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dc.contributor.author
Peñaherrera Pazmiño, Ana Belén  
dc.contributor.author
Isa Jara, Ramiro Fernando  
dc.contributor.author
Hincapié Arias, Elsa Lourdes  
dc.contributor.author
Gómez, Silvia  
dc.contributor.author
Belgorosky, Denise  
dc.contributor.author
Agüero, Eduardo Imanol  
dc.contributor.author
Tellado, Matías Nicolás  
dc.contributor.author
Eijan, Ana Maria  
dc.contributor.author
Lerner, Betiana  
dc.contributor.author
Perez, Maximiliano Sebastian  
dc.date.available
2025-02-28T10:19:51Z  
dc.date.issued
2024-11  
dc.identifier.citation
Peñaherrera Pazmiño, Ana Belén; Isa Jara, Ramiro Fernando; Hincapié Arias, Elsa Lourdes; Gómez, Silvia; Belgorosky, Denise; et al.; AQSA—Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices; MDPI; Journal of Imaging; 10; 11; 11-2024; 1-18  
dc.identifier.issn
2313-433X  
dc.identifier.uri
http://hdl.handle.net/11336/255362  
dc.description.abstract
Sphere formation assay is an accepted cancer stem cell (CSC) enrichment method. CSCsplay a crucial role in chemoresistance and cancer recurrence. Therefore, CSC growth is studied inplates and microdevices to develop prediction chemotherapy assays in cancer. As counting spheres cultured in devices is laborious, time-consuming, and operator-dependent, a computational program called the Automatic Quantification of Spheres Algorithm (ASQA) that detects, identifies, counts, and measures spheres automatically was developed. The algorithm and manual counts were compared, and there was no statistically significant difference (p = 0.167). The performance of the AQSA is better when the input image has a uniform background, whereas, with a nonuniform background, artifacts can be interpreted as spheres according to image characteristics. The areas of spheres derived from LN229 cells and CSCs from primary cultures were measured. For images with one sphere, area measurements obtained with the AQSA and SpheroidJ were compared, and there was no statistically significant difference between them (p = 0.173). Notably, the AQSA detects more than one sphere, compared to other approaches available in the literature, and computes the sphere area automatically, which enables the observation of treatment response in the sphere derived from the human glioblastoma LN229 cell line. In addition, the algorithm identifies spheres with numbers to identify each one over time. The AQSA analyzes many images in 0.3 s per image with a low computational cost, enabling laboratories from developing countries to perform sphere counts and area measurements without needing a powerful computer. Consequently, it can be a useful tool for automated CSC quantification from cancer cell lines, and it can be adjusted to quantify CSCs from primary culture cells. CSC-derived sphere detection is highly relevant as it avoids expensive treatments and unnecessary toxicity.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
MDPI  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
ARTIFICIAL INTELLIGENCE  
dc.subject
CANCER  
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CSCS  
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ALGORITHM  
dc.subject.classification
Otras Nanotecnología  
dc.subject.classification
Nanotecnología  
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INGENIERÍAS Y TECNOLOGÍAS  
dc.title
AQSA—Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2025-02-26T11:57:35Z  
dc.journal.volume
10  
dc.journal.number
11  
dc.journal.pagination
1-18  
dc.journal.pais
Suiza  
dc.description.fil
Fil: Peñaherrera Pazmiño, Ana Belén. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional; Argentina  
dc.description.fil
Fil: Isa Jara, Ramiro Fernando. Universidad Tecnológica Nacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Hincapié Arias, Elsa Lourdes. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina  
dc.description.fil
Fil: Gómez, Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina  
dc.description.fil
Fil: Belgorosky, Denise. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina  
dc.description.fil
Fil: Agüero, Eduardo Imanol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina  
dc.description.fil
Fil: Tellado, Matías Nicolás. Universidad de Buenos Aires; Argentina  
dc.description.fil
Fil: Eijan, Ana Maria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Oncología "Ángel H. Roffo"; Argentina  
dc.description.fil
Fil: Lerner, Betiana. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional; Argentina  
dc.description.fil
Fil: Perez, Maximiliano Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnológica Nacional; Argentina  
dc.journal.title
Journal of Imaging  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2313-433X/10/11/295  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3390/jimaging10110295