# Patent

## Title
Method and system for non-invasively monitoring fluid flow in a subject

## Abstract

A fluid flow monitoring system is provided that has a processor utility which is connectable to an acoustic generator associated with acoustic ports and is operable for generating signals S0 to activate the acoustic ports for irradiating a region of interest with acoustic radiation of a certain frequency range centered at a frequency F0 and is connectable to at least one light output port associated with one or more light detectors for receiving light of at least one wavelength λ from the region of interest including light tagged by said acoustic radiation. The processor utility may be configured for analyzing the generated signals S0 and data indicative of the received light including light tagged by the corresponding acoustic radiation and determining correlation between the signals S0 and the data indicative of the received light, the correlation being informative of a measure of fluid flow in a turbid medium.

## Background
This is a Continuation in Part Application of U.S. patent application Ser. No. 12/498,045 filed on Jul. 6, 2009, which claims the benefit of U.S. Provisional Application No. 61/078,410 filed on Jul. 6, 2008. The disclosure of the prior applications is hereby incorporated by reference in its entirety.


FIELD OF THE INVENTION
The invention is generally in the field of fluid flow measurements, and relates to a method and system for monitoring fluid flow through turbid media. The invention is particularly useful for medical applications such as measuring blood flow in a subject, as well as measurement of some other blood related parameters.
BACKGROUND OF THE INVENTION
Remote monitoring of fluid flow provides utility across a wide range of industrial and healthcare applications. In medical diagnosis, treatment and monitoring, there is frequent need to measure blood flow in order to monitor tissue perfusion, metabolism and general health. This need stems from the biological requirement for transport of oxygen and nutrients to tissues and the removal of waste products (M. E. Raichle and M. A. Mintun, “Brain work and brain imaging”, Annu Rev Neurosci 2006; 29:449-476).
Existing methods for measuring biological flow include laser Doppler measures of reflected energy changes (as disclosed for example in U.S. Pat. No. 4,109,647), variation in impedance on the scalp surface (e.g. US 2008/0200787), or the use of invasive flowmeters implanted directly into the tissue (e.g. U.S. Pat. No. 5,579,774).
Various techniques for non-invasive measurements of blood related parameters have been developed. Such techniques include frequency-domain spectroscopy, and photoacoustic spectroscopy [D M Hueber et al Phys. Med. Biol. 46 (2001) 41-62].
A productive approach to non-invasive monitoring in healthcare settings is the use of ultrasound tagged light. (U.S. Pat. No. 7,541,602, WO 06/097910, WO 05/025399, all assigned to the assignee of the present application). In this method, the intersection of electromagnetic and acoustic signals has been used to monitor tissue optical properties.
GENERAL DESCRIPTION
There is a need in the art for a novel technique enabling the fluid flow measurement, such as blood flow, in a non-invasive, non-ionizing manner to limit discomfort and possible hazards to a patient.
The present invention utilizes the principles of ultrasound tagging of light to monitor flow within a turbid medium. More specifically, the tagging of light by acoustic radiation is used to determine the optical response of a region of interest in the medium, enabling determination of the flow within the region of interest from said optical response. More specifically, according to this technique, a region of interest in a subject (e.g. human body) is illuminated with light of at least one wavelength, and is irradiated with acoustic radiation (preferably ultrasound) such that the acoustic radiation overlaps the illuminated region in at least a part of the region of interest (this overlapping volume is termed “tagged volume”). Light scattered from the subject's body, including photons that are tagged by the acoustic radiation and those that are not, is appropriately detected as producing a speckle pattern, and the detected light has a spectral component at the ultrasound frequency.
The main idea of the invention is to extract information about the blood flow in a subject (generally fluid flow in turbid media) from acousto-optic measurements based on the ultrasound tagging of light. The inventors have found that correlation between light tagged by acoustic radiation and the signal which generates the corresponding acoustic radiation is indicative of a measure of fluid flow in the medium. Also, the inventors have found that a measure of blood flow can be obtained from data indicative of a power spectrum of the received light, including light tagged by the acoustic radiation, namely from the parameters of at least one peak in said power spectrum.
The inventors have found that blood flow within the sampled volume affects the temporal correlation between the light photons. As the flow increases, this results in a decrease in the amplitude and in a broadening of the width of the spectral component at the ultrasound frequency.
The following examples can be used to determine parameters of the signal that correspond to measures of flow. According to one not limiting example, for the case of blood flow in tissue, a measure of flow can be defined as: blood flow velocity (measured in cm/sec), blood perfusion (measured in mL (blood)/100 mg (tissue)/min), hemoglobin concentration (Ctot) as a function of time, oxygenated hemoglobin or oxygen saturation as a function of time.
According to one broad aspect of the invention, there is provided a monitoring system for monitoring fluid flow in a turbid medium. The system comprises a processor utility which is connectable to an acoustic generator associated with one or more acoustic ports and is operable for generating signals S0 to activate said one or more acoustic ports for generating acoustic radiation of a certain frequency range centered at a frequency F0 to irradiate a region of interest, and is connectable to at least one light output port associated with one or more light detectors for receiving light of at least one wavelength λ from the region of interest including light tagged by said acoustic radiation. The processor utility is configured and operable for analyzing the generated signals S0 and data indicative of the received light including light tagged by the corresponding acoustic radiation and determining correlation between said signals S0 and said data indicative of the received light, said correlation being informative of a measure of fluid flow in the medium.
The acoustic signal has one of the following profiles: a continuous wave (CW); a modulated continuous wave (e.g. coded signal, e.g. coded signal with narrow autocorrelation); and/or a pulse or sequence of pulses.
In some embodiments of the invention, the processor utility is configured and operable to determine said correlation by carrying out the following:
determining time-based cross correlation, CCA(τ,λ,T), between said signals S0 and said data indicative of the received light, said time-based cross correlation being calculated for each wavelength λ of light and at a time delay τ from onset of the acoustic signal, and
determining autocorrelation UTLA of said cross correlation CCA(τ,λ,T) at different times T, being time stamps of different measurement times, said autocorrelation UTLA being indicative of a measure of fluid flow within the medium as a function of depth z in the medium.
The autocorrelation UTLA for a predetermined τ, being a function of ΔT, τ and λ, can be determined as follows:

