Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/0093—Detecting, measuring or recording by applying one single type of energy and measuring its conversion into another type of energy
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
  • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
  • A61B5/0536—Impedance imaging, e.g. by tomography
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B2576/00—Medical imaging apparatus involving image processing or analysis

Definitions

• the present invention relates to acoustoelectric imaging methods and devices.
• Organs such as the heart, skeletal muscles and the brain are constantly scanned by electrical impulses that carry information in neurons, or trigger muscle or myocardial contractions. To be able to image the propagation of these impulses is extremely important to diagnose numerous pathologies and to understand the brain mechanisms by the functional exploration of the brain.
• Acousto-electrical imaging exploits the interaction between ultrasound and electrical currents to determine the value of electrical current at the points of interaction between ultrasound and tissue, typically at the focal spot of a focused ultrasound wave.
• the present invention is intended to overcome this disadvantage.
• the invention proposes an acousto-electrical imaging method, comprising:
• step (b) an image forming step, in which the Erawi raw electrical signals (t) obtained in step (a) are determined by an image of the medium comprising a mapping of electric currents (this is that is, a map of electrical values representative of the local current densities at each point in the middle).
• step b) at least from the N raw electrical signals Era i (t) is determined for a number M of fictitious focal points P k in the field of observation, electrical values Ecoherent * each corresponding to the electrical signal which would have been picked up if an ultrasound wave focused at the point P k had been emitted by said transducers;
• the raw electrical signals Erawl (t) are applied to a WT -1 inverse wavelet transform and then to an inverse Radon transform R -1 (the raw electrical signals Erawl (t) can of course undergo a preliminary treatment before the inverse Radon transform R -1 );
• step (b) an echographic image of the medium made with the set of transducers is superimposed on the mapping of electric currents;
• acoustic transducers RFrawi, i (t) representative of ultrasound waves reverberated by the medium respectively from the incident waves 1 are detected by the transducers (during the step ( b), from the N sets of RFrawi signals, i (t) picked up, M coherent RFcoherent acoustic signals ⁇ , are determined . (t) corresponding to the acoustic signals that would have been received by the transducers ⁇ if an ultrasonic wave focused at the point P k had been emitted by said transducers, and the ultrasound image of the medium is calculated from the coherent acoustic signals;
• the ultrasound image is determined by channeling from the coherent acoustic signals
• the medium to be imaged is a human or animal tissue.
• the invention also relates to a device for implementing an acousto-electrical imaging method, comprising a set of transducers Ti, minus an electrical sensor, and control means and treatment adapted for:
• FIG. 1 is a schematic view of a device for implementing a method according to one embodiment of the invention.
• FIG. 2 is a block diagram of part of the device of FIG. 1.
• FIG. 1 shows an example of an acoustoelectric imaging device adapted to image a medium 1 by emission and reception of ultrasonic compression waves (for example of frequencies between 0.2 and 40 MHz), with simultaneous measurement of electrical values.
• ultrasonic compression waves for example of frequencies between 0.2 and 40 MHz
• the medium 1 to be imaged may consist in particular of tissues of a patient or of an animal, in particular a muscle (myocardium or other) or a brain.
• the imaging device comprises for example:
• a network 2 of n ultrasonic transducers comprising for example a few hundred transducers and adapted to produce a two-dimensional image (2D) of an observation field (zone of interest, scanned by the ultrasonic waves) in the medium 1 to be imaged ;
• an electronic rack 3 or the like controlling the array 2 of transducers and adapted to acquire the signals picked up by this array of transducers;
• a computer 4 or the like to control the electronic bay 3 and to display the ultrasound images obtained from said captured signals.
• the network 2 of transducers may for example be a linear array formed by a transducer array juxtaposed along an axis X, the Z axis perpendicular to the axis X designating the direction of the depth in the field of view.
• the transducers will be denoted Ti, where i is an index designating the rank of each transducer along the X axis.
• Transducer networks are also possible in the context of the present invention, in particular two-dimensional arrays.
• the device further comprises at least one electric sensor E1 (FIG. 2), constituted for example by two electrodes measuring an electric potential difference.
• This electrical sensor can advantageously be fixed to the transducer network 2 and adapted to come into contact with the medium 1 to be imaged at the same time as the transducers of the network 2.
• the number of electric sensors El used is relatively small, generally less than 10, advantageously less than 5 and most often 1.
• the bay electronic device 3 can include for example:
• n + 1 analog / digital converters 5 (A / D ⁇ - A / D e ) connected individually to the n transducers ⁇ of the transducer network 2 and to the electrical sensor El, n + 1 buffer memories 6 (Bi-B e ) respectively connected to the n analog / digital converters 5,
• CPU central unit 8 communicating with the buffer memories 6 and the computer 4,
• MEM memory 9
• DSP digital signal processor
• n + 1 analog / digital converters 5 (A / D +/- A / D e ) can be identical, as can the n + 1 buffer memories 6 (Bi-B e ), so that the device used can be simply a device conventionally used in ultrafast acoustic imaging.
• This device makes it possible to implement an acousto-electrical imaging method of the medium 1, which notably includes the following steps, implemented by the central processing unit 8 of the processor 8 and the digital signal processor 10:
• the network 2 of transducers and the electric sensor E1 are brought into contact with the medium 1 and a number N of incident ultrasonic waves is emitted in the medium 1 by the transducers ⁇ (N may be for example between 2 and 100, in particular between 5 and 10).
• the incident waves in question are unfocused (more precisely, not focused in the field of view) and have respectively different wavefronts, that is to say wavelengths of different shapes and / or different orientation.
• the incident waves may be plane or divergent waves whose respective F wavefronts (the wavefront F of a single wave is shown in FIG. 1) have different inclinations, characterized by their angles of rotation. respective inclinations ⁇ measured between their propagation direction V and the Z axis, or diverging waves emitted as if they came from different points of space.
• the example of plane waves will be considered in what follows.
• Incident waves are generally pulses of less than one microsecond, typically about 1 to 10 cycles of the ultrasonic wave at the center frequency.
• the incident wave shots may be separated from each other for example from about 50 to 200 microseconds.
• Each incident wave encounters in the middle 1 diffusers that reverberate the incident wave.
