EP4629885A1

EP4629885A1 - System and method for biological deep-tissue imaging

Info

Publication number: EP4629885A1
Application number: EP23900190.2A
Authority: EP
Inventors: Avraham SCHROEDER; Ravit ABEL; Yonina Eldar; Yonathan EDER
Original assignee: Technion Research and Development Foundation Ltd; Yeda Research and Development Co Ltd
Current assignee: Technion Research and Development Foundation Ltd; Yeda Research and Development Co Ltd
Priority date: 2022-12-08
Filing date: 2023-12-07
Publication date: 2025-10-15
Also published as: WO2024121852A1

Abstract

A system and method is presented for imaging a biological tissue, marked by metal particles, in at least one region of interest in the biological tissue. The system comprises: a frequency modulated continuous wave (FMCW) transceiver system comprising at least one radiation transmitter and at least one radiation receiver, the FMCW transceiver being configured to transmit series of millimeter wavelength signals to interact with each of said at least one region of interest and receive radiation originated within a field of view of the transceiver, and generate raw measured data indicative of received radiation; and a control system configured and operable to receive and process said raw measured data, the processing comprising extracting from said raw measured data, data indicative of radiation response of said metal particles to said interaction with the millimeter wavelength signals for each of said at least one region of interest, and determining map data indicative of a distribution of said metal particles within each region of interest.

Description

SYSTEM AND METHOD FOR BIOLOGICAL DEEP-TISSUE IMAGING

TECHNOLOGICAL FIELD AND BACKGROUND

The presently disclosed subject matter is in the field of imaging techniques and relates to a method and system for biological tissue imaging.

Deep-tissue imaging enabled by tracking specific compounds in the human body plays an important role in medicine, particularly for performing safe and precise diagnostics and therapeutics. However, penetration of biological and physical barriers, such as the cranium, with noninvasive radiation is challenging. Widespread imaging methods enabling penetration of biological and physical barriers include magnetic resonance imaging (MRI), computed tomography (CT) and ultrasound-based imaging. The known methods of metallic nanoparticle tracking and imaging that can penetrate well into deep tissues are MRI and CT. However, a CT scan is performed with ionizing radiation which causes damage to healthy tissues and genetic materials. Though magnetic resonance imaging (MRI) does not employ ionizing radiation, this and the abovementioned imaging methods require the patient to lay still inside a magnetic coil, from several minutes to over an hour, and necessitate a well-trained staff for performing the scan, as well as specialized physicians to analyze the raw data obtained thereof.

Another medical imaging approach is ultrasound which transmits sound waves. However sound waves, while safe, do not travel well through relevant media, such as bone tissue and air (comprising many bodily cavities). This also limits the distance of the scanned object from the ultrasound probe and requires direct contact of the probe with the body part or a few centimeters of proximity. In all the above-mentioned approaches, only one person and one area of the body can be scanned simultaneously. GENERAL DESCRIPTION

There is a need in the art for a new imaging technique allowing effective deep tissue imaging.

The present disclosure presents a novel technique for noninvasive deep-tissue imaging by tracking metallic nanoparticles in the biological tissue using mm-wave based imaging (radar-based imaging). Preferably, the metallic nanoparticles are gold nanoparticles (GNPs), e.g. spherical GNPs, e.g., 5 nm diameter GNPs.

Gold nanoparticles (GNPs) are FDA-approved particles for various therapeutic applications and are considered safe due to their biologically inert nature. For example, utilizing GNPs’ tendency to accumulate in tumors and inflamed tissues is considered to improve the diagnosis, detection and treatment of diseases, such as cancer and Alzheimer’s. GNPs are characterized by high cell uptake, by conjugating to a specific antibody that may be engineered to accumulate in a desired tissue or cell population. GNPs also gained interest in their ability to cross the blood-brain barrier (BBB) which prevents compounds including most of the known drugs from reaching the brain. Hence, they have the potential to improve brain therapy. GNPs are easy to conjugate to the surface of drug delivery systems. Tracking GNPs will allow evaluation of the location and concentration of a conjugated drug or device inside the human body serving as a conjugated marker to improve imaging guided drug therapy.

The present disclosure, in some of its aspects, provides a new methodology for remotely localizing and tracking GNPs in various therapeutic settings, including through biological tissues, using a compact millimeter wave radar system. The technique of the present disclosure provides, by appropriately modeling the problem, for localizing GNP concentrations, as well as high sensitivity for detecting changes in concentrations that relate to changes in the intensity of the reflected signals. This technique provides a noninvasive, non-ionizing, simple approach for bioimaging and tracking of GNP inside the body.

