefficient measurements on seventeen different stacks of materials. Initial measurements are used to build a lookup table of features that are then used to classify three independent sets of follow-up measurements on the same stacks. After processing and consideration of very thin and very low loss materials, the error rates for classification are found to be between 5.9% and 14.7%. This confirms that features extracted from a simple, calibrated one-port broadband reflection coefficient measurement provide sufficient information to identify the composition of a layered stack, modeling tissue layers.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"36-41"},"PeriodicalIF":3.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Malignant melanoma, the aggressive form of skin cancer, progresses via radial and vertical growth. The aim of this study is to assess the feasibility of microwave-based diagnosis of melanoma at different stages of tumor progression. To this end, we used the physiological data for melanoma progression to develop a theoretical model of melanoma growth, followed by the oil-in-gelatin based tissue phantoms, which aim to mimic the dielectric behavior of the tissues under consideration. The phantoms are then dielectrically characterized using a slim-form open-ended coaxial probe by systematically sampling dielectric values across the mimicked skin surfaces at a range of points over the 0.5 – 26.5 GHz frequency range. The resulting observations revealed that the microwave spectroscopy exhibits the capability not only to distinguish between healthy and malignant skin, but also differentiate between tumors at different stages of vertical growth, which may not be visually discernible from the skin surface. The measured results are compared with the estimated dielectric values of malignant melanoma using Lichteneker's mixing equation obtained from the literature and it was observed that the measured results closely agree with the literature values.
{"title":"Models of Melanoma Growth for Assessment of Microwave-Based Diagnostic Tools","authors":"Jasmine Boparai;Rachel Tchinov;Oliver Miller;Yanis Jallouli;Milica Popović","doi":"10.1109/JERM.2024.3430315","DOIUrl":"https://doi.org/10.1109/JERM.2024.3430315","url":null,"abstract":"Malignant melanoma, the aggressive form of skin cancer, progresses via radial and vertical growth. The aim of this study is to assess the feasibility of microwave-based diagnosis of melanoma at different stages of tumor progression. To this end, we used the physiological data for melanoma progression to develop a theoretical model of melanoma growth, followed by the oil-in-gelatin based tissue phantoms, which aim to mimic the dielectric behavior of the tissues under consideration. The phantoms are then dielectrically characterized using a slim-form open-ended coaxial probe by systematically sampling dielectric values across the mimicked skin surfaces at a range of points over the 0.5 – 26.5 GHz frequency range. The resulting observations revealed that the microwave spectroscopy exhibits the capability not only to distinguish between healthy and malignant skin, but also differentiate between tumors at different stages of vertical growth, which may not be visually discernible from the skin surface. The measured results are compared with the estimated dielectric values of malignant melanoma using Lichteneker's mixing equation obtained from the literature and it was observed that the measured results closely agree with the literature values.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"305-315"},"PeriodicalIF":3.0,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.1109/JERM.2024.3426270
Ali Kaiss;Md. Asiful Islam;Asimina Kiourti
We report Beat Estimation, a novel method used to calculate Heart Rate Variability (HRV) from low Signal to Noise Ratio (SNR) data (−7 dB to −4 dB in this work) acquired via wearable magnetocardiography (MCG). MCG activity is first collected using an in-house wearable sensor and filtered to remove noise outside the band of interest. Beat Estimation extracts a single heart beat from the filtered recording and correlates it with a small number of beats individually to average out the remaining noise. The de-noised beat is then correlated with the full recording to identify the location of each of the heart beats. Using these locations, HRV parameters are, finally, calculated. Results show $sim$99.9% accuracy in estimating HRV metrics using beat-to-beat intervals as opposed to traditional R-to-R-peak intervals. The average accuracy of detecting the true location of beats is shown to increase to 96.43% using Beat Estimation as opposed to 59.98% using our previous method that relied on R-peak detection. In summary, Beat Estimation renders wearable MCG sensors capable of accurately estimating HRV, despite the low SNR levels associated with sensor operation. The approach can be game-changing in assessing heart health, cardiovascular fitness, stress levels, cognitive workload, and more.
