Y. Xu, H. L. Graber, R. L. Barbour SUNY Downstate Medical Center

1. Spatial Deconvolution of 3-D Diffuse Optical Tomographic Time Series: Influence of Background Medium Heterogeneity Y. Xu, H. L. Graber, R. L. Barbour SUNY Downstate Medical Center

2. Acknowledgements • National Institutes of Health (NIH) • R21-HL67387 • R21-DK63692 • R41-CA96102 • R41-NS050007 • R43-NS49734 • U.S. Army • DAMD017-03-C-0018

3. Enhanced CW DOT Images

4. Medium Image Medium Image M M M M Reconstruction Reconstruction Filter Origin of Low Resolution in DOT?

5. Medium Detector Data Image μa(r), D(r) R(r) t = t0: μa(t)1, D(t)1 μa(r), D(r) R(r) t = t0+Δt: μa(r), D(r) μa(r), D(r) R(r) R(r) t = t0+3Δt: t = t0+2Δt: μa(t)2, D(t)2 Spatial Deconvolution Approach

6. Image Medium Deconvolution operator, or Filter = Spatial Deconvolution Approach

7. Reconstruction time  10-2 s Deconvolution time  10-3 s Spatial Deconvolution Result

8. Gray Matter Scalp White Matter Skull CSF M. Temporalis Structural MRI-based Heterogeneity

9. Scalp Skull Muscle CSF Gray Matter White Matter Source/Detector Complex Heterogeneous “Cylinder”

10. Static Tumor: μa = 0.24 cm-1, μ′s = 10 cm-1 CSF: μa = 0.08 cm-1, μ′s = 10 cm-1; μa = 0.04 cm-1, μ′s = 5 cm-1 Static Tumor: μa = 0.24 cm-1, μ′s = 10 cm-1 CSF: μa = 0.08 cm-1, μ′s = 10 cm-1; μa = 0.04 cm-1, μ′s = 5 cm-1; μa = 0.01 cm-1, μ′s = 1 cm-1 Static Tumor: μa = 0.24 cm-1, μ′s = 10 cm-1 CSF: μa = 0.08 cm-1, μ′s = 10 cm-1 Dynamic Tumor: f = 0.06 Hz, m = 20% Gray matter: f1 = 0.1 Hz, m = 10%; f2 = 1.0 Hz, m = 2% Static Tumor: μa = 0.24 cm-1, μ′s = 10 cm-1 CSF: μa = 0.08 cm-1, μ′s = 10 cm-1; μa = 0.04 cm-1, μ′s = 5 cm-1; μa = 0.01 cm-1, μ′s = 1 cm-1; μa = 0.005 cm-1, μ′s = 0.5 cm-1 inclusion gray matter Contrast Scalp, Skull, Muscle, White matter: μa = 0.08 cm-1, μ′s = 10 cm-1 (D = 0.0331 cm)

11. Overestimated CSF Optical Coefficients Underestimated CSF Optical Coefficients Overestimated CSF Optical Coefficients No Mismatch Recovered Images

12. Target Medium Deconvolved Image (No Mismatch) Deconvolution + Temporal LPF + Spatial LPF Deconvolution + Temporal LPF Noise Level 1: 1% – 10% Noise Level 2: 2% – 20% Noise Level 3: 3% – 30% Impact of Noise in Data

13. Reconstruct Update Homogeneous Medium + Baseline Data (Mean) What if We Don’t Have an MRI? (I) MRI (II)

14. What if We Don’t Have an MRI?

15. Conclusions • Complex medium heterogeneity can have the effect of increasing the spatial and temporal accuracy of deconvolved reconstructed images • Effect of errors in estimates of background optical coefficient values depends on the direction of the error • Overestimating the optical coefficients produces image quality degradation • Underestimating them has minimal, or even beneficial, effects

16. Conclusions • Two effective methods for increasing confidence in accuracy of deconvolved images • Use structural images to design reference media • Use one nonlinear image reconstruction sequence to produce a heterogeneous reference medium