1. Introduction
Microwave Radiometry (MWR) is the measurement technique involved in the characterization of the natural electromagnetic radiation in the microwave spectrum. This technique has been commonly employed in many areas, encompassing physics, chemistry, and engineering [
1]. In connection with the radio astronomy field, its typical receiver configurations have been applied to biomedical applications for the detection and diagnosis of pathologies in which an internal temperature gradient has been observed [
2,
3]. As a non-ionizing, non-invasive and inherently safe technique, MWR enables the measurement of internal body temperatures with or without contact for the early diagnosis of several pathologies [
3,
4,
5].
Microwave technology has confirmed its effectiveness to provide temperature patterns at a depth of several centimetres [
6,
7]. The internal temperature of human body tissues can differ several degrees from that of the surface or skin [
8]. Thus, monitoring both internal as well as superficial temperatures and analysing their differences constitutes a significant issue for a variety of medical diagnostic and treatment procedures [
9]. In this regard, several medical applications have already implemented MWR systems for the detection of superficial breast cancer, atherosclerosis, rheumatoid arthritis, diabetic pathologies, urogenital diseases, as well as the measurement of internal brain temperatures [
2,
3,
5,
10,
11,
12,
13,
14,
15,
16,
17,
18]. MWR has been also demonstrated in preclinical research for the analysis of the thermal radiation of internal tissues, assessing temperature changes in malignant tumours that may serve as a diagnostic marker [
19].
X-rays, ultrasound, and magnetic resonance imaging (MRI) are widespread techniques used in clinical applications. However, these techniques show some disadvantages or limitations, such as cost, sensitivity or discomfort depending on the application [
10]. MRI and X-rays are generally expensive and non-portable, but show high spatial resolution [
20]. In addition, X-rays are considered as ionizing radiation. On the other hand, internal thermometers are also employed to measure temperatures within the body, but they are invasive, not convenient for long-term monitoring and cause discomfort to patients [
21]. Thus, the main goal of MWR is to provide a non-ionizing, non-invasive, fast, low-priced, and passive system that is able to penetrate into the tissues.
Microwave frequencies improve transmission features in comparison with infrared thermography when applied to human body tissues [
22]. The infrared transmission depth within tissues is truly small, and the detected radiation essentially comes from the surface of the skin [
22]. MWR is directed at detecting the thermal radiation originating from the internal layers or tissues, minimizing the effect of the skin. The penetration depth of microwave radiation depends on the dielectric properties and water content of the targeted tissues; however, lowering the frequency has demonstrated greater detection depths [
2,
23]. Human body tissues behave as partially transparent layers for the electromagnetic radiation at microwave frequencies, particularly below 6 GHz. Thus, microwave thermal radiation can be detected up to a few centimetres since penetration depth is in the same order of the radiation wavelength [
6].
However, a significant difference is still noticed between the radiated energy at the infrared and microwave ranges. The radiation intensity at microwave frequencies is considerably lower than the one at the infrared spectrum, and close to detection limits [
5]. Therefore, a very sensitive receiver is required to detect the tiny power levels naturally radiated from biological tissues.
MWR systems proposed for medical applications have been commonly implemented following a Dicke topology, using a switch at the input [
9,
24,
25,
26,
27,
28,
29,
30,
31,
32]. The incoming signal is, therefore, periodically switched with a known reference, providing a differential output of the detected signals in correspondence to each input. These systems usually provide long-term continuous measurements in which gain and noise fluctuations are removed by selecting an appropriate switching frequency.
Alternative solutions for biomedical applications based on pseudo-correlation topologies can be implemented [
33]. This configuration is typically employed on astrophysical instrumentation [
34,
35,
36] and presents an improved performance. The system offers a simultaneous observation of two signals with a smaller dependence on gain fluctuations [
37], a longer observation time, as well as higher stability. The receiver should be calibrated to convert the input power to temperature and remove gain fluctuations to provide a continuous output signal during a long-term period of time.