UTLA(ΔT,τ,λ)=∫dT·CCA(T,τ,λ)·CCA(T+ΔT,τ,λ).

A measure of flow can be determined from a decay coefficient of UTLA(ΔT, τ, λ).
The processor utility may be configured for measuring a decay time Tdecay, thus providing information indicative of the measure of flow within the monitored medium. For example, the processor utility calculates the decay time Tdecay from a single UTLA signal or from a sum/average over such signals.
The time-based cross correlation CCA(τ,λ,T) is equivalently called UTL(τ,λ,T) (i.e. Ultrasound Tagged Light), and these expressions are interchangeably used through the application herein.
In yet some other embodiments of the invention, the processor utility is configured and operable to determine said correlation and a flow index by carrying out the following:
determining time-based cross correlation, UTL(τ,λ,T), between said signals S0 and said data indicative of the received light, said time-based cross correlation being calculated for each wavelength λ of light and at a time delay τ from onset of the acoustic signal, and
determining a CFI (Calculated Flow Index) from said UTL, by normalizing the UTL to the average light intensity (DC value) of the received light to account for the effect of the light intensity on the amplitude of the cross correlation, and calculating the CFI from an interest range of the normalized UTL curve.
The Flow index has been found by the inventors to be linearly dependent on the flow velocity. Also, a correlation has been found between the CFI and the known laser Doppler flow measurements.
The monitoring system preferably includes a control panel associated with a measurement unit. This control panel includes said at least one light output, said one or more acoustic ports, and also at least one light input for illumination of the region of interest with light of one or more wavelengths. The light input(s) is/are associated with one or more light sources (e.g. lasers) producing light of different wavelengths, or with at least one tunable light source.
According to another broad aspect of the invention, there is provided a monitoring system for monitoring fluid flow in a turbid medium, the system comprising: a processor utility which is connectable to an acoustic generator associated with one or more acoustic ports and is operable for generating signals (S0) to activate said one or more acoustic ports for irradiating a region of interest with acoustic radiation of a certain frequency range centered at a frequency F0 and is connectable to at least one light output port associated with one or more light detectors for receiving light of at least one wavelength λ from the region of interest including light tagged by said acoustic radiation, the processor utility being configured and operable for analyzing data indicative of a power spectrum of the received light including light tagged by the acoustic radiation; identifying in said data at least one of the following light intensity peaks: a peak around said frequency F0, a peak around a harmonic of said frequency F0; and determining a measure of the fluid flow according to parameters of said at least one peak.
In some embodiments, the processor utility may also analyze the data indicative of the received light to identify in said data a DC intensity peak and use the parameters of such at least two peaks for the fluid flow measure. The acoustic signal in this case may be in the form of a continuous wave or modulated continuous wave.
According to yet another broad aspect of the invention, there is provided, a control unit for use in monitoring fluid flow in a turbid medium. The control unit comprises a processor utility configured for communication with an acoustic generator for receiving data indicative of generated signals S0 corresponding to signals which activate one or more acoustic ports for irradiating a region of interest with acoustic radiation of a certain frequency range centered at a frequency F0, and for communication with one or more light detectors (or associated therewith one or more light output ports) for receiving data indicative of detected light of at least one wavelength λ including light tagged by said acoustic radiation. The processor utility is configured for processing and analyzing data indicative of the detected light and generating output data indicative of correlation between said signals S0 and said data indicative of the received light, said correlation being informative of a measure of the fluid flow in the medium.
More specifically, the invention is useful for blood flow measurements and is therefore described below with respect to this specific application.