Radars are common in use in the vehicle industry and lately have gained interest in medical monitoring and imaging applications. The injection of GNPs for medical purposes is FDA approved, as well as the use of radar for monitoring and scanning humans.

A radar may be configured as a hand-held electronic device with transmitting and receiving antennas. It transmits nonionizing electromagnetic waves in the millimeter range. When a wave hits an object, it creates reflected/scattered waves (generally, object's response to interaction with radar radiation) that can be detected by the radar's receiving antennas. The radiation response carries information about the objects. A radar wave can reach objects through physical barriers such as walls and skulls.

The present disclosure provides a new method to detect GNPs in tissues, using radar radiation. The inventors have found a correlation between signals received by radar, and being indicative of the radiation response of the object, to the presence and concentration of GNPs enabling detection and location of GNPs in a tissue. Thus, this method allows detection of nanoparticles based on non-ionizing radiation from a radar device and imaging a region of interest "marked" by the presence/ distribution of GNPs, enabling improved and simple diagnostic and precision medicine.

According to one broad aspect of the technique of the present disclosure, it provides a system for imaging a biological tissue, marked by metal particles, in at least one region of interest in the biological tissue. The system comprises: a frequency modulated continuous wave (FMCW) transceiver system comprising at least one radiation transmitter and at least one radiation receiver, the FMCW transceiver being configured to transmit series of millimeter wave signals to interact with each of said at least one region of interest and receive radiation originated within a field of view of the transceiver, and generate raw measured data indicative of received radiation; and a control system configured and operable to receive and process said raw measured data, the processing comprising extracting from said raw measured data, data indicative of radiation response of said metal particles to said interaction with the millimeter wave signals for each of said at least one region of interest, and determining map data indicative of a distribution of said metal particles within each region of interest.

In some embodiments, the control system comprises a localization module configured and operable to process data indicative of the raw measured data and extract therefrom said map data indicative of the radiation response of said metal particles, for each of said at least one region of interest.

In some embodiments, the control system also comprises a pre-processor configured and operable to pre-process the raw measured data to obtain said data indicative thereof on the form of a data matrix Y of the received signals by all of said at least one receiver over transmitted signals per frame. The localization module may thus be configured and operable to recover, from the matrix Y, a matrix X containing complex amplitudes of the received signals and thereby determine the map data.

The metal particles preferably include nanoparticles. The metal particles preferable include gold particles, and even ore or preferably gold nanoparticles (GNPs), e.g., of an average size of 5 nanometers.

In some embodiments, the FWCM transceiver system is configured and operable to utilize, for each of said at least one receiver, a single-channel front end thereof, said measured data being in the form of a data matrix indicative of consecutive beat signals.

According to another broad aspect of the technique of the present disclosure, it provides a method for imaging a biological tissue, marked by metal particles, in at least one region of interest in the biological tissue, the method comprising: transmitting series of millimeter frequency modulated continuous wave (FMCW) signals towards the tissue to interact with each of said at least one region of interest and receiving radiation returned from the tissue, and generating measured data indicative of received radiation; and processing said measured data, the processing comprising: extracting, from said measured data, data indicative of radiation response of said metal particles to said interaction with the millimeter wave signals for each of said at least one region of interest, and determining map data indicative of a distribution of said metal particles within each region of interest.

The metal particles may be introduced into the biological tissue through drug intake via a drug delivery system, e.g., comprising at least one of the following: liposomes, lipids nanoparticles, polymers. In some embodiments, the metal particles operate as a drug delivery system bringing one or more drugs to the region of interest, thereby enabling to monitor the drug effect on the region of interest via imaging of the map of the distribution of the metal particles.

In some embodiments, the metal particles are introduced into said biological tissue through injection.

As noted above, the metal particles preferably include nanoparticles, which are preferably gold nanoparticles (GNPs), e.g., of an average size of 5 nanometers. The region of interest being imaged may be a brain region.

In some embodiments, the map data of the distribution of the metal particles in the region of interest may be used to guide photodynamic and/or photothermal treatment of the region of interest.