Significant differences are found between astrophysical and medical applications. A narrow input dynamic range is required to measure body temperatures at short distances [
26], opposite to the large bandwidths and huge distances relevant in astrophysical applications. MWR systems can be designed using commercial off-the-shelf (COTS) components that reduce the size of the receiver. In addition, long and continuous observation times are employed on astrophysical instrumentation to improve the minimum detectable temperature or sensitivity, enabling the detection of faint radio sources [
1]. Thus, the receiver requires periodical calibrations to overcome and correct fluctuations on the receiver noise temperature and gain.
Although this effect is also important and calibration is required for MWR receivers aimed at biomedical applications, instantaneous measurements should be performed to avoid patient discomfort due to extended examination times. For these reasons, a new receiver configuration is required to provide a reduced contribution to the total noise temperature as well as additional output signals to calculate drift effects and recalibrate its response.
In this context, the final goal is to define a clinical workflow for diabetic foot neuropathies in which superficial and internal temperature measurements are combined. Initially, an infrared sensor acquires images from the skin surface [
38,
39,
40], providing the superficial temperature. Subsequently, after image processing, anomalous temperature patterns are detected over specific areas, in which MWR is employed to provide complementary in-depth measurements for further analysis [
33]. Thus, a MWR system able to detect significantly small radiated power differences from tissues is required, while adding the lowest achievable noise contribution.
The measured temperature is derived from the system calibration, which requires the extraction of the receiver response curve and the correction of any drift on its performance. The proposed system is dedicated to providing clinical practitioners a diagnostic tool to improve their capabilities, which, in combination to already established technologies, may provide significant advances in monitoring the targeted pathologies. In this particular case, the proof-of-concept technology provides a diagnostic tool intended for diabetic foot neuropathies [
16,
41], although other soft tissue pathologies, in which diagnosis, detection, and monitoring based on temperature measurements, can be targeted.
The diagnosis of lung complications derived from COVID-19 disease is also supported by internal measurements yielded by a MWR system [
42]. The microwave system supplies internal temperature measurements of body tissues, which complements the superficial measurement given by infrared sensors [
43]. MWR has already demonstrated a significant detection improvement when applied to diabetic patients, with satisfactory sensitivity and specificity rates [
16], and new approaches are being modelled to early detect foot ulcers [
41]. Thus, potential risks can be detected prior to a visible sign on the skin surface or irreversible damage is caused.
This paper is focused on the design of a new receiver configuration based on a pseudo-correlation type radiometer for a medical application, particularly diabetic foot neuropathies. The aim of the proposed balanced topology is to provide measurable detected signals to correct drifts in its performance, and to simultaneously reduce the noise introduced by the receiver. Thus, the main advantage is the possibility to obtain an unknown input temperature after the initial calibration is performed, employing the set of signals provided by the receiver, adjusting the calibration and correcting its drifts during the measurement. The output signals are proportional to the input ones and, simultaneously, to the combination between them, using 180 hybrid couplers together with power splitters.
Then, the analysis of this set of signals provides additional information to extract the noise contributions of each component in the receiver chain and possible fluctuations in the output signals that can be subsequently corrected. The receiver is designed using commercial COTS measured microwave devices and custom designs with electromagnetic simulations of hybrid couplers and power splitters. The proposed receiver is centred at 3.5 GHz for comparison to a previously implemented pseudo-correlation radiometer [
33]. Additionally, at this frequency, a reasonable compromise is achieved between the spatial resolution and depth measurements in lossy tissues, as well as less electromagnetic interferences than at lower frequencies [
28].
2. Background Overview of MWR Systems for Medical Applications
MWR systems are intended to detect very small temperature variations in subcutaneous layers. Thus, the radiometer should be configured to provide high sensitivity, low noise, and low gain drift for a continuous measurement [
9]. In addition, the operation frequency of the receiver should be low enough to provide a penetration depth of several centimetres into tissues [
6].