BRIEF DESCRIPTION OF THE DRAWINGS
In order to understand the invention and to see how it may be carried out in practice, embodiments will now be described, by way of non-limiting examples only, with reference to the accompanying drawings, in which:
FIG. 1 is a block diagram of an example of a monitoring system of the present invention suitable for non-invasively measuring blood flow in a subject;
FIGS. 2a-c exemplify a train of ultrasound pulses, a detected light intensity and the temporal cross correlation between the generated ultrasound signal and the detected light;
FIG. 2d shows an example of a CCA(λ,τ) (UTL(λ,τ)) signal as a function of delay time τ;
FIG. 3 exemplifies the CCA(T,λ,τ) for different time stamps T;
FIG. 4 shows a flow diagram of a method of the invention for calculating a flow parameter from the autocorrelation of CCA(λ,τ);
FIG. 5 shows the light intensity power spectrum in the vicinity of the ultrasound frequency (marked as “0”);
FIG. 6 shows a flow index defined according to the width of the power spectrum, as a function of time, during a measurement on a human arm that includes two cuff occlusions marked by two straight bold lines;
FIG. 7 illustrates influence of flow on the amplitude of the CCA(λ,τ) signal during a session of cuff occlusion when the light and ultrasound are emitted into the patient's arm; and
FIGS. 8a-c show the results of an experiment conducted by the inventors using a phantom mimicking a flow within a tissue.