BRIEF DESCRIPTION OF THE DRAWINGS

Fig. 1 shows, by way of a block diagram, the system of the present disclosure;

Fig. 2 shows the main components of the FMCW radar suitable to be used in the system of Fig. 1;

Fig. 3A is a flow diagram describing the method of measuring a 2D image of a region of interest using the technique of the present disclosure;

Fig. 3B shows schematically the exemplary method of the present disclosure in which 200 frames are averaged in 10 sec to obtain the final 2D image of the region of interest;

Fig. 4 shows a transmission electron microscopy (TEM) image of 5 nm GNPs used for injection to an ex vivo cow brain on a carbon film on a copper grid;

Fig. 5A exemplifies the system setup for measuring 4 ml glass test vial with 5 nm GNPs with a radar transmitted horizontally towards the upright glass test vial;

Fig. 5B exemplifies the system setup for measuring the same 4 ml glass test vial as in Fig. 5A wherein the radar is transmitted vertically towards the lying glass test vial, attached to the upper part of a Styrofoam platform;

Fig. 5C exemplifies a schematic setup of the scanning radar, wherein the radar is horizontally transmitted towards a silicone test tube inserted into the center of an ex-vivo cow brain;

Fig. 5D shows a photo of a cow's brain injected with the GNPs and scanned by the radar;

Figs. 6A to 6F show range angle and normalized magnitude estimations vs. GNP concentrations for experiments #2 (Figs. 6A to 6C: glass vial) and

#5 (Figs. 6D to 6F: cow brain), respectively. The dashed red lines and black vertical lines respectively denote the search boundaries and the transitions between different GNP concentrations;

Figs. 6G to 61 show the effect of different GNP concentrations on the normalized magnitude estimations for experiments #2 (Fig. 6G), #5 (Fig. 6H) and for all 5 u l experiments (Fig. 61); notations: ns: no significant difference, *: p < 0.03,** : p < 0.02,*** : p < 0.002, ***: p < 0.0001, calculated by one-way ANOVA and Dunnett test;

Figs. 7A to 7F show normalized range-angle maps showing the absolute values of X_; for 1=1 of each of the following trials (concentrations in [nM]): Fig. 7A: u=l (0), Fig. 7B: u=6 (0.04), Fig. 7C: u=l 1 (0.2), Fig. 7D: u=16 (1), Fig. 7E: u=21 (5), Fig. 7F: u=26 (25).

Figs. 8A shows the magnitude of the reflected signal from cow’s brain before and after 1^st and 2^nd 5 nm GNPs injection of 250 mL at a concentration of 90.8 nM, normalized to the magnitude of a detected brain without any injection. ** denotes p<0.01, *** denotes p<0.001; and Figs. 8B to 8D show three spatial mappings of the cow's brain irradiated with the radar in which the brain is recognized and localized (marked in x). The x-axis represents the angle in degrees between the radar and the objects and the y-axis represents the distance in meters. The three maps correspond, respectively, to scans of the brain before any injection (Fig. 8B), and after 1^st (Fig. 8C) and 2^nd (Fig. 8D) injections of 250ul 5nm GNPs, 90.8 nM.

DETAILED DESCRIPTION OF EMBODIMENTS

Reference is made to Fig. 1 showing by way of a block diagram a system 100 configured and operable according to the technique of the present disclosure for noninvasive imaging of biological tissues, e.g., in a body part of a subject. According to this technique, the tissue in the region of interest is marked by introduction (e.g., injection or drug intake) of metallic nanoparticles in the tissue, and the imaging utilizes radar radiation for tracking the nanoparticles. Preferably, the nanoparticles are gold nanoparticles GNPs. The system 100 includes a frequency modulated continuous wave (FMCW) radar system 10, and a control system 12.

As shown in Fig. 2, the radar system 10 operates to transmit radiation towards a zone including one or more regions of interest - one such region of interest ROI (e.g., brain region) being shown in the figure, and receive a response radiation from said zone within the field of view FOV of the radar. The FMCW radar 10 may be of any known suitable configuration, i.e., may include any antenna setup, including at least one signal transmitter Tx producing at least one transmitting signal in which the frequency varies linearly with time, and one or multiple signal receivers Rx receiving signal responses from the irradiated zone. As shown in the figure, a baseband signal is obtained from a mixer which mixes the transmitted signal and the received scattered signal to create what is termed an intermediate frequency (IF) signal or a beat signal. The beat signal is a signal formed by a conditioning circuit, which includes an anti-alias (low pass) filter LPF and an amplifier (not shown), and is then sampled by an analog to digital converter ADC and processed by a digital signal processor DSP to assemble the output data.

