Diagnostics (Oct 2023)

A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics

  • Simona-Alina Duca-Barbu,
  • Alexandru Adrian Bratei,
  • Antonia-Carmen Lisievici,
  • Tiberiu Augustin Georgescu,
  • Bianca Mihaela Nemes,
  • Maria Sajin,
  • Florinel Pop

DOI
https://doi.org/10.3390/diagnostics13213338
Journal volume & issue
Vol. 13, no. 21
p. 3338

Abstract

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Bone metastases represent about 70% of breast cancer metastases and are associated with worse prognosis as the tumor cells acquire more aggressive features. The selection and investigation of patients with a high risk of developing bone metastasis would have a significant impact on patients’ management and survival. The patients were selected from the database of Carol Davila Clinical Nephrology Hospital of Bucharest. Their tumor specimens were pathologically processed, and a representative area was selected. This area was scanned using an Olympus VS200 slide scanner and further analyzed using QuPath software v0.4.4. A representative group of approximately 60–100 tumor cells was selected from each section, for which the following parameters were analyzed: nuclear area, nuclear perimeter, long axis and cell surface. Starting from these measurements, the following were calculated: the mean nuclear area and mean nuclear volume, the nucleus to cytoplasm ratio, the length of the two axes, the long axis to short axis ratio, the acyclicity and anellipticity grade and the mean internuclear distance. The tumor cells belonging to patients known to have bone metastasis seemed to have a lower nuclear area (2, p = 0.0035), smaller long axis (p = 0.0015), smaller values for the small axis (p = 0.0008), smaller mean nuclear volume (3, p = 0.0146) and lower mean internuclear distance (p = 0.0007) but a higher nucleus to cytoplasm ratio (>1.1, p = 0.0418), higher axis ratio (>1.2, p = 0.088), higher acyclicity grade (>1.145, p = 0.0857) and higher anellipticity grade (>1.14, p = 0.1362). These parameters can be used for the evaluation of risk category of developing bone metastases. These results can be useful for the evaluation of bone metastatic potential of breast cancer and for the selection of high-risk patients whose molecular profiles would require further investigations and evaluation.

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