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Phenotype-Motivated Strategies for Optical Detection of Breast Cancer

Phenotype-Motivated Strategies for Optical Detection of Breast Cancer. Randall L. Barbour, Ph.D. OSA, Miami April 30th, 2014. Cancerous Healthy. DOT: Contrast Mechanisms for Tumor Detection. Dynamic (Functional) Intrinsic - Vascular Rhythms Injectable dyes

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Phenotype-Motivated Strategies for Optical Detection of Breast Cancer

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  1. Phenotype-Motivated Strategies for Optical Detection of Breast Cancer Randall L. Barbour, Ph.D. OSA, Miami April 30th, 2014 R.L. Barbour

  2. Cancerous Healthy DOT: Contrast Mechanisms for Tumor Detection • Dynamic (Functional) • Intrinsic - Vascular Rhythms • Injectable dyes • Induced: • Breast compression • Respiratory gases • Breathing maneuvers Static: • Intrinsic: (2-3x) • Hb signal, Scattering • H2O, Lipid Sluggish Perfusion Reduced Oxygenation Increased Total Hb R.L. Barbour

  3. Cancer cells are usually insensitive to anti growth signals, they divide in the absence of proper signals, and they lose their capability of programmed cell death, which is called apoptosis. Because of that, cancer cells have the potential to replicate themselves limitlessly and generate vast cell populations. These abnormalities can lead to the formation of tumors. The movement of tumor cells to neighboring and distant parts of the body is known as metastasis. In order for tumors to grow beyond a few mm it needs new blood supply, which is called angiogenesis. Hallmarks of Cancer NO Sustained Inflammatory Response Insensitivity to anti-growth signals Evading* apoptosis Self-sufficiency in growth signal Tissue* invasion and metastasis Limitless replicative potential ↑ Hb Total ↓ HbO2 Sat Enhanced* angiogenesis ~3:1 Increased Stiffness 10:1 3 R.L. Barbour

  4. Apply Maneuvers Develop New Instrumentation + Exploit principal features of tumor phenotype Improved Detection of Breast Cancer Our Approach R.L. Barbour

  5. Tumor Detection Strategy R.L. Barbour

  6. DOT employs diffuse light that propagates through tissue, at multiple projections, to yield three-dimensional quantified tomographic images of the internal optical properties of organs. Light propogate in scattering medium in a banana shape path. Diffuse Imaging: Diffuse Optical Tomography (DOT) f0 f3 f4 f2 f1 Source Detectors Detectors Oxyhemoglobin Tumor Deoxyhemoglobin 6 R.L. Barbour

  7. This simple schematics explains the effects of compression on breast tissue hemodynamics. Blood reduction is expected as a results of compression. Because of the increase resistance to flow, enhanced stiffness, and poor perfusion in tumor, the blood reduction in tumor is expected to be slow, and this enhances its contrast. Blood reduction depends on the type, amplitude, and duration of compression. Thus, rich information can be extracted from studying hemodynamic responses to different types of compressions. Response to Compression P p Oxyhemoglobin Deoxyhemoglobin P P P P Tumor 7 R.L. Barbour

  8. $ Carbogen is a gas mixture of oxygen and carbon dioxide. Carbogen Breathing increases tissue oxygen saturation. Since tumors have high total hemoglobin concentration with low oxygen saturation, breathing carbogen is expected to increase their oxygen saturation relatively higher than normal tissue, and this will enhance breast cancer contrast. Response to Carbogen 98% O2,2% CO2 98% O2,2% CO2 98% O2,2% CO2 98% O2,2% CO2 Oxyhemoglobin Deoxyhemoglobin 8 R.L. Barbour

  9. $ • The MH should do four functions: • Support stable optodes contact with breasts. • Accommodate a wide range of breast sizes. • Measure the biomechanical properties of breast tissue. • Apply controlled articulations Support Arm 4 4 4 5 5 3 3 3 5 5 6 6 Detector Module Detector Module 8 LD1 LD2 6 7 2 1 8 9 Power Supply Motor Controller 7 9 New Instrumentation (1) laser beam combiner, (2) optical switch, (3) detector fibers, (4) sensing heads, (5) stepper motor drivers, (6) detection units, (7) servo motor controller, (8) personal computer, and (9) linear power supply. LD: Laser Diode. R.L. Barbour

  10. The core of my research was to $ The simultaneous scanning of both breasts is an important feature, because the optical images of the contralateral healthy breast will be used as a reference. I published a paper about this instrument in the Journal of Optical Society of America A. Apply controlled mechanical provocations Examine both breasts simultaneously Design Goals R. Al abdi, H.L. Graber, Y. Xu, and R.L. Barbour, "Optomechanical imaging system for breast cancer detection," J. Optical Society of America A, Vol. 28, pp. 2473-2493 (2011). 10 R.L. Barbour

