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Gopalakrishnan, K.; Adhikari, A.; Pallipamu, N.; Singh, M.; Nusrat, T.; Gaddam, S.; Samaddar, P.; Rajagopal, A.; Cherukuri, A.S.S.; Yadav, A.; et al. Applications of Microwaves in Medicine Leveraging Artificial Intelligence. Encyclopedia. Available online: https://encyclopedia.pub/entry/42797 (accessed on 23 July 2024).
Gopalakrishnan K, Adhikari A, Pallipamu N, Singh M, Nusrat T, Gaddam S, et al. Applications of Microwaves in Medicine Leveraging Artificial Intelligence. Encyclopedia. Available at: https://encyclopedia.pub/entry/42797. Accessed July 23, 2024.
Gopalakrishnan, Keerthy, Aakriti Adhikari, Namratha Pallipamu, Mansunderbir Singh, Tasin Nusrat, Sunil Gaddam, Poulami Samaddar, Anjali Rajagopal, Akhila Sai Sree Cherukuri, Anmol Yadav, et al. "Applications of Microwaves in Medicine Leveraging Artificial Intelligence" Encyclopedia, https://encyclopedia.pub/entry/42797 (accessed July 23, 2024).
Gopalakrishnan, K., Adhikari, A., Pallipamu, N., Singh, M., Nusrat, T., Gaddam, S., Samaddar, P., Rajagopal, A., Cherukuri, A.S.S., Yadav, A., Manga, S.S., Damani, D.N., Shivaram, S., Dey, S., Roy, S., Mitra, D., & Arunachalam, S.P. (2023, April 04). Applications of Microwaves in Medicine Leveraging Artificial Intelligence. In Encyclopedia. https://encyclopedia.pub/entry/42797
Gopalakrishnan, Keerthy, et al. "Applications of Microwaves in Medicine Leveraging Artificial Intelligence." Encyclopedia. Web. 04 April, 2023.
Applications of Microwaves in Medicine Leveraging Artificial Intelligence
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This entry is adapted from the peer-reviewed paper 10.3390/electronics12051101

Microwaves are non-ionizing electromagnetic radiation with waves of electrical and magnetic energy transmitted at different frequencies. They are widely used in various industries, including the food industry, telecommunications, weather forecasting, and in the field of medicine. Microwave applications in medicine are relatively a new field of growing interest, with a significant trend in healthcare research and development. The first application of microwaves in medicine dates to the 1980s in the treatment of cancer via ablation therapy; since then, their applications have been expanded. Significant advances have been made in reconstructing microwave data for imaging and sensing applications in the field of healthcare. Artificial intelligence (AI)-enabled microwave systems can be developed to augment healthcare, including clinical decision making, guiding treatment, and increasing resource-efficient facilities. 

microwaves medicine imaging radiometry telemetry

1. Diagnostic Applications of Microwaves

1.1. Microwave Imaging (MWI) Techniques

Various imaging methods have evolved over the course of time, such as X-ray, computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), digital mammography, and diagnostic sonography, among others, which provide information about tissues [1]. However, these methods have varying limitations, such as complexity, high cost, low spatial resolution, low sensitivity to tissue changes, or exposure to harmful radiation and nephrotoxic contrast agents. Microwave imaging (MWI) is an emerging method that has the potential to overcome some of these limitations. MWI is feasible because dielectric properties vary from one tissue type to another and between healthy and abnormal tissues. It can be easily mapped using a system consisting of antenna pairs or arrays, a vector network analyzer (VNA), and a radio frequency switch to control the antennas. Measured tissue properties can be expressed as a visual image for medical personnel to interpret, assess, and make evidence-based decisions.
Based on holographic domains, this technology can be broadly classified as follows:
  • Qualitative: It uses confocal microwave imaging and radar imaging algorithms where every single antenna is used to transmit and receive its own scattered signal. This technique has shown promising results so far. In oncology, its utility to detect malignant breast tissue was elicited by Oloumi et al. using the time-domain UWB circular-SAR technique [2]. Another study conducted by Grzegorczyk TM et al. in 2012 revealed the first 3D reconstructed image of breast tissue using microwaves within a timeframe of twenty minutes [3]. Surprisingly, attempts have also been made to use it in acute care settings to identify the site of brain stroke. The associated edema or hemorrhage causes up to 20% alteration in dielectric properties of the brain tissue [4]. Another common pathology researchers encounter very frequently in clinical practice is osteoporosis, which is very prevalent in post-menopausal females and elderly populations. The existing gold standard investigation used for its diagnosis, i.e., dual X-ray absorptiometry (DXA), exposes the patient to radiation and fails to assess bone quality, which is dictated by microarchitecture, composition, and the degree of microdamage. These problems can be easily circumvented by MWI, as shown in a study by Amin et al. on weight-bearing trabecular calcaneal bone [5]. However, even with the immense potential to evolve into a prominent diagnostic tool, using microwave energy for imaging needs extensive research as not many studies are available to properly evaluate dielectric properties of all the body tissues, facilitate clinical translation of these measurements, and address its potential limitations.
  • Quantitative: also known as microwave tomography (MT): It relies on the tissue dielectric properties (relative permittivity and conductivity) to create an image of the tissue using a set of antennas where one of them is used to illuminate the tissue and others gather the scattered waves. On a technical aspect, MWI is plagued by the inverse electromagnetic (EM) scattering problem during the processing of the data for image reconstruction. Typically, iterative inversion methods such as the Born iterative method (BIM), distorted Born iterative method (DBIM), contrast source inversion, etc., are used, but even with advances in numerical methods, solving the inverse problem is still challenging due to slow convergence, non-linearities, and ill-posedness leading to false solutions and unstable outcomes. This difficulty is further complicated by the 3D nature of the imaging domain, increasing the computational demand and processing times [6][7]. This is where deep learning (DL), a subset of artificial intelligence (AI), comes to the rescue, as it can quickly reconstruct the images within a few seconds or minutes, making the overall process suitable for real-time applications. According to L Ahmadi et al., DL approaches have been proven to be twice as fast for similar accuracy thresholds compared to conventional iterative methods [8]. AI is a rapidly evolving field with new architectures and approaches demonstrated by researchers in different areas. Many studies reveal a variety of DL architectures for MWI. Xudong Chen et al. authored a comprehensive review of different types of DL approaches explicitly used for solving inverse EM problems [9]. However, solving this inverse scattering problem in a 3D domain, at high resolution and dynamic range, is still a big challenge where AI can play a crucial role.

