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1. Introduction 2 Early detection of malignant tumors Cancer is responsible for almost 25% of all deaths in the US! [1] Most common types of cancer in.

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Presentation on theme: "1. Introduction 2 Early detection of malignant tumors Cancer is responsible for almost 25% of all deaths in the US! [1] Most common types of cancer in."— Presentation transcript:

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2 Introduction 2 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]. 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] ModelExperimentsSummary 5-year relative survival rates among patients diagnosed with selected cancers 2005 [4] Theoretical Results

3 Introduction 3 Existing methods for screening DrawbacksAdvantagesMethod Ionizing radiation, Uncomfortable Relatively accurate Mammography Very high false positivesVery simple, Low cost and low risk PSA + Physical exam Uncomfortable, Risk of complications Actual view of the colon, Samples Colonoscopy Low accuracyVery simple, Low cost and low risk Occult blood High doses of Ionizing radiation, Expensive AccurateCT-Scan Extremely expensive, Needs special housing Accurate, Non ionizing radiation MRI ModelExperimentsSummary Theoretical Results

4 Introduction 4 Magneto-Acoustic detection Phase I: Nano-particles injection Antibody conjugated MNP solution Tumor Tumor with conjugated MNP acting as acoustic dipole Acoustic probe Phase II: Magneto-Acoustic detection External Magnetic field ModelExperimentsSummary Theoretical Results

5 Introduction 5 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. ModelExperimentsSummary Theoretical Results

6 Introduction Analytic model allows the understanding and optimization of the system 6 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 symmetry 2.Spherical rigid tumor ModelExperimentsSummary Theoretical Results Analytic model allows the understanding and optimization of the system

7 Introduction 7 Model structure ModelExperimentsSummary Theoretical Results

8 8 Magnetic flux generated by a solenoid IntroductionModelExperimentsSummary 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

9 9 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: IntroductionModelExperimentsSummary Theoretical Results

10 10 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: IntroductionModelExperimentsSummary Combining all three force together with Newton's second law yields a non linear, second order differential equation: Theoretical Results

11 11 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: IntroductionModelExperimentsSummary Theoretical Results

12 12 Acoustic sensor model IntroductionModelExperimentsSummary Theoretical 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: N EM (t)=I s (t)*H m 3. Additive measurement white noise: N w (t) The sum is convolved with the sensor transfer function: H s Results

13 13 Simulated magnetic flux density IntroductionModel Theoretical Results ExperimentsSummary 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

14 14 Simulated magnetic force IntroductionModel Theoretical Results ExperimentsSummary 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

15 15 Simulated time-varying forces IntroductionModel Theoretical Results ExperimentsSummary Force amplitude varies from 20 N/m 3 up to 200 N/m 3 and higher. The magnetic force is the dominant force. The elastic force determines the equilibrium displacement.

16 16 Simulated motion of the tumor IntroductionModel Theoretical Results ExperimentsSummary 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

17 17 Simulated pressure field IntroductionModelExperimentsSummary Theoretical Results Tumor location Traveling wave Standing wave  Model

18 18 Simulated acoustic signal IntroductionModelExperimentsSummary Theoretical 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.

19 19 Experimental setup I IntroductionModelExperimentsDiscussion Theoretical Results Aim: measurement of the electrical properties of the solenoids Method : Inductance was measured at 36 kHz using a Wheatstone bridge circuit.

20 20 Experiment I - results IntroductionModelExperimentsDiscussion Theoretical 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)

21 21 Experimental setup II IntroductionModelExperimentsDiscussion Theoretical 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.

22 22 Experiment II - results IntroductionModelExperimentsSummary Theoretical 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.

23 23 Experiment II - results - cont. IntroductionModelExperimentsSummary Theoretical 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.

24 24 Experimental setup III IntroductionModelExperimentsSummary Theoretical 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.

25 25 Experiment III - results IntroductionModelExperimentsSummary Theoretical 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

26 26 Experimental setup IV IntroductionModelExperimentsSummary Theoretical 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.

27 27 Experiment IV - results IntroductionModelExperimentsSummary Theoretical 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 28 Experiment IV - results - cont. IntroductionModelExperimentsSummary Theoretical 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%!

29 29 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) IntroductionModelExperimentsSummary Theoretical Results

30 30 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 IntroductionModelExperimentsSummary Theoretical Results

31 31

32 32 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 IntroductionModelExperimentsSummary Theoretical Results

33 Introduction 33 Super-Paramagnetic Nano-Particles (MNPs) Ferromagnetic: High magnetization, Many domains, Hysteresis Super-paramagnetic: High magnetization, 1 domain, No hysteresis ModelExperimentsSummary Theoretical Results

34 Introduction 34 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 ModelExperimentsSummary Theoretical Results

35 Introduction 35 Comparison with other MNP based methods ModelExperimentsSummary Theoretical Results PlacementCostDepthAccuracy Scan Times Method Special HousingVery High Tens of cm 1 mm1/2 Hr MRI scans with MNPs as contrast agents [53] Point of CareLow1 cmA few mm1 Hr Thermography with MNP specific heating [15] Medical CenterLowA few cm 1 cm A few minutes Ultrasound scans with PFC [55] Special HousingHighA few cmA few mm1/2 Hr Ultrasound excitation of asymmetric MNPs with Magnetic measurements [57] Medical CenterMediumA few cm1 cm A few minutes Doppler measurements of magnetically excited MNPs [14] Point of CareLowUnknown <1 Min This work - Measurements of pressure waves induced by magnetically excited MNPs

36 Introduction 36 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 ModelExperimentsSummary Theoretical Results

37 37 Solenoid optimization IntroductionModel Theoretical Results ExperimentsSummary The model predicts an optimal number of windings. Optimization criterion was maximal force applied on 3cm deep tumor.  Model

38 38 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 IntroductionModelExperimentsSummary Theoretical Results

39 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. 39 Example application IntroductionModelExperimentsSummary Theoretical 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.


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