Design and Initial Testing of Imager for Simultaneous Bilateral Optical Mammography OSA Biomedical Optics Topical Meeting April th, 2004 Miami, Florida Randall L. Barbour, Ph.D. SUNY Downstate Med. Ct., Brooklyn, NY

CONFLICT NIRx Medical Technologies, LLC

Motivation for Time-Series Imaging Basic Physiology: Tissue-Vascular Coupling –Oxygen delivery to tissue Blood Volume Blood Oxygenation –Regulation of vascular response Neural, hormonal, metabolic Vascular rhythms Clinical Applications: Functional changes precede structural changes

Motivation for Time Series Breast Imaging Figure 1. Corrosion Cast of Tumor Vasculature. tp, = tumor periphery, st = surrounding tissue. From Ref., p. 16. Corrosion Cast of Tumor Vasculature

Technology Development

Approach to System Design Goal: Systems that have turn-key functionality that are suitable for a range of applications. Problem Areas –Data Collection. –Data Integrity. –Image Recovery. –Time-Series Image Analysis. –Image Display.

System Design Approach Large dynamic range (10 9 ) Variable framing rate ( Hz) Multiwavelength (2-4 color) Automated set-up and control Real-time visualization System-data integrity checks Custom configured measuring heads Comprehensive software: –System control, image recovery, signal analysis, image display. Integrated vital sign monitoring.

Time Series Optical Tomography Frame

SUNY DYNOT Breast Imager Single, Dual Breast Measurement Heads Time multiplexed DC Illumination 32 source x 64 detector channels per breast. 64 channel optical switch 2-90 Hz framing rate Advantage of Dual Breast Measurement: - Provides for differential measurement!

Breast Measurement Heads Single Breast - Medieval StyleDual Breast - Madonna Style

Detector fibers 760 nm 830 nm Detector setup Source fibers Source fibers LEFT RIGHT

Dual Breast Set-up Screen

Dual Breast Display Screen

CASE STUDIES

Tumor Detection by Response to Transient Hypoxemia Time point Normalized detector reading Healthy Tumor bearing HbO 2 Hb

Image of Transient Hypoxemia Relative Contrast Figure 5. Right, 3D DYNOT image of tumor identifying imbalance in tissue oxygen supply/demand. Image was produced without need of contrast agents or compression. Left, sonogram image of same breast showing location of tumor. Note close agreement in size and location. Tumor

Valsalva Maneuver

Vascular Response to Valsalva Maneuver

GLM Analysis: Percentage of Variance Accounted for by Model Function

1.5e e-9 2.1e e-8 P1: Left Breast P1: Right Breast st derivative of the deoxyhemoglobin image time series at indicated time points indicated along the Valsalva maneuver (1) (tumor-bearing patient: P1) Ductal Carcinoma

1.1 e e e e-8 N1: Left Breast N1: Right Breast st derivative of the deoxyhemoglobin image time series at indicated time points indicated along the Valsalva maneuver (2) (Healthy Volunteer)

Simultaneous Bilateral Measurements Look for differential responses in baseline and in response to provocation!

Spatially averaged, low-pass filtered ( Hz) total Hb (i.e., blood volume) baseline signals (left breast, right breast) Baseline Comparisons Amplitude CSD Phase CSD

Patient with active breast cancer: Baseline Spatially averaged, bandpass filtered ( Hz) total Hb baseline signals

Breast Cancer Patient Time-dependent, spatial standard deviation of bandpass filtered total Hb baseline signals Is the respiratory rhythm simply absent from the left breast? No! Presence of respiratory peak in SD time series indicates that there is, instead, loss of coordinated activity in the breast at this frequency. FT phase is spatially heterogen- eous, and contributions from all parts of the breast cancel out in the mean time series. CSD Phase of Mean time series

Bilateral Response to Valsalva: Healthy Subject

st Derivative Images for Deoxy Hb: Healthy Subject Time Points

Bilateral Response to Valsalva: Cancer Patient Time Point Left Right 3050 Tumor

Summary Developed a integrated measuring system capable of simultaneous bilateral time-series breast imaging. Preliminary studies have shown evidence of characteristic changes to both baseline and response to provocation. The form of these changes include disturbances in basal rhythms, and localized rates of change following a respiratory maneuver.

SUNY-NIRx Development Team Key Personnel DegreeExpertiseResponsibility Randall Barbour Ph.D. Biochem, Lab. Med., Biomedical OpticsPI Harry Graber Ph.D. Biophysics, Theory, Signal analysisSenior Appl. Specialist Yaling PeiPh.D.Engineering, Numerical Methods, Algorithm Dev.Dir. Software Eng. Christoph SchmitzPh.D.Physics, System design and integrationDir. Engineering David KlemerM.D., Ph.D.Int. Med., Elec. Eng., Application DevelopmentMedical Director Mikhail LevinPh.D.Physics, Physical OpticsOptical System Design Margarita LevinPh.D.Physics, Physical OpticsSys. Testing, Validation Yong XuPh.D. Physics, Numerical MethodsAlgorithm Development Raphael AronsonPh.D.Physics, TheoryAdv. Theory Studies Nelson FrancoM.D.Surgical ResidentBreast Studies Rosemarie Hardin M.D.Surgical ResidentBreast Studies Michael KatzM.D.Surgical ResidentLimb Studies Alessandro Smeraldi M.D.Vascular Fellow (Staten Island U. Hosp)Limb Studies

Acknowledgements NYS Department of Health Army Research Office NIH: NIBIB, NIHLB, NINDS, NCI, NIDDK

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