Microwave Near-field Imaging of Human Tissue: Hopes, Challenges, Outlook

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Microwave Near-field Imaging of Human Tissue: Hopes, Challenges, Outlook Natalia K. Nikolova nikolova@ieee.org McMaster University, 128 Main Street West, Hamilton, ON L8S 4K1, CANADA Department of Electrical and Computer Engineering

Outline microwave imaging emerging modality in medical imaging imaging approaches experimental setups reconstruction approaches recent developments sensors and phantoms data acquisition via aperture scanning real-time reconstruction approaches looking forward WMG: Recent Developments in Microwave Imaging and Detection 2

Microwave Imaging Emerging Modality first systematic studies date back to 1978 [Larsen & Jacobi eds. 1986] S 21 scan, 3.9 GHz dissection S 21 co-pol canine kidney scan in water [Jacobi 1978] chirp-radar scan (5 MHz to 2 GHz) S 21 cross-pol 3

Microwave Imaging: Conclusions from Early Experiments resolution on the order of a centimeter coupling microwave energy into tissue improved by coupling liquids significant tissue heterogeneity significant tissue dissipation compromise between penetration depth (better at low frequencies) and resolution (better at high frequencies) optimal frequency range: 2 GHz to 8 GHz [Lin 25],.5 GHz to 3 GHz [Li 24, Semenov 25] microwaves hold promise for early-stage breast cancer diagnostics [Sepponen 1987] WMG: Recent Developments in Microwave Imaging and Detection 4

Microwave Imaging: Some Facts about Breast Cancer the 2 nd largest cause of female cancer deaths in the US; annually: over 2, diagnosed, about 4, dying; incidence among women: 1 in 8 [ACS 21] early-stage (below 1.5 cm) detection is crucial (> 9% survival rate) current modalities are not satisfactory mammography: the standard, high false-negative rate (~15%), ionizing, discomfort due to compression MRI: not suitable for mass screening, high false-positive rate, contrast agent required ultrasound: low specificity, operator dependent [www.breastcancer.org] WMG: Recent Developments in Microwave Imaging and Detection 5

Advantages of Microwave Imaging advantages of microwave technology in cancer diagnostics safe: non-ionizing and very low SAR (frequent check-ups) no need for significant breast compression relatively cheap compact technology (deployment in GP offices) other applications of near-field microwave imaging security surveillance (concealed weapon detection) underground surveillance nondestructive testing and evaluation WMG: Recent Developments in Microwave Imaging and Detection 6

Tissue Constitutive Parameters breast tissue constitutive parameters [Lazebnik 27, Halter 29] 5 major tissue types: skin, muscle, adipose (fat), fibroglandular (FG), cancerous (benign, malignant) adipose tissue features the lowest ε r and σ (ε r 4 to 6 and σ.2 S/m @ 3 GHz) while tumors feature the highest values (ε r 44 to 59 and σ 2.5 to 3 S/m @ 3 GHz) contrast between FG tissue and tumors is small ( 1% in ε r, up to 1% in σ, still under investigation); FG tissue is the place where most cancers appear [Lazebnik 27, Poplack 27, Halter 29] significant frequency dispersion WMG: Recent Developments in Microwave Imaging and Detection 7

Tissue Constitutive Parameters Ongoing Studies more on the contrast between healthy FG tissue and tumors previous studies ex vivo, small-scale, inconsistent protocols for tissue acquisition, many discrepancies, claim high contrast (factors of 5 to 1) between normal breast tissue and malignant tissue two major recent studies ex vivo U of Wisconsin-Madison & U of Calgary [Lazebnik 27] very low mean contrast: in ε r about 8%, in σ about 1% in vivo Dartmouth College [Poplack 27, Halter 29] contrasts are higher in vivo ε r and σ decrease after excision more in vivo studies necessary WMG: Recent Developments in Microwave Imaging and Detection 8