1.2. Microwaves in Diagnostic Pathology

Diagnostic pathology is a specialized area of medical science focusing on disease identification. Suspected tissues such as tumors are excised from patients and are processed in the laboratory for examination. Tissue preparation typically includes two essential techniques where microwaves are commonly used, i.e., fixation and staining of the sample tissues:
  • Fixation is a chemical preservation process to maintain the in vivo cellular and extracellular morphological state for analysis [10].
  • Staining is used to highlight important features and enhance the contrast for microscopy [11].
Conventional fixation and staining methods are time-consuming and result in artifacts such as shrinkage that can affect the quality of the analysis. Immediate fixation is required to halt autolysis and preserve the tissue. Proper staining is needed to minimize any biasing effects in visual contrast. To reduce the tissue processing times, microwave (MW) heating at 2.45 GHz is used to accelerate the fixation and staining techniques. Some studies have shown that MW-based techniques reduced the tissue processing time from 1/3 to 1/10 of the conventional procedures [12].
Decreased tissue processing times have been reported with MW-based methods, with an approximate processing duration of 113 min, as opposed to conventional methods that can be as high as 515 min.
AI-based solutions to optimize tissue heating at different frequencies are possible to enhance staining approaches. A wide range of data of different tissue heating profiles or fingerprints can be generated and optimized using AI to subsequently improve staining that will improve disease diagnostics using microwaves.
Microwave irradiation can be applied to expedite the process of routine, special, metallic, as well as immunofluorescent staining, as it helps with diffusing the dye into the tissue and binding to the substrate, which is a key step in tissue staining [12][13]. Furthermore, microwave-assisted rapid tissue processing technology has a higher safety profile, as it eliminates the usage of harmful chemicals such as formalin and xylene as opposed to conventional methods [13][14]. There is increased clinical use of this technology in neuropathology when using stereotactic brain biopsy techniques, which require rapid intraoperative techniques such as the smear technique and cryostat section [15]. Microwave technology can be used to immediately fix the cryostat sections, lay out a superior tissue morphology, and further promote the usage of special stains and immunochemistry for diagnostic purposes. In addition, this technique does not provide undesirable effects while using special stains and causes only minor shrinkage artifacts as opposed to conventional formalin fixation [16]. In addition to faster processing, MW techniques improve the uniformity of the temperature in the tissue and allow precise temperature control when used in conjunction with fiber-optic temperature sensors.
One of the challenges of pathology analysis is the need for skilled specialists with years of experience. Repetitive and tedious tasks make it challenging for human interpreters to maintain a high level of performance, leading to errors. Digital pathology and AI over the last two decades have proven to be important alternatives to reduce this burden on specialists. A study published in 2019 introduced the DAPPER framework that included a deep-learning pipeline and histological imaging [17]. The study compared the classification performance of the framework against an expert pathologist using tiles (histological images). The results demonstrated that the AI framework could classify the tiles with higher accuracy. Whole slide imaging (WSI) are rich datasets that have enabled the use of AI in pathology and surpassed the capabilities of human interpreters [18]. MW-based tissue preparations, a rich set of WSI data, and continuously evolving AI algorithms have transformed diagnostic pathology, improving the efficiency and accuracy of the outcomes.

