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Fig 1.

The area selection and calculation using Photoshop.

(a) Using the “Magnetic Lasso” Tool, the nipple area was selected and calculated by counting the number of pixels enclosed in the area. (b) Using the “Similar” function, the whole blood flow signals within the traced nipple was defined and calculated by counting the number of pixels.

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Fig 1 Expand

Table 1.

Clinical and pathological findings of the 12 patients.

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Table 1 Expand

Fig 2.

An 81-year-old woman with Paget disease (Case 7).

(a) Scaling and erosion of the affected right nipple. (b) Blood flow signals inside the affected nipple as observed using Doppler sonography. (c) Nipple enhancement by CE-MRI. (d) Histopathological examinations with hematoxylin and eosin staining reveal Paget cells within the epidermis and capillary proliferation within the dermis (×100).

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Fig 3.

(a) Visualized hypervascularity of the affected nipple with Paget disease (Case 1). (b) Unchanging blood flow signals of the affected nipple with simple dermatitis (Case 8).

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Fig 4.

Comparison of nipple blood flow ratios between the affected and unaffected nipples with each condition.

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Fig 5.

Histopathological examinations of capillary proliferation of the nipple–areolar region by hematoxylin and eosin staining.

(a) Normal skin control with Paget disease (×40). (b) Normal skin control with Paget disease (×100). (c) Paget lesion at ×40). (d) Paget lesion at ×100). (e) Dermatitis at ×40). (f) Dermatitis at ×100). Bar, 50 μm (b, d, and f).

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Fig 6.

Comparison of the capillary density (a, all; b, ø > 50 μm) by histological examination.

ANOVA, Paget disease vs. dermatitis: p = 0.0003 for all capillaries (a) and p = 0.0004 for capillaries thicker than 50 μm (b). The mean (±SD).

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Table 2.

The findings of mammography, grayscale sonography, and CE-MRI for seven patients with Paget disease.

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Table 2 Expand