Monitoring Electric-Field Induced Changes in Biological Tissues and Phantoms By Using Ultrasound

Jagdish Bhatt M.Sc. Candidate Supervisor: Dr. Yuan Xu January 8, 2015

Outline

• Principles of Ultrasound Imaging

• Motivation

• Experimental Methods

• Results

• Conclusions

2

• Future Work

Principles of Ultrasound Imaging

Figure : Basic principles of Ultrasound imaging

J. G. Fox, S. W. Barthold, M. T. Davisson, and A. L. Smith, The Mouse in Biomedical Research Normative Biology, Husbandry, and Model, Second Edition. Burlington: American College of laboratory Animal Medicine series, 2007

• Reflection of sound energy by interfaces and scatters

• Ultrasound waves are reflected from the interfaces when there is change in density or bulk modulus of the material • Echo waves are received by the

transducer to form a A-line.

• Scan the transducer to obtain B mode images.

3

Motivation

• To use ultrasound to image the electric/electro-kinetic properties of biological tissues

• The electric/electro-kinetic properties of tissues

are correlated to the physiological and pathological status of tissues

4

Electro-kinetic Phenomena (EKP)

Motion of particles and fluids under the influence of an electric field:

• Electrophoresis The movement of electrically charged particles (solid, liquid or

gaseous) in an electric field, which is filled with a liquid as second phase.

• Electro-osmosis The movement of a liquid along a solid or a liquid surface driven by an electric field

5

Electrophoresis

𝑣𝑒= −𝜖0𝜖𝑟𝐸𝜁

𝜂

Where, 𝐸 is the electric field strength 𝜁 is the zeta potential 𝜖0 is the permittivity of the vacuum , 𝜖𝑟is the relative permittivity of the liquid, 𝜂 is the coefficient of viscosity of the medium and 𝑣𝑒 is the electrophoretic velocity of the particles.

Figure : Principle of the particle electrophoresis

6

Fel = -EQ Ffr = 6 π η r ve

F. Simon, “Electro-kinetic Phenomena,” Leibniz Institute of Polymer Research, Dresden, Germany, 2009.

Electro-osmosis

7

Figure: The principle of electro-osmosis.

• A. V. Delgado, F. González-Caballero, R. J. Hunter, L. K. Koopal, and J. Lyklema, “Measurement and interpretation of electrokinetic phenomena,” J. Colloid Interface Sci, vol. 309, no. 2, pp. 194–224, May 2007.

• Electro-osmosis, Thomson-Brooks/Cole, 2004

𝑣𝑒𝑜 = 𝜖𝑟𝑠𝜖0𝜁

𝜂𝐸

Where, 𝜖𝑟𝑠 is the relative

permittivity of the electrolytic solution, 𝐸 is the electric field strength 𝜁 is the zeta potential, 𝜂 is the coefficient of viscosity of the medium and 𝜖0 is the permittivity of the vacuum.

The electro osmotic velocity is given by the Smoluchowski equation:

Experimental Methods

Figure 1: Schematic diagram of transducer and sample

Figure2: Experimental setup

O. Doganay and Y. Xu, “The effect of electric current in biological tissues on ultrasound echoes,” 2009 IEEE Int. Ultrason. Symp., pp. 2103–2106, Sep. 2009.

O. Doganay and Y. Xu, “Electric-field induced strain in biological tissues.,” J. Acoust. Soc. Am., vol. 128, no. 5, pp. EL261–7, Nov. 2010. 8

9

Hypothesis and objectives

Hypothesis: • Electric field can induce mechanical changes on biological tissues and ultrasound phantoms

depending on the amplitude, frequency and duration of the applied electric field. • Amplitude of the ultrasound echoes from the tissues can be monitored to reveal the current

distribution in the sample.

Objectives: • Study the electric/electro-kinetic effects in layered tissues (muscle-fat) and phantoms. • Study the electric field induced mechanical changes (EIMC) based on the changes in

amplitude of RF signals, mean of the signal spectrum at the modulation frequency, RMS of the noise in the spectrum and SNR during the application of electric field in tissues and phantoms.