1.3. Microwave-Based Molecular Diagnostics

Molecular diagnostics (MDx) is another area of laboratory science specialized in genomic investigations, where microwaves are being used. Microwave-accelerated metal-enhanced fluorescence (MAMEF) explains the platform and application combining microwave heating and metal-enhanced fluorescence (MEF) [19][20][21]. Microwave energy is used for DNA extraction. Lyse-It is a rapid and low-cost method to prepare sample cells and fragment the DNA and RNA, protein release, and degradation in a single step [22]. The technology uses a gold bow-tie vapor deposited on a glass slide which is then used for cellular lysis. The rapid creation of thermal and convection gradients exceeds the mechanical strength of the cell membranes and results in biomolecule degradation. The level of fragmentation is dependent on MW power and irradiation time. An increase in either MW power or exposure time results in an increase in fragmentation [23].
The challenge of COVID-19 raised expectations for better diagnostics, isolation, treatment, and tracking. Rapid molecular diagnostics such as real-time reverse transcriptase polymerase chain reaction (RT-PCR) are indispensable for COVID-19 diagnosis. Although this test was widely used across the world, it requires a long duration of ~6 h from the time of sampling before conclusions can be drawn. The study used raw data consisting of fluorescence values measured over 40 cycles from RT-PCR on nasopharyngeal swab specimens from each patient. A deep-learning (DL) model was developed and trained on the time-series fluorescence dataset from the RT-PCR. A DL model approach achieved a sensitivity of 93.33%, while the RT-PCR test had a sensitivity of 89%. The study confirms that the diagnostic speed can be greatly improved without sacrificing sensitivity [24]. The use of microwaves along with artificial intelligence together are great amplifiers of speed and sensitivity in the field of molecular diagnostics.

1.4. Dielectric Spectroscopy Applications

Dielectric spectroscopy is an effective method that can measure the dielectric property or permittivity of a material under test (MUT). The dielectric properties of different biological tissues at microwave frequencies have been investigated by many researchers in the last two decades to build tissue dielectric property databases [25][26][27][28]. This section discusses the developments and possible applications of machine learning using dielectric spectroscopy data.

1.4.1. Breast

A study reported by Helwan et al. used machine-learning techniques such as feedforward neural networks using the backpropagation learning algorithm (BPNN) and radial basis function network (RBFN) for breast tissue classification [29]. They used a dielectric dataset from the UCI repository under the breast tissue database (classification category). The RBFN showed the best performance at around 94.33% classification accuracy.

1.4.2. Liver

Microwave ablation demands accurate knowledge of the dielectric properties of the liver. Researchers over the years have measured and documented the in vivo and ex vivo dielectric characteristics of different animal as well as human liver tissues. In addition, few animal studies show immense scope for dielectric spectroscopy paired with artificial intelligence (AI) in the diagnosis of liver diseases. In a study conducted by Yilmaz on rats having a malignant liver, the author classified the liver tissue using support vector machine (SVM) learning algorithms and experimented on a total of 771 in vivo samples from 30 adult female albino rats with an open-ended coaxial probe technique. Out of these, they were able to identify cancerous and normal tissue correctly and reported that SVM algorithms with radial basis had 98.3% accuracy in identifying cancerous tissue vs. normal tissue [30].

1.4.3. Kidney

Banu Sacli et al. [31] used dielectric properties of naturally formed renal calculi (calcium oxalate, cystine, struvite) measured using an open-ended contact probe technique between 500 MHz and 6 GHz. He used a machine-learning model k-nearest neighbors (KNN) to classify the types of renal calculi. The algorithm had 98.17% accuracy. H. Rahmani et al. [32] used a machine-learning algorithm to classify the permittivity of normal and wounded skin created by scratch, punch, and UVB burn using principal component analysis for data dimensionality reduction on the measured loss tangent (ε″/ε′) data. Furthermore, they used the gaussian mixture model (GMM), an unsupervised learning method, support vector classifier (SVC), a supervised learning method, naïve Bayes, and neural net to classify between normal skin and punch wound and reported 97% to 100% accuracy of using these models.

1.4.4. Lungs

In China, Lu et al. [33] developed an ML model (XG Boost) combining dielectric properties to assess whether thoracic lymph nodes were benign or malignant in patients with non-small cell lung cancer. Traditionally, surgeons use frozen sections to diagnose metastatic lymph nodes, which is time-consuming and expensive. They used XG Boost, where the model accuracy was 87.8% with a sensitivity of 58.33% and specificity of 100%. Therefore, they combined this with the SMOTE algorithm and found that the sensitivity was 83.33% and specificity was 96.55%. These machine-learning models can be helpful to surgeons intraoperatively to rapidly diagnose with high efficacy.