• the reverberated ultrasound wave is picked up by the transducers ⁇ of the network.
• the signal thus captured by each transducer ⁇ comes from the whole of the medium 1, since the incident wave is not focused in transmission.
• the electric sensor El captures an electrical signal E (t) during the propagation of the incident ultrasonic wave, and this electrical signal results from the interaction between the incident wave and the medium 1 to be imaged over the entire line represented by the wavefront, at each moment of measurement.
• Reverberant signals picked up by the n transducers Ti are then digitized by the corresponding analog-digital converters A / D ⁇ and stored in the corresponding buffers Bi, while the electrical signal is digitized by the analog-digital converter A / D e and stored in the corresponding buffer memory B e .
• the signals thus stored in the buffers after each firing incident will be called hereinafter raw data.
• These raw data consist of n + 1 raw time signals RFrawi, i (t) and Erawi (t) picked respectively by the transducers ⁇ and the electric sensor El after the incident ultrasound wave firing 1.
• the signals stored in the buffers Bi-B e are transferred to the memory 9 of the signal processor 10 for processing by this processor.
• the memory 9 thus contains N matrices (vectors) of n + 1 raw signals.
• Step (a) is repeated at a fast rate, for example 500 Hz or more, which is made possible by the small number N of incident waves used to make an image.
• a number M of synthetic coherent data matrices is calculated by the processor 8, respectively at M points P k (x, z) of the observation field (where k is an integer between 1 and M and x, where z is the coordinates of the point ⁇ 3 ⁇ 4 on the X, Z axes.
• Each of these M coherent synthetic data vectors comprises n RFcoherentk time signals, i (t) corresponding to the signals that would be picked up respectively by the transducers ⁇ if the transducers emitted an incident wave focused at the point P k .
• Consistent data matrices can be obtained for example by assuming a homogeneous propagation velocity c throughout the medium 1 for ultrasonic compression waves, according to the principle explained in particular in document EP2101191 or in the article by Montaldo et al. "Coherent plane-wave compounding for high-resolution ultrasound and transient elastography” (IEEE Trans Ultrasound Ferroelectr Freq Control 2009 Mar; 56 (3): 489-506).
• the spatially coherent acoustic signal for the transducer Ti corresponding to the virtual focusing point P k , is then calculated according to the formula:
• RFcoheren ⁇ j ⁇ B (l) RFraw Uj (r (l, k, i, j)) (1)
• B (1) is a weighting function for the contribution of each incident wave shot 1 (in common cases, the values B (l) can all be equal to 1).
• This RFcoherent signal k i j has a single value for each point Pk.
• This electrical value is that which would be measured by the electric sensor El if an incident ultrasonic wave focused at P k had been emitted, particularly if a sufficient number of incident waves are emitted to obtain an acousto-electric image, for example 40 to 100 waves. incidental to get a great image resolution.
• Ecoherent values k are representative of the electric currents at the points P k , in the same way as the electrical values captured in the aforementioned acousto-electrical imaging methods, and thus provide a mapping of the electric currents in the field of view.
• the coherent data matrices RFcoherent k and optionally the Ecoherentk values can then be optionally refined by correcting the effects of aberrations in the medium 1, for example as explained for example in the documents EP2101191 or Montaldo et al.
• Coherent plane-wave compounding for Very High Frame Rate Ultrasound and Transient Elastography "(IEEE Trans Ultrasound Ferroelectr Freq Control 2009 Mar; 56 (3): 489-506).
• mapping of the electric currents can be presented on the screen of the computer 4, possibly in superposition with an echographic image B mode of the medium 1 or another image of said medium 1, in particular an echographic image obtained from the Ecoherent matrices k by channel formation in reception, as explained for example in the aforementioned EP2101191 document.
• the raw electrical signal Eraw k (t) can be modeled as follows:
• K is an interaction constant of the order of 1CT 9 Pa -1
• p is the resistivity of the medium
• y is a coordinate along a Y axis perpendicular to the (X, Z) plane and
• J is the detected current density distribution, i.e., the dot product of the current density vector by the electrode sensitivity vector of the electric sensor E1.
• the emitted ultrasonic wave being an impulse plane wave, ⁇ ⁇ ( ⁇ , ⁇ , ⁇ ) can be parameterized as a function of the emission angle ⁇ and the time t. Ignoring the Y direction, we have:
• ⁇ ( ⁇ , ⁇ ) AP (-qsin9 + ctcosG, qcosG + ctsinG),
• the acousto-electric signal becomes:
• RJ (6, ci) ⁇ J (x, z) .S (x, sin ⁇ + z, cos ⁇ - ct) dxdz (4)
• R [J] is the Radon transform
• the incident wave is not a Dirac pulse but a finite frequency band pulse signal, which will result in a convolution with respect to the variable and the Radon transform:
• W (ct) is the emitted waveform and ® is the convolution product.
• n and m can be adjusted within the frequency band of the transducer.
• This convolution nucleus is equivalent to a transform into ridgelettes ("ridgelet transform") [E. J. Candes, "Ridgelets: Theory and Applications,” Stanford University, 1998] of current density distribution.
• the ridgelette decomposition has several mathematical properties such as a Parseval-Plancherel relation, a reconstruction formula, a parsimonious representation of slowly varying objects far from linear discontinuities, and can be expressed as a composition of a wavelet transform and the Radon transform.
• the inversion occurs in two steps: first, inverting the WT wavelet transform, then inverting the Radon R transform.
• SNR signal to noise ratio
• One approach is to emit incident waves as short pulses as possible, which optimizes the resolution. However, this corresponds to a low emitted energy and therefore a low SNR.
• a third approach is to issue a "chirp" that can be used to do pulse compression. This approach maximizes SNR while maintaining image throughput.
• SNR can also be improved by limiting the effect of noise. Since the ridgelette transform is a parsimonious basis that will represent the current density distribution with a small number of large coefficients and a large number of small coefficients, denoising can be achieved simply by applying thresholding on the obtained signals.
• a first approach consists of a thresholding eliminating 'small' coefficients. Otherwise, it is also possible to use the physics of the problem. For example, coefficients containing mainly noise can be identified by performing cross-correlation on received signal windows for two emissions of opposite polarities. In addition these signals can be subtracted to eliminate systemic artifacts.
• the RFcoherent k matrices can be calculated as explained in the above method b1) to further form a two-dimensional ultrasound image (B mode) of the field of view, by channel formation on reception, as explained for example in the document EP2101191 mentioned above.
• This ultrasound image B mode (or another echographic image or not) of the field of view may possibly be superimposed on the mapping of the electrical values determined previously, and it is possible to display on the computer screen 4 at a time the Ultrasound image of the medium and mapping of electrical currents.

