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...
| الحاوية / القاعدة: | Diagnostics |
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| المؤلفون الرئيسيون: | , , , , , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
MDPI AG
2023-10-01
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.mdpi.com/2075-4418/13/21/3338 |
| _version_ | 1852651609732939776 |
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| author | Simona-Alina Duca-Barbu Alexandru Adrian Bratei Antonia-Carmen Lisievici Tiberiu Augustin Georgescu Bianca Mihaela Nemes Maria Sajin Florinel Pop |
| author_facet | Simona-Alina Duca-Barbu Alexandru Adrian Bratei Antonia-Carmen Lisievici Tiberiu Augustin Georgescu Bianca Mihaela Nemes Maria Sajin Florinel Pop |
| author_sort | Simona-Alina Duca-Barbu |
| collection | DOAJ |
| container_title | Diagnostics |
| 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<sup>2</sup>, <i>p</i> = 0.0035), smaller long axis (<9 µm, <i>p</i> = 0.0015), smaller values for the small axis (<7 µm, <i>p</i> = 0.0008), smaller mean nuclear volume (<200 µm<sup>3</sup>, <i>p</i> = 0.0146) and lower mean internuclear distance (<10.5 µm, <i>p</i> = 0.0007) but a higher nucleus to cytoplasm ratio (>1.1, <i>p</i> = 0.0418), higher axis ratio (>1.2, <i>p</i> = 0.088), higher acyclicity grade (>1.145, <i>p</i> = 0.0857) and higher anellipticity grade (>1.14, <i>p</i> = 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. |
| format | Article |
| id | doaj-art-e7c2389fb94a49b58c59fc13ed1997e4 |
| institution | Directory of Open Access Journals |
| issn | 2075-4418 |
| language | English |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-e7c2389fb94a49b58c59fc13ed1997e42025-08-19T21:40:54ZengMDPI AGDiagnostics2075-44182023-10-011321333810.3390/diagnostics13213338A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational MathematicsSimona-Alina Duca-Barbu0Alexandru Adrian Bratei1Antonia-Carmen Lisievici2Tiberiu Augustin Georgescu3Bianca Mihaela Nemes4Maria Sajin5Florinel Pop6Department of Pathology, “Carol Davila” Clinical Nephrology Hospital, 010731 Bucharest, RomaniaFaculty of Chemical Engineering and Biotechnologies, University Politehnica of Bucharest, 011061 Bucharest, RomaniaDepartment of Pathology, “Carol Davila” Clinical Nephrology Hospital, 010731 Bucharest, RomaniaDepartment of Pathology, University of Medicine and Pharmacy “Carol Davila”, 020022 Bucharest, RomaniaInternational Computer High School of Bucharest, 032622 Bucharest, RomaniaDepartment of Pathology, University of Medicine and Pharmacy “Carol Davila”, 020022 Bucharest, RomaniaDepartment of Pathology, “Carol Davila” Clinical Nephrology Hospital, 010731 Bucharest, RomaniaBone 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<sup>2</sup>, <i>p</i> = 0.0035), smaller long axis (<9 µm, <i>p</i> = 0.0015), smaller values for the small axis (<7 µm, <i>p</i> = 0.0008), smaller mean nuclear volume (<200 µm<sup>3</sup>, <i>p</i> = 0.0146) and lower mean internuclear distance (<10.5 µm, <i>p</i> = 0.0007) but a higher nucleus to cytoplasm ratio (>1.1, <i>p</i> = 0.0418), higher axis ratio (>1.2, <i>p</i> = 0.088), higher acyclicity grade (>1.145, <i>p</i> = 0.0857) and higher anellipticity grade (>1.14, <i>p</i> = 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.https://www.mdpi.com/2075-4418/13/21/3338breast cancerbone metastasistumor morphometrydigital pathology |
| spellingShingle | Simona-Alina Duca-Barbu Alexandru Adrian Bratei Antonia-Carmen Lisievici Tiberiu Augustin Georgescu Bianca Mihaela Nemes Maria Sajin Florinel Pop A Novel Algorithm for Evaluating Bone Metastatic Potential of Breast Cancer through Morphometry and Computational Mathematics breast cancer bone metastasis tumor morphometry digital pathology |
| 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 | breast cancer bone metastasis tumor morphometry digital pathology |
| url | https://www.mdpi.com/2075-4418/13/21/3338 |
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