1.4.5. Machine Learning to Solve Analytical Problems

The use of machine-learning models has been largely used to resolve analytical problems or to classify the permittivity associated with the usage of dielectric spectroscopy. Dielectric properties are expressed using parametric models (mathematical models) such as multi-pole Debye or Cole–Cole expression for better understanding or to represent the tissue performances over a wide frequency range [34]. Historically, numerical statistical nonlinear regression or similar techniques are mostly used to fit these measured complex permittivity results with Debye or Cole–Cole parameters [34][35].
Recent literature described the usage of machine-learning models to improve this data-fitting process. Yilmaz et al. used a particle swarm optimization algorithm to fit Cole–Cole parameters to the average of multiple measurements from the same animal liver sample [30]. Salahuddin et al. used six different optimization algorithms, i.e., least squares method, particle swarm optimization, weighted least squares algorithm, hybrid particle swarm–least squares algorithm, one-stage genetic algorithm, and two-stage genetic algorithm, to fit measured data to the multi-pole Debye model. According to the reported work novel, a two-stage genetic algorithm proved to be the most effective and efficient method. Recently Bai et al. published a study that presented an extensive analysis of recent accomplishments of deep-learning methods for solving linear inverse problems [36].

1.5. Microwave Radiometry in Medicine

Microwave radiometry (MWR) is a safe and patient-friendly technology to measure and visualize the temperatures of human tissues. In this technology, a signal is received from tissues’ intrinsic radiation, wherein the power of the tissues in the microwave range is proportional to the average temperature of tissues in the volume under the antenna. MWR is a novel technique currently being explored as a potential way to detect at-risk vascular lesions.
Despite recent developments in vascular imaging technologies that allow risk categorization of asymptomatic patients based on the degree of carotid artery stenosis and how prone the plaque is to rupture, risk stratification remains a challenging task [37][38]. Intravascular thermography is a method that detects vulnerable plaques, but its invasive nature excludes it from being used as a screening tool. Hence, the hunt for non-invasive indicators for assessing vascular inflammation in patients at high cardiovascular risk is still an area of active research. It was reported that there is appreciable temperature variation in normal and atherosclerotic vessels, and MR gives a reliable measurement of the internal tissue temperature by converting electromagnetic radiation to microwave frequencies [39]. Non-invasive sensors have also been developed to detect these changes [40]. MWR has also been applied in oncology, where the temperature variation of malignant breast tissue compared to the normal surrounding tissue due to their more rapid growth and replication was detected using MR sensors.
However, the major roadblock in its clinical use is that—being a newer technique—healthcare professionals are not adapting to its interpretation and use. This can be addressed using artificial intelligence models to interpret data from these sensors to extract useful information, translate it to prognosticate patients, and provide the best diagnostic capacity in a timely manner [41]. The use of MWR and artificial intelligence together was attempted by Levshinskii et al. [42], wherein deep-learning models were employed to identify chronic venous insufficiency due to temperature alteration in the inflamed vessel walls.

2. Applications of Microwaves in Treatment

2.1. Microwave Ablation

Microwave ablation is a form of thermal ablative technique that causes coagulative necrosis and cell death via two mechanisms: dipole and ionic. Water molecules are dipoles, and when energy is applied, these molecules in the tissue agitate continuously, generating heat that leads to cell death [43][44]. This technique is used to treat various benign and malignant tumors, including tumors of the liver, pancreas, kidney, breast, and adrenal. As in other ablation techniques, microwave ablation allows for different approaches, including percutaneous, laparoscopic, and open surgical access. Other than tumors, MWA is also used in treating biliary strictures and cholecystocutaneous fistulas, particularly as a minimally invasive procedure in poor surgical candidates. It was also used in the ablation of focal nodular hyperplasia in children without necrotizing the adjacent structures such as the gallbladder, highlighting the precision and effectiveness of the procedure [45]. Following are various treatments using microwave ablation techniques and how AI has been used thus far.

