Patent Application
20240090826
The present invention relates to the field of analysis of biological tissues, and in particular microwave based techniques to analyze variations in biological tissue considering the effect of physiological and biological properties on microwave signals.
Low muscle mass is associated with negative outcomes such as more surgical complications, longer length of hospital stays, lower physical function, poorer quality of life and shorter survival. As such, the potential clinical benefits of preventing and reversing this condition for are likely to impact patient outcomes and resource utilization/health care costs along the care continuum. In secondary care such as geriatric care and home care, quality of life in ageing people is hampered by a decline in muscle mass, with an increased risk of falling, increased morbidity in disease and a decreased life expectancy.
This decline in muscle mass in combination with strength and function, a condition known as sarcopenia, is recognized in many medical conditions as an important risk factor for mortality and morbidity. The significance of sarcopenia is evident in a variety of diseases, in various patient groups and in different clinical settings, and therefore across the whole continuum of care. Sarcopenia can be prevented or treated by physical activity and nutritional intervention. Although these interventions have been shown to be cost-effective, the condition has to be diagnosed before any treatment can be initiated and continuously optimized depending on patients' body composition and treatment profile. A delay in detection of sarcopenia increases the risk of falling, hampers mobility, increases the risk of severe complications in people undergoing treatment for diseases, and has a negative influence on survival. In the healthcare system, the treating physicians as well as the healthcare system itself are affected because of the higher complication rates and lower survival of patients. The associated longer admission times and higher costs put an additional burden on the system.
In several widely adopted definitions, bioimpedance, CT scanning, and muscle function determined by mobility tests or strength tests are all used. None of these tests shows high accuracy or reproducibility, leading to underdiagnosis of sarcopenia. Moreover, the availability of techniques like CT scanning hampers their widespread use and makes repeated measurements at regular intervals, for example to monitor the effect of interventions and ongoing treatment, impossible. As a consequence, people either are either not identified as sarcopenic, or the effect of treatment cannot be evaluated.
Currently the assessment of body composition is done using CT, MRJ and DEXA scans. Ultra sound and Body Impedance Analysis (BIA) are other techniques. All these methods suffer from high cost constrains as far as regular patient follow-ups are concerned. Some of them are not even suited for frequent follow-ups due to radiation concerns. Others such as BIA and Ultrasound suffer from lack of resolution and accuracy. Especially in the case of BIA body fluids (electrolyte) play a decisive role in the analysis outcome, which means the patient's water saturation level can alter the body composition readings. This is a major shortcoming of BIA technique.
Human body communications (HBC), also termed IntraBody Communication (IBC), have lately received a good deal of interest in healthcare monitoring and treatment applications.
Wearable sensor arrangements comprising microwave antennas are known in the art, such as through US2014/0253397 and US2018/0042513. Sensor arrangements comprising microwave antennas for introduction into the body are also known in the art, such as through WO2018/081602.
The present invention aims to provide a new diagnostic and multimodal approach for measurement of body composition that is simple, accurate, non-ionizing, and readily available for the benefit of people at risk for low muscle mass resulting in sarcopenia across a large spectrum of the general population.
While the sensor arrangements according to the prior art may function well for their intended use, they are not configured for use according to the present invention. In particular, the present invention relates on analysis of signals transmitted between at least two microwave antennas within the tissues of a subject. It is therefore necessary to cancel direct coupling between the antennas through creeping wave coupling on the body surface. This is a non trivial task due to the off-the plane propagation initiated by the fringe fields around the antennas. This problem is solved by the present inventors by inclusion of a band-stop structure that cancel both in-plane and off-plane signal propagation, i.e. cancel direct coupling between the microwave antennas.
According to a first aspect there is provided a sensor arrangement comprising a support substrate and at least two microwave antennas fixedly arranged in or on the support substrate, each microwave antenna being separated from all other microwave antennas by a band-stop structure configured to cancel direct coupling between the microwave antennas, the sensor arrangement further comprising microwave signal transmission paths configured to transmit microwave signals to or from the microwave antennas.
The sensor arrangement according to the invention provides a well-defined sensor set-up that reduces disturbances caused by movement of the antennas and direct coupling between the antennas.
According to some embodiments, said microwave antennas are fixedly arranged 20-160 mm apart, such as 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, or 150 mm apart.
According to some embodiments, said microwave antennas are split ring resonators.
According to some embodiments, the sensor comprises one or more microwave signal contacts connected to the transmission paths to the microwave antennas to facilitate easy connection to, and disconnection from, a microwave signal generator and/or a microwave signal processing unit.