6 Tissue Constitutive Parameters Illustration [Trehan 29] Relative permittivity 5 4 3 2 1 fat fibro muscle trans tumor 3 4 5 6 7 8 9 1 f (GHz) Conductivity (S/m) 14 12 1 8 6 4 2 fat fibro muscle trans tumor WMG: Recent Developments in Microwave 3 Imaging 4 5and Detection 6 7 8 9 9 1 f (GHz)

Microwave Imaging Approaches in Breast-cancer Research ACTIVE PASSIVE HYBRID tomography holography pulsed radar radiometry microwaveinduced confocal ultrasound imaging imaging (3) nonlinear (1) indirect inversion holography tomography reflection/ (4) chirp-pulse diffraction tomography (2) transmission holography (1) Dartmouth College (US) Duke University (US) Carolinas Medical Center (US) Delft University of Technology (the Netherlands) Université de Nice-Sophia Antipolis (France) (1),(2) Chalmers University of Technology (Sweden) (2) University of Genoa, Niigata University MIST TSAR (5) (6) Multi-static DAS time (8) reversal (7) (3) Northumbria University (UK) (4) McMaster University (Canada) thermoacoustic tomography microwave elastography (5) University of Wisconsin-Madison (US) (6) University of Calgary (Canada) (7) University of Bristol (UK) (8) Northeastern University (US) (9) (9) University of Queensland (Australia) 1

Experimental Setups: Data-acquisition Arrangements may use co-pol and cross-pol interrogation in time or frequency domain planar scan supine cylindrical scan prone MIST planar scan prone TSAR circular-array scan prone tomography WMG: Recent Developments in Microwave Imaging and Detection 11

Experimental Setups: Coupling Liquids tanks of coupling liquids typically used to improve energy coupling into tissue Dartmouth C [Meaney 2] U of Manitoba [Zakaria 21] U of Calgary [Sill 25] 12

Liquid-free Experimental Setups recent trend toward liquid-free setups (gels may be used instead) easy maintenance no danger of contamination contact with tissue through thin layers of protective coating & gel challenging sensor design Duke U [Stang 29] U of Bristol [Research Review, Winter 29 online publicity material] www.bristol.ac.uk/news/29/6169.html WMG: Recent Developments in Microwave Imaging and Detection 13

Outlook: Imaging Algorithms and Software microwave holography sensitivity-based reconstruction confocal multistaticreconstruction diffraction tomography EM models and gradient-based nonlinear inversion real-time performance 14

Outlook: Hardware and Measurements improving sensors miniaturization crucial in array configurations improving scanning apparatus co- and cross-pol interrogation crucial for specificity time-domain interrogations chirp waveforms vs. pulsed radar pulse shaping in vivo measurements of healthy and malignant breast tissues contrast agents for microwave imaging 15

This talk is the basis of an overview paper by the same title to appear in the IEEE Microwave Magazine in October 211. Thank you! 16

Recent Developments: Sensors design requirements for aperture-scan sensors no coupling liquids frequency range within UWB (3.1 GHz to 1.6 GHz) 2log 1 S 11 1 db Ptissue coupling efficiency 8% ec = P small front aperture in shielded dielectric-filled TEM horns [Amineh 29] [Moussakhani 21] WMG: Recent Developments in Microwave Imaging and Detection 17

Fully Shielded Dielectric-filled TEM Horn Sensor tissue layers [Moussakhani 21] dielectric material ε r 1 tanδ.2 [ECCOSTOCK, Emmerson&Cuming Microwave Products] 2 mm 3 mm balun 18

dielectric constant 45 4 35 3 25 2 15 1 5 TEM Horn Sensor: Properties of Tissue Phantom Tissue layer Skin layer 4 5 6 7 8 9 1 f (GHz) effective conductivity (S/m) 1 9 8 7 6 5 4 3 Tissue layer Skin layer [Trehan 29] phantom: glycerin-based substitute mimicking human tissue 2 WMG: Recent Developments in Microwave Imaging 4 5and Detection 6 7 8 9 191 f (GHz)