2.1.1. Liver

Many patients with small hepatocellular carcinomas may benefit from ablation therapy as their first-line therapy or as an alternative for those who are not candidates for surgery. Thermal ablation involves heating cancerous tissues to high enough temperatures (usually over 60 °C) to cause prompt coagulative necrosis. MWA for hepatocellular carcinoma (HCC) was first used in Japan by Saitsu et al. [46] and has been used worldwide for the last two decades. MWA is a safe technique for the treatment of unresectable liver tumors with a mortality that ranges from 0% to 0.36%. Liang P et al. created practice guidelines for ultrasound-guided MWA for liver cancer which aim to standardize MWA treatment and criteria for treatment candidates. A better convection profile, greater consistent intratumoral temperatures, quicker ablation periods, and the capacity to employ numerous probes to treat multiple tumors at once are all advantages of MWA. According to Izzo et al. [47], MWA is considered superior to radiofrequency ablation (RFA) for liver tumors with perivascular lesions, suggesting that candidates for MWA should be chosen according to patient characteristics for ablation. In an attempt to identify the differences between microwave ablation (MWA) systems using different frequencies, Kerri A Simo et al. [48], found that both 915 MHz and 2.45 GHz MWA systems achieve reproducible hepatic tumor ablation.

2.1.2. Bone

  • Tumors
The primary composition of bone is collagen and inorganic salts, which makes it relatively hard, making it able to withstand high heat. For this reason, microwaves can be used in the treatment of primary bone tumors as well as bony metastasis [49]. RFA and cryoablation (CA) are considered well-established, safe, effective, and durable methods of treatment for painful bone tumors and bone metastasis [50][51]. Microwave ablation has been added to the arsenal of treatment for the ablation of bone tumors in recent times [52]. Direct MW-induced thermocoagulation was used in a procedure by Fan et al. to treat 62 patients with diverse bone cancers. The goal of this surgical procedure was to isolate the tumor from nearby healthy structures. Out of 62 patients, 57 had local tumor control, but 5 had local fracture problems. However, the effectiveness of these minimally invasive treatments for malignant bone metastases must be established through extensive randomized multicenter trials [49][53]. Research findings and clinical experience concerning the use of microwave ablation to treat bone cancers in the limbs have been compiled, and a clinical guideline has been created to standardize the application of this treatment of bone tumors in the limbs. Through the use of evidence-based medicine, this guideline aims to provide a solid clinical foundation for indications, preoperative evaluation, and decision making, perioperative management, and complications. The goal of the recommendation is to standardize care and enhance the therapeutic effectiveness of MWA of bone cancers in the extremities [54].
  • Osteomyelitis
Osteomyelitis is an inflammatory disorder of the bone caused by infection. It is still challenging for orthopedic surgeons because of its protracted treatment process. The reported infection control rate ranges from 67 to 95%, and 5% to 33% of patients suffer from a recurrence of infection [55]. Patients with this condition have impaired local blood supply to the bone. Therefore, improving blood supply and tissue perfusion will help promote microbial clearance in infected areas and reduce recurrence in susceptible areas. By raising the temperature of deep tissues, MW diathermy can cause hyperthermia in tissue, which can speed up the healing process, boost drug activity, provide more effective pain relief, aid in the clearance of toxic waste, promote tendon flexibility, and lessen muscle and joint stiffness. Additionally, hyperthermia causes changes in the cell membrane, hyperemia, enhanced local tissue drainage, and elevated metabolic rate [56]. In a study, 40 rats infected with methicillin-sensitive Staphylococcus aureus in the medullary cavity of the right tibia were randomly assigned to one of four treatment groups: saline (control); saline + MW therapy; systemic cefuroxime; or systemic cefuroxime + MW therapy. This experimental model revealed that MW therapy significantly enhanced the effectiveness of the systemic antibiotic medication. However, more clinical research is necessary before this therapeutic option may be used on patients [57].

2.1.3. Uterus

  • Menorrhagia
Menorrhagia is a type of abnormal uterine bleeding that occurs in 53 out of 1000 women. Symptoms may include bleeding for 7 or more days and soaking through one or more sanitary pads or tampons every hour for several consecutive hours [58]. Although the definitive treatment is hysterectomy, it has physical and emotional complications along with high social and economic costs. To remove the complete thickness of the endometrium while maintaining the structural integrity of the reproductive system, several less invasive surgical procedures have been devised. The first-generation endometrial ablation techniques were introduced in the mid-1980s and included loop resection, rollerball, or laser ablation. The second-generation ablation techniques include thermal balloon (Thermachoice), hot fluid circulation (Hydro ThermAblator), cryotherapy (Her Option), microwave energy (MEA), and radiofrequency electrosurgery (NovaSure) [59]. Indeed, second-generation endometrial ablation is becoming the new gold standard for dysfunctional uterine bleeding [60].
Thermal endometrial ablation using microwaves, a recent treatment, is a minimally invasive technique that thermally eliminates the endometrial lining of the uterine cavity to reduce bleeding. A comparison of microwave endometrial ablation (MEA) with transcervical resection of the endometrium (TRCE) was performed and was followed up for a minimum of five years. Published operational results for this trial and clinical outcome at one year and two years showed that MEA produced equivalent clinical results to TCRE but with some operational advantages. In addition to being as effective at reducing menstruation symptoms, MEA also produces higher levels of acceptance, is easy to learn, is performed more quickly, is cost-effective, and is tolerable under local anesthesia compared to TCRE [61].
  • Fibroids
The most frequent benign pelvic tumors in women of reproductive age are uterine fibroids or leiomyomas. Any thermal ablative treatment for uterine fibroids aims to safely remove as much fibroid tissue as possible while leaving the surrounding uterine tissue unharmed [62]. In 2005, Goldberg described fibroid degeneration following microwave ablation of the endometrium [63]. A transvaginal ultrasound probe coupled to a 14-gauge needle set in an adapter has been used for transcervical microwave ablation of fibroids. A study of nine women undergoing transcervical microwave ablation of their fibroids found a decrease in volume between 37 and 69% at 6 months with no significant complications [64]. A similar study used a 20 mm long antenna that can operate in both continuous and pulsed microwave modes with a 15-gauge microwave needle. Following this, the mean fibroid volume reduction following the treatment is 90 and 94%, and no major adverse events were described and concluded that percutaneous microwave thermal ablation is a quick, painless, and minimally invasive technique that can be used to treat fibroid [65].