{"title":"Estimating Heart Rate Variability in Challenging Low SNR Regimes Using Wearable Magnetocardiography Sensors","authors":"Ali Kaiss;Md. Asiful Islam;Asimina Kiourti","doi":"10.1109/JERM.2024.3426270","DOIUrl":"https://doi.org/10.1109/JERM.2024.3426270","url":null,"abstract":"We report <sc>Beat Estimation</small>, a novel method used to calculate Heart Rate Variability (HRV) from low Signal to Noise Ratio (SNR) data (−7 dB to −4 dB in this work) acquired via wearable magnetocardiography (MCG). MCG activity is first collected using an in-house wearable sensor and filtered to remove noise outside the band of interest. <sc>Beat Estimation</small> extracts a single heart beat from the filtered recording and correlates it with a small number of beats individually to average out the remaining noise. The de-noised beat is then correlated with the full recording to identify the location of each of the heart beats. Using these locations, HRV parameters are, finally, calculated. Results show <inline-formula><tex-math>$sim$</tex-math></inline-formula>99.9% accuracy in estimating HRV metrics using beat-to-beat intervals as opposed to traditional R-to-R-peak intervals. The average accuracy of detecting the true location of beats is shown to increase to 96.43% using <sc>Beat Estimation</small> as opposed to 59.98% using our previous method that relied on R-peak detection. In summary, <sc>Beat Estimation</small> renders wearable MCG sensors capable of accurately estimating HRV, despite the low SNR levels associated with sensor operation. The approach can be game-changing in assessing heart health, cardiovascular fitness, stress levels, cognitive workload, and more.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"27-35"},"PeriodicalIF":3.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-08DOI: 10.1109/JERM.2024.3420737
Yuchen Ma;Changrong Liu;Yong Huang;Hua Ke;Xueguan Liu
To improve the wireless power transfer efficiency (PTE) of implantable medical devices (IMDs), a receiving rectenna consisting of a magneto-electric (ME) heterostructure mechanical antenna combined with an RF inductive coil is proposed in this paper. The receiving antenna, which operates at 54 kHz, consists of a ME antenna of 30 × 10 × 0.456 mm3 and a 60-turn inductive coil wound of 30 × 12 × 3 mm3. The receiving and transmitting antennas are analyzed and the wireless power transfer performance is measured. The specific absorption rate (SAR) at the resonant frequency is simulated to satisfy the safety standard. The final measured PTE at a distance of 15 mm between the transmitting coil and the proposed receiving antenna is 2.8159%, which is considerably higher than that of a single ME antenna or an inductive coil. The proposed receiving antenna is suitable for wireless biomedical devices.
{"title":"Combined Magnetoelectric/Coil Receiving Antenna for Biomedical Wireless Power Transfer","authors":"Yuchen Ma;Changrong Liu;Yong Huang;Hua Ke;Xueguan Liu","doi":"10.1109/JERM.2024.3420737","DOIUrl":"https://doi.org/10.1109/JERM.2024.3420737","url":null,"abstract":"To improve the wireless power transfer efficiency (PTE) of implantable medical devices (IMDs), a receiving rectenna consisting of a magneto-electric (ME) heterostructure mechanical antenna combined with an RF inductive coil is proposed in this paper. The receiving antenna, which operates at 54 kHz, consists of a ME antenna of 30 × 10 × 0.456 mm<sup>3</sup> and a 60-turn inductive coil wound of 30 × 12 × 3 mm<sup>3</sup>. The receiving and transmitting antennas are analyzed and the wireless power transfer performance is measured. The specific absorption rate (SAR) at the resonant frequency is simulated to satisfy the safety standard. The final measured PTE at a distance of 15 mm between the transmitting coil and the proposed receiving antenna is 2.8159%, which is considerably higher than that of a single ME antenna or an inductive coil. The proposed receiving antenna is suitable for wireless biomedical devices.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"15-26"},"PeriodicalIF":3.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-04DOI: 10.1109/JERM.2024.3419232
Leonardo Makinistian;Leandro Vives
Over the last decades, the interest on the biological effects of static and extremely low frequency magnetic fields (ELF-MF) on living organisms has been continuously growing. A myriad of bioeffects has been reported in the most diverse models, from bacteria and fungi to plants and even humans. Motivation has encompassed the most basic scientific curiosity, but also the concern for possible detrimental effects and the search for therapeutic and technological uses of ELF-MF. Experimentation has, to some extent, also focused on putting to test theoretical models of interaction. A substantial variety of devices, and even whole facilities, were developed to explore this yet poorly understood topic. In this review, we provide an up-to-date survey of the said devices and facilities, plus a revision on the various types of shielding reported in the literature. Finally, we enumerate a wide range of possible applications that are currently under study, whose development inevitably depends on an appropriate choice of field-generating devices, facilities and shielding. This should help researchers design their own experimental set ups from a wide perspective of what has already been developed and tested to date.