The Dicke topology has been typically employed in MWR systems for biomedical applications [
9,
24,
25,
26,
27,
28,
29]. They have been designed using COTS components, centred at diverse frequency bands and focused on monitoring internal body temperatures of a single tissue or a stack of tissue layers.
Figure 1 illustrates the commonly implemented configuration, in which a switch located at the antenna output alternates the incoming signal with a single- [
28] or two-reference load [
9,
26].
Thus, a two-level half-cycle output signal of the sequential input measurements is provided at the output port of the receiver. This topology is able to remove gain fluctuations by appropriately selecting the switching frequency [
34]. Then, the receiver is calibrated at the sample rate defined by the switching signal, since the receiver periodically measures a known input signal and corrects the drifts in its response. The amplification stage should be designed considering the detectable power window at the detection stage, as well as the low noise power level radiated from body tissues. The noise power radiated from an object in the microwave spectrum is approximated by Rayleigh-Jean’s law and expressed as
where
k is the Boltzmann constant,
T (K) is the temperature, and
B (Hz) is the effective bandwidth. Then, an equivalent power of around −174 dBm/Hz is radiated from body tissues at a temperature of 310 K (37
C).
The analysis of the Dicke receiver shown in
Figure 1 provides two alternating half-cycle detected output signals, expressed as
and
where
C is a proportionality constant,
G is the gain of the receiver,
k is the Boltzmann constant,
B is the effective bandwidth,
Tant is the noise temperature measured by the antenna,
Tref is the noise temperature of the reference load, and
Trec is the equivalent noise temperature of the receiver, which is calculated as
where
TLNA1 and
TLNA2 are the equivalent noise temperatures of
LNA1 and
LNA2 with gains
GLNA1 and
GLNA2 respectively.
LSW,
LBPF1, and
LBPF2 are the losses of the switch,
BPF1, and
BPF2, respectively, all at a physical temperature
Tph, equivalent to the ambient temperature.
Dicke radiometers cancel gain fluctuations in the system for a sufficiently high modulating frequency [
34], despite the radiometric sensitivity being degraded since the target is only measured half of the time [
44].
A Dicke configuration is not unique for biomedical applications. Other commonly used schemes implemented in astrophysical instrumentation, such as correlation or pseudo-correlation topologies [
34,
35], can be applied [
33]. The main advantage of correlation schemes is to avoid the input switch to alternate between signals. A correlation radiometer multiplies different input signals coming from antennas employing identical receivers connected in parallel and providing a single correlated output [
45]. The pseudo-correlation radiometer combines the comparison with a reference load from the Dicke radiometer with the combination of signals from the correlation radiometer but providing additional output signals [
36].
Using the latter topology, a simultaneous observation of two voltage signals, antenna and reference load inputs, are available during the measurement process, providing a continuous output voltage proportional to the difference between the two input signals [
33]. In addition, a higher stability, voltage sensitivity, and observation time are improved in comparison to the Dicke scheme [
36,
37,
46]. Finally, correlation techniques reduce the impact of intrinsic gain and noise temperature fluctuations in comparison to conventional configurations [
47].
Table 1 lists some microwave radiometers employed for biomedical applications for comparison purposes. Simulation results based on real measurements are compared with other MWR systems, and a significant noise temperature reduction is observed with the proposed new configuration.
From a simplified analysis of the scheme proposed in [
33], which considers a perfect isolation between hybrid coupler ports and avoids mismatching effects, two in-phase voltage signals are provided at output ports prior to combining them. These are proportional to the individual incoming signals at the reference load and the antenna ports, respectively [
33].
For the calculation of the equivalent noise temperature of the pseudo-correlation receiver,
Trec2, identical subsystems are considered in both branches, which means that, for example, the noise of the amplifiers are equal in magnitude, although they are not correlated [
48]. Thus, it is expressed as
-4.6cm0cm
where
TLNA1i is the equivalent noise temperatures,
GLNA1i is the gains of each
LNA1i (with
i = 1, 2, 3), and
Li is the losses associated with band-pass filters (
i =
BPF1j, with
j = 1, 2, 3) or 90
hybrid couplers (
i =
H90j, with
j = 1, 2), respectively, all of them at a physical temperature
Tph, equivalent to the ambient temperature.