According to some embodiments, the sensor comprises at least one microwave switch arranged in a transmission path between a microwave signal contact and two or more microwave antennas.
According to some embodiments, at least three microwave antennas are fixedly arranged in or on said support substrate.
This enables simultaneous collection of signal data from a plurality of receiver antennas and provides for a more extensive analysis of the biological tissue.
According to some embodiments, the support substrate is flexible.
The sensor arrangement needs good contact with skin surface for efficient signal coupling. Selection of substrate material should thus preferably make the solid substrate flexible and/or stretchable to provide good contact when applied on a body of a subject. Polydimethysiloxane (PDMS) and Galinstan (Liquid metal) based stretchable fabrication technology are currently contemplated to ensure surface compliance.
According to some embodiments, the support substrate has an adhesive coating for fixing the sensor arrangement on the skin of a subject.
According to a second aspect there is provided a system comprising a sensor arrangement according to the first aspect; a tuneable microwave signal generator configured to generate and transmit a microwave signal to a first microwave antenna in the sensor arrangement; and a signal processing unit arranged to receive the transmitted microwave signal from at least one second microwave antenna in the sensor arrangement.
According to some embodiments, the signal processing unit is configured to analyse a change in the transmitted microwave signal between said first microwave antenna and said at least one second microwave antenna.
According to some embodiments, the change in said microwave signal is a change in amplitude and/or a phase delay.
According to some embodiments, the tuneable microwave signal generator can generate microwave signals in a frequency range of 2.45 GHz to 10 GHz.
According to some embodiments, the system is suitable for non-invasive assessment of a property of subdermal tissue in a subject, and the signal processing unit is configured to correlate a change in the transmitted microwave signal between the first microwave antenna and the at least one second microwave antenna with properties of subdermal tissue in the subject.
According to some embodiments, the sensor arrangement incorporated in the system comprises at least three microwave antennas and the signal processing unit is arranged to receive said microwave signal from at least two second microwave antennas in said sensor arrangement; and the signal processing unit is configured to correlate a change in the transmitted microwave signal between the first microwave antenna and each of the at least two second microwave antennas with the property of subdermal tissue in a subject.
According to some embodiments, the property of subdermal tissue is selected from the group consisting of fat content of muscle tissue, thickness of muscle tissue, thickness of fat tissue.
According to a third aspect there is provided a method for non-invasive assessment of a property of subdermal tissue in a subject comprising the steps
According to some embodiments, the method comprises the steps
According to some embodiments, the change in the transmitted microwave signal is a change in amplitude and/or a phase delay.
According to some embodiments, steps S2 and S3 are repeated at least four times with microwave signals of frequency 2.45; 5, 8, and 10 GHz.
According to some embodiments, the property of subdermal tissue is selected from the group consisting of fat content of muscle tissue, thickness of muscle tissue, thickness of fat tissue.
Effects and features of the second and third aspects are to a large extent analogous to those described above in connection with the first aspect. Embodiments mentioned in relation to the first aspect are largely compatible with the second and third aspects.
The present disclosure will become apparent from the detailed description given below. The detailed description and specific examples disclose preferred embodiments of the disclosure by way of illustration only. Those skilled in the art understand from guidance in the detailed description that changes and modifications may be made within the scope of the disclosure.
Hence, it is to be understood that the herein disclosed disclosure is not limited to the particular component parts of the device described or steps of the methods described since such device and method may vary. It is also to be understood that the terminology used herein is for purpose of describing particular embodiments only, and is not intended to be limiting. It should be noted that, as used in the specification and the appended claim, the articles “a”, “an”, “the”, and “said” are intended to mean that there are one or more of the elements unless the context explicitly dictates otherwise. Thus, for example, reference to “a unit” or “the unit” may include several devices, and the like. Furthermore, the words “comprising”, “including”, “containing” and similar wordings does not exclude other elements or steps.
The above objects, as well as additional objects, features and advantages of the present disclosure, will be more fully appreciated by reference to the following illustrative and non-limiting detailed description of example embodiments of the present disclosure, when taken in conjunction with the accompanying drawings.
The present invention uses the Radio Frequency (RF) propagation technique to understand the geometrical distribution of a multi-layered tissue by calculating the signal loss while the signal is propagating through the tissues.