{"title":"Devices, Facilities, and Shielding for Biological Experiments With Static and Extremely Low Frequency Magnetic Fields","authors":"Leonardo Makinistian;Leandro Vives","doi":"10.1109/JERM.2024.3419232","DOIUrl":"https://doi.org/10.1109/JERM.2024.3419232","url":null,"abstract":"Over the last decades, the interest on the biological effects of static and extremely low frequency magnetic fields (ELF-MF) on living organisms has been continuously growing. A myriad of bioeffects has been reported in the most diverse models, from bacteria and fungi to plants and even humans. Motivation has encompassed the most basic scientific curiosity, but also the concern for possible detrimental effects and the search for therapeutic and technological uses of ELF-MF. Experimentation has, to some extent, also focused on putting to test theoretical models of interaction. A substantial variety of devices, and even whole facilities, were developed to explore this yet poorly understood topic. In this review, we provide an up-to-date survey of the said devices and facilities, plus a revision on the various types of shielding reported in the literature. Finally, we enumerate a wide range of possible applications that are currently under study, whose development inevitably depends on an appropriate choice of field-generating devices, facilities and shielding. This should help researchers design their own experimental set ups from a wide perspective of what has already been developed and tested to date.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 2","pages":"141-156"},"PeriodicalIF":3.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144117311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-02DOI: 10.1109/JERM.2024.3418716
Giuseppe Carluccio;Sukhoon Oh;Sangwoo Kim;Donghyuk Kim;Karthik Lakshmanan;Christopher M. Collins
Objectives: Estimation of Specific energy Absorption Rate (SAR) is critical to assess RF safety for devices that rely on the transmission of electromagnetic energy, such as cellphones or MRI coils. SAR generates local heat which can damage human tissues and it is usually estimated through numerical simulations. We describe a method to estimate the SAR distribution in phantoms that is fast and not computationally demanding, based on the evaluation of temperature increase maps. Technology or Method: The presented method relies on the inversion of a previously published method to quickly estimate the temperature increase with the knowledge of the SAR distribution and thermal properties. By reversing the process, we can estimate the SAR from temperature increase maps and material thermal properties. To demonstrate the method, we utilize temperature maps measured with MRI-based thermography and compare the estimated SAR maps with those obtained through electromagnetic simulations. We have performed these comparisons with two datasets, one 2D and one 3D, and we have considered the impact of potential sources of errors such as the acquisition time and discontinuities at the interface air/sample. Results: The method can estimate SAR distribution from experimental temperature increase maps within few seconds, and produces SAR distributions similar to those from simulation of the experimental situation. Clinical or Biological Impact : The method we present can quickly estimate SAR distribution to assess RF safety of radiofrequency devices.
目的：估算比能量吸收率（SAR）对于评估依赖电磁能量传输的设备（如手机或核磁共振成像线圈）的射频安全至关重要。SAR 会产生局部热量，对人体组织造成损害，通常通过数值模拟来估算。我们介绍了一种基于温度升高图评估的方法来估算模型中的 SAR 分布，这种方法速度快，计算要求低。技术或方法：所介绍的方法依赖于对之前公布的一种方法进行反演，从而利用 SAR 分布和热特性知识快速估算温升。通过反向过程，我们可以根据温升图和材料热特性估算出 SAR。为了演示这种方法，我们利用基于核磁共振成像的热成像技术测得的温度图，并将估算的 SAR 图与电磁模拟获得的 SAR 图进行比较。我们用两个数据集（一个是二维数据集，一个是三维数据集）进行了比较，并考虑了潜在误差源（如采集时间和空气/样品界面的不连续性）的影响。结果该方法可在几秒钟内根据实验温度升高图估算出 SAR 分布，并得出与模拟实验情况相似的 SAR 分布。临床或生物学影响：我们提出的方法可以快速估算 SAR 分布，以评估射频设备的射频安全性。
{"title":"A Fast Method to Estimate the SAR Distribution From Temperature Increased Maps","authors":"Giuseppe Carluccio;Sukhoon Oh;Sangwoo Kim;Donghyuk Kim;Karthik Lakshmanan;Christopher M. Collins","doi":"10.1109/JERM.2024.3418716","DOIUrl":"https://doi.org/10.1109/JERM.2024.3418716","url":null,"abstract":"<bold>Objectives:</b>\u0000 Estimation of Specific energy Absorption Rate (SAR) is critical to assess RF safety for devices that rely on the transmission of electromagnetic energy, such as cellphones or MRI coils. SAR generates local heat which can damage human tissues and it is usually estimated through numerical simulations. We describe a method to estimate the SAR distribution in phantoms that is fast and not computationally demanding, based on the evaluation of temperature increase maps. \u0000<bold>Technology or Method:</b>\u0000 The presented method relies on the inversion of a previously published method to quickly estimate the temperature increase with the knowledge of the SAR distribution and thermal properties. By reversing the process, we can estimate the SAR from temperature increase maps and material thermal properties. To demonstrate the