TEM Horn Sensor: Coupling Coefficient 1.9 previous antenna TEM in [8] horn improved proposed TEM antenna horn.8 Coupling Efficiency.7.6.5.4 lower loss lower leakage improved impedance match.3 P.2 tissue ec = Pin.1 3 4 5 6 7 8 9 1 11 Frequency (GHz) 2

Raster Scanning: Experimental Setup 2-port S-parameter measurement: complex transmission coefficient S 21 antennas solenoids VNA phantom LNA power amp 21

1. Calibrate VNA Raster Scanning: Measurement Procedure 2. Measure background phantom S b jk ( xy, ), jk=, 1, 2 3. Measure object under test S m jk ( xy, ), jk=, 1, 2 4. Calculate calibrated scattering parameters c m b jk jk jk S ( xy, ) = S ( xy, ) S ( xy, ), jk, = 1,2 WMG: Recent Developments in Microwave Imaging and Detection 22

Raster Scanning: 2-D Images of S-parameter Magnitude EXAMPLE 1: MEASUREMENT OF TWO SCATTERERS IN A 3-CM THICK PHANTOM Scatterer Position (mm) Size (mm) Material 1 1 1 alginate Sc1 ( 4,25) [before diffusion] powder Sc2 (9, 25) 15 15 15 glycerin sketch of scanning setup 23

Raster Scanning: 2-D Images of S-parameter Magnitude (2) Dielectric constant 6 5 4 3 2 1 Background Sc1 Sc2 Effective conductivity (S/m) 1 3 4 5 6 7 8 9 1 f (GHz) 15 5 phantom electrical properties Background Sc1 Sc2 3 4 5 6 7 8 9 1 f (GHz) 24 x 1 9

Raster Scanning: 2-D Images of S-parameter Magnitude (3) Example 1: S c 21 images after smoothing 5 4 x 1-3 6 5 x 1-3 6 5 x 1-3 4.5 y z (mm) 3 2 1-1 -2 5 4 3 2 z (mm) 5 4 3 2 z (mm) 4 3.5 3 2.5 2 1.5-3 -4-5 -2 2 1 5 GHz 7 GHz 9 GHz -5-2 2 1-5 -2 2 x (mm) x (mm) x (mm) 1.5 VNA settings averaging: 1 bandwidth: 1 khz smoothing: 5% sampling rate along x and y: 5 mm WMG: Recent Developments in Microwave Imaging and Detection 25

Raster Scanning: 2-D Images of S-parameter Magnitude (4) EXAMPLE 2: MEASUREMENT OF TWO SCATTERERS IN A 5-CM THICK HOMOGENEOUS PHANTOM two identical tumor simulants made of alginate powder (electrical properties at 5 GHz shown in figure) WMG: Recent Developments in Microwave Imaging and Detection 26

Raster Scanning: 2-D Images of S-parameter Magnitude (5) Example 2: S c 21 images after smoothing 7 6 5 GHz 7 GHz 7 6 7 6 9 GHz 5 5 5 4 3 4 3 4 3 2 2 2 1 1 1 1 2 3 4 5 6 7 x (mm) 1 2 3 4 5 6 7 x (mm) 1 2 3 4 5 6 7 x (mm) image quality is low the two targets are fused together due mainly to integrating property (low-pass filtering) of the relatively large sensor aperture WMG: Recent Developments in Microwave Imaging and Detection 27

Raster Scanning: Data Processing for Image Enhancement Step 1: 2-D images of calibrated S-parameter magnitude simulation at 5 GHz [FEKO] measurement at 5 GHz ε r,b = 1 σ = 1 S/m b 3.8 15 2 3 5 ε r,t = 15 σ = 2 S/m t 4 3 2 2 1-2 -4 c 21 S ( xy, ) -4-2 2 4 x (mm) -1-2 -3 c 21 S ( xy, ) -3-2 -1 1 2 3 x (mm) 28

Raster Scanning: Data Processing for Image Enhancement (2) Step 2: Image de-blurring via complex blind deconvolution [Khalatpour 21] simulation at 5 GHz [FEKO] measurement at 5 GHz ε r,b = 1 σ = 1 S/m b 2 15 3 5 3.8 ε r,t = 15 σ = 2 S/m t 4 3 2 1-1 -2-3 -4-4 -3-2 -1 1 2 3 4 x (mm) 35 25 15 5-5 -15-25 -35-35 -25-15 -5 5 15 25 35 x (mm) 29