The received signal's signal-to-noise ratio (SNR), which requires the underlying multilayer human body that governs the microwave propagation, and its impact on attenuation must be resolved so that Human Body Communication (HBC) systems are designed and implemented accurately. One of the main considerations of these requirements is the study of electromagnetic (EM) signal propagation characteristics in the body tissue. Microwave propagation is then investigated based on the tissue dielectric properties in terms of their reflection, signal loss, attenuation, and penetration depth.
In fat channel microwave communication, the human fat tissue acts as the main signal propagation medium, which implies that the dimensional variations in the fat channel will be reflected in the signal coupling level. This attribute opens up a sensing possibility of the physical dimensions of the channel, which is essentially the thickness of fat tissue. The fat channel is confined by skin and muscle tissues. While variations in the skin thickness are not significant, variations in the muscle could be. In other words, both fat and muscle thickness variations can have a combined effect on fat channel communication. In this work, we utilize the variability between different tissue thicknesses as a precursor to assess the signal attenuation level, which in turn, is a marker of underlying tissue distribution.
The technique for tissue analysis according to the invention is non-invasive, non-ionizing and objective compared to other state-of-the-art modalities.
In one aspect, the present invention relates to a device (a sensor arrangement) comprising two antennas separated by a fixed distance, of which one sends interrogating signals to assess the tissue properties whereas the other antenna serves as the receiver. The antennas are separated by a physical structure (a band stop structure) that obstructs the formation of creeping waves resulting in direct signal coupling between the antennas. Instead, coupling between the antennas are provided for deeper within the tissues. Furthermore the frequency of operation of the antennas may be tuned to increase the penetration of the microwave signal into the tissue, controllable through different wavelength's angle of incidence behaviour to select any particular subdermal tissue for interrogation.
The feasibility of the concept mentioned above is examined using microstrip Split Ring Resonators (SRRs) to estimate the EM signal loss through biological tissue. Two prototypes consisting of three layers of tissue thickness (skin, fat and muscle) are presented primarily for the measuring conditions and the personal characteristics of human tissues.
This invention indicates an analysis approach to examine the influence of the tissue proportions on the EM signal coupling.
In the exemplary section, a laboratory setup comprising of two SRR sensors and an ex-vivo porcine experimental model for biological tissues are disclosed. Also provided is an intensive parametric analysis of a variety of fat and muscle thickness values at different sensor distances, which enabled us to conclude the underlying EM signal coupling. Finally, a validation between electric field (Efield) and penetration depth and their associated effects on signal loss due to the variation in thickness and distance is provided.
The present disclosure will now be described with reference to the accompanying drawings, in which preferred example embodiments of the disclosure are shown. The invention may, however, be embodied in other forms within the scope of the appended claims and should not be construed as limited to the herein disclosed embodiments.
The microwave antennas 104 may be fixedly arranged 20-250 mm, such as 20-160 mm apart. In embodiments having more than two microwave antennas, the microwave antennas being separated by the longest distance may be separated by up to 160 or 250 mm, and the other microwave antenna(s) may be evenly distanced from the longest separated microwave antennas, or by fixed distances such as 20, 30, 40 or 50 mm.
In embodiments, said microwave antennas are split ring resonators. The split ring resonator sensor design used the concept of a single split microstrip ring resonator (known as microstrip gap) as illustrated in
Each tissue is characterized by differences in dielectric properties, focusing primarily on relative permittivity, εr, and conductivity, σ. In particular, the conductivity of skin and muscle tissues at high frequencies is much higher than the conductivity of fat tissue. This is because of the high water content in skin and muscle compared to the low content of water in fat and bone.
The present invention is complementary to this approach. The signal connection was chosen to be perpendicular to the ring's plane and at the center of the ring's projection on the ground plane. Therefore, a SubMiniature version A (SMA) connector was employed and the signal's transition to a microstrip line starts from the bottom (ground) in the center of the ring's projection and to the edges of the parallel section of T-shape microstrip line. The sensor input impedance is optimized to be close to 50.
As shown in
The signal processing unit 204 is configured to analyse a change in the transmitted microwave signal between said first microwave antenna 104a and said at least one second microwave antenna 104b. The signal processing unit (204) preferably has enough computational capacity to process the received signals and calculate the respective properties of subdermal tissue of the patient in real-time. The provision of a communication link to a data storage will help the data to be logged and stored in the data storage, such as a cloud service, and thus help to make a good estimate of patient progress in rehabilitatory settings. Thus the system (200) will be a versatile system offering real-time insight into the body composition and at the same time registering the variations of muscle mass over time which ensures care continuum.