method, we utilize temperature maps measured with MRI-based thermography and compare the estimated SAR maps with those obtained through electromagnetic simulations. We have performed these comparisons with two datasets, one 2D and one 3D, and we have considered the impact of potential sources of errors such as the acquisition time and discontinuities at the interface air/sample. \u0000<bold>Results:</b>\u0000 The method can estimate SAR distribution from experimental temperature increase maps within few seconds, and produces SAR distributions similar to those from simulation of the experimental situation. \u0000<bold>Clinical or Biological Impact</b>\u0000: The method we present can quickly estimate SAR distribution to assess RF safety of radiofrequency devices.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"8 3","pages":"298-304"},"PeriodicalIF":3.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142041466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/JERM.2024.3416758
Md. Abdul Awal;Azin S. Janani;Sasan Ahdi Rezaeieh;Graeme A. Macdonald;Amin Abbosh
Metabolic dysfunction-associated steatotic liver disease ranks among the most prevalent chronic liver conditions worldwide. To reduce its burden, early diagnosis is vital to enable timely medication and rehabilitation. The non-invasive diagnosis of liver health is challenging due to the limitations of existing methods. For this purpose, the design of portable non-invasive electromagnetic sensors requires knowledge of how human liver tissue and other abdominal tissues interact with electromagnetic waves. This necessitates the accurate characterisation of dielectric properties of the liver and adjacent abdominal tissues. Since postmortem changes or prolonged storage significantly change those properties and lead to incorrect interpretation, fresh human abdominal tissues, including skin, fat, muscle, and liver, were obtained at surgery, and their dielectric properties were measured immediately in the microwave frequency range of 0.5 GHz to 15 GHz. An adaptive weighted vector mean optimization algorithm was used to derive the parameters of a second-order Cole-Cole model using the experimental data. Statistical and cluster analyses were performed on the curated database following the derived model. The results showed that hepatic steatosis significantly changed the dielectric properties of the liver $(p < 0.001)$. Moreover, the liver had distinct dielectric properties from the skin, fat, and muscle tissues $(p < 0.05)$. These findings suggest that electromagnetic sensors could be used to assess liver health in a non-invasive way, which could improve liver health outcomes and reduce costs.
{"title":"Towards Non-Invasive Liver Health Monitoring: Comprehensive Microwave Dielectric Spectroscopy of Freshly Excised Human Abdominal Tissues","authors":"Md. Abdul Awal;Azin S. Janani;Sasan Ahdi Rezaeieh;Graeme A. Macdonald;Amin Abbosh","doi":"10.1109/JERM.2024.3416758","DOIUrl":"https://doi.org/10.1109/JERM.2024.3416758","url":null,"abstract":"Metabolic dysfunction-associated steatotic liver disease ranks among the most prevalent chronic liver conditions worldwide. To reduce its burden, early diagnosis is vital to enable timely medication and rehabilitation. The non-invasive diagnosis of liver health is challenging due to the limitations of existing methods. For this purpose, the design of portable non-invasive electromagnetic sensors requires knowledge of how human liver tissue and other abdominal tissues interact with electromagnetic waves. This necessitates the accurate characterisation of dielectric properties of the liver and adjacent abdominal tissues. Since postmortem changes or prolonged storage significantly change those properties and lead to incorrect interpretation, fresh human abdominal tissues, including skin, fat, muscle, and liver, were obtained at surgery, and their dielectric properties were measured immediately in the microwave frequency range of 0.5 GHz to 15 GHz. An adaptive weighted vector mean optimization algorithm was used to derive the parameters of a second-order Cole-Cole model using the experimental data. Statistical and cluster analyses were performed on the curated database following the derived model. The results showed that hepatic steatosis significantly changed the dielectric properties of the liver <inline-formula><tex-math>$(p < 0.001)$</tex-math></inline-formula>. Moreover, the liver had distinct dielectric properties from the skin, fat, and muscle tissues <inline-formula><tex-math>$(p < 0.05)$</tex-math></inline-formula>. These findings suggest that electromagnetic sensors could be used to assess liver health in a non-invasive way, which could improve liver health outcomes and reduce costs.","PeriodicalId":29955,"journal":{"name":"IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology","volume":"9 1","pages":"2-14"},"PeriodicalIF":3.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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