5. Discussion
The described receiver presents an improved configuration in terms of noise temperature as compared with previously described systems aimed at biomedical applications. As noticed in the noise temperature equations, the main contribution was due to the low-noise amplifiers, placed at the front part of the receiver. Then, the contribution to the receiver noise of the input hybrid coupler and subsequent components in a pseudo-correlation topology were minimized by the gain of the first amplifier. Considering the Dicke configuration, the switch located at the antenna output introduced losses to the receiver, degrading the overall system noise temperature. Furthermore, the sensitivity of the receiver was also improved, since the object under test was measured during the whole observation time.
The proposed configuration focused on instantaneous measurements of body tissues; however, long-time operation of this kind of receiver involves a periodic calibration to avoid drifts in the receiver performance. The presented radiometer enables the end user to correct receiver drifts after a single calibration employing the set of output signals provided. The receiver is initially calibrated, and then, for further tests, it could remain switched on. Although the receiver could suffer from amplitude, phase, and noise temperature drifts, these could be corrected using the described method by employing the set of outputs.
The LNAs employed in the receiver were the model TAMP-362GLN+ from MiniCircuits [
51,
54], and its performance can be analysed using the data provided by the manufacturer. According to these data, typical gain and noise figure drifts lower than 0.008 dB/K and 0.004 dB/K, respectively, are expected for measurements performed at ambient temperatures of 233.15, 298.15, and 358.15 K. The radiometer presented is focused on biomedical applications, in which the measurement scenario is under controlled ambient temperature conditions, since it is a mandatory requirement for human body tissues characterization. Thus, the LNAs will be employed under small changes in the ambient temperature, and thus their drifts in gain or noise are expected to be small. In addition, the drifts in the LNAs performance are considered to be in the same way for the all units regarding the manufacturer’s data.
Noise, gain, or phase drifts can occur in any component of the receiver branches. The measurement of the antenna temperature is accurate when these changes occur proportionally for each pair of amplifiers, as the most critical subsystems, without imbalance between branches, that is, their responses vary in the same way. This means that an increase in the operating temperature would produce the same gain reduction, noise increase, or phase drift, respectively. Then, the initial calibration would be still valid, whereas the real-time measurements of αmed and Trec3med avoid a large error. Applying the proposed method and avoiding any gain or noise drift, the error in the antenna temperature is lower than 0.05 K.
On the other hand, a change up to 3 dB in the gain for both branches simultaneously would imply an error lower than 0.5 K in the antenna temperature using the initial calibration and real-time measurements. In addition, a gain or noise difference between amplifiers connected to antenna and reference ports can be corrected during the real time measurement, and the obtained error is below 1 K for a 0.5 dB gain imbalance. However, a gain imbalance of the amplifiers in the branches between 180 hybrid couplers provides relative errors larger than 1 K if it becomes greater than 0.2 dB during the simulations.
For phase drifts up to 4 between the branches between the couplers, an error of 0.6 K is obtained in the value of the antenna temperature. However, through the values obtained for the output powers PV1 and PV4, the imbalance can be evaluated to perform a new calibration. Therefore, by simply evaluating the power splitter outputs, different drift responses in each amplifier would imply that the radiometer should be calibrated again. Finally, further research will be performed after fabrication, assembly, and experimental characterization of a set of multifrequency radiometers designed with the proposed topology.
The limitations of the described configuration involve more devices compared with the Dicke receiver. This higher amount of COTS and custom designed components for the radiometer requires a precise and careful assembly. In addition, the receiver requiers the design of 180 hybrid couplers with balanced amplitude and phase responses. These circuits are typically commercially available in coaxial connectors. However, they do not allow a high level of integration and compactness of the radiometer, so a dedicated microstrip design is employed.