DETAILED DESCRIPTION OF EMBODIMENTS
Reference is made to FIG. 1 showing schematically an example of a monitoring system, generally designated 100, configured and operable according to the invention for non-invasive monitoring of one or more blood related parameters including a blood flow parameter. System 100 is configured as a control station and includes a control unit 102 and a control panel 104 which is associated with a measurement unit. Control panel 104 is in communication with utilities of control unit 102 and with those of the measurement unit. At least a part of the control panel 104 may be integral with control unit 102 and configured to connect respective ports of the control panel to those of the to external measurement unit, or may be part of the measurement unit and connected to the control unit via wires or via wireless signal transmission.
Control panel 104 includes one or more light output ports 116, one or more light input ports 114, and one or more acoustic ports 112. Light output port(s) 116 is/are associated with one or more photodetectors either directly or via guiding element(s), e.g. optical fiber(s). Light input port(s) 114 is/are associated with one or more light sources (lasers) either directly or via guiding element(s), e.g. optical fiber(s). Control unit 102 includes inter alia a data processing utility 102A (including also an analog-to-digital converter), an acoustic generator 102C and a data presentation utility 102B such as display, as well as user interface (not shown). Also preferably provided in the control unit 102 is an illumination controller 102D. Illumination controller 102D may be used for selecting one or more light inputs and/or one or more light outputs for the illumination and light collection from multiple ports.
Data processing utility 102A includes appropriate hardware and/or software modules. As will be described more specifically further below, the data processing utility includes inter alia a module capable of processing measured optical data coming from photodetector(s) (light output(s) 116) and signal S0 from acoustic generator 102C and determining cross correlation, (CCA(λ,τ)), between signal S0 indicative of acoustic (ultrasound) radiation (e.g. coded signal or continuous signal) and the corresponding measured data indicative of detected light including ultrasound tagged light signals. The data indicative of the detected light may be the amplitude of such signal or its absolute value, or another function corresponding to this signal. The output of such cross-correlator module includes for example amplitude or phase of the cross correlation at different delays of the acoustic signal, as will be described below.
Light input port(s) 114 is/are operated (e.g. via illumination controller 102D or manually by user) to deliver coherent laser light into the media (including a region of interest), and light scattered back from the tissue within the illuminated region (including at least a part of the region of interest) is collected by at least one light output port 116 that is associated with (coupled to) a photodetector. Acoustic generator 102C generates signals S0 of certain frequency range, centered at frequency (F0) and operates an ultrasound transducer (constituted by acoustic port 112) to emit ultrasound waves of said frequency (F0) into the monitored medium that is simultaneously illuminated by the laser light, and when interacting with light in the media “tags” the light that travels through the medium. Therefore, some of the light detected at the light output 116 is modulated at the ultrasound frequency (F0), or at the vicinity of the ultrasound frequency.
As has been said already, when a light beam enters a semi-infinite turbid medium, photons scatter many times before exiting the medium. The trajectories of photons that exit the medium at a distance d from the source are within a “banana” shape. The location of the peak of the photon's distribution along the axis perpendicular to the source-detector axis is around d/2.
When the light source is coherent, different photons that travel through different trajectories interfere constructively and destructively at the detector plane, creating numerous bright and dark spots called speckles.
In biological tissues, the medium through which light travels is in constant motion due to cells' or large molecules' finite temperature. Therefore, the speckle pattern is varying as a function of time. When the movements within the tissue are substantial relative to those induced by temperature, e.g. due to blood flow, the temporal correlation between the trajectories of the photons that reach the detector decreases and results in a decrease of speckle contrast.
Light that travels through a medium that is irradiated with an ultrasound (US) beam is “tagged” by the acoustic wave through the acousto-optic effect. Therefore, the speckle pattern obtained from such a medium will have a modulated component at the US frequency in addition to the random speckle variations.
The generation of acoustic waves can be in one of the following modes: a continuous wave (CW), a modulated continuous wave (coded), or a single pulse or sequence of pulses (burst). In some embodiments of the invention, the ultrasound is generated by a coded signal with a narrow autocorrelation. The principles of this technique are described in U.S. Pat. No. 7,541,602, assigned to the assignee of the present application and incorporated herein by reference with respect to this specific but not limiting example. The acoustic radiation generated into the turbid medium has a pressure profile PA(τ) within the medium; here τ is the time delay within a single ultrasound tagged signal CCA(λ,τ) from the onset of the acoustic wave. The “narrow autocorrelation function” refers to an autocorrelation which is negligible for any delay time τ larger than the determined time resolution of the system. The latter may for example be determined as the time resolution of detection of the electromagnetic radiation response, or as the temporal bandwidth of the acoustic excitation of the ultrasound transducer, or as the required spatial resolution divided by the speed of sound in the media.
Light of wavelength λ is irradiated into the medium (e.g. using illumination controller 102D and light input ports 114), and detected by at least one light output element 116. The cross correlation, CCA(τ,λ), of the detected light intensity (I) at each wavelength λ with signals S0 at delay τ (constituting the data indicative of the detected light including ultrasound tagged light signals) has contributions from the ultrasound pressure amplitude as a function of delay τ, PA(τ), and from the light distribution LD(λ) in the monitored medium at depth z, where z is a function of τ as will be shown below. In other words, CCA(τ,λ) represents the light distribution at wavelength λ at depth z multiplied by the acoustic power distribution or pressure amplitude, or a function of the acoustic pressure amplitude (PA(τ)) at a distance z from the acoustic transducer.
Turning to FIGS. 2a-c, these show an example of a short train of US pulses introduced into the tissue (FIG. 2a), the measured light intensity detected (FIG. 2b), and the time-based cross correlation (CCA/UTL curve) between the US pulse train and detected light provided as a depth profile of the tagged light intensity which corresponds to a cross section of the “banana” (FIG. 2c).
As said above, the ultrasound is preferably generated by a coded signal with a narrow autocorrelation. An exemplary coded series G(t) comprising of “1” and “−1” bits having a narrow autocorrelation is used. Such a series provides high SNR due to its relatively long length while maintaining a high temporal resolution. The series is transformed into a complex series g(t)=G(t)e2πft and the transmitted ultrasound signal is Re(g(t)). The amplitude of the UTL signal at delay τ, and for a specific λ, is defined by:

UTL(τ)=|ΣtI(t)*g(t+τ)|2  (1)

where I(t) is the detected light intensity at time t.

