A non-parametric method for the analysis of experimental tumour growth data

R. Chignola, D. Liberati, E. Chiesa, C. Anselmi, R. Foroni, S. Sartoris, A. Brendolan, G. Tridente, G. Andrighetto

Research output: Contribution to journalArticlepeer-review

Abstract

Analysis of tumour growth is required to investigate the biology of tumours and to determine the effects of new anti-tumour therapies. A non-parametric mathematical method for the analysis of a set of experimental tumour growth data is described. The method is based on the similarity between time series of tumour size measurements (e.g. tumour volume), similarity being defined as the Euclidean distance between data measured for each tumour at the same time. Subsets of similar time series are found for a given population of tumours. A biologically meaningful parameter H has been derived which is a measure of the scattering of experimental volume samples. The method has been applied to the analysis of the growth of (i) untreated multicellular tumour spheroids obtained with different cell lines and (ii) spheroids treated with cytotoxic drugs (immunotoxins). Results are compared with those previously obtained by applying the classical Gompertz growth model to the analysis of treated and untreated spheroids.

Original languageEnglish
Pages (from-to)537-542
Number of pages6
JournalMedical and Biological Engineering and Computing
Volume37
Issue number4
Publication statusPublished - 1999

Keywords

  • Mathematical modelling
  • Signal analysis
  • Tumour growth
  • Tumour spheroids
  • Variability

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management
  • Computer Science Applications
  • Computational Theory and Mathematics

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