Amplitude change due to electric current

Figure: The echo signals from a piece of bovine muscle tissue before electric current and after electric current application were compared.

O. Doganay and Y. Xu.The effect of electric current in biological tissue on ultrasound echoes, 2010.

11

Experiment phantoms (a) (b)

(c) (d)

Figure: (a) Porcine heart muscle and the gelatin sample. (b) Porcine heart sample fixed with electrodes and placed on the top of the gelatin sample. (c) Porcine heart muscle, fat and the gelatin sample. (d) Porcine heart sample fixed with electrodes and placed on the top of the fat.

12

Data Analysis

1. Amplitude change in various windows with slow time

0 100 200 300 400 500 600 700 800-1

-0.5

0

0.5

1

1.5x 10

-3

Slow time(s)

Am

plitu

de(V

)

Figure: The amplitude change of a porcine heart muscle window. The current applied from 191s to 572s (1.33V/cm and 0.02Hz) for 381s.

13

2.Frequency spectrum of the signal during electric field application

200 250 300 350 400 450 500 550-1

-0.5

0

0.5

1

1.5x 10

-3

slow time(s)

Am

plitu

de(V

)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-4

Frequency (Hz)

Am

p,F

FT

(a) (b)

Figure: (a) A part of a signal of a porcine heart muscle window during electric field application. (b) Frequency spectrum of the signal.

14

3. Mean signal and root mean square value of the noise

(i) Amean = 𝐴𝑖5𝑖=−5

11

Where, Ai is the amplitude corresponding to ith frequency in the spectrum and i is

an integer. Where N is the total number of points (frequencies) between 0.05Hz and 0.25Hz, A is the amplitude of each small peaks corresponding to nth frequencies in the spectrum

(ii) Arms = 1

𝑁 𝐴 𝑛 2

Figure: Schematic representation of the signal and noise in the spectrum

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-4

Frequency (Hz)

Am

p,F

FT

Signal

Noise

15

4. signal-to-noise ratio (SNR)

Signal-to-noise ratio (SNR) = 𝑴𝒆𝒂𝒏 𝒔𝒊𝒈𝒏𝒂𝒍

𝑹𝑴𝑺 𝒏𝒐𝒊𝒔𝒆

Figure: Schematic representation of the signal and noise in the spectrum

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-4

Frequency (Hz)

Am

p,F

FT

Signal

Noise

Samples for experiments

1. Gelatin layer electrically isolated from tissue layer • Longer time experiment using porcine heart muscle and gelatin sample

separated by thin plastic

• Shorter time experiment using porcine heart muscle and gelatin sample separated by thin plastic

2. Gelatin layer in contact with tissue layer • Longer time experiment using layered tissues and phantoms (porcine

heart muscle, fat and gelatin) without using plastic between samples

• Longer time experiment using porcine heart muscle and gelatin sample without using plastic between samples

3. Uniform gelatin phantom

16

17

(A) Ultrasound RF signal, mean of the signal, RMS noise and signal-to-noise ratio

0 20 40 60 80-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Fast time (µs)

Ech

o A

mpl

itude

(mV

)

a

Figure: (a) Ultrasound RF signal versus fast time (20.29 µs/30.20 µs/37.73 µs corresponds to the front, mid and rear boundaries). (b) Mean of the signal. (c) Root mean square (RMS) of the noise. (d) Signal-to-noise ratio (SNR) with fast time.

20 25 30 35 400

2

4

6

8

10

Fast time (µs)

SN

R

d

20 25 30 35 400

1

2

3

4

5

6x 10

-4

Fast time (µs)

Am

plitu

de(V

)

c

RMS noise

20 25 30 35 400

0.2

0.4

0.6

0.8

1

1.2x 10

-3

Fast time (µs)

Am

plitu

de(V

)

b

Mean signal

1. Results of gelatin layer electrically isolated from tissue layer (i) Longer time experiment using porcine heart muscle and gelatin sample

Muscle

Gel

18

(B) Amplitude versus slow time and their spectrums during electric field

Figure: (a), (c) and (e) are amplitude changes of porcine heart windows 42, 50 and 51. (b), (d) and (f) are frequency spectrums during electric current of pork heart windows 42, 50 and 51 respectively.