Landscapes

• Health & Medical Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Medical Informatics (AREA)
• Biophysics (AREA)
• Pathology (AREA)
• Engineering & Computer Science (AREA)
• Biomedical Technology (AREA)
• Heart & Thoracic Surgery (AREA)
• Physics & Mathematics (AREA)
• Molecular Biology (AREA)
• Surgery (AREA)
• Animal Behavior & Ethology (AREA)
• General Health & Medical Sciences (AREA)
• Public Health (AREA)
• Veterinary Medicine (AREA)
• Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
• Radiology & Medical Imaging (AREA)
• Ultra Sonic Daignosis Equipment (AREA)
• Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Priority Applications (4)

Applications Claiming Priority (2)

Publications (1)

Family

ID=49876745

Family Applications (1)

Country Status (6)

Families Citing this family (2)

Family Cites Families (16)

• 2013
  • 2013-07-22 FR FR1357178A patent/FR3008806B1/fr not_active Expired - Fee Related
• 2014
  • 2014-07-21 US US14/907,178 patent/US20160157728A1/en not_active Abandoned
  • 2014-07-21 WO PCT/FR2014/051880 patent/WO2015011393A1/fr not_active Ceased
  • 2014-07-21 JP JP2016528586A patent/JP6415555B2/ja not_active Expired - Fee Related
  • 2014-07-21 EP EP14755868.8A patent/EP3024378A1/fr not_active Withdrawn
• 2016
  • 2016-01-21 IL IL243744A patent/IL243744A0/en unknown

Non-Patent Citations (4)

Also Published As

Similar Documents

Legal Events