As indicated above, the time parameter τ is the time delay within a single CCA(λ,τ) signal from the onset of the signal generated by acoustic generator. FIG. 2d shows an example of a CCA(λ,τ) signal as a function of delay time τ while the wave length λ is fixed; this graph is actually indicative of the signal dependence on the z-coordinate in the medium where the signal has been generated (where the “tagging” occurred). The time parameter τ signifies the depth coordinate (z) along the path of the acoustic signal within the monitored region according to the following:




  
    z
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        ∫
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      ⁢
      
        
          
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where νUS(τ) is the ultrasound velocity within the region of the monitored medium reached by the ultrasound at a delay τ.

Each CCA(λ,τ) signal carries its own time stamp T which signifies the time of the onset of the acoustic signal. An example of such signals, calculated for different times T and different time delays τ is shown in FIG. 3 and is therefore marked CCA(λ,τ,T).
Referring to FIG. 4, there is exemplified a flow diagram 200 of a method of the invention for calculation of function UTLA, being the autocorrelation of the CCA(τ,λ,T) at different times T. More specifically, CCA(λ,τ,T) for at least one wavelength λ is calculated by the correlator module of the processing utility (step 202), and a certain value of τ is set (step 204). For a predetermined τ, UTLA(ΔT, τ, λ) is calculated as autocorrelation of CCA(λ,τ,T) as follows (step 206):

UTLA(ΔT,τ,λ)=∫dT·CCA(T,τ,λ)·CCA(T+ΔT,τ,λ)  (2)

Then, a flow measure can be calculated from the decay coefficient of UTLA(ΔT, τ, λ)—step 208. This is associated with the following:
UTLA decays with increasing ΔT, the decay being characterized by a decay constant Tdecay, which depends on the tissue properties. For example, the decay can be exponential:

UTLA(ΔT,τ,λ)∝exp(−ΔT/Tdecay).  (3)

The CCA signal and thus the UTLA signal are affected by the movement of scattering centers within the monitored medium. Variations in the distribution of scattering centers lead to a decorrelation of the UTLA signal. Thus, Tdecay is indicative of variations and rate of variations in the scattering centers' distribution within the monitored medium. More specifically, a flow within the monitored medium leads to a variation of the scattering centers within the medium and therefore to changes in the decay constant Tdecay. An increase in flow within the monitored medium leads to a shorter correlation time between CCA signals, and a smaller Tdecay, while a decrease in flow leads to a larger Tdecay.
UTLA is a function of τ, and therefore a function of the depth coordinate z along the ultrasound path into the monitored medium. Hence, UTLA provides information indicative of a measure of flow within the medium as a function of depth.
According to another embodiment of the present invention, it is possible to learn about the fluid flow by extracting and calculating a flow index CFI directly from the UTL curve, and without the calculation of the UTLA. Firstly, the UTL curve is normalized to the average light intensity (DC value) to account for the effect of the light intensity on the amplitude of the UTL. Secondly, the CFI is calculated from a predetermined part of the normalized UTL function, where said part corresponds to the range of interest k to k+N of the normalized curve, as follows:




  
    
      
        
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where t is the discrete recording time.