Deducing the signal amplitude and phase delay at receiver probes (104b, 104c) provides the information on tissue composition. The microwave signal generator (202) is configured to generate different signal frequencies enabling the signal confinement in various tissues as shown in the
To avoid signal leakage into the free-space (air) from the transmitter probe (104a), which would limit the signals from coupling into deeper tissue layer, band-stop structures (106) as shown in
The third aspect of this disclosure shows a method for non-invasive assessment of a property of subdermal tissue in a subject as illustrated in
In embodiments, the change in the transmitted microwave signal is a change in amplitude and/or a phase delay.
In embodiments, steps S2 and S3 are repeated a plurality of times with different frequencies, such as repeated 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 times or more. Each repetition may be performed with microwave signals of frequency in a range from 2 GHz, 2.45 GHz, 5 GHz, 8 GHz, or 10 GHz, to 2.45 GHz, 5 GHz, 8 GHz, or 10 GHz. In one embodiment steps S2 and S3 are repeated at least four times with microwave signals of frequency 2.45; 5, 8, and 10 GHz.
In embodiments, the property of subdermal tissue is selected from the group consisting of fat content of muscle tissue, thickness of muscle tissue, thickness of fat tissue.
In some embodiments, signal loss or path loss for the transmitted microwave signal or signals between the first microwave antenna and each of the at least two second microwave antennas is correlated with properties of muscle tissue in the subject.
In some embodiments, the correlation is performed by comparing the observed change, such as the observed signal loss or path loss, with a look-up table created by recording observed changes in the microwave signal for a number of biological tissue samples of known properties, optionally at a plurality of different frequencies.
For purpose of numerical simulation analysis of signal loss, we show the development of two 3D models using the Computer Simulation Technology (CST) software based on Ultra Sound (US) tissue thickness measurements.
The inventors' approach is to develop a multilayer homogeneous model that have been considered for numerical and experimental studies. This model consists of a three-layer tissue thickness containing skin, h5, fat, h6 and muscle, h7. Here, the skin thickness is kept constant (2.3 mm), while, the fat and muscle thicknesses are varied from 5 mm to 35 mm in 10 mm steps and from 10 mm to 50 mm in 20 mm steps, respectively. The length of simulation model is 250 mm and the width is 120 mm, which optimizes the condition for signal loss. As mentioned earlier, human tissues can be classified into those with high water content (like muscle and skin) and those with low water content (like fat).
Therefore, the influences of fat and muscle thickness on the EM signal loss between transmitter and receiver sensor are examined and analyzed.
A numerical study was performed to demonstrate that an SRR has the sensing capability with which multilayer tissues can be analyzed. The SRRs are placed above the body tissue, which is a multilayer medium consisting of air, skin, fat and muscle, to couple the EM signal inside the body tissue. The distance between the two SRRs are varied from 20 mm to 160 mm, and the amplitude and phase of the coupled signal for the fat layer are reported. As shown in
To calculate the free space coupling of the SRRs, two simulations are conducted. In the first simulation, the two SRRs are apart from each other and are connected with free space channel and in the second simulation; they are placed on the body tissue.
To analyze further, the variation of distance between the SRR sensors, which is increased from 20 mm to 250 mm, is investigated.
Next,
From results shown in the
Furthermore, we observed that the influence of the increasing distance between Tx and Rx sensors as a function of the layered fat and muscle tissue does provide significant difference on signal loss as shown in
Another notable aspect that can be seen in
In
In summary
Ex Vivo Experimental Set-Up and Measurements
We emulate human tissues using fresh porcine belly as commonly used in in-body imaging and power transfer systems. These tissues have layer structures that are complex and include skin, fat and muscle. Furthermore, these tissue EM properties are similar to human tissues. This tissue material, therefore, provides an ideal environment for human tissue emulation. The skin, fat and muscle porcine belly tissue were separated and finely minced with a meat mincer. The three-layered tissue structure, which contains skin, fat and muscle (top to bottom), is placed and arranged in a custom-made 3D printed plastic container and supported by a 5 mm-thick plate below the muscle layer.
The size of mold are 250 mm length, 60 mm width and 80 mm height. By varying the leveling plate underneath muscle layer, the thickness of the fat and muscle layer in exvivo tissue can be changed. On the other hand, a flexible, broadband, lightweight and multilayer flat carbon loaded laminate polyurethane (PU) foam based microwave absorber is used for experimental setup (FU-ML-120, Sahajanand Laser Technology Ltd, Gujarat, India). The dimension of microwave absorber are 600 mm length, 600 mm width and 120 mm height and reflectivity performance is −17 dB at 2.0 GHz.
