Abstract | CONTEXT:
Phyllodes tumors of the breast are uncommon, comprising 0.3% to 0.9% of female primary breast tumors. Owing in part to their rarity, definitive, objective, reproducible morphologic criteria that reliably distinguish benign from low-grade malignant or malignant phyllodes tumors have yet to be established. OBJECTIVE: To use image analysis to quantitate and compare morphologic features of different groups of fibroepithelial tumors ( FETs) of the breast. DESIGN:
Hematoxylin- eosin-stained sections of 41 FETs previously identified as fibroadenoma, benign phyllodes, low-grade malignant phyllodes, or high-grade malignant phyllodes were blinded and studied using a Leica DMRA2 microscope and OpenLab Image Analysis software. Features measured included mitotic rate per 10 high-power fields, stromal cellularity, nuclear size, stromal overgrowth, and the largest and smallest stromal-epithelial surface area ratios. Epithelial appearance was measured on a semiquantitative basis. Features of each case including tumor size, margin status, and the presence of necrosis or heterologous elements were also considered; these data were retrieved from surgical pathology reports. RESULTS: Quantitative measures of stromal cellularity, stromal-epithelial ratio, mitotic rate, stromal overgrowth, and mean nuclear diameter were developed and found to stratify a population of FETs by the current classification system of fibroadenoma, benign, and low-grade or high-grade malignant phyllodes tumor. CONCLUSIONS: Quantitative morphologic features of FETs can be used to stratify these tumors by subtype. Use of these quantitative criteria could reduce interrater variability in histologically identifying FETs by subclass.
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Authors | Ann Marie McKenna, Melania Pintilie, Bruce Youngson, Susan J Done |
Journal | Archives of pathology & laboratory medicine
(Arch Pathol Lab Med)
Vol. 131
Issue 10
Pg. 1568-73
(Oct 2007)
ISSN: 1543-2165 [Electronic] United States |
PMID | 17922594
(Publication Type: Journal Article)
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Topics |
- Breast Neoplasms
(classification, pathology)
- Cell Nucleus
(pathology)
- Female
- Humans
- Image Processing, Computer-Assisted
- Phyllodes Tumor
(classification, pathology)
- Stromal Cells
(pathology)
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