2.1.4. Prostate

In elderly men, benign prostatic hyperplasia (BPH) is a prevalent illness that may cause uncomfortable symptoms in the lower urinary tract (LUTS). More than 30% of men aged 65 and older possess irritable (frequency, nocturia, urgency) and/or obstructive urinary symptoms associated with BPH, including weak stream, hesitation, intermittency, and incomplete emptying [66]. Transurethral resection of the prostate (TURP) has been the gold-standard treatment for reducing urinary symptoms and enhancing urine flow in symptomatic BPH. However, the morbidity of TURP is increasing; subsequently, less invasive techniques have been developed for treating BPH [67]. Transurethral microwave thermotherapy (TUMT), in which microwaves are used to induce coagulation necrosis in prostatic tissue, appears to be a safe and efficient treatment for BPH [68]. It has also been proposed that this heating also destroys the alpha-adrenergic receptors, thereby increasing the urinary flow after the TUMT [69]. It has also been shown that TUMT increases sensory frequency, which also helps in relieving the irritative symptoms of the bladder [70]. Compared to TURP, microwave thermotherapy can be performed as an outpatient procedure and has fewer, milder adverse effects. However, the improvement in urinary symptoms and urine flow was better after TURP; nevertheless, fewer men required retreatment. Additional research is required to assess the long-term effects of microwave thermotherapy and develop the most efficient microwave thermotherapy equipment and energy levels [67].

2.1.5. Kidney

Whenever renal cell carcinoma is diagnosed, researchers usually opt for radical nephrectomy, which is associated with significant morbidity and mortality. With standard nephrectomy posing a high risk for older or comorbid patients, localized kidney tumors are being treated with percutaneous ablation. The most challenging issue with partial nephrectomy is the inability to control bleeding while the treatment is being performed [71]. Controlling parenchymal bleeding in solid vascular organs has been possible because Tabuse invented the microwave tissue coagulator in 1979 [72]. This device, according to Kagebayashi, was also helpful in partial nephrectomy [73]. Six patients underwent laparoscopic partial nephrectomy with a microwave tissue coagulator for small renal tumors. In terms of cancer control, five out of six patients had their tumors completely removed, while the sixth patient had the tumor capsule damaged. Laparoscopic partial nephrectomy with a microwave tissue coagulator is useful for small renal tumors, providing short operating time, minimal blood loss, and rapid recovery. However, it is necessary to compare the method to surgical treatments or other percutaneous ablation approaches in a comparative randomized mode [71].

2.1.6. Adrenal

Local tumor ablation in the adrenal gland presents unique challenges secondary to the adrenal gland’s unique anatomic and physiological features. Technically successful microwave ablation of primary adrenocortical cancer and adrenal metastases has been described by Simon and colleagues. Following adrenal microwave ablation, short-term follow-up outcomes are similarly positive. Given the cystic structure of adrenal metastases and the failure of radiofrequency to sufficiently heat cystic tumors, microwave ablation is thought to be preferable over RF ablation [74]. However, applying slowly in increments may be trickier with microwave ablation since it raises temperature more quickly than RFA. Even if it is theoretical, microwaves might present different difficulties for a titrated ablation in the case of more excessive catecholamine release than RFA [75].