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

slow time(s)

Am

plit

ude(V

)

a

Pork muscle 42

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

c

Pork 50

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

e

pork 51

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

b

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

d

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

f

Start of current — 209s End of current — 1223s

19

Amplitude versus slow time and their spectrums during electric field

Continued..

Figure: (g), (i) and (h), (j) are amplitude changes and frequency spectrums of gelatin windows 112 and 115 respectively.

0 500 1000 1500-6

-4

-2

0

2

4

6x 10

-4

Slow time(s)

Am

plit

ude(V

)

g

Gel 112

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-5

Frequency (Hz)

Am

p,F

FT

h

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

i

Gel 115

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-5

Frequency (Hz)

Am

p,F

FT

j

20

(A) Ultrasound RF signal, mean of the signal, RMS noise and signal-to-noise ratio

0 20 40 60 80-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Fast time (µs)

Ech

o A

mpl

itude

(mV

)

a

Figure: (a) Ultrasound RF signal versus fast time (17.37 µs/27.24 µs/32.9 µs corresponds to the front, mid and rear boundaries). (b) Mean of the signal. (c) Root mean square (RMS) of the noise. (d) Signal-to-noise ratio (SNR) with all the windows

18 20 22 24 26 28 30 32 34

0.5

1

1.5

2

2.5

3

3.5x 10

-4

Fast time (µs)

Am

plitu

de (

V)

b

Mean signal

18 20 22 24 26 28 30 32 34

0.5

1

1.5

2

2.5

3

3.5

4x 10

-4

Fast time (µs)

Am

plit

ude (

V)

c

RMS noise

18 20 22 24 26 28 30 32 340

1

2

3

4

5

6

Fast time (µs)

SN

R

d

(ii) Shorter time experiment using porcine heart muscle and gelatin sample

21

(B). Amplitude versus slow time and their spectrums during electric field

Figure: (a), (c) and (e) are amplitude changes of porcine heart windows 46, 47 and 50. (b), (d) and (f) are frequency spectrums during electric current of porcine heart windows 46, 47 and 50 respectively.

0 100 200 300 400 500 600 700 800-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plitu

de(V

)

a

Pork 46

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

b

0 200 400 600 800-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

c

Pork 47

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

d

0 100 200 300 400 500 600 700 800-1

-0.5

0

0.5

1

1.5x 10

-3

Slow time(s)

Am

plit

ude(V

)

e

Pork 50

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-4

Frequency (Hz)

Am

p,F

FT

f

Start of current — 191s End of current — 572s

22

Amplitude versus slow time and their frequency spectrums during electric field

Continued..

Figure: (g) and (h) are the comparison of amplitude change of porcine heart muscle window 47 and 50 and their frequency spectrums during electric current. (i), (k) and (j), (l) are amplitude changes of gelatin window 97 and 102 and their frequency spectrums respectively.

0 200 400 600 800-1

-0.5

0

0.5

1

1.5x 10

-3 g

Pork 47

Pork 50

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4

5

6x 10

-4

Frequency (Hz)

Am

p,

FF

T

h

Pork 47

Pork 50

0 200 400 600 800-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

i

Gel 97

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

2

4

6

8x 10

-5

Frequency (Hz)

Am

p,F

FT

j

0 200 400 600 800-6

-4

-2

0

2

4

6x 10

-4

Slow time(s)

Am

plit

ude(V

)

K

Gel 102

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-5

Frequency (Hz)

Am

p,F

FT

L

23

(A) Ultrasound RF signal, mean of the signal, RMS noise and signal-to-noise ratio

0 20 40 60 80-1

-0.5

0

0.5

1

Fast time (µs)

Ech

o A

mpl

itude

(mV

)

a

Figure: (a) Ultrasound RF signal versus fast time (18.51 µs/27.29µs/31.38 µs/37.31µs corresponds to the front, muscle-fat, fat-gelatin and rear boundaries) (b) Mean of the signal. (c) Root mean square (RMS) of the noise. (d) Signal-to-noise ratio (SNR) with all the windows.