Traditionally, FMCW radar receivers use both an in-phase (I) and a quadrature -phase (Q) channels in their receivers. Using both channels allow forming I and Q components of the received signals to generate a beat signal which includes both phase and amplitude data without a loss of information. The technique of the present disclosure may utilize such traditional approach, or may in some embodiments, utilize only a single channel of the receiver, e.g., the In-phase (I) beat signal, thus reducing processing times and avoiding the complications related to combining the two channels. The latter is associated with the following: I/Q imbalances are known to occur due to mismatches between the parallel sections (or channels) of the receiver chain providing the I and the Q signal paths, while the lack of perfect orthogonality and difference in gain levels in each channel might corrupt the desired information to be extracted.

Turning back to Fig. 1, the output data provided by the radar system is measured data MD indicative of the received radiation response. This measured data MD is received and processed by the control system 12.

The control system 12 is typically a computerized system which is in signal/data communication (via wires or wireless communication of any known suitable type) with the radar system 10. The control system includes inter alia data input and output utilities (not shown), memory 14, and a processing utility 16. The processor utility 16 is configured and operable to receive and process the measured data MD and determine a 2D map of signal powers received from the nanoparticles' containing region of interest.

The processor unit 16 is configured according to the technique of the present disclosure and includes a pre-processing module 18 and a localization module 20. The pre-processing module 18 receives the measured data MD from the radar and performs an averaging of a predetermined number of frames to increase SNR. In addition, the pre-processing module 18 constructs the required matrices for signal processing based on parameters stored in the memory 14.

The localization module 20 is configured and operable to localize each region of interest, using any known in the art suitable technique, e.g., such reconstruction method as Gradient Descent method. Once the objects (regions of interest) within the field of view of radar are localized, the processor unit 16 generates data indicative of the average power of the reflected radar signals at each pixel. By this, map data (2D or 3D map) of the nanoparticles' distribution in the region of interest is determined.

Reference is made to Fig. 3A showing by way of a flow diagram 300 the exemplary method of the present disclosure. The region of interest (ROI) is marked by injection of nanoparticles (e.g., GNP) in step 302. Then, measuring / imaging session is performed by irradiating the region of interest by radar radiation and detecting the radiation response thereof, including reflected signals from the nanoparticles (step 304), providing corresponding measured data. More specifically, the input data (beat signals) are obtained from in-phase channels of FMCW radar by sending consecutive chirps (e.g., 200) for L frames (one chirp per frame) and measuring the beat signals (with N samples per chirp). This constitutes the measured data MD entering the processing unit 16.

At each predefined time interval Tint, the input data (measured data MD) is pre-processed to assemble a data matrix Y by averaging the fast-time row samples of each G chirps to increase SNR (step 306). A matrix X containing the complex amplitudes of the beat signals is recovered from the matrix Y (step 308) using any known in the art suitable technique, e.g., such reconstruction method as Gradient Descent method.

In the next step 310, the map of signal power as a function of radial distance and azimuth angle for each localized region of interest is extracted. Finally, the data are presented as an intensity map where the radial distance and azimuth angle of each localized region of interest with respect to the radar is indicated with the color indicating the power of the detected signal at the respective pixel, as shown in Fig. 3B.

In the following, an exemplary method of signal processing of the reflected radar signals by the nanoparticles inside the tissue is presented. A typical linear FMCW radar transmits L frames of a saw-tooth waveform at each given time frame, called chirp, whose frequency linearly increases over time. The chirp signals are propagating towards a solution containing a GNP concentration, regarded as an object at a distance do and azimuth angle θ₀ relative to the radar antennas. The reflected echo signals are mixed with versions of the transmitted ones to obtain analog base-band signals, called beat signals, with attenuated amplitude xo corresponding to the radar-cross-section (RCS) of the measured GNPs. For each frame, the beat signals are sequentially sampled by the ADC (Analog to Digital Converter), resulting in discrete signals of length N. The FMCW radar is based on a SIMO (Single Input Multiple Output) Uniform Linear Array (ULA) with a single transmitter and K receivers spaced by (1) where /. denotes the chirp's maximal wavelength.

Ideally, to measure a single object at angle θ₀ and distance d₀ (here, the GNP concentration), one can employ the standard signal model: for n = 1, ... ,N fast-time samples, k = 1, ... , K receivers, and I = 1, ..., L slow-time frames. Tf denotes the ADC sampling interval and f₀ is the beat frequency which satisfies where c denotes the speed of light and is the rate of the frequency sweep of each chirp, with B and T_c respectively being the chirp's total bandwidth and duration. Since in the present disclosure static aggregates of GNPs are measured, changes in motion along the slow-time axis I are negligible; thus i^s considered as phase noise. It is noted that the received amplitude, distance, and angle are unknown in advance.