Raster Scanning: Data Processing for Image Enhancement (3) Step 3: Image enhancement via 2-D microwave holography (holography operates on de-blurred signal) simulation at 5 GHz [FEKO] measurement at 5 GHz ε r,b = 1 σ = 1 S/m b 3.8 15 2 3 5 ε r,t = 15 σ = 2 S/m t [Ravan 21] 4 3 2 2 1-2 -1-2 -4-4 -2 2 4 x (mm) -3-3 -2-1 1 2 3 x (mm) 3

ε r,b = 1 σ = 1 S/m b Raster Scanning: Data Processing for Image Enhancement (4) comparison: holography operates directly on raw signal simulation at 5 GHz [FEKO] measurement at 5 GHz 3.8 15 2 3 5 ε r,t = 15 σ = 2 S/m t c S21( xy, ) 4 3 2 2 1-2 -1-2 -4-3 -4-2 2 4 x (mm) -3-2 -1 1 2 3 x (mm) 31

Raster Scanning: Data Processing for Image Enhancement (5) images at other frequencies (after de-blurring and holography) measurement 3 3 3 2 2 2 1 1 1 y ( ) -1-1 -1-2 -3 5 GHz -3 7 GHz 7 GHz -3-2 -1 1 2 3 x (mm) -2-3 -2-1 1 2 3 x (mm) -2-3 9 GHz -3-2 -1 1 2 3 x (mm) WMG: Recent Developments in Microwave Imaging and Detection 32

Recent Advances: 3D Near-field Holography gaining depth information via 3-D microwave holography [Amineh 21] simulation from 3 GHz to 1 GHz ε r,b = 16 σ =.5 S/m b z dipole 1 works on de-blurred signals 2 mm 8 mm UWB information needed 3.1 GHz to 1.6 GHz band (FCC) is feasible 2 mm ε r,t = 32 σ = 1 S/m t 54 mm x 3 mm y dipole 2 [FEKO] 33

Recent Advances: 3D Near-field Holography (2) 4 2 z = 24 mm 3D holographic image (slice format) 4-2 2-4 -4-2 2 4 x (mm) z = 3 mm -2 4-4 2-4 -2 2 4 x (mm) z = 36 mm -2 4-4 2-4 -2 2 4 x (mm) z = 42 mm 4-2 2-4 -4-2 2 4 x (mm) z = 48 mm -2 4-4 2-4 -2 2 4 x (mm) 4 2-2 z = 6 mm -4-4 -2 2 4 x (mm) -2 z = 54 mm -4-4 -2 2 4 x (mm) 34

3D Holography: Vector Examples (Co- & Cross-pol) dipole 1 [Amineh&Khalatpour, 211] 2 mm 2 mm 2 mm 5 mm 3 mm dipole 2 35

3D Holography: Co- & Cross-pol (2) (а) (b) (c) 36

3D Holography: Co- & Cross-pol (3) dipole 1 2 mm (а) 2 mm 5 mm 2 mm 3 mm (b) dipole 2 (c) 37

3D Near-field Holography Performance Measures advantages fast computations real-time performance very robust to noise in UWB ( 3 GHz to 1 GHz) yields 3D images with good resolution RESOLUTION ESTIMATES FOR THE UWB RANGE (3 GHZ TO 1 GHZ ) [ASSUMED AVERAGE TISSUE PARAMETERS ε r 16 AND σ 4 S/M] δ z δ 5.4 mm 4.2 mm limitations assumes homogeneous background based on the linear Born approximation works well only with weak scatterers 38

