Transcript Slide 1

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EARLY DETECTION OF
MALIGNANT TUMORS USING
MAGNETICLY INDUCED
PRESSURE WAVES
Idan Steinberg - 25.11.2010
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Early detection of malignant tumors
Cancer is responsible for almost 25%
of all deaths in the US! [1]
Most common types of cancer in
developed countries are: Lung,
breast, prostate and colon [2].
Early detection of cancer greatly
improves patient survival and quality
of life. e.g: Kakinuma R. has shown
that regular screening tests for lung
cancer improved the 5-year survival
rates from 49% to 84%! [3]
5-yearEstimated
relative survival
patients
numbers rates
of newamong
cancer cases
diagnosed
with
cancersin2005
4[]
(incidence)
andselected
deaths (mortality)
2002][1
Introduction
Model
Theoretical
Results
Experiments
Summary
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Existing methods for screening
Method
Advantages
Drawbacks
Mammography
Relatively
accurate
Ionizing radiation,
Uncomfortable
PSA +
Physical exam
Very simple, Low
cost and low risk
Very high false positives
Colonoscopy
Actual view of the Uncomfortable, Risk of
colon, Samples
complications
Occult blood
Very simple, Low
cost and low risk
Low accuracy
CT-Scan
Accurate
High doses of Ionizing
radiation, Expensive
MRI
Accurate, Non
ionizing radiation
Extremely expensive,
Needs special housing
Introduction
Model
Theoretical
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Experiments
Summary
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Magneto-Acoustic detection
Phase I:
Nano-particles injection
Tumor
Phase II:
Magneto-Acoustic detection
Acoustic
probe
External
Magnetic field
Tumor with
conjugated MNP
acting as acoustic
dipole
Antibody
conjugated MNP
solution
Introduction
Model
Theoretical
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Experiments
Summary
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Research Goals
To date, no method exists for early detection of cancer that
is general, accurate, low cost and has high throughput.
To overcome the drawbacks of existing methods, we propose
a new method for early cancer detection which is based upon
magneto-acoustic detection of tumor specific superparamagnetic nano-particles.
The goal of this research is to provide a theoretical
& experimental Proof of Concept of such a method
Introduction
Model
Theoretical
Results
Experiments
Summary
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Magneto-Acoustic analytic model
To asses the feasibility, an analytic models was developed &
validated by comparison to both FEM model and experiments
Analytic model allows the understanding and optimization
of the system
Model
assumptions:
Analytic
model allows the understanding and optimization
1. Axial symmetry
system
2. Spherical rigid tumor
Introduction
Model
Theoretical
Results
Experiments
of the
Summary
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Model structure
Solenoid Geometrical
Parameters
Ri , DW , NR , NZ
1b
Magnetic Flux Model
Magnetic
Flux Density
3
Bz  z, t 
Solenoid
Current
I S t 
1a
Inductance Model
Solenoid Electrical
RS , LS
Parameters
2
Magnetic Force
Model
Electrical Circuit
Model
Magnetic F z, t

M 
Force
4
Mechanical Forces
Model
Tumor
Acceleration
Electromagnetic
N t   I S t 
Noise
A t 
5
Acoustic Model
Acoustic
Pressure
P  r , z, t 
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Acoustic Sensor
Model
Acoustic
Signal
S t 
Introduction
Model
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Experiments
Summary
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Magnetic flux generated by a solenoid
Axial magnetic flux of a single current loop:
For multiple windings - integrate with respect to z and R:
For the flux gradient - differentiate with respect to z :
Results
Introduction
Model
Theoretical
Results
Experiments
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Magnetic forces acting on the tumor
Langevin dynamics predicts the magnetization of the tumor
volume:
The magnetic body force on the entire tumor results from
minimal energy considerations:
Results
Introduction
Model
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Experiments
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Mechanical forces & The equation of motion
Mechanical forces are surface forces:
•
Elastic retention force of the displaced tissue
•
Drag force due to tumor speed
Under the assumptions of rigid and spherical tumor the two
forces can be expressed as:
Combining all three force together with Newton's second law
yields a non linear, second order differential equation:
Results
Introduction
Model
Theoretical
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Acoustic pressure field
The acoustic pressure field is calculated by the scalar wave equation.
Tumor induced motion creates an acoustic dipole source term.