However, in realistic indoor environments, the received signal is affected by background noise as well as reflections from clutter in varying angular and radial positions. Hence, the extended model for a general case of Q > 1 objects in the radar's FOV is given by where {w[n, I, k]} is a 3-D sequence of zero mean i.i.d. complex Gaussian noise with variance σ².

The received signal is comprised of Q components where the q'th component is defined by four parameters: a constant amplitude x_q, related to the RCS of the q'th object, a beat frequency fq which is proportional to the q'th object's radial distance d_q by an azimuth angle θ_q and a phase noise Assuming that each object has a distinct pair of distance and angle, the model in Eq. (3) can be rewritten for M general radial distances and P general azimuth angles as follows: where each (m, p} component is associated with reflection from a different pair of distance and angle, including reflection from the GNP concentration, as the component in Eq. (2). Based on the latter, x_{m p} denotes the beat amplitude of the {m, p}'th component, which can be zero if there is no reflection and includes the unknown amplitude of the GNP concentration, x₀.

Each frequency f_m is distinct and proportional to a different radial distance from the radar cZ_m. where the unknown distance d₀ is among the distances

The slow-time (along the successive frame time scale) varying phase °f each component is given by:

The model considers a total of P possible azimuth angles d in the following phase shifts due to the ULA antenna geometry: where the unknown angle θ₀ is among the angles

The slow-time varying complex amplitude is defined as For each frame I the samples of from Eq. (4) can be assembled into NxK matrix , which satisfies: (9)

Where is a Vandermonde matrix, whose entries are given by A(n, m) = whose entries are given by s the unknown matrix of complex amplitudes which satisfy is the noise matrix where

To examine the effect of varying GNP concentrations on the parameters , the inventors perform U independent trials as a function of concentration. In each trial, L frames of chirps are transmitted toward a known GNP concentration. Hence, the following assumptions are made for every trial u = 1, ... , U ;

A-1 The parameters are constant in all L frames.

A-2 The number of components This means that each X a Q-sparse matrix.

A-3 The GNP reflection is the strongest among all other objects in the radar's FOV. trials, and thereby track their values for varying GNP concentrations.

The signal processing operates to recover in order to locate the desired object and analyze the average power across experiments.

The solution consists of two stages. In the first stage, a pre-processing stage, the chirps are averaged, and the matrices A and B are constructed.

It is assumed that the fast-time frequencies lie on the Nyquist grid, i.e., (10) where ' is determined by the ADC component. Using Eq. (10) and the definition above allows to construct the A matrix as Then, it is possible to construct matrix B by using Eqs. (7) and (1) and assuming that the angle grid of the radar is covering FOV of 180 degrees: where A_θ denotes the spacing of the angle grid. Using Eqs. (7) and (11) and since, as defined above, it follows that:

In the following, the amplitude (x), the range (d) and the angle (θ) of the GNPs signals are estimated.

Based on A-l, the inventors start by coherently integrating the measurements (Eq. (9) to increase the signal-to-noise ratio (SNR), i.e., the average matrix is defined by the element- wise averaging which according to Eq. (9) satisfies (12) sparse matrix. Hence, it is recovered from Y using the following optimization problem:

Here, to promote the sparsity in X the inventors use the regularization parameter y > 0 and the mixed norm defined as the sum of all absolute values of X. Here, Eq. (13) is solved using the fast iterative soft-thresholding algorithm (FISTA), and the support S is found by selecting the Q largest magnitudes of X. It is noted that predetermined boundaries of range and angle, which serve as a region of interest (ROI), can aid in evaluating S, which finds Q pairs of 2D {m, p] coordinates. It is further noted that the magnitudes of X form the range-angle localization map.

Using S, the amplitudes of the detected objects are estimated by the Least-Squares (LS) solution, which by the Vandermonde structure of A can be written as are respectively the m'th row of a partial DFT matrix and the p'th row of B (Eq. (9)) corresponding to the q'th element of S. Finally, based on A-3, the estimated amplitude of the GNP is selected by

Based on the selected pair of S, the m'th index corresponds to the estimated radial distance d₀ through Eqs. (5) and (10) while the p'th index corresponds to the estimated azimuth angle via Eq. (11).

In the following, the technique of the present disclosure used for bioimaging and tracking metallic nanoparticles is demonstrated.

