Literature DB >> 7488961

Modeling of radiogenic responses induced by fractionated irradiation in malignant and normal tissue.

W Düchting1, T Ginsberg, W Ulmer.   

Abstract

The aim of this contribution is to outline how methods of system analysis, control theory and computer science can be applied to simulate malignant and normal cell growth and to optimize cancer treatment. Based on biological observations and cell kinetic data, our group has constructed three types of computer models: 1) A cell cycle model describing the spatial (3D) and temporal growth of tumor spheroids; 2) A compartment model describing the growth of rapidly proliferating normal cells; 3) A compartment model simulating slowly proliferating normal tissues. These growth models have been extended by an irradiation model based on the linear-quadratic survival function. Different clinical fractionation schemes (standard-, super-, hyperfractionation and weekly high single dose) have been applied to the tissues mentioned above. The simulation results show that in the case of irradiating a rapidly growing tumor spheroid the hyperfractionation (3 x 1-1.5 Gy per day) leads to a particularly good anti-tumor effectiveness. On the other hand, the radiogenic response of rapidly growing normal tissue to a hyperfractionated treatment schedule is severe. The same result is observed when simulating the late reaction on slowly growing parenchymal tissue. Therefore, this therapeutic modality is ensured only if the overall dose is reduced from DTOTAL = 60 Gy to DTOTAL = 50 Gy.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1995        PMID: 7488961     DOI: 10.1002/stem.5530130737

Source DB:  PubMed          Journal:  Stem Cells        ISSN: 1066-5099            Impact factor:   6.277


  8 in total

1.  Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer.

Authors:  W M Harriss-Phillips; E Bezak; E K Yeoh
Journal:  Br J Radiol       Date:  2011-10       Impact factor: 3.039

2.  Optimal solution for a cancer radiotherapy problem.

Authors:  A Bertuzzi; C Bruni; F Papa; C Sinisgalli
Journal:  J Math Biol       Date:  2013-01       Impact factor: 2.259

Review 3.  Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.

Authors:  Maria Protopapa; Anna Zygogianni; Georgios S Stamatakos; Christos Antypas; Christina Armpilia; Nikolaos K Uzunoglu; Vassilis Kouloulias
Journal:  J Neurooncol       Date:  2017-10-28       Impact factor: 4.130

4.  Optimal weekly scheduling in fractionated radiotherapy: effect of an upper bound on the dose fraction size.

Authors:  C Bruni; F Conte; F Papa; C Sinisgalli
Journal:  J Math Biol       Date:  2014-08-29       Impact factor: 2.259

5.  The HYP-RT hypoxic tumour radiotherapy algorithm and accelerated repopulation dose per fraction study.

Authors:  W M Harriss-Phillips; E Bezak; E Yeoh
Journal:  Comput Math Methods Med       Date:  2012-06-19       Impact factor: 2.238

6.  Introduction of hypermatrix and operator notation into a discrete mathematics simulation model of malignant tumour response to therapeutic schemes in vivo. Some operator properties.

Authors:  Georgios S Stamatakos; Dimitra D Dionysiou
Journal:  Cancer Inform       Date:  2009-10-21

Review 7.  In silico modelling of tumour margin diffusion and infiltration: review of current status.

Authors:  Fatemeh Leyla Moghaddasi; Eva Bezak; Loredana Marcu
Journal:  Comput Math Methods Med       Date:  2012-07-11       Impact factor: 2.238

Review 8.  In silico modelling of treatment-induced tumour cell kill: developments and advances.

Authors:  Loredana G Marcu; Wendy M Harriss-Phillips
Journal:  Comput Math Methods Med       Date:  2012-07-12       Impact factor: 2.238

  8 in total

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