Solution by separation of variables:
Results
Introduction
Model
Theoretical
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Experiments
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Acoustic sensor model
The measured signal from the acoustic sensor is due to:
1. Acoustic signal proportional to the acceleration of the skin:
2. Additive EM noise from the solenoids: NEM(t)=Is(t)*Hm
3. Additive measurement white noise: Nw(t)
The sum is convolved with the sensor transfer function: Hs
Results
Introduction
Model
Theoretical
Results
Experiments
Summary
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Simulated magnetic flux density
The model and FEM both predicts
the rapid decay of the magnetic field
FEM confirms that the
effect of deviations from
the symmetry axis is small
Model 
Introduction
Model
Theoretical
Results
Experiments
Summary
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Simulated magnetic force
For the magnetic flux operating
point, the magnetization is well
within the linear range
Maximal force is achieved
0.5 mm after the solenoid.
The magnetic force decays
exponentially with distance.
Model 
Introduction
Model
Theoretical
Results
Experiments
Summary
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Simulated time-varying forces
Force amplitude varies from 20 N/m3 up to 200 N/m3
and higher. The magnetic force is the dominant force.
The elastic force determines the equilibrium displacement.
Introduction
Model
Theoretical
Results
Experiments
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Simulated motion of the tumor
The displacement is practically constant & in the
nm scale. The velocity is one order of magnitude
higher (still very small). The acceleration is much Model 
higher and measurable.
Introduction
Model
Theoretical
Results
Experiments
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Simulated pressure field
Tumor
location
Model 
Introduction
Model
Theoretical
Results
Experiments
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Simulated acoustic signal
The acoustic signal presents a series of alternating
peaks. for deeper the tumors, the peaks are smaller
and more spread. Also, the delay is greater.
Introduction
Model
Theoretical
Results
Experiments
Summary
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Experimental setup I
Aim: measurement of the electrical properties of the solenoids
Method : Inductance was measured at 36 kHz using a Wheatstone
bridge circuit.
Introduction
Model
Theoretical
Results
Experiments
Discussion
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Experiment I - results
Solenoids 1,2 do not fit the model predictions due
to problems in production. Solenoids 3,4 accurately
fit the model (less 5% error)
Introduction
Model
Theoretical
Results
Experiments
Discussion
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Experimental setup II
Aim: measurement of the magnetic field of the solenoids
Method : Measurements were taken using a fluxmeter
at various points in space with different axial and radial
distances.
Introduction
Model
Theoretical
Results
Experiments
Discussion
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Experiment II - results
Solenoids 3,4 generate almost equal magnetic fields
which are in accordance with the model. Deviations
from the 95% confidence intervals only occur close
to the solenoids due to fringe effects.
Introduction
Model
Theoretical
Results
Experiments
Summary
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Experiment II - results - cont.
The radial dependence of the magnetic field is
negligible (less then 5% at 5 mm radial distance).
This effect allows the calculation of the field only
on the symmetry axis.
Introduction
Model
Theoretical
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Experimental setup III
Aim: measurement of the magnetic force acting on
MNPs immersed in a diamagnetic solution (Feridex®).
Method : MNP solution was weighted with an accurate
laboratory weight.
Introduction
Model
Theoretical
Results
Experiments
Summary
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Experiment III - results
Again, measurements correlate very well with the
theoretical model. Small deviations only occur at close
distances. The magnetic force decays rapidly (faster then
a mono-exponent) affecting the depth of detection
Introduction
Model
Theoretical
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Experimental setup IV
Aim: measurement of the acoustic signal received from a
phantom of the tissue and MNP conjugated tumor.
Method : Measurements were performed on an agar tissue
phantom inside an acoustic bath. Signal was measured without
magnetic field, without tumor phantom and with both.
Solenoid 2
Acoustic
sensor
DC PSU
Amplifier
Power
Signal
Oscilloscope
A\D
Acoustic bath +
tumor phantom
Modulator
Solenoid 1
ch1
ch2
Trigger
Introduction
Model
Theoretical
Results
Experiments
Summary
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Experiment IV - results
Estimation of the EM noise using a 10-th order moving average
is good at low frequencies. The estimated acoustic signal is a
bit noisy but still clearly presents the typical peak structure
predicted by the model.
Introduction
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Experiment IV - results - cont.
The Root Mean Square of Differences between the estimated
acoustic signal and the model is 8%. Comparing the model with
the estimated acoustic signal in the absence of the tumor
phantom results in an RMSD measure of 35%!
