Abstract

We have examined the measured sensitivity and edge resolution to an included tumor in MR-derived maps of the breast exposed to NIR illumination. A large parameter space was explored, enabling a systematic examination of the influence that measurement parameters (e.g., view angle, source position, wavelength) and target medium parameters (e.g., breast and tumor size, background tissue properties, and tumor contrast) have on the computed responses. The significance of these finding on data collection schemes for imaging studies is discussed.

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References

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  1. S. Fantini, S. A. Walker, M. A. Franceschini., A. E. Cerussi, et al., "Characterization of breast tumors by frequency-domain optical mammography," In Advance in Optical Imaging and Photon Migration, J. G. Fujimoto et al, ed., Vol. 21 of OSA Proceeding Series (Optical Society of America, Whashington, D. C., 1998), pp. 289-293.
  2. V. Ntziachristos, X. H. Ma, M. Schnall, A. Yoldh and B. Chance, "Concurrent multi-channel time-resolved NIR with MR mammography instrumentation and initial clinical results," Ibid., pp. 284-288.
  3. R. L. Barbour, R. Andronica, Q. Sha, H. L. Graber, and I. Soller, "Development and evaluation of the IRIS- OPTIscanner, a general-purpose optical tomographic imaging system," Ibid., pp. 251-255.
  4. B.W. Pogue, M. Testorf, U. L. Osterberg, and K. D. Paulsen, "Development of quantitative imaging in frequency-domain diffuse optical tomography for breast cancer detection," Ibid., pp. 245-250.
  5. S. B. Colak, D. G. Papaioannou, G. W. 't Hooft, M. B. van der Mark, et al., "Tomographic image reconstruction from optical projections in light-diffusing media," Appl. Opt. 36,180-213 (1997).
    [CrossRef] [PubMed]
  6. R. L. Barbour, H. L. Graber, J. Chang, S.-L. S. Barbour, P. C. Koo and R. Aronson, "MRI-guided optical tomography: Prospects and computation for a new imaging method," in Computational Science & Engineering, (Institute of Electical and Electronic Engineerings, New York, 1995), pp. 63-76.
    [CrossRef]
  7. "VoxelView 2.5 User's Guide," Vital Images, Inc. www.vitalimages.com (1995).
  8. H. W. Shen and C. R. Johnson, "Semi-automatic image segmentation: A biomedical thresholding approach," Technical Report UUCS-94-019, Dept. of CS, Univ. of Utah (1994).
  9. D. F. Watson, "Computing the n-dimensional Delaunay tesselation with applications to Voronoi polytopes," Computer Journal 24(2), 167-172 (1981).
    [CrossRef]
  10. N. Weatherill, and O. Hassan, "Efficient three-dimensional grid generation using the Delaunay triangulation," Proceeding of the 1st European CFD Conference, 1 (1992).
  11. R. Beck, B. Erdmann and R. Roitzsch, "Kaskade 3.0 - An object-oriented adaptive finite element code," Technical report TR 95-4, Konrad-Zuse-Zentrum f?r Informationstechnik, Berlin (1995).
  12. T. L. Troy, D. L. Page, D. L. and E. M. Sevick-Muraca, "Optical properties of normal and diseased breast tissues: Prognosis for optical mammography," J. Biomedical Opt. 3, 342-355 (1996).
    [CrossRef]
  13. H. L. Graber, Y. Pei, R. Aronson, H. and R. L. Barbour, "Dependence of object sensitivity and resolution on optical thickness of scattering media," Appl. Opt. submitted.

Other (13)

S. Fantini, S. A. Walker, M. A. Franceschini., A. E. Cerussi, et al., "Characterization of breast tumors by frequency-domain optical mammography," In Advance in Optical Imaging and Photon Migration, J. G. Fujimoto et al, ed., Vol. 21 of OSA Proceeding Series (Optical Society of America, Whashington, D. C., 1998), pp. 289-293.

V. Ntziachristos, X. H. Ma, M. Schnall, A. Yoldh and B. Chance, "Concurrent multi-channel time-resolved NIR with MR mammography instrumentation and initial clinical results," Ibid., pp. 284-288.

R. L. Barbour, R. Andronica, Q. Sha, H. L. Graber, and I. Soller, "Development and evaluation of the IRIS- OPTIscanner, a general-purpose optical tomographic imaging system," Ibid., pp. 251-255.

B.W. Pogue, M. Testorf, U. L. Osterberg, and K. D. Paulsen, "Development of quantitative imaging in frequency-domain diffuse optical tomography for breast cancer detection," Ibid., pp. 245-250.

S. B. Colak, D. G. Papaioannou, G. W. 't Hooft, M. B. van der Mark, et al., "Tomographic image reconstruction from optical projections in light-diffusing media," Appl. Opt. 36,180-213 (1997).
[CrossRef] [PubMed]

R. L. Barbour, H. L. Graber, J. Chang, S.-L. S. Barbour, P. C. Koo and R. Aronson, "MRI-guided optical tomography: Prospects and computation for a new imaging method," in Computational Science & Engineering, (Institute of Electical and Electronic Engineerings, New York, 1995), pp. 63-76.
[CrossRef]

"VoxelView 2.5 User's Guide," Vital Images, Inc. www.vitalimages.com (1995).

H. W. Shen and C. R. Johnson, "Semi-automatic image segmentation: A biomedical thresholding approach," Technical Report UUCS-94-019, Dept. of CS, Univ. of Utah (1994).