18 20 22 24 26 28 30 32 34 36 380

0.5

1

1.5

2x 10

-3

Fast time (µs)

Am

plitu

de (

V)

b

Mean signal

18 20 22 24 26 28 30 32 34 36 380

1

x 10-4

Fast time (µs)

Am

plitude (V

)

c

RMS noise

18 20 22 24 26 28 30 32 34 36 380

5

10

15

20

25

30

Fast time (µs)

SN

R

d

2. Results of gelatin layer in contact with tissue layer (i) Longer time experiment using porcine heart muscle, fat and gelatin

Muscle

Fat Gel

24

(B). Amplitude versus slow time and their spectrums during electric field

Figure: (a), (c) and (b), (d) are the amplitude change signal of the porcine heart muscle window 35 and 36 and their frequency spectrums respectively. (e) and (f) are amplitude change signal of fat window 106 and it’s frequency spectrum.

0 200 400 600 800 1000 1200 1400 1600-1.5

-1

-0.5

0

0.5

1x 10

-3

slow time(s)

Am

plit

ude(V

)

a

Pork 35

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

2

4

6x 10

-4

Frequency (Hz)

Am

p,F

FT

b

0 200 400 600 800 1000 1200 1400 1600-2

-1

0

1x 10

-3

slow time(s)

Am

plit

ude(V

)

c

Pork 36

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

2

4

6x 10

-4

Frequency (Hz)

Am

p,F

FT

d

0 200 400 600 800 1000 1200 1400 1600-1

-0.5

0

0.5

1x 10

-3

slow time(s)

Am

plit

ude(V

)

e

Fat 106

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

2

4

6

8x 10

-5

Frequency (Hz)

Am

p,F

FT

f

Start of current — 217s End of current — 1382s

25

Amplitude versus slow time and their spectrums during electric field

Continued..

Figure: (g) and (h) are the amplitude change signal of the fat window 108 and it’s frequency spectrum. (i), (k) and (j), (l) are the amplitude change signal of gelatin window 127 and 133 and their frequency spectrums respectively.

0 200 400 600 800 1000 1200 1400 1600-1

-0.5

0

0.5

1x 10

-3

slow time(s)

Am

plit

ude(V

)

g

Fat 108

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

2

4

6

8x 10

-5

Frequency (Hz)

Am

p,F

FT

h

0 200 400 600 800 1000 1200 1400 1600-1

-0.5

0

0.5

1x 10

-3

slow time(s)

Am

plit

ude(V

)

i

Gel 127

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

0.2

0.4

0.6

0.8

1x 10

-4

Frequency (Hz)

Am

p,F

FT

j

0 200 400 600 800 1000 1200 1400 1600-5

0

5x 10

-4

slow time(s)

Am

plitu

de(V

)

k

Gel 133

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

2

4

6x 10

-5

Frequency (Hz)

Am

p,F

FT

l

26

(A) Ultrasound RF signal, mean of the signal, RMS noise and signal-to-noise ratio

0 20 40 60 80-1

-0.5

0

0.5

1

Fast time (µs)

Echo A

mplit

ude(m

V)

a

Figure: (a) Ultrasound RF signal versus fast time (19.45 µs/26.54 µs/32.79 µs corresponds to the front, mid and rear boundaries). . (b) Mean of the signal. (c) Root mean square (RMS) of the noise. (d) Signal-to-noise ratio (SNR) with fast time.