Introduction
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Summary
1. Magneto-Acoustic detection was proved to be feasible
both theoretically and experimentally
2. Extensive analytic and numeric models were developed
3. Based on the analytic model an experimental setup
was optimized and built
4. The model predict accurately the results of all
laboratory experiments
5. Magneto-Acoustic detection shows great promise for
quick detection of deep tumors (up to a few cm
beneath the skin)
Introduction
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Future Work
Three main goals to be achieved:
1. Estimation of tumor parameters:
size
depth
location (e.g. by triangulation)
2. increase test efficiency (higher fields, multiple
sensors, robust signal processing algorithm)
3. In-vitro & In-vivo experiments up to clinical trials
Introduction
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Theoretical
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Reference
1. Parkin, D. M. et al. CA Cancer J Clin 2005;55:74-108.
2. J. L. Mulshine, M.D. and D. C. Sullivan, M.D. N Engl J Med 2005;352:2714-20.
3. Kakinuma R. et al. Proceedings of the Lung Cancer Workshop, Tokyo,
November 7, 2003:18.
4. Kalambur V S, Han B, Hammer B E, Shield T W and Bischof J C 2005 In vitro
characterization of movement, heating and visualization of magnetic
nanoparticles for biomedical applications Nanotechnology 16 1221–33
5. Akira I. et al. Magnetite nanoparticle - loaded anti-HER2 immunoliposomes,
for combination of antibody therapy with hyperthermia, Cancer Letters 212
(2004) 167–175
6. Shinkai M. et al. Targeting Hyperthermia for Renal Cell Carcinoma Using
Human MN Antigen specific Magnetoliposomes. Jpn. J. Cancer Res. 92,
1138–1146, 2001
7. Biao L.E. et al , Preparation of tumor-specific magnetoliposomes and their
application for hyperthermia, Chem. Eng. Jpn, 2001
Introduction
Model
Theoretical
Results
Experiments
Summary
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Super-Paramagnetic Nano-Particles (MNPs)
Ferromagnetic: High magnetization, Many domains, Hysteresis
Super-paramagnetic: High magnetization, 1 domain, No hysteresis
Introduction
Model
Theoretical
Results
Experiments
Summary
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Tumor Targeting
MNPs are made of iron oxide core (~10 nm diameter) with
different biocompatible coatings [4].
Nano–particles are small enough to diffuse from the blood vessel
into the tissue.
Conjugated antibodies allows for targeting different cancer types:
• HER2 - Breast Cancer[5].
• MN - renal cell carcinoma [6]
• U251- SP (G22 antibody) - Glioma [7]
Antibody
Coating
SPM Core
Introduction
Model
Theoretical
Results
Experiments
Summary
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Comparison with other MNP based methods
Scan
Accuracy
Times
Depth
MRI scans with MNPs as
contrast agents [53]
1/2 Hr
1 mm
Tens of
cm
Thermography with
MNP specific heating [15]
1 Hr
A few mm
1 cm
Low
Point of Care
Ultrasound scans with PFC
[55]
A few
minutes
1 cm
A few cm
Low
Medical Center
High
Special Housing
Medium
Medical Center
Low
Point of Care
Method
Ultrasound excitation of
asymmetric MNPs with
1/2 Hr A few mm A few cm
Magnetic measurements [57]
Doppler measurements of
A few
magnetically excited MNPs
1 cm
A few cm
minutes
[14]
This work - Measurements of
pressure waves induced by
<1 Min Unknown Unknown
magnetically excited MNPs
Introduction
Model
Theoretical
Results
Cost
Placement
Very High Special Housing
Experiments
Summary
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Solenoid design
Solenoid design posses some challenges to the designer:
1. Large number of windings: magnetic field/Ampere ↑,
current ↓.
2. No good model for inductance.
3. Hysteresis loss & eddy currents at the magnetic core,
Skin effect, Capacitance between windings
Results
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Theoretical
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Summary
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Solenoid optimization
The model predicts an optimal number of windings. Optimization
criterion was maximal force applied on 3cm deep tumor.
Model 
Introduction
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Results
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Summary
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Limitations
1. High Electro-Magnetic noise limits
measurement accuracy. A possible solution is
the use of an acoustic waveguide to distance
the sensor.
2. The method only applies to solid tumors, with
known specific antigens.
3. Organs filled with air or other fluids will block
the acoustic signal
Introduction
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Example application
Breast tissue is flattened out between the two solenoid Breast
tissue is flattened out between the two solenoids in a similar
fashion to mammography. Then an alternating magnetic field is
applied. A single or multiple acoustic sensors can then pick the
signal on the breast surface. s in a similar fashion to
mammography. Then an alternating magnetic field is applied. A
single or multiple acoustic sensors can then pick the signal on the
Breast tissue is flattenedbreast
out between
surface. the two solenoids in a
similar fashion to mammography. Then an alternating
magnetic field is applied. A single or multiple acoustic sensors
can then pick the signal on the breast surface.
Introduction
Model
Theoretical
Results
Experiments
Summary