  11. A clam-shell and articulating elements design which is similar to human hand was used to accommodate a wide range of breast sizes and to apply pressure provocations. Optical scan is done in the seated position, where patient should be the most comfortable. In this design a uniform pressure can be applied, and the articulating elements can conform to the breast shape. Articulating Sensing Head Articulating Elements Strain reliefs 64 D x 32 S (760 – 830 nm)/ measuring head = 8192 channels 2 Hz framing rate ~16KHz sampling rate 11 R.L. Barbour

  12. To summarize, the main three $ Combinations of these domains can yield either additive or wholly new information, depending on whether one domain interacts with the other. $ In this report, we described a new approach to breast imaging based on the interaction between controlled applied mechanical force and tissue hemodynamics. Opto-Mechanical Imaging R.L. Barbour

  13. Both breasts were placed inside the sensing heads, and then a baseline pressure of approximately 0.4 lb (1.8 N) was applied. A baseline scan of about 5-10 minutes was collected with the patient at rest. Then an automatic control was activated to apply a set of pressure provocations (10 min). $ 5 minutes after that, participant was given a facemask to breath Carbogen gas, wait for 5-10 min, and then a second set of pressure provocations was applied while patient was breathing Carbogen. Data Collection Articulation Setup and baseline Craniocaudal articulation Articulation Carbogen inspiration Regulator and flow gauge Craniocaudal articulation 98 % O2, 2% CO2 5 L/min 13 R.L. Barbour

  14. Articulation Parameter Space Amplitude (1x, 2x) Duration (1, 2min) Rate (fast) Sequence (AB, BA) Partial/uniform Quasistatic Loading-Unloading Wave-like Vibratory Creep Mono-multiphasic 14 R.L. Barbour

  15. Available Data • Optical Measures 760, 830 nm • Applied Force – strain gauge measure • Displacement } • Viscoelastic Response • Hemodynamic Response +/- Respiratory Gases Hypothesis: Optomechanical sensing provides for improved performance for breast cancer detection. R.L. Barbour

  16. The picture is for the finite element model that we used for image reconstruction, It has similar shape and size of a real breast inside the sensing heads. The normalized difference method was used to reconstruct changes in background optical properties. Then the changes in the background optical properties were transformed into changes in hemoglobin concentrations using the molar extinction coefficients of oxyhemoglobin and deoxyhemoglobin. Hb Image Reconstruction Normalized Difference Method: u1 and u2 represent two measures at two different times ur and Wr are computed from the reference model. x is the difference between the optical properties of the target and the reference model. W 12 cm x D 10 cm x H 6 cm 3908 voxel/pixel Y. Pei, H.L. Graber, and R.L. Barbour, "Influence of systematic errors in reference states on image quality and on stability of derived information for DC optical imaging," Applied Optics, Vol. 40, pp. 5755-5769 (2001). 16 R.L. Barbour

  17. The second part of specific aim 2 is to $ The critical need served by phantoms is that they essentially are the only way to conduct imaging studies where “the right answer” is known a priori. The balloon phantom was built to evaluate and quantify the effects of breast deformation and size variation on the measured optical signals and image reconstruction algorithms. It was constructed using a latex balloon filled with intra-lipid and India ink solution, and its size was changed by pumping more fluid. A liquid crystal cell was fixed at the center to produce dynamic contrast. Validate System Performance Dynamic Phantoms: Programmable Attenuation LC Cells Torso phantom Sensing head Balloon Phantom R.L. Barbour, R. Ansari, R. Al abdi, H.L. Graber, M.B. Levin, Y. Pei, C.H. Schmitz, and Y. Xu, "Validation of near infrared spectroscopic (NIRS) imaging using programmable phantoms," Paper 687002 in Design and Performance Validation of Phantoms Used in Conjunction with Optical Measurements of Tissue (Proceedings of SPIE, Vol. 6870), R.J. Nordstrom, Ed. (2008). 17 R.L. Barbour

  18. These results was obtained from driving the LCCs inside the torso-phantom with a square wave. Shown in the left figure are tracings of the input driving function and the recovered optical signals at both wavelengths 760 nm and 830 nm. The high contrast area coincide with true location of the LCCs. Torso Phantom Experiment True location of the LCC LCC: Liquid Crystal Cell 18 R.L. Barbour

  19. Clinical Study • Resting State • Articulation • Carbogen • Hemodynamic Analysis • 3D image time series reconstruction • Biomarker extraction: Bilateral comparison • Mechanical Analysis • Young’s Modulus (Elasticity) • Maxwell’s Model (Viscoelasticity) R.L. Barbour

