# US 11,432,805 B2 · Estimation and display for vector doppler imaging using plane wave transmissions

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- Number: US 11,432,805 B2
- Document ID: US11432805B2
- Status: Granted
- Kind: B2
- Application number: 16/560,851
- Filed: 2019-09-04
- Published: 2019-12-26
- Granted: 2022-09-06
- Earliest claimed: 2011-10-19
- Assignees: Verasonics, Inc.
- Applicants: Verasonics, Inc.
- Inventors: John Flynn; Ronald Elvin Daigle
- Web page: https://patentgrep.com/patent/US11432805B2

## CPC

- A61B 8/5223: {for extracting a diagnostic or physiological parameter from medical diagnostic data (for algorithms to analyse biomedical images G06T7/0012)}
- A61B 8/06: Measuring blood flow
- A61B 8/14: Echotomography
- A61B 8/4483: {characterised by features of the ultrasound transducer}
- A61B 8/463: {characterised by displaying multiple images or images and diagnostic data on one display}
- A61B 8/488: {involving Doppler signals}
- A61B 8/5207: {involving processing of raw data to produce diagnostic data, e.g. for generating an image}
- A61B 8/5269: {involving detection or reduction of artifacts}
- G01S 15/8977: {using special techniques for image reconstruction, e.g. FFT, geometrical transformations, spatial deconvolution, time deconvolution}
- G01S 15/8984: {Measuring the velocity vector}
- G01S 15/8995: {Combining images from different aspect angles, e.g. spatial compounding}
- G01F 1/663: by measuring Doppler frequency shift
- G01S 15/8979: {Combined Doppler and pulse-echo imaging systems}
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01F: MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME

## Abstract

Vector Doppler Imaging (VDI) improves on conventional Color Doppler Imaging (CDI) by giving speed and direction of blood flow at each pixel of a display generated by a computing system. Multiple angles of Plane wave transmissions (PWT) via an ultrasound transducer conveniently give projected Doppler measurements over a wide field of view, providing enough angular diversity to identify velocity vectors in a short time window while capturing transitory flow dynamics. A fast, aliasing-resistant velocity vector estimator for PWT is presented, and VDI imaging of a carotid artery with a 5 MHz linear array is shown using a novel synthetic particle flow visualization method.

## Claims

### Claim 1

A method of producing blood flow velocity vector imagery, comprising:
emitting at least two unfocused plane wave acoustic signals M at at least two angles, where M is a number of plane wave acoustic signal emissions, to a transducer array into a medium over substantially an entire field of measurement;
receiving scattered and reflected ultrasonic signals on the transducer array to form received ultrasonic signals in response to the emission;
processing the received ultrasonic signals to generate extracted information for constructing a blood flow vector velocity signal by:
wall filtering the extracted information to generate wall-filtered information;
using the wall-filtered information to form autocorrelation values and Doppler frequency estimates;
partitioning of a bistatic range-rate model into linear and nonlinear parts; and
solving the partitioned model by the weighted least squares scheme for the blood flow vector velocity signal v corresponding to at least one point in the medium;
generating blood flow vector velocity signals;
detecting the presence of blood flow corresponding to a display device pixel by qualifying blood flow vector velocity signals through a series of tests on values of quality metrics produced as byproducts of the blood flow vector velocity estimation procedure; and
generating on a display device blood flow vector velocity imagery from the blood flow vector velocity signals.

### Claim 2 (depends on 1)

The method of claim 1, wherein the emitting and receiving comprise transmitting multiple plane wave acoustic signals and receiving the scattered and reflected ultrasonic signals in ensembles with a timing consistent with Doppler measurements and with a dwell at one or more discrete angles to the transducer array into the medium, with respect to the transducer coordinates, of transmitted plane wave propagation.

### Claim 3 (depends on 2)

The method of claim 2, comprising preprocessing the received ultrasonic signals independently for each transmission angle using one or more of wall filtering, auto-correlation, and Doppler frequency estimation.

### Claim 4 (depends on 3)

The method of claim 3, comprising assembling Doppler frequency estimates from all transmission angles in a specific bistatic range-rate model and computing an inference of blood flow vector velocity estimates within the field of measurement.

### Claim 5 (depends on 4)

The method of claim 4, comprising partitioning of the bistatic range-rate model with aliasing bias vectors into linear and nonlinear parts.

### Claim 6 (depends on 5)

The method of claim 5, comprising using variance components as quality estimates for frequency estimates corresponding to each of the plane wave angle data.

### Claim 7 (depends on 6)

The method of claim 6, comprising computing Doppler frequency estimate variance, in analogy to the variance of the angle associated with a complex Rice random variable, from Doppler signal-to-noise ratio.

### Claim 8 (depends on 6)

The method of claim 6, comprising computing Doppler frequency estimate variance from instantaneous frequency deviates referenced to mean frequency.