D. F. Watson, "Computing the n-dimensional Delaunay tesselation with applications to Voronoi polytopes," Computer Journal 24(2), 167-172 (1981).
[CrossRef]

N. Weatherill, and O. Hassan, "Efficient three-dimensional grid generation using the Delaunay triangulation," Proceeding of the 1st European CFD Conference, 1 (1992).

R. Beck, B. Erdmann and R. Roitzsch, "Kaskade 3.0 - An object-oriented adaptive finite element code," Technical report TR 95-4, Konrad-Zuse-Zentrum f?r Informationstechnik, Berlin (1995).

T. L. Troy, D. L. Page, D. L. and E. M. Sevick-Muraca, "Optical properties of normal and diseased breast tissues: Prognosis for optical mammography," J. Biomedical Opt. 3, 342-355 (1996).
[CrossRef]

H. L. Graber, Y. Pei, R. Aronson, H. and R. L. Barbour, "Dependence of object sensitivity and resolution on optical thickness of scattering media," Appl. Opt. submitted.

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Figures (16)

Fig. 1.
Fig. 1.

(a) Image of a coronal slice of a breast derived from MRI maps; (b) FEM model used for computation.

Fig. 2.
Fig. 2.

Data acquisition geometry for a full tomographic view with 36 detectors in a uniform ring geometry (only 9 detector are shown in the figure). The arrows show two different source locations used for the reported results.

Fig. 3.
Fig. 3.

Illustration of parameters used to define edge resolution. See text for details.

Fig. 4.
Fig. 4.

Percent change in sensitivity versus view angle for different target sizes, with Case 3 tumor contrast and tumor size of r=1%, embedded in a homogeneous background medium.

Fig. 5.
Fig. 5.

Percent change in sensitivity versus (a) the cross-sectional area ratio for different breast diameters and (b) the breast diameter for different cross-sectional area ratios, for a Case 1 background medium (homogeneous) and Case 3 tumor contrast for a detector at 180° from the source.

Fig. 6.
Fig. 6.

EFWHM versus (a) the cross-sectional area ratio for different breast diameters and (b) the breast diameter for different cross-sectional area ratio with Case 1 background medium and Case 3 tumor contrast at 180° view angle. Definition of symbols is given in Fig. 5.

Fig. 7.
Fig. 7.

Plot of EFWHM versus sensitivity to an included tumor for a detector 180° from the source. Varied are the breast and tumor size in homogeneous background media for three different ranges of tumor contrast. In (a), the absorption coefficient is fixed to 0.08 cm-1 and the scattering coefficient varies from 10 to 40 cm-1; (b) absorption coefficient is fixed to 0.2 cm-1 and the scattering coefficient varies from 10 to 40 cm-1; and (c) the scattering coefficient of tumor is fixed to 10 cm-1 and the absorption coefficient varies from 0.08 to 0.4 cm-1.

Fig. 8.
Fig. 8.

Percent change in sensitivity versus view angle for different background media with a breast size of d=16 cm, tumor size of r=0.25 %, and Case 1 tumor contrast.

Fig. 9.
Fig. 9.

Percent change in sensitivity versus view angle for different breast sizes, with Case 3 tumor contrast and tumor size of r=1%, embedded in Case 6 background medium

Fig. 10.
Fig. 10.

Ratio of sensitivity at 180° view angle to that at 200°, versus (a) the cross-sectional area ratio for different breast diameters and (b) the breast diameter for different cross-sectional area ratio with Case 6 background tissue and Case 3 tumor contrast. Definition of symbols is given in Fig. 5.

Fig. 11.
Fig. 11.

Ratio of the maximum sensitivity caused by source 1 (θ=00) and source 2 (θ=-400) versus (a) the cross-sectional area ratio for different breast diameters and (b) the breast diameter for different cross-sectional area ratio with case 6 background tissue and case 3 tumor contrast. Definition of symbols is given in Fig. 5.

Fig. 12.
Fig. 12.

Ratio of sensitivity change of case 6 background medium to homogeneous background medium (case 1) versus (a) the cross-sectional area ratio for different breast diameters and (b) the breast diameter for different cross-sectional area ratio with case 3 tumor contrast at 180° view angle. Definition of symbols is given in Fig. 5.

Fig. 13.
Fig. 13.

Plot of EFWHM versus sensitivity for a detector 180° from the source. Shown are responses caused by variations of breast size and tumor size, for a Case 6 background medium and three different tumor contrast values. Range of contrast values examined for each panel is the same as described in the legend of Figure 7.

Figure14: .
Figure14: .

ercent change in sensitivity versus view angle for different breast diameters, with case 8 tumor contrast and tumor-to-breast area ratio r=1%, embedded in (a) homogeneous, (b) case 4, (c) case 5 and (d) case 8 background media, respectively. The legend shown applies to all panels.

Fig. 15.
Fig. 15.

Optimal wavelength approach

Fig. 16.
Fig. 16.

Combination of radial compression and optimal wavelength approaches

Tables (4)

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Table 1: Diameters of breasts and embedded tumors

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Table 2: Optical properties of tumor tissue

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Table 3: Optical properties of background tissue

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Table 4. Influence of a radial compression maneuver on sensitivity and edge resolution

Equations (3)

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· [ D ( r ) u ( r ) ] μ a ( r ) u ( r ) = δ ( r r s ) , r Ω
D ( r ) = 1 3 [ μ a ( r ) + μ ' s ( r ) ] .
δ u = u ( r ) b u ( r ) t u ( r ) b

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