  20. An IRB approved clinical study was conducted on 28 healthy volunteers, 23 breast cancer patients, and 33 women with benign breast lesions to assess the imager’s efficacy for detecting breast cancer lesions. Subject Demographics N = 84 20 R.L. Barbour

  21. Resting State Response R.L. Barbour

  22. Resting State Response • Approach: • Collect Baseline Time Series (~5 min) • Reconstruct 3D Image Time Series • Reduce Data Dimensionality: Integrate across temporal/spatial domains R.L. Barbour

  23. Group means and standard errors of PDs of power spectrum density (PSD) that was calculated from SM{HbTot} in baseline. The benign-pathology and healthy subjects are combined in one group (green curve). The error bars are the standard errors across subjects (inter-patients). Significant differences between cancer group compared to benign-pathology and healthy subjects group were found at low and high frequency band (p<0.01) (0.05-0.1 Hz, 0.5-0.7 Hz). Baseline Power Spectrum Density N = 18 N = 48 NO effect 23 R.L. Barbour

  24. Resting State Image: TSD R Coronal L R Axial L R Sagittal L 0.3 0.25 0.2 0.15 0.1 0.05 15 10 5 0 -5 10 5 0 -5 10 5 0 -5 0 5 10 15 20 0 5 10 15 20 -5 0 5 10 15 1 cm Tumor R Sagittal L R Coronal L R Axial L 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 10 5 0 -5 10 5 0 -5 15 10 5 0 -5 0 5 10 15 20 0 5 10 15 20 -5 0 5 10 15 4 cm Tumor R.L. Barbour

  25. Resting State Metric Performance SM: Spatial Mean TSD: Temporal Standard Deviation SSD: Spatial Standard Deviation

  26. Articulation Study R.L. Barbour

  27. Structural L MRI Tumor US X-ray Opto- mechanical Optical PET Functional TI Elasto-graphy CBE Mechanical Opto-Mechanical Imaging R.L. Barbour

  28. In this slide shows tissue reaction to a 7.1 N quasastatic compression. four phases of mechanical provocations $ The force relaxation and recovery phenomena are intrinsic properties of visco-elastic material of breast tissue. Tissue reaction to articulation Fast Relaxation Slow Relaxation Force Relaxation (Viscoelastic) Elastic Compression Decompression Recovery Baseline 28 R.L. Barbour

  29. Computed path-length from the force relaxation after a 7.1 N full compression. Change in Hb signals were calculated in the late period of stress relaxation, where path-length changes between sources and detectors were very low. Thus, measured optical signals highly represent hemodynamic responses of the breast. I did the same analysis during the force recovery period. Response to Articulation Δ1 Displacement [mm] Δ2 Δ3 Time [sec] 29 R.L. Barbour

  30. Maxwell model for stress relaxation R.L. Barbour

  31. To study the interaction of controlled applied mechanical provocation on tissue hemodynamics, a linear-elastic finite element analysis on a homogeneous poroelastic tissue model was used to predict the effect of compression on the internal forces, and to work as a protocol guidance The spatial maps of the effective stress for a wave-like compression (from left to right), and reconstructed changes in total hemoglobin are shown below. HbTot images are from a healthy participant, who was 43 years old with size D breast and BMI of 35. Notice the correlation between blood exclusion and the computed effective stress (blood move from high pressure regions to the low pressure regions). Protocol Guidance: Numerical Modeling – Hemodynamic Response Quasistatic wave-like Loading σ ΔHbTot Linear Elastic Model σ Effective Stress FE-Bio, University of Utah 31 R.L. Barbour

  32. The group means and standard errors of the average time constants during slow force relaxation are shown. No significant difference between cancer group compared to benign-pathology and healthy groups. The average value of slow relaxation is 30.0±1.8 seconds, which consistant to what was reported by Carp et al in 2009. Force Relaxation (Viscoelastic) 32 R.L. Barbour

  33. The group means and standard errors of the average young’s modulus (stiffness) during 7.1 N compression. No significant difference between cancer group compared to other category groups: benign-pathology, healthy groups, or both together. Young’s Modulus (Elastic) P-values Cancer vs. All: 0.413 Cancer vs. Benign: 0.331 Cancer vs. Healthy: 0. 615 33 R.L. Barbour

  34. To extend this normalization method to be used into two Hb signals, The Mahalanobis distance, which is analogue of univariate z-score, was used. • It permits straightforward evaluation of each data point’s statistical distance from the mean value of the two Hb signals. • MD was calculated in three steps: $ • Subtracting the mean. • Projecting the results into the eigenvectors of the two Hb signals covariance matrix • Dividing the results by their standard deviation in the healthy breast. Mahalanobis Distance (MD) Normalized to the healthy breast Original data 34 R.L. Barbour