### Claim 9 (depends on 6)

The method of claim 6, comprising modeling of hypothesized aliasing bias of Doppler frequency and providing consequent corrective adjustments on individual plane wave angle channels affected by aliasing to allow interpretation of aliasing up to twice the pulse rate frequency and prevent image blackout during Doppler aliasing events typically appearing during the systole cardiac phase.

### Claim 10 (depends on 9)

The method of claim 9 comprising the providing of restrictions to hypothesized aliasing bias vectors into adjacent plane wave angles, in groups of one or more aliased plane wave angle channels in the model.

### Claim 11 (depends on 5)

The method of claim 5 comprising using Doppler frequency variances at each plane wave emission angle to formulate a weighted least squares estimation scheme that computes blood flow vector velocity estimates and an optimal hypothesized aliasing bias vector.

### Claim 12 (depends on 1)

The method claim 1, further comprising: performing blood flow detection by qualification tests on by-products of the blood flow vector velocity estimation procedure, comprising:
a. testing computed values of blood flow vector velocity estimate precision;
b. testing computed values of combined power of lag-one autocorrelation values;
c. testing computed values of normalized velocity magnitude;
d. testing computed values of autocorrelation residual; and
e. testing computed values of whitened frequency residual resulting in declaration of pixels being displayed as flow information if qualified by the tests.

### Claim 13 (depends on 1)

The method of claim 1, comprising:
correcting a Spectral Doppler image trace frequency scale with a reciprocal of the bistatic range-rate model; and generating on a display device blood flow vector velocity imagery from the blood flow vector velocity signals as a quantitative blood velocity spectrum from the correcting of the Spectral Doppler image trace frequency scale.

### Claim 14 (depends on 1)

The method of claim 1, comprising:
generating on a display device blood flow vector velocity imagery from the blood flow vector velocity signal, as quantitative instantaneous blood flow rate by:
integrating blood flow velocity vectors, projected to the surface normal, over a voxel surface slicing the vessel; and
displaying the result as instantaneous flow rate, on a format analogous to Spectral Doppler Image, with the vertical axis labeled in flow rate units.

### Claim 15 (depends on 1)

The method of claim 1, comprising:
generating on a display device blood flow vector velocity imagery from the blood flow vector velocity signal, by synthetic particle entrainment with independent particle processing, the steps including:
adjusting particle density to follow dynamics of flow extent from frame to frame, for multiple unconnected flow regions;
testing for particles leaving flow region, and responding to the affirmative by deleting relevant particles from particle list;
testing for particles entering flow regions, and responding to the affirmative by creating particles in associated pixels probabilistically;
propagating each particle in the particle list forward in time by advancing its spatial position according to its nearest coincident blood flow vector velocity estimate; and
scaling of the collection of displayed particle propagation velocities by a desired “slowdown” factor to enable viewing of particle flow paths at an arbitrarily reduced speed.

### Claim 16 (depends on 1)

The method of claim 1, wherein the partitioning of the bistatic range rate model comprises the model f=Av+b+e, wherein v is a blood flow velocity vector at an image point and v=[σx, σz]T, b represents bias due to aliasing and is equal to 0 when there is no biasing, e is stochastic error, and the model matrix A is dimensioned [M×2] and has rows αm(θm), where:
a
m
=
1
λ
⁡
[
sin
⁡
(
θ
m
)
,
1
+
cos
⁡
(
θ
m
)
]
with explicit terms for bias due to aliasing of Doppler frequencies.

### Claim 17

An ultrasound processing system, comprising:
a module adapted to generate an acoustic signal, receive at least one echo of the acoustic signal at a plurality of receiving elements in the module and obtain a plurality of echo signals therefrom; and
a processor coupled to the module and configured to:
extract information from the plurality of echo signals to construct a blood flow vector velocity signal by:
wall filtering the extracted information;
using the wall-filtered information to form autocorrelation values and Doppler frequency estimates;
partitioning of a bistatic range-rate model into linear and nonlinear parts; and
solving the partitioned model by the weighted least squares scheme corresponding to at least one point in the medium; and
detect the presence of blood flow at a display device pixel by qualifying blood flow vector velocity signals through a series of tests on values of quality metrics produced as byproducts of the blood flow vector velocity estimation procedure; and
a display device configured to generate blood flow vector velocity imagery from the blood flow vector velocity signals.

### Claim 18 (depends on 17)

The system of claim 17 wherein the partitioning of the bistatic range rate model comprises the model f=Av+b+e, wherein v is a blood flow velocity vector at an image point and v=[σx, σz]T, b represents bias due to aliasing and is equal to 0 when there is no biasing, e is stochastic error, and the model matrix A is dimensioned [M×2] and has rows αm(θm), where:
a
m
=
1
λ
⁡
[
sin
⁡
(
θ
m
)
,
1
+
cos
⁡
(
θ
m
)
]
with explicit terms for bias due to aliasing of Doppler frequencies.