References 1. Larsen and Jacobi, eds., Medical Applications of Microwave Imaging, IEEE Press, 1986. 2. L.E. Larsen and J.H. Jacobi, Microwave interrogation of dielectric targets. Part I: By scattering parameters, Med. Phys. 5 (6), 1978. 3. L.E. Larsen and J.H. Jacobi, Microwave interrogation of dielectric targets. Part II: By microwave time delay spectroscopy, Med. Phys. 5 (6), 1978. 4. J. C. Lin, Frequency optimization for microwave imaging of biological tissue, Proc. IEEE, 73 (2), 25. 5. D. Li, P.M. Meaney, T. Reynolds, S.A. Pendergrass, M.W. Fanning, and K.D. Paulsen, Parallel-detection microwave spectroscopy system for breast imaging, Rev. Sci. Instruments 75 (7), 24. 6. S.Y. Semenov et al., Microwave-tomographic imaging of the high dielectriccontrast objects using different image-reconstruction approaches, IEEE Trans. Microw. Theory Tech. 53 (7), 25. 7. R.E. Sepponen, Medical Diagnostic Microwave Scanning Apparatus, US Patent 4,641,659 1987. 8. M. Lazebnik et al., A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries, Phys. Med. Biol. 52, Apr. 27; ibid. Oct. 27. 39

References 8. Poplack et al., Electromagnetic breast imaging: Results of a pilot study in women with abnormal mammograms, Radiology 243, May 27. 9. R.J. Halter et al., The correlation of in vivo and ex vivo tissue dielectric properties to validate electromagnetic breast imaging: initial clinical experience, Physiol. Meas. 3, 29. 1. P.M. Meaney et al., A clinical prototype for active microwave imaging of the breast, IEEE Trans. Microw. Theory Tech. 48 (11), 2. 11. A. Zakaria, C. Gilmore, and J. LoVetri, Finite-element contrast source inversion method for microwave imaging, Inverse Problems 26, 1151, 21. 12. J.M. Sill and E.C. Fear, Tissue sensing adaptive radar for breast cancer detection experimental investigation of simple tumor models, IEEE Trans. Microw. Theory Tech. 53 (11), 25. 13. J.P. Stang et al., A tapered microstrip patch antenna array for use in breast cancer screening via 3D active microwave imaging, IEEE AP-S/URSI Int. Symp. Antennas & Propagation, 29. 14. A.Trehan, Numerical and Physical Phantoms for Microwave Imaging of Human Tissue, M.A.Sc. Thesis, McMaster University, 29. WMG: Recent Developments in Microwave Imaging and Detection 4

References 15. N.K. Nikolova and Y.S. Rickard, Nonradiating electromagnetic sources in a nonuniform medium, Phys.Rev. E 71, 16617, 25. 16. F.-C.Chen and W.C. Chew, Experimental verification of super resolution in nonlinear inverse scattering, Applied Phys. Lett. 72, 1998. 17. R.K. Amineh and N.K. Nikolova, Design, fabrication, and characterization of ultra-wide band TEM horn for microwave imaging, 14 th Int. Symp. on Antenna Technology and Applied Electromagnetics and the American Electromagnetics Conference (ANTEM/AMEREM 21), July 21. 18. A. Khalatpour et al., Image quality enhancement in the microwave raster scanning method, IEEE MTT-S Int. Microwave Symp. 211, June 211, submitted. 19. M. Ravan, R.K. Amineh, and N.K. Nikolova, Two-dimensional near-field microwave holography, Inverse Problems 26, 5511, 21. 2. R.K. Amineh, M. Ravan, N.K. Nikolova, and A. Khalatpour, Threedimensional near-field microwave holography using reflected and transmitted signals, IEEE Trans. Antennas Propagat., submitted. WMG: Recent Developments in Microwave Imaging and Detection 41

References 21. L. Liu, A. Trehan, and N.K. Nikolova, Near-field detection at microwave frequencies based on self-adjoint response sensitivity analysis, Inverse Problems 26, 151, 21. 22. Y. Song and N.K. Nikolova, Memory efficient method for wideband self-adjoint sensitivity analysis, IEEE Trans. Microwave Theory Tech. 56 (8), 28. WMG: Recent Developments in Microwave Imaging and Detection 42