  35. 3D images (coronal, sagittal and axial) of the calculated MD from a subject with breast cancer. MD was calculated from (ΔHbTot,ΔHbDeoxy) during the 4.4 N mediolateral relaxation. The subject was 50 year old, with size D breasts, and BMI of 44, and had a 4 cm invasive ductal carcinoma in the left breast. Normalization using Mahalanobis Distance enhance image contrast These contrasts are 5-6 times those seen in optical static images. Articulation MD images Right breast Left breast 5-6 x increased contrast vs. static measures 50 y/o, BMI 44, 4 cm IDC in the left breast MD of (ΔHbTot,ΔHbDeoxy) 35 R.L. Barbour

  36. Group means and standard errors of PDs in number of pixels that have MD greater than 5.5. Measurements were done after 4.4 N full compression, 4.4 N mediolateral relaxation, 7.1 N full compression, 7.1 N mediolateral relaxation, and 7.1 N mediolateral compression. Mahalanobis distances were calculated from the (ΔHbTot,ΔHbDeoxy). The error bars are the standard errors across subjects (inter-patients). Significant differences (p<0.01) between cancer group compared to benign-pathology and healthy groups were found under all types of articulations with smallest p-value for 4.4 N mediolateral relaxation (p= 7.8 x 10-5). Articulation MD p = 0.002 p = 0.003 p = 2.3x10-5 p = 0.005 p = 0.005 36 R.L. Barbour

  37. Spatial mean time series of HbSat and HbTot responses to carbogen inspiration. Subject was 65 years old, with a BMI of 29 and size D breasts, and she had a 2.5 cm invasive ductal carcinoma tumor in the left breast. Red dots on the graphs indicate the start of carbogen breathing. The difference between the values of tissue oxygen saturation before and after Carbogen inspiration (Δ) were used to produce breast cancer predictors. Carbogen Inspiration 37 R.L. Barbour

  38. Coronal sections of the MDs thresholded at 5.5 for (ΔHbTot ,ΔHbSat) Cancer patient was 34 y/o with BMI of 29 and 1-cm Invasive Ductal Carcinoma in the right breast at 4 clk. Benign pathology subject was 48 y/o, with BMI of 46, and Fibrocystic changes and microcalcification in the right breast in UOQ. Healthy: 43 y/o, with BMI of 35. Carbogen Inspiration MD Left breast Right breast 34 y/o BMI 29 1 cm IDC Cancer - Right 48 y/o BMI 46 Fibrocystic changes Benign pathology -Right 43 y/o BMI 35 Healthy Healthy 38 R.L. Barbour

  39. Cancer predictors derived from the three protocols, baseline, articulation and carbogen inspiration, have shown their potential to diagnose breast cancer. BLR was used to compute different multivariate predictors. In this table an example of four multivariate predictors and their ROC results are shown. Diagnostic accuracy of 93% was achieved by combining predictors from baseline, articulation, and carbogen inspiration. Summary of Clinical Performance BLR: Binary Logistic Regression, LOOCV: Leave-Out-One Cross Validation, AUC: Area Under Curve. 39 R.L. Barbour

  40. Summary of Finding Biomarkers extracted from controlled articulation, carbogen inspiration and resting dynamics all exhibit good diagnostic performance. Manipulation protocols yield superior tumor sizing and localization. Multivariate predictors show excellent diagnostic accuracy for detection of breast cancer (93%). 40 R.L. Barbour

  41. Future Directions Refine Protocols Develop platform having reduced format Correlation measures with gene expressions Improve performance of predictors for tumor recurrence, metastasis, sensitivity to chemotherapy etc. 41 R.L. Barbour

  42. Group means and standard errors of PDs in number of pixels that have MD greater than 5.5 during baseline, Articulation, and Carbogen breathing. The group mean of the number of pixels during baseline are significantly greater than those during articulation and carbogen breathing. This indicate that the contrast during baseline was diffused, extended beyond the margin of the tumor, and involve a large percentage of tumor bearing breast. These results suggest that the diagnostic power for breast cancer during baseline can be measured with low density optical sensors. Volumetric Response p= 0.047 p= 0.033 42 R.L. Barbour

  43. Downsampling Source/detector Source/detector Detector Detector only 43 R.L. Barbour

  44. To evaluate if the downsampling can work, Computed the percentage of channels that have higher temporal variance in the tumor bearing breast than the contralateral healthy breast. Shown are Group mean and standard deviation of high- and low density results. Results suggest that the increase temporal variance in the tumor bearing breast during baseline can be measured using low density optical sensors. Results of downsampling 44 R.L. Barbour

  45. R.L. Barbour

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