The range of interest can be chosen as the range over which the UTL curve is most sensitive to flow variations. This can be carried out by calculating a linear regression between CFI and the real velocity rates for different interest ranges. It has been found by the inventors that the CFI is linearly dependent on the actual flow velocity/rate.
In the above-described example, generation of an acoustic wave by a coded signal with narrow autocorrelation was considered. The invention is not limited to this specific example.
In some other embodiments of the invention, the acoustic radiation is generated by signal S0 in the form of a pulse or a series of pulses (PU(T)), i.e., not necessarily a coded signal. Light of wavelength λ is irradiated into the medium, and detected by at least one light output element. The cross correlation CCA(τ,λ) is that of the detected light intensity at wavelength λ with the pulse or series of pulses that generate the acoustic signal, the time parameter τ being the time within a single CCA signal. Each CCA signal carries its own time stamp T which signifies the time the acoustic signal was generated. Using short pulses allows for probing variations on shorter time scales.
The UTLA signal, being an autocorrelation of the CCA(τ,λ) at different times T, is calculated according to equation (2) above, and the decay time Tdecay is measured, thus providing information indicative of a measure of flow within the monitored medium. Depending on the time resolution requirement, Tdecay can be calculated from a single UTLA signal or from a sum/average over such signals.
In yet other embodiments of the invention, the generated acoustic signal is a continuous wave (CW), or a series of phase synchronized pulses (i.e. modulated CW). Light of wavelength λ is irradiated into the medium, and detected by at least one light output element. The spectral width of the power spectrum of the detected light intensity (|/(Ω)|2) is peaked around at least two frequencies: 0 Hz (i.e. DC) and at the ultrasound frequency (F0) and its harmonics (multiples of F0). A measure of flow in the monitored medium is defined according to parameters of at least the peak at F0. Furthermore, a measure of flow in the monitored medium can be characterized by a combination of parameters from the peak at F0 and/or the peaks at its harmonics, and/or the DC peak.
An example for the power spectrum around F0 is shown in FIG. 5. In this example a CW ultrasound wave of F0=1 MHz was transmitted into the tissue by an ultrasound transducer (acoustic output 112) positioned between two optical fibers (light input 114 and light output 112). The signal output of the photodetector was digitized and the power spectrum of the collected light was calculated for two flow conditions, Flow 1 and Flow 2 where Flow1>Flow2. As can be seen, the width of the power spectrum during Flow 1 is wider than that during Flow 2 and its peak is lower.
The width of the power spectrum peaks is affected by frequency broadening effects, such as Doppler broadening due to Brownian motion of scattering centers within the monitored medium. When there is an increase in flow, the spectral width increases, while a decrease in flow results in a narrower power spectrum. The power spectrum width is therefore indicative of a measure of flow.
For example, the spectral width can be determined as the width of a Lorentzian fit to the power spectrum. As another example, one can measure the full width at half maximum amplitude of the power spectrum at F0. Other methods can be used to correlate a parameter of the power spectrum (e.g. width, standard deviation, peak amplitude, or any other fitting function) to the flow in the underlying monitored medium. In addition, comparisons to matching parameter measures for the DC power spectrum can be made. These can contribute to an increase in the measurement accuracy, reduce error and improve stability of the measurement.
An example of a measurement of flow during a cuff occlusion performed on a human arm is shown in FIG. 6. The cuff is inflated two times, with a reflow in between the two inflations. A flow index was defined according to spectral width (i.e. the width of the distribution according to a Lorentzian shape was correlated to the flow, and is defined as the flow index). The flow index is plotted as a function of time. As clearly seen in the figure, during the cuff occlusions (marked by dark bold straight lines below the curve), the flow index decreased significantly, while an expected increase in flow due to hyperemia can clearly be seen between the cuffing episodes. A calibration curve can thus be calculated, based on simultaneous measurement of different flow conditions (for example, different flow velocities, or different volume/min) to provide a scaled measurement of flow.
Turning back to FIG. 2, the amplitude of the CCA(λ,τ) signal at a predetermined delay time τ is affected by flow in the underlying monitored medium. An increase in flow results in a decrease in the CCA(λ,τ) signal amplitude, while a decrease in flow results in an increase in the CCA(λ,τ) signal amplitude. In particular, flow in the underlying monitored medium affects the peak CCA(λ,τ) amplitude. Such an example is shown in FIG. 7, depicting the influence of blood flow in a patient's arm on the peak amplitude of the CCA(λ,τ) signal during a session of cuff occlusion when the light and ultrasound were emitted into the patient's arm. The flow index was taken to be a function of the inverse CCA(λ,τ) peak height. During the cuff occlusion, the blood flow decreased.
The following is another experiment that was conducted by the inventors relating to the CFI and the linear relationship between the CFI and the flow.
A phantom model that mimics blood flow in the tissue was designed. The optical and acoustic properties of the phantom were similar to those of tissue. The phantom encapsulated millimeter size flow channels organized in rows of channels, positioned one above the other, in order to mimic shallow and deep vessels in the tissue.
Experiments were carried out with different flow rates. In each session a chosen flow rate was set and fluid flow was kept constant for 2 minutes. Six experiments were performed to test the sensitivity to fluid flow in deeper channels.
FIG. 8a shows the UTL curves for three different flow rates, 750 μl/min, 1750 μl/min and 0 μl/min, from up down respectively. It can be clearly seen that when the flow rate increased, the maximum amplitude decreased and got wider.
An example for choosing the range of interest between k and k+N, in order to calculate the CFI, is shown in FIG. 8b. The UTL curve presents the results of the 750 μl/min flow.
After choosing the most sensitive interest range, CFI was calculated, according to equation (4), over 2 minutes for each flow rate. Abnormal UTL frames were rejected before calculating the CFI at time points where the DC light intensity exceeded 2.5 standard deviations from its mean value. As a robust estimator, the median value of CFI was calculated. For evaluation of CFI, a comparison to Laser Doppler was performed. The correlation between the laser Doppler's flow index and CFI is presented in FIG. 8c. The correlation coefficient (r2) between CFI and Laser Doppler's Flow Index was 0.94. Those skilled in the art will appreciate that various modifications and changes can be applied to the embodiments of the invention described hereinabove without departing from its scope defined in and by the appended claims.

