Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma

Johanna Sapi, Daniel Andras Drexler, Istvan Harmati, Annamaria Szeles, Bernadett Kiss, Z. Sápi, L. Kovács

Research output: Conference contribution

8 Citations (Scopus)

Abstract

Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.

Original languageEnglish
Title of host publicationSACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings
Pages303-308
Number of pages6
DOIs
Publication statusPublished - 2013
Event8th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2013 - Timisoara
Duration: máj. 23 2013máj. 25 2013

Other

Other8th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2013
CityTimisoara
Period5/23/135/25/13

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Tumors
Identification (control systems)
Linear regression
Antibodies
Regression analysis
Linear systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

Cite this

Sapi, J., Drexler, D. A., Harmati, I., Szeles, A., Kiss, B., Sápi, Z., & Kovács, L. (2013). Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma. In SACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings (pp. 303-308). [6608987] https://doi.org/10.1109/SACI.2013.6608987

Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma. / Sapi, Johanna; Drexler, Daniel Andras; Harmati, Istvan; Szeles, Annamaria; Kiss, Bernadett; Sápi, Z.; Kovács, L.

SACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2013. p. 303-308 6608987.

Research output: Conference contribution

Sapi, J, Drexler, DA, Harmati, I, Szeles, A, Kiss, B, Sápi, Z & Kovács, L 2013, Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma. in SACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings., 6608987, pp. 303-308, 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2013, Timisoara, 5/23/13. https://doi.org/10.1109/SACI.2013.6608987
Sapi J, Drexler DA, Harmati I, Szeles A, Kiss B, Sápi Z et al. Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma. In SACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2013. p. 303-308. 6608987 https://doi.org/10.1109/SACI.2013.6608987
Sapi, Johanna ; Drexler, Daniel Andras ; Harmati, Istvan ; Szeles, Annamaria ; Kiss, Bernadett ; Sápi, Z. ; Kovács, L. / Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma. SACI 2013 - 8th IEEE International Symposium on Applied Computational Intelligence and Informatics, Proceedings. 2013. pp. 303-308
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