2.1.7. Thyroid

Non-invasive procedures such as microwave, radiofrequency, high-intensity focused ultrasound, percutaneous ethanol injection (PEI), sclerotherapy, and laser photocoagulation (HIFU) ablation have been suggested as alternatives to surgery, particularly for the compression of nearby structures and cosmetic issues [76][77]. A clinical study was conducted on eleven patients with benign thyroid nodules who underwent MWA. In this small, non-randomized feasibility study, nodule volume was reduced by more than 50%, which resolved the cosmetic complaints of people with compressive neck symptoms. Nine participants with nodular goiter-related pain and two participants with Hashimoto’s thyroiditis improved upon treatment. The study concluded that it is possible to treat thyroid nodules that are cytologically benign with ultrasound-guided percutaneous MWA.

2.1.8. Lung

In the past two decades, there has been a significant diversity in the curative management of lung cancers, both primary and metastatic. MWA is a relatively recent thermal ablation technology that is being used more frequently to treat incurable lung cancers. Wolf et al. published the first substantial patient series study on it in 2008 [78]. MWA typically creates wider, more spherical, and predictable ablation zones because the tissue is evenly penetrated by the microwave field and is less affected by its characteristics. The extension of the ablation zone is particularly dependent on heat conduction, especially at its periphery, due to the high electrical resistivity of a ventilated lung and the tissue inhomogeneity. MWA causes thrombosis in vessels less than 6 mm in diameter and is less vulnerable to the heat sink effect [79]. Initial animal experiments have demonstrated definite advantages of MWA over RFA. MWA produces ablation zones that are larger, more spherical, and less time-consuming. However, the scant and inconsistent research on MWA does not offer enough proof to suggest a benefit over RFA in terms of local control or overall survival [80].

2.1.9. Heart

The role of microwave energy also extends to therapeutics, as it is used to treat various cardiac arrhythmias, i.e., idiopathic sinus node tachycardia and atrial fibrillation, using a minimally invasive transthoracic approach [81][82]. Strides have been made by using microwave-based irrigated ablation of deep myocardial ectopic foci of ventricular arrhythmias without damaging the superficial epicardial tissue and surrounding coronaries and thus preventing complications of conventional radiofrequency ablation [83]. The utilization of microwave energy has also sprawled into treating various peripheral vascular lesions, as was observed in studies by Zhang et al. and Sun et al., where microwave-based ablation was successfully used to coagulate and stop the bleeding from the renal and hepatic arteries, respectively, by using a percutaneous approach. This was found to be superior to the currently used intraluminal drug injections [84][85]. The ability of MR to detect temperature changes can also be used for targeted therapy, as was attempted by Tarakanov et al. [86], to treat patients with lower back pain.

2.2. Microwave Ablation with AI

In the past decade, there has been a continuous development of machine-learning and computational models for thermal ablative procedures. Most of these models have been applied to RFA with very scarce application in MWA. There is less information and technique to automate treatment detection of thermal ablation using MWA. Some researchers have incorporated AI and ML models to optimize and predict MWA outcomes. Brunese et al. [87], conducted a study to test machine-learning models to automatically predict the thermal ablation treatment and reduce tissue damage for patients under analysis using features from the patient medical health records. The model reached an F1 score of 0.91 using the NBTree classification algorithm to 0.92 with the LibSVM and Neural Network classification algorithm. Chao An et al. developed an ML model to predict the early recurrence of cancer in patients treated with MWA in the early stages of hepatic cell carcinoma (HCC) based on the clinical text data. After using SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) algorithms as interpretation algorithms, the authors finally concluded that the ML method using the XGBoost model helps physicians with decision making before MWA for HCC in clinical practice and trials [88]. Although these studies have incorporated AI for thermal ablative techniques, further research in the development of ML models is necessary for more accurate diagnosis and treatment outcomes.

3. Microwave Energy in Drug Delivery

Advancement in technology has opened various doors to increase the efficacy and decrease the side-effect profile of various drugs, especially those used in cancer treatments. Various methods, including therapeutic drug monitoring, tailoring the dose, and selective use of drugs, have been used conventionally. However, a relatively new approach to delivering the drugs to their targeted action sites and circumventing any systemic interaction is currently being explored [89]. These drug delivery systems are a formulation or a device involved in transporting a pharmaceutical compound to its target site for a desired therapeutic effect. The working principle behind this is the development of a carrier molecule that transports the drug to the required site and releases it in a controlled manner triggered by changes in the surrounding environment (change in pH, temperature, chemical milieu, etc.) or by application of external magnetic field, ultrasound, or microwaves. Among these approaches, drug release controlled by temperature changes has attracted much attention because it does not rely on changes in specific chemical properties of the environment, which can be problematic in intracellular or in vivo applications [90]. However, it has limited application in vivo because of the damage caused to the non-target tissues and poor penetration into the deeper tissues.
Emerging evidence with the development of nanoparticles that have microwave-absorbing properties can address most of the limitations of these delivery systems. It allows for a non-invasive approach, allowing the carrier to heat faster and providing better thermal efficiency while allowing the stimulus to penetrate deep (10–15 cm) into the body [91][92]. A study conducted by Peng et al. in 2014 provided tangible evidence that particles coated by specific microwave-absorbing materials such as ZnO: Er(3+), Yb(3+) can successfully deliver chemotherapeutic drug etoposide. The use of microwave-based systems also helps to tackle the crystallization of drug compounds. This occurs due to the low water solubility of most compounds leading to their poor bioavailability. Converting the crystal structure of drugs to amorphous forms using microwave irradiation can form a supersaturated formulation with better bioavailability. Although the amorphous structure is unstable and can reconvert into a crystal form, various studies have been conducted to explore the possibility of making stable amorphous compounds with better potency than conventional drug forms [92][93]. Furthermore, the remarkable advancements in nanotechnology have resulted in the development of implantable robots which can perform controlled and targeted drug delivery [94]. These can be used along with artificial intelligence and deep-learning methods to develop novel astute delivery systems which can assess the dose, drug selectivity, and their targeted release depending upon the disease burden and pathology [95].