## Claims

1. A monitoring system for monitoring fluid flow in turbid medium, the system comprising:
a processor utility which is connectable to an acoustic generator associated with one or more acoustic ports and is operable for generating signals S0 to activate said one or more acoustic ports for generating acoustic radiation of a certain frequency range centered at a frequency F0 to irradiate a region of interest and is connectable to at least one light output port associated with one or more light detectors for receiving light of at least one wavelength λ from the region of interest including light tagged by said acoustic radiation, the processor utility being configured and operable for carrying out the following:
analyzing the signals S0 and data indicative of the received light including light tagged by the corresponding acoustic radiation and determining time-based correlation, UTL(τ,λ,T), between said signals S0 and said data indicative of the received light, said time-based correlation, UTL(τ,λ,T), being a function of wavelength λ of light and at a time delay τ from the generation of the acoustic radiation and being informative of a measure of fluid flow in the medium; and
processing said time-based correlation, UTL(τ,λ,T), and determining a Calculated Flow Index (CFI), said processing comprising normalizing the UTL(τ,λ,T) to an average light intensity received during the measurement period and obtaining a normalized UTL function, and calculating the CFI from a predetermined part of the normalized UTL function.

2. A monitoring system according to claim 1, wherein the acoustic radiation has one of the following profiles: a continuous wave (CW); a modulated continuous wave; and a pulse or sequence of pulses.

3. A monitoring system according to claim 1, wherein the processor utility is configured and operable to determine said CFI by applying the following equation to the normalized UTL function:




  
    
      
        
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        )
      
    
  



wherein DC(t) is the average light intensity, t is the discrete recording time, and the predetermined part of the normalized UTL function is defined by a range of interest from k to k+N of the normalized function.

4. A monitoring system according to claim 1, wherein the processor utility is configured and operable to determine said time-based correlation by carrying out the following:
determining cross correlation, CCA(τ,λ,T), between said signal S0 generated by acoustic generator and said data indicative of the received light, said cross correlation being calculated for each wavelength λ of light and at a time delay τ from onset of signal S, and
determining auto correlation UTLA of said cross correlation CCA(τ,λ,T) at different times T being time stamps of different measurement times, said autocorrelation UTLA being indicative of a measure of fluid flow within the medium as a function of depth z in the medium.

5. A monitoring system according to claim 4, wherein the processor utility is configured for determination of said autocorrelation UTLA for a predetermined τ, being a function of ΔT, τ and λ, as follows:


UTLA(ΔT,τ,λ)=∫dT·CCA(T,τ,λ)·CCA(T+ΔT,τ,λ),


and determining the flow measure from a decay coefficient of UTLA(ΔT,τ,λ).

6. A monitoring system according to claim 5, wherein the acoustic signal is a coded signal with a narrow autocorrelation.

7. A monitoring system according to claim 5, wherein the processor utility is configured for measuring a decay time Tdecay, thus providing information indicative of the measure of flow within the monitored medium.

8. A monitoring system according to claim 7, wherein the processor utility is configured for calculating the decay time Tdecay from a single UTLA signal or from a sum/average over such signals.

9. A monitoring system according to claim 7, wherein the acoustic signal is in the form of a pulse or a series of pulses.

10. A monitoring system according to claim 8, wherein the acoustic signal is in the form of a pulse or a series of pulses.