The inventors used Texas Instruments IWR1642 76 to 81 [GHz] mm-wave radar sensor for transmitting frequency-modulated continuous wave (FMCW) signals and analyzing the received echoes, utilizing its ULA configuration of a single transmitter (TxO) and K = 4 receivers (RxO — Rx3). The main radar parameters for assembling the samples in Eq. (9) were set as follows: λ = 3.89 [mm], which corresponds to a center frequency of 77[GHz], T_c = 57[/rs] and S = 70 , which corresponds to a bandwidth of B ≈ 4[GHz], and f_ADC = 4[MHz], with selected N = 200 and M = N /2 = 100. Each 10-second trial u consists of L = 200 transmission frames of length 50 [ms], with 100 consecutive chirps per frame, coherently summed to increase the SNR. The parameters for solving Eq. (13) using FISTA were set to y = 1e4, with Lipschitz constant and maximum number of iterations equal to 1e7 and 1000, respectively. The range and angle search boundaries for evaluating S were selected as [0.17 0.5] m and [—40 40]deg, respectively. Finally, the angle grid spacing was set to Δ_θ = 1 (Eq. (11)).

The reflected waves were used to extract information about the distance and the angle of objects in the radar scanning area based on the signal processing procedure detailed above. The extraction of both distance and azimuth angle results in 2-D maps that contain valuable information about the radar scanning area that can be utilized to track GNPs.

Reference is made to Fig. 4 showing a transmission electron microscopy (TEM) image of 5 nm GNPs used in the experiments, on a carbon film and on a copper grid. The scale bar on the right side of the figure measures 20 nm. GNPs were purchased from Cytodiagnostics Inc. (Canada) and dissolved in double distilled water to mimic GNPs in a biological aqueous environment.

The inventors performed a total of 5 experiments, each comprising U=30 independent trials of 10 seconds, divided into 6 segments of 5 repetitions. In each segment, the transmission was performed towards a different GNP concentration (0.04, 0.2, 1, 5, and 25 nM). In experiments #1 and #2, the radar was placed on a table at a distance of ~20 cm horizontally from a 4 ml cylindrical glass test vial, as shown in Fig. 5A. In experiments #3 and #4, the inventors assembled a Styrofoam platform in which the radar was placed at a distance of ~35 cm beneath a similar glass vial, attached to the upper part of the platform so that vertical upward transmission is carried out, as shown in Fig. 5B.

To examine the ability to detect GNPs through complex biological tissues, the inventors used an ex- vivo cow brain in experiment #5, where the radar was placed on a table at a distance of ~20 cm horizontally from a 3 mm silicon test tube, inserted into the center of the brain to simulate a blood vessel, as shown in Figs. 5C. In all the experiments, the inventors directed the radar towards the center of the GNP concentration, i.e., at an azimuth angle of approximately 0 deg relative to the radar antennas.

In the following the inventors show the estimated variables from Exp.

#2 (of a glass vial), from Exp. #5 (of a cow brain) and a summary bar plot of all 5 experiments. In addition, the inventors depict the range-angle maps showing the absolute values of X (Eq. (13)) from Exp. #2, for trials of different concentrations to show how the maps change accordingly.

Reference is made to Figs. 6A to 6F show range angle and normalized magnitude estimations vs. GNP concentrations. This is shown for experiments #2 (Figs. 6A to 6C: glass vial) and #5 (Figs. 6D to 6F: cow brain), respectively. In the figures, dashed red lines L_r and black vertical lines Lb respectively denote the search boundaries and the transitions between different GNP concentrations. Figs. 6G to 61 show the effect of different GNP concentrations on the normalized magnitude estimations ( for experiments #2 (Fig. 6G), #5 (Fig. 6H) and for all 5 experiments (Fig. 61). In the figures, "ns" means "no significant" difference.

One can observe in Figs. 6A and 6B (Exp. #2) and Figs. 6D and 6E (Exp. #5) that both the range and angle estimates remain stable across trials and correspond to the position of the GNPs center with negligible changes w.r.t. the resolution limitations: 0_res ≈ 30 deg for K = 4 receiver elements and or a 4 GHz bandwidth. Figs. 6C, 6G

(Exp. #2), Figs. 6F, 6H (Exp. #5), and Fig. 61 (summary of all 5 experiments) track the differences in the values of normalized magnitude estimations in response to changes in GNP concentrations. The normalization is carried out by dividing by the average of the values from the water segment, for measuring the changes w.r.t. the water case. Figs. 6G to 61 depict the (±mean standard deviation) of each segment and a significance testing relative to water by oneway ANOVA and Dunnett test, with p denoting the p-value.

