Complex shape markers can detect alterations in the spatial distribution of cell nuclei in human lung squamous cell carcinoma: a useful tool for automatic analysis?
Lung cancer is the leading cause of cancer-related death. The use of computational methods to quantify changes that are not perceptible to the human eye is increasing in digital pathology imaging and has quickly improved detection rates at a low cost. Therefore, the present study aims to use complex...
| Publicado en: | Histochemistry & Cell Biology Vol. 163; no. 1; pp. 1 - 10 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180733815&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180733815 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09486143 NQI jtl: Histochemistry & Cell Biology issn: 09486143 maglogo: N pubinfo: dt: 2025 vid: 163 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 180733815 10.1007/s00418-024-02336-3 180733815 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Complex shape markers can detect alterations in the spatial distribution of cell nuclei in human lung squamous cell carcinoma: a useful tool for automatic analysis? aug: au: dos Santos, Ana Vitoria Ferreira da Silva Ferreira, Renan Gabriel das Chagas Angelo Mendes Tenorio, Fernanda Maia, Carina Scanoni da Silva Junior, Valdemiro Amaro de Albuquerque Nogueira, Romildo Tenorio, Bruno Mendes affil: https://ror.org/047908t24 Department of Histology and Embryology, Bioscience Center, Federal University of Pernambuco, Av. Prof. Moraes Rego, S/N, Cidade Universitária, 760-420, Recife, Pernambuco, Brazil sug: ab: Lung cancer is the leading cause of cancer-related death. The use of computational methods to quantify changes that are not perceptible to the human eye is increasing in digital pathology imaging and has quickly improved detection rates at a low cost. Therefore, the present study aims to use complex computational shape markers as tools for automated analysis of the spatial distribution of cells in microscopy images of squamous cell lung carcinoma (SqCC). Photomicrographs from pathology glass slides in the LC25000 dataset were used in this study. Compared with those of the control, the fractal dimension (28%) and lacunarity (41%) of the cell nuclei changed in SqCC. The multifractal analysis revealed a significant difference in parameters Dq, α, and f(α) for all values of q (−10 to + 10), with a greater increase for more positive q values. The values at q + 10 increased by 34% for Dq, 36% for α, and 53% for f(α) in the SqCC images. The circularity, area, and perimeter also changed in the SqCC images. However, the parameters of aspect ratio, roundness, and solidity did not significantly differ between SqCC and benign tissue. The complex shape markers with the greatest changes in this study were the f(α) values for multifractality (53%) and lacunarity (41%). In conclusion, automated quantification of the spatial distribution of cell nuclei can be a fast, low-cost tool for evaluating the microscopic characteristics of SqCC; therefore, complex shape markers could be useful tools for software and artificial intelligence to detect lung carcinoma. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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