20 22 24 26 28 30 32 340

1

2

3

4

5

x 10-4

Fast time (µs)

Am

plitu

de (

V)

c

RMS noise

20 22 24 26 28 30 32 34

0

2

4

6

8

10

12

x 10-4

Fast time (µs)

Am

plit

ude (

V)

b

Mean signal

20 22 24 26 28 30 32 340

2

4

6

Fast time (µs)

SN

R

d

(ii). Longer time experiment using porcine heart muscle and gelatin sample without using plastic between samples

27

(B). Amplitude versus slow time and their spectrums during electric field

Figure: (a), (c) and (b), (d) are amplitude changes and frequency spectrums of porcine heart muscle windows 41 and 40 respectively.

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plitu

de(V

)

a

Pork 41

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

x 10-4

Frequency (Hz)

Am

p,F

FT

b

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plitu

de(V

)

c

Pork 40

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

1

2

3

4x 10

-4

Frequency (Hz)

Am

p,F

FT

d

Start of current — 184s End of current — 1243s

28

Amplitude versus slow time and their frequency spectrums during electric field

Continued..

Figure: (e), (g) and (f), (h) are amplitude changes and frequency spectrums of gelatin windows 83 and 86 respectively.

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

e

Gel 83

0 0.1 0.2 0.3 0.4 0.50

2

4

6

8x 10

-5

Frequency (Hz)

Am

p,F

FT

f

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plit

ude(V

)

g

Gel 86

0 0.1 0.2 0.3 0.4 0.50

1

2

3

4x 10

-5

Frequency (Hz)

Am

p,F

FT

h

29

3. Single Gelatin Experiment (A) Ultrasound RF signal, mean of the signal, RMS noise and signal-to-noise ratio

0 20 40 60 80-1

-0.5

0

0.5

1

Fast time (µs)

Echo A

mplitu

de(m

V)

a

20 22 24 26 28 300

1

2

3

4

5

6x 10

-4

Fast time (µs)

Am

plitu

de (

V)

b

Mean signal

20 22 24 26 28 300

1

2

3

4

5

6x 10

-4

Fast time (µs)

Am

plitu

de (

V)

c

RMS noise

20 22 24 26 28 300

1

2

3

4

5

Fast time (µs)

SN

R

d

• SNR varies even in a homogeneous sample! Figure: (a) Ultrasound RF signal with fast time (b) Mean of the signal (c) RMS of the noise (d) SNR with fast time

30

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plitu

de(V

)

a

Gel 48

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

0.2

0.4

0.6

0.8

1

1.2x 10

-4

Frequency (Hz)

Spectr

um

Am

plitu

de

b

0 500 1000 1500-1

-0.5

0

0.5

1x 10

-3

Slow time(s)

Am

plitu

de(V

)

c

Gel 49

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.450

0.5

1

1.5x 10

-4

Frequency (Hz)

Spectr

um

Am

plitu

de

d

(B). Amplitude versus slow time and their spectrums during electric field

Figure: (a), (c) and (b), (d) are the amplitude changes and frequency spectrums of the gelatin windows 48 and 49 respectively

Start of current — 191s End of current — 1251s

31

Conclusions • The effect of electric field in layered phantoms was quantified by finding the

frequency spectrums, mean amplitude of the signals, root mean square of the noise and Signal-to-noise ratio . SNR was found to be the best measure to demonstrate the current distribution in tissues and phantoms.

• The SNR was compared in both cases when the samples were separated and not

separated by the insulator (thin plastic). There was significant difference in SNR between the different parts of the sample when there was insulator. However, the difference is much smaller when there was no plastic between samples.

32

Future Work

• In future, the two dimensional method, B-mode ultrasound can be investigated for the better understanding of the EIMC SNR in tissue and samples during electric field application.

• In the future study, it would be interesting to investigate quantitatively the dependence of EIMC SNR on the current distribution in the samples. If the current distribution in a sample can be measured, it is possible to reconstruct the electric impedance of the sample, which can provide useful diagnostic information.

33

Acknowledgements

Supervisor: Dr. Yuan Xu Committee Members: Dr. Vladislav Toronov Dr. Jahan Tavakkoli

34

Thank you !