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

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’ managem...

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Autores principales: Duca-Barbu, Simona-Alina, Bratei, Alexandru Adrian, Lisievici, Antonia-Carmen, Georgescu, Tiberiu Augustin, Nemes, Bianca Mihaela, Sajin, Maria, Pop, Florinel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650224/
https://www.ncbi.nlm.nih.gov/pubmed/37958234
http://dx.doi.org/10.3390/diagnostics13213338
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author Duca-Barbu, Simona-Alina
Bratei, Alexandru Adrian
Lisievici, Antonia-Carmen
Georgescu, Tiberiu Augustin
Nemes, Bianca Mihaela
Sajin, Maria
Pop, Florinel
author_facet Duca-Barbu, Simona-Alina
Bratei, Alexandru Adrian
Lisievici, Antonia-Carmen
Georgescu, Tiberiu Augustin
Nemes, Bianca Mihaela
Sajin, Maria
Pop, Florinel
author_sort Duca-Barbu, Simona-Alina
collection PubMed
description 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 (<55 µm(2), p = 0.0035), smaller long axis (<9 µm, p = 0.0015), smaller values for the small axis (<7 µm, p = 0.0008), smaller mean nuclear volume (<200 µm(3), p = 0.0146) and lower mean internuclear distance (<10.5 µm, 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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spelling pubmed-106502242023-10-30 A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics Duca-Barbu, Simona-Alina Bratei, Alexandru Adrian Lisievici, Antonia-Carmen Georgescu, Tiberiu Augustin Nemes, Bianca Mihaela Sajin, Maria Pop, Florinel Diagnostics (Basel) Article 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 (<55 µm(2), p = 0.0035), smaller long axis (<9 µm, p = 0.0015), smaller values for the small axis (<7 µm, p = 0.0008), smaller mean nuclear volume (<200 µm(3), p = 0.0146) and lower mean internuclear distance (<10.5 µm, 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. MDPI 2023-10-30 /pmc/articles/PMC10650224/ /pubmed/37958234 http://dx.doi.org/10.3390/diagnostics13213338 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Duca-Barbu, Simona-Alina
Bratei, Alexandru Adrian
Lisievici, Antonia-Carmen
Georgescu, Tiberiu Augustin
Nemes, Bianca Mihaela
Sajin, Maria
Pop, Florinel
A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title_full A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title_fullStr A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title_full_unstemmed A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title_short A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics
title_sort novel algorithm for evaluating bone metastatic potential of breast cancer through morphometry and computational mathematics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650224/
https://www.ncbi.nlm.nih.gov/pubmed/37958234
http://dx.doi.org/10.3390/diagnostics13213338
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