The SRR sensors were attached to the surface of skin layers by using a stretchable strap to be sure that the sensor remains in good contact with skin and retains a constant pressure throughout the measurement. The sensors were then aligned as shown in
Additionally, this ex-vivo model was examined to gauge the depth of penetration by analyzing the E-field distribution of the layered tissues. Inferences from the E-field distribution simulation were made to characterize the signal loss in the experimental setup and the results have been compared. The penetration depth provides good information for analysing sensor performance, especially E-field distribution in different tissues, and can be used for future work in clinical measurements.
The electromagnetic (EM) waves mainly propagate around the human body surface via diffusion. As an outcome, the human body, a high-loss dielectric medium, usually has huge impacts on the signal propagation. Additionally, as the human tissues contain a range of dielectric properties, a functional model of the body would need to be studied on the signal propagation. Specifically, when RF signals propagate from a high dielectric property medium (like skin or muscle) to low dielectric property medium (like fat), it bends away from the direction perpendicular to the interface between the materials. This means that any signal that is reflected into the body has to travel across multiple centimeters (cm) of multilayer tissue and face multiple reflections before it can exit to the air. Thus, signal propagation in each layer is assumed to be linear, but across layers, it can change to multiple directions. To validate the effect of fat and muscle layer variation, the thickness of skin (2.5 mm) layer remains fixed; meanwhile, the variation of fat thickness is adjusted from 5 mm to 35 mm by 10 mm steps. Furthermore, the variation of muscle thickness from 10 mm to 50 mm by 20 mm steps has also been considered. It is necessary to calculate and sum up the maximum and minimum difference of magnitude of S21, |S21|, required to propagate across each model layer. To calculate the signal loss, skin and muscle are considered to remain constant and the maximum and minimum signal loss are reckoned by varying fat layer thickness. Therefore, the different signal loss, S21 (in dB), can be calculated by:
Δsignalloss=Max−Min (1)
where Δsignalloss is the signal loss, S21 (dB) and Max-Min is the difference between maximum and minimum signal at any variation of fat and muscle thicknesses.
This will provide a basis for the comparison of approximations that can be used from human tissue model for reflectivity and refractivity, and their suitability for integration into larger EM models.
E-Field Distribution Analysis
In addition to the described attenuation of the signal due to the difference in dielectric properties, the distribution of E-field is presented when propagating from one layer to another.
We considered three experimental scenarios to inspect the E-field distribution between Tx and Rx sensor at a fixed distance of 100 mm:
In
For the arrangement of scenario 3 (
The transmitted RF signal is constantly attenuated while passing through the fat tissue where the attenuation depends on the thickness of fat. Hence, the reflected signal from the next tissue declines even further and is causing the exponential fading of signal, especially from the beginning of the muscle tissue.
In summary, we observe two types of eigenmodes, namely, the bound states and the free state. The former are the modes bounded in the fat layer and they trap the signal mainly in the layer between skin and muscle. The latter are modes that trap the signal of the exterior mode, which are not bound to the layered fat but are flowing in the open regions.
Penetration Depth Assessment
Penetration depth was observed by examining the same experimental scenario from the previous section. The examination was done from the simulated E-field and the results were correlated. The defined E-field position was thus got from the axis Ez. Thus, the E-field distribution was measured perpendicularly to the Tx sensor plane along the Ez axis. The starting position of the Ez axis was taken into account at the maximum E-field strength at the sensor interface and the surface of the skin.
On average, 200 V/m (44.5%) of the E-field intensity increases on a boundary skin-fat and decreases into the next layer. The depth was gradually decreased once the E-field arrives at an average fat thickness of 10 mm. Another notable aspect to be observed in
Looking at the multilayer tissue thickness composition of all
The system and method according to the invention is useful in the quantification of muscle mass at any anatomical location of human body. It uses microwave signals which are selective towards human tissue properties. Since the passage of microwave signal is affected by various human tissues differently it gives the perfect opportunity to quantify any specific or group of tissues that microwave passes through. The microwave signal generator is configured to generate different signal frequencies enabling the signal confinement in various tissues as shown in the
The person skilled in the art realizes that the present disclosure is not limited to the preferred embodiments described above. The person skilled in the art further realizes that modifications and variations are possible within the scope of the appended claims. Additionally, variations within the scope of the appended claims can be understood and effected by the skilled person in practicing the claimed disclosure, from a study of the drawings, the disclosure, and the appended claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1951161-7 | Oct 2019 | SE | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/SE2020/050976 | 10/14/2020 | WO |