4. Microwaves in Telemetry

Telemetry can be defined as the automatic measurement and wireless transmission of data from remote sources. In medicine, it is widely used to monitor heart rate and rhythm (EKG), respiratory rate, partial pressure of oxygen in the blood, serum glucose, neural recordings, stimulation devices, and cochlear and retinal implants while the patient is ambulatory and not restricted to bedside monitors. Most of the conventional monitoring systems use inductive transmission for both data transfer and device recharge, with issues of high power requirement and biocompatibility. However, newer options in the form of high-frequency (~400 MHz) microwave devices with small implantable antennas can serve the same purpose with better battery life and compatibility [96][97][98][99].
Over the decades, various engineering techniques such as AI and machine learning have been used in the field of medicine. They have served as a catalyst, whether it be increasing the clinical and treatment outcome or early diagnosis of a disease. One such interesting application is in the analysis of telemetry data, as enlightened by a study that used AI analysis of continuous EEG data to rapidly determine a good 6-month functional outcome for patients [97]. Similarly, machine learning has been used to analyze the telemetry data to detect sepsis in its early stages and determine the optimal timing for antibiotics and additional fluids. This can have great positive impacts on patient outcomes [100]. Despite these promising results, clinical implementation is still a barrier, and future studies should be focused on sorting out the evidence that can be incorporated widely into AI. This can be achieved by the collaboration of experts in their respective fields, such as clinicians and data analysts [101].

5. Microwaves in Hospital Waste Management

The majority of waste that requires inactivation processes comes from research facilities and commercial companies, yet most of it is generated from hospitals. About 10% of hospital waste is biohazardous, requiring proper inactivation [102]. There are four basic domains for the treatment and safe disposal of such waste, namely chemical, thermal, biological, and irradiative. Incineration and autoclaving are the most widely used of all these. However, this can be achieved by microwave irradiation as well. Ideally, the waste generated should be inactivated at the site of production, but this can be cumbersome and resource-intensive, making it less suitable for low-resource settings.
Microwave irradiation is an emerging method to achieve sterilization of waste as it has been commercially used, for example, in Sanitec systems and documented to destroy pathogens such as E. coli, Bacillus subtilis, and Salmonella. These were exposed to a conventional microwave at around 2500 MHz and had a 6-log cycle reduction in viability [103]. Various studies conducted on food articles replicated the same results. In a study carried out by Song et al., it was observed that microwaves reduced salmonella in peanut butter without deteriorating the quality of the food [104]. There was also complete inactivation of E. coli and microflora when microwaves were used on mechanically tenderized beef at temperatures above 70 degrees Celsius for more than 1 min [105].
The mechanism of its action is yet to be fully defined, but it is postulated to be a combination of thermal effects on the dipolar components in the waste and nonthermal alteration in protein structures of the infectious waste constituents [106][107]. However, it is more suitable than conventional methods in terms of cost-effectiveness, transportation, and eco-friendliness [108].

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Subjects: Engineering, Biomedical
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Keerthy Gopalakrishnan
,
Aakriti Adhikari
,
Namratha Pallipamu
,
Mansunderbir Singh
,
Tasin Nusrat
,
Sunil Gaddam
,
Poulami Samaddar
,
Anjali Rajagopal
,
Akhila Sai Sree Cherukuri
,
Anmol Yadav
,
Shreya Sai Manga
,
Devanshi N. Damani
,
Suganti Shivaram
,
Shuvashis Dey
,
Sayan Roy
,
Dipankar Mitra
,
Shivaram P. Arunachalam
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Revisions: 2 times (View History)
Update Date: 07 Apr 2023
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