11. A monitoring system according to claim 1, comprising a control panel associated with a measurement unit, said control panel comprising at least one light input for illumination of the region of interest with light of one or more wavelengths, said at least one light output, and said one or more acoustic ports.

12. A monitoring system according to claim 11, wherein the at least one light input is associated with one or more light sources producing light of different wavelengths, or at least one tunable light source.

13. A monitoring system for monitoring a fluid flow in a turbid medium of a subject, the monitoring system comprising:
at least one light input port associated with one more light sources for generating light of at least one wavelength λ to illuminate a region of interest in the subject;
an acoustic generator associated with at least one acoustic port, the acoustic generator being operable for generating signals S0 to activate said at least one acoustic port for irradiating a region of interest with acoustic radiation of a certain frequency range centered at a frequency F0;
at least one light output port associated with one or more light detectors for receiving light of at least one wavelength λ from the region of interest including light tagged by said acoustic radiation and generating data indicative thereof; and
a processor utility which is connected to the acoustic generator and to the at least one light output port for receiving data indicative of the generated signals S0 and said data indicative of the received light, the processor utility being configured and operable for carrying out the following:
analyzing said data indicative of the generated signals S0 and said data indicative of the received light for determining time-based correlation, UTL(τ,λ,T), between them being a function of wavelength λ of light and at a time delay τ from the generation of the acoustic radiation; normalizing the UTL(τ,λ,T) to an average light intensity and obtaining a normalized UTL function using processing said time-based correlation, UTL(τ,λ,T), determining a Calculated Flow Index (CFI) from a predetermined part of the normalized UTL function, said CFI being a measure of the fluid flow in the region of interest in the subject.

14. A control unit for use in monitoring fluid flow in a turbid medium, the control unit comprising a processor utility configured for communication with an acoustic generator for receiving therefrom data indicative of signals S0 corresponding to signals which activate one or more acoustic ports for irradiating a region of interest with acoustic radiation of a certain frequency range centered at a frequency F0 and for communication with and one or more light detectors for receiving data indicative of detected light of at least one wavelength λ including light tagged by said acoustic radiation, the processor utility being configured for processing and analyzing said data indicative of the detected light and generating output data indicative of time-based correlation between said signals S0 and said data indicative of the detected light, using said time-based correlation for determining a Calculated Flow Index being informative of a measure of the fluid flow in the medium.

15. A control unit according to claim 14, wherein said processing and analyzing comprises analyzing the signals S0 and data indicative of the detected light including light tagged by the corresponding acoustic radiation and determining the time-based correlation, UTL(τ,λ,T), as a function of wavelength λ of light and at a time delay τ from the generation of the acoustic radiation, normalizing the UTL(τ,λ,T) to an average light intensity and obtaining a normalized UTL function, and calculating the Calculated Flow Index CFI from a predetermined part of the normalized UTL function.

16. A control unit according to claim 15, wherein the processor utility is configured and operable to determine said CFI by applying the following equation to the normalized UTL function:




  
    
      
        
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        4
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wherein DC(t) is the average light intensity, t is the discrete recording time, and the predetermined part of the normalized UTL function is defined by a range of interest from k to k+N of the normalized function.

17. A control unit according to claim 15, wherein the processor utility is configured and operable to determine said time-based correlation by carrying out the following:
determining cross correlation, CCA(τ,λ,T), between said signal S0 generated by acoustic generator and said data indicative of the detected light, said cross correlation being calculated for each wavelength λ of light and at a time delay τ from onset of signal S, and
determining auto correlation UTLA of said cross correlation CCA(τ,λ,T) at different times T being time stamps of different measurement times, said autocorrelation UTLA being indicative of a measure of fluid flow within the medium as a function of depth z in the medium.

18. A control unit system according to claim 17, wherein the processor utility is configured for determination of said autocorrelation UTLA for a predetermined τ, being a function of ΔT, τ and λ, as follows:


UTLA(ΔT,τ,λ)=∫dT·CCA(T,τ,λ)·CCA(T+ΔT,τ,λ),


and determining the flow measure from a decay coefficient of UTLA(ΔT, τ, λ).

19. A control unit according to claim 18, wherein the processor utility is configured for measuring a decay time Tdecay, thus providing information indicative of the measure of flow within the monitored medium.

20. A control unit according to claim 19, wherein the processor utility is configured for calculating the decay time Tdecay from a single UTLA signal or from a sum/average over such signals.