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Fine Structure of Breast Tissue on Micro Computed Tomography

Rationale and Objectives

To evaluate the feasibility of micro computed tomography (CT) to assess the fine structure of breast tissue.

Methods and Materials

Breast core needle biopsy specimens (0.8 to 1.2 mm diameter) from fifteen women with clustered microcalcifications were examined using micro CT with isotropic voxels of 8.4 μm. Reconstructed two- and three-dimensional images were compared with the corresponding histological slices. Gray-scale measurements were performed in adipose tissue, fibroglandular tissue, fibrous tissue, microcalcifications, and tumor. The Tukey-Kramer method was applied to test the statistically significant differences between gray-scale attenuation values of breast tissue components.

Results

Soft-tissue architecture appearance at micro CT closely approximated that obtained by light microscopy at low power field. The Tukey-Kramer method revealed statistically significant differences for attenuation values for all combinations of breast tissue components with the exception of fibroglandular tissue versus fibrous tissue.

Conclusions

Micro CT is feasible for the differentiation of breast tissue components from core needle specimens.

Micro computed tomography (micro CT) is an in vitro and in vivo tomographic method to examine tissue specimens and small animals at micrometer resolution . Contrary to the gold standard of histological serial sectioning, this imaging method provides two- and three-dimensional information and new insights into the micro structure of tissues without destruction of the specimen.

Micro CT has been employed to analyze the architecture of the bone in osteoporosis, osteopenia, malformations, and tumors . Many studies have been published showing excellent correlation between three-dimensional micro CT stereological parameters and standard two-dimensional histomorphometry . Soft-tissue imaging with micro CT, however, is challenging because of the low intrinsic contrast between the different tissue components. By using sophisticated preparative and staining techniques, it is possible to image the terminal air spaces, subendocardial capillary network, vasa vasorum of the aorta, coronary artery plaque lesions, and microvascular architecture of the kidneys .

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Materials and methods

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Specimen Workup and Micro CT Imaging

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Comparison of Micro CT images with Histopathological Sections

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Statistical Analysis

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Results

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Figure 1, Invasive ductal carcinoma and extensive carcinoma in situ. (a) Magnification radiogram shows microcalcifications but allows no further tissue differentiation. (b) Coronal micro computed tomography (CT) image (MPR) generated with a soft reconstruction algorithm. Encircled area showing multiple rounded microcalcifications ( black arrows ) in tumor tissue ( open arrows ). Bar at the bottom indicating distance of 1 mm. (c) Corresponding histological section. Note comparability of distribution of different tissues components at micro CT and photomicrograph.

Figure 2, Transverse micro computed tomography image of a biopsy specimen with benign fibrocystic disease, reconstructed with a soft-tissue algorithm. High contrast between parenchyma ( open arrow ) and fatty tissue; 0.02-mm thick septa of fibrous tissue ( black arrows ) are seen. Arrowhead indicates paraffin coat. Bar at the bottom indicates distance of 1 mm.

Figure 3, Correlation of micro computed tomography (a) and photomicrograph (b) depicting an enlarged lactiferous duct with retained secretions ( star ) with a diameter of 1 mm. Thick fibrotic wall ( white open arrow ). Black arrows indicating small microcalcifications.

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Figure 4, Graph shows 95% confidence intervals of differences in mean gray-scale attenuation values for each tissue pair. Intervals—depicted as dotted lines in parenthesis—not crossing the zero-line ( vertical dotted line ), imply differences at the P ≤ .05 level of significance. The more the bars are distant from the zero-line the higher the level of significance. Note, only the fibroglandular (parenchyma)−fibrosis pair does not reach level of significance.

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Discussion

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Conclusion

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