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Quantification of the morphologic features of fibroepithelial tumors of the breast.

AbstractCONTEXT:
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.
AuthorsAnn Marie McKenna, Melania Pintilie, Bruce Youngson, Susan J Done
JournalArchives of pathology & laboratory medicine (Arch Pathol Lab Med) Vol. 131 Issue 10 Pg. 1568-73 (Oct 2007) ISSN: 1543-2165 [Electronic] United States
PMID17922594 (Publication Type: Journal Article)
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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