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EARLY DETECTION OF EARLY DETECTION OF MALIGNANT TUMORS USING MALIGNANT TUMORS USING

MAGNETICLY INDUCED MAGNETICLY INDUCED PRESSURE WAVESPRESSURE WAVES

Idan Steinberg - 25.11.2010Idan Steinberg - 25.11.2010

Introduction

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Early detection of malignant tumorsCancer 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].

Estimated numbers of new cancer cases (incidence) and deaths (mortality) in

2002 [1]

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]

Model Experiments Summary

5-year relative survival rates among patients diagnosed with selected cancers 2005 [4]

Theoretical Results

Introduction

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Existing methods for screeningMethodAdvantagesDrawbacks

MammographyRelatively accurate

Ionizing radiation, Uncomfortable

PSA + Physical exam

Very simple, Low cost and low risk

Very high false positives

ColonoscopyActual view of the colon, Samples

Uncomfortable, Risk of complications

Occult bloodVery simple, Low cost and low risk

Low accuracy

CT-ScanAccurate High doses of Ionizing radiation, Expensive

MRIAccurate, Non ionizing radiation

Extremely expensive, Needs special housing

Model Experiments SummaryTheoretical Results

Introduction

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Magneto-Acoustic detection Phase I:

Nano-particles injection

Antibody conjugated MNP solution

Tumor

Tumor with conjugated MNPacting as acoustic dipole

Acoustic probe

Phase II:Magneto-Acoustic detection

External Magnetic field

Model Experiments SummaryTheoretical Results

Introduction

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Research Goals

The goal of this research is to provide a theoretical & experimental Proof of Concept of such a method

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 super-paramagnetic nano-particles.

Model Experiments SummaryTheoretical Results

Introduction

Analytic model allows the understanding and optimization of the system

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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

Model assumptions: 1. Axial symmetry2. Spherical rigid tumor

Model Experiments SummaryTheoretical Results

Analytic model allows the understanding and optimization of the system

Introduction

7 Model structure Solenoid Geometrical

Parameters

Inductance ModelMagnetic Flux Model

Electrical Circuit Model

,zB z t

, , ,i W R ZR D N N

,S SR L

SI t

Solenoid Current

Solenoid Electrical Parameters

Magnetic Force Model

Mechanical Forces Model

Acoustic ModelAcoustic Sensor

Model

Magnetic Flux Density

Tumor Acceleration

,MF z tMagnetic Force

A t

Acoustic Pressure

, ,P r z t

SN t I tElectromagnetic

Noise

Acoustic Signal

S t

1b

3

1a

2

4

5 6

Model Experiments SummaryTheoretical Results

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Magnetic flux generated by a solenoid

Introduction Model Experiments Summary

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 :

Theoretical Results

Results

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Magnetic forces acting on the tumor

The magnetic body force on the entire tumor results from minimal energy considerations:

Langevin dynamics predicts the magnetization of the tumor volume:

Introduction Model Experiments SummaryTheoretical Results

Results

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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:

Introduction Model Experiments Summary

Combining all three force together with Newton's second law yields a non linear, second order differential equation:

Theoretical Results

Results

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Acoustic pressure fieldThe acoustic pressure field is calculated by the scalar wave equation. Tumor induced motion creates an acoustic dipole source term.

Solution by separation of variables:

Introduction Model Experiments SummaryTheoretical Results

Results

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Acoustic sensor model

Introduction Model Experiments SummaryTheoretical Results

1. Acoustic signal proportional to the acceleration of the skin:

The measured signal from the acoustic sensor is due to:

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

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Simulated magnetic flux density

Introduction Model Theoretical Results Experiments Summary

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

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Simulated magnetic force

Introduction Model Theoretical Results Experiments Summary

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

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Simulated time-varying forces

Introduction Model Theoretical Results Experiments Summary

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.

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Simulated motion of the tumor

Introduction Model Theoretical Results Experiments Summary

The displacement is practically constant & in the nm scale. The velocity is one order of magnitude higher (still very small). The acceleration is much higher and measurable.

Model

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Simulated pressure field

Introduction Model Experiments SummaryTheoretical Results

Tumor location

Traveling

wave

Standing wave

Model

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Simulated acoustic signal

Introduction Model Experiments SummaryTheoretical Results

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.

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Experimental setup I

Introduction Model Experiments DiscussionTheoretical Results

Aim: measurement of the electrical properties of the solenoids Method : Inductance was measured at 36 kHz using a Wheatstone bridge circuit.

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Experiment I - results

Introduction Model Experiments DiscussionTheoretical 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)

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Experimental setup II

Introduction Model Experiments DiscussionTheoretical Results

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.

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Experiment II - results

Introduction Model Experiments SummaryTheoretical 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.

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Experiment II - results - cont.

Introduction Model Experiments SummaryTheoretical Results

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.

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Experimental setup III

Introduction Model Experiments SummaryTheoretical Results

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.

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Experiment III - results

Introduction Model Experiments SummaryTheoretical 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

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Experimental setup IV

Introduction Model Experiments SummaryTheoretical Results

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.

DC PSU

Modulator

Amplifier

Oscilloscope A\D

ch1 ch2

Signal

Acoustic sensor

Solenoid 1

Solenoid 2

Trigger

Power

Acoustic bath + tumor phantom

27 Experiment IV - results

Introduction Model Experiments SummaryTheoretical 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.

28 Experiment IV - results - cont.

Introduction Model Experiments SummaryTheoretical Results

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%!

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Summary1. Magneto-Acoustic detection was proved to be feasible

both theoretically and experimentally 2. Extensive analytic and numeric models were developed3. Based on the analytic model an experimental setup

was optimized and built4. The model predict accurately the results of all

laboratory experiments5. Magneto-Acoustic detection shows great promise for

quick detection of deep tumors (up to a few cm beneath the skin)

Introduction Model Experiments SummaryTheoretical Results

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Future WorkThree 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 Model Experiments SummaryTheoretical Results

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Reference1. 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 Experiments SummaryTheoretical Results

Introduction

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Super-Paramagnetic Nano-Particles (MNPs)

Ferromagnetic: High magnetization, Many domains, HysteresisSuper-paramagnetic: High magnetization, 1 domain, No hysteresis

Model Experiments SummaryTheoretical Results

Introduction

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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

Model Experiments SummaryTheoretical Results

Introduction

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Comparison with other MNP based methods

Model Experiments SummaryTheoretical Results

MethodScanTime

s

Accuracy

DepthCostPlacement

MRI scans with MNPs as contrast agents [53]

1/2 Hr1 mmTens of

cmVery High

Special Housing

Thermography withMNP specific heating [15]

1 HrA few mm1 cmLowPoint of Care

Ultrasound scans with PFC [55]

A few minutes

1 cmA few cmLowMedical Center

Ultrasound excitation of asymmetric MNPs with Magnetic measurements [57]

1/2 HrA few mmA few cmHighSpecial Housing

Doppler measurements of magnetically excited MNPs [14]

A few minutes

1 cmA few cmMediumMedical Center

This work - Measurements of pressure waves induced by magnetically excited MNPs

<1 MinUnknownUnknownLowPoint of Care

Introduction

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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

Model Experiments SummaryTheoretical Results

Results

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Solenoid optimization

Introduction Model Theoretical Results Experiments Summary

The model predicts an optimal number of windings. Optimization criterion was maximal force applied on 3cm deep tumor.

Model

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Limitations1. 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 Model Experiments SummaryTheoretical Results

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 surface.

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Example application

Introduction Model Experiments SummaryTheoretical Results

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.