Three distinct phenomena can be seen in Figs. 6C, 6F, 6G, 6H and 61. First, a gradual increase in the reflected signal amplitudes (expressed in the values of due to an increase in the GNP concentration, for 0.04 — 5 nM. Second, at concentrations of 0.04 nM and 1,5 nM, respectively, the intensity of the reflections was significantly lower and higher than water (with p < 0.002 in the summarized analysis in Fig. 61). This suggests that GNPs at these concentrations may be detected in aqueous environments, found in the human body. Third, at concentrations of 0.2 nM and 25 nM, the strength of the reflections is not significantly distinct from the water case, implying that the difference from water is only evident within a restricted range of concentrations. These results show the potential of the proposed approach for long-term monitoring of the accumulation or decay of GNPs in targeted organs for improved diagnosis and treatment.

Figs. 7A to 7F show the range-angle maps (showing the magnitudes of X (Eq. (13)) from experiment #2, normalized according to the average of the values from the water segment, of each of the following trials (concentrations): u = 1,6,11,16,21,26(0,0.04,0.2,1,5,25 nM). Specifically, Fig. 7A shows u=l (0), Fig. 7B shows u=6 (0.04), Fig. 7C shows u=l 1 (0.2), Fig. 7D shows u=16 (1), Fig. 7E shows u=21 (5), and Fig. 7F shows u=26 (25). By evaluating it is possible to localize and track clusters of GNPs in varying concentrations. The red x marks the selected whose indices indicate the frame's estimated location of the GNP cluster by (range) and (angle). Changes in the color of the cluster can be seen along Figs. 7A to 7F that correspond to changes in the intensity of the reflections, as shown in Fig. 6G. Using these maps, it is possible to track clusters of GNPs in varying concentrations and locations. Figs. 8A to 8D show results of ex- vivo injections of GNP into cow's brains (refer to photo of Fig. 5D). Each brain was injected with 250pl of 90.8 nm GNPs twice, with 3 minutes between the injections. After each injection the inventors waited 1 min to let the GNPs naturally diffuse in the brain, then transmitted signals from the radar. The radar transmitted signals for 10 seconds in each activation with a frame duration of 50ms, resulting in 200 frames. The reflected echoes were received by 4 receiving antennas and analyzed by the signal processing procedure described above. The radar was activated before the injections, after the first and after the second injection, 5 times in each state.

A radar scanning of a cow's brain was performed before any injection, and after first and second injection of GNPs. Each injection and scanning period took 3 minutes. Fig. 8A shows the average power extracted from radar scans of the reflected signal from the brain before and after first and second injection of 250ul 5nm GNPs at a concentration of 90.8nM. The power shown is normalized to the power detected from a brain without any injection and the p- values (5 injections at each state) are indicated by: **p<0.01, ***p<0.001.

Figs. 8B to 8D show the corresponding 2-D spatial maps obtained using the signal processing procedure described above. The recognized location of the brain is marked with x. The green-yellow area in the maps represents the whole brain. The X axes represent the angle in degrees between the radar and objects and the Y axes represent the distance (range) in meters. The three maps correspond, respectively, to scans of the brain before any injection (Fig. 8B), and after first (Fig. 8C) and second (Fig. 8D) injections each of 250ul 5nm GNPs, 90.8mM. The maps indicate an increment in the reflected signal power in the detected brain after each injection, thereby demonstrating the novel use of the tracking of metal nanoparticles with mm-waves for bioimaging.

The novel technique of the present invention, providing detection of metallic nanoparticles in biological tissues, using radar as a noninvasive approach and without the use of ionizable radiation may find wide applications in medicine as it is a new key ability required for imaging and diagnostics.

One direct application may be in detecting GNPs in patients undergoing treatments including the injection of GNPs, such as photodynamic and photothermal treatments. Furthermore, GNPs can be conjugate to drug delivery systems such as liposomes, lipids nanoparticles, polymers, and more. In some cases, GNPs themselves are used as a drug delivery system. Tracking them will allow an analysis of each patient’s response to the treatment. By knowing where in the body a drug accumulates, whether it reached the target tissue, and how long it took, effective medical treatment can be tailored to each patient. Knowing where nanoparticles in the body are located is also an important ability for drug delivery systems with the local external triggering mechanism .

The GNPs’ ability to accumulate in cancer cells can be utilized for early detection of metastasis using the technique of the present disclosure. By injecting cancer patients with GNPs, metastasis can be found and treated. Accumulation of GNPs in a specific tissue may indicate the presence of a tumor .

Claims

CLAIMS:

1. A system for imaging a biological tissue, marked by metal particles, in at least one region of interest in the biological tissue, the system comprising: a frequency modulated continuous wave (FMCW) transceiver system comprising at least one radiation transmitter and at least one radiation receiver, the FMCW transceiver being configured to transmit series of millimeter wavelength signals to interact with each of said at least one region of interest and receive radiation originated within a field of view of the transceiver, and generate raw measured data indicative of received radiation; and a control system configured and operable to receive and process said raw measured data, the processing comprising extracting from said raw measured data, data indicative of radiation response of said metal particles to said interaction with the millimeter wavelength signals for each of said at least one region of interest, and determining map data indicative of a distribution of said metal particles within each region of interest.

2. The system according to claim 1, wherein the control system comprises a localization module configured and operable to process data indicative of the raw measured data and extract therefrom said map data indicative of the radiation response of said metal particles, for each of said at least one region of interest.

3. The system according to claim 2, wherein the control system comprises a preprocessor configured and operable to pre-process the raw measured data to obtain said data indicative thereof on the form of a data matrix Y of the received signals by all of said at least one receiver over transmitted signals per frame.

4. The system according to claim 3, wherein the localization module configured and operable to recover, from the matrix Y, a matrix X containing complex amplitudes of the received signals and thereby determine the map data.

5. The system according to any one of the preceding claims, wherein said metal particles comprise nanoparticles.

6. The system according to any one of the preceding claims, wherein said metal particles comprise gold particles.

7. The system according to claim 6, wherein said metal particles comprise gold nanoparticles (GNP).

8. The system according to claim 7, wherein said GNPs are of an average size of 5 nanometers.

9. The system according to any one of the preceding claims, wherein the FWCM transceiver system is configured and operable to utilize, for each of said at least one receiver, a single-channel front end thereof, said measured data being in the form of a data matrix indicative of consecutive beat signals.

10. A method for imaging a biological tissue, marked by metal particles, in at least one region of interest in the biological tissue, the method comprising: transmitting series of millimeter frequency modulated continuous wave (FMCW) signals towards the tissue to interact with each of said at least one region of interest and receiving radiation returned from the tissue, and generating measured data indicative of received radiation; and processing said measured data, the processing comprising: extracting, from said measured data, data indicative of radiation response of said metal particles to said interaction with the millimeter wave signals for each of said at least one region of interest, and determining map data indicative of a distribution of said metal particles within each region of interest.

11. The method according to claim 10, wherein said metal particles are introduced into said biological tissue through drug intake via drug delivery system.

12. The method according to claim 11 , wherein the drug delivery system comprises at least one of the following: liposomes, lipids nanoparticles, polymers.

13. The method according to claim 11 or 12, comprising gold nanoparticles (GNPs) conjugate with the drug delivery system.

14. The method according to claim 10, wherein said metal particles operate as a drug delivery system bringing one or more drugs to the region of interest, thereby enabling to monitor the drug effect on the region of interest via imaging of the 2D map of the distribution of the metal particles.

15. The method according to claim 10, wherein said metal particles are introduced into said biological tissue through injection.

16. The method according to any one of claims 10 to 15, wherein said metal particles comprise nanoparticles.

17. The method according to any one of claims 10 to 15, wherein said metal particles comprise gold particles.

18. The method according to claim 17, wherein said metal particles comprise gold nanoparticles (GNPs).

19. The method according to claim 18, wherein said GNPs are conjugated to antibodies.

20. The method according to claim 18 or 19, wherein said GNPs are of an average size of 5 nanometers.

21. The method according to any one of claims 10 to 20, wherein said receiving of the returned radiation is performed using one or more receivers, utilizing, for each of said one or more receivers, a single-channel front end thereof, said measured data being in the form of a data matrix indicative of consecutive beat signals.

22. The method according to any one of claims 10 to 21, wherein said processing comprises: analyzing the raw measured data and obtaining data indicative thereof in the form of a data matrix Y of the received signals by all receivers over transmitted signals per frame, and recovering, from the matrix Y, a matrix X containing complex amplitudes of the received signals and thereby determining the map data.

23. The method according to any one of claims 10 to 22, wherein said at least one region of interest is a brain region.

24. The method according to any one of claims 10 to 23, further comprising using the map data of the distribution of the metal particles within the region of interest to guide photodynamic and/or photothermal treatment of the region of interest.