Literature DB >> 12859142

Growth of a virtual tumour using probabilistic methods of cell generation.

L Marcu1, T van Doorn, S Zavgorodni, I Olver.   

Abstract

A study into treatment enhancement in combined chemo-radiotherapy for unresectable head and neck cancer has initiated the development of a computer model of tumour growth. The model is based on biological parameters, and characterises tumour growth prior to chemo-radiotherapy. Tumour growth starting from a single stem cell is modelled using the Monte Carlo method. The type of the cell function, their relative proportions on mitosis, their proliferative capacity, the duration of the four phases of the cell cycle, the mean cell cycle time, and the cell loss due to natural causes are the main parameters of the basic model. A Gaussian distribution function operates in establishing the cell cycle time, with a mean value of 33 hours, while the cell type is sampled from a uniform distribution. With the established model, the sensitivity of the developed tumour's cell population to the stem, proliferative and nonproliferative ratio at mitosis was assessed. The present model accurately reflects the exponential distribution of cells along the cell cycle (70% cells in GI phase, 15% in S, 10% in G2, 5% in M) of a developed tumour as described in the literature. The proportion of stem, finitely proliferating and resting cells during tumour growth is maintained within their biological limits (2% stem, 13% finitely proliferating, 85% nonproliferating cells). The ratio (R = 3) between the time necessary to develop a clinically detectable tumour (10(9) cells) and the further time to grow to its lethal size (10(12) cells) is in accordance with the biological data when tumour volume is compared for the two periods (30 doublings and 10 doublings respectively). In conclusion, computer simulation can illustrate the biological growth of a tumour and the cell distribution along the cell cycle. These distributions may then be used in the assessment of tumour response to radiotherapy and to specific chemotherapeutic agents.

Entities:  

Mesh:

Year:  2002        PMID: 12859142     DOI: 10.1007/bf03178288

Source DB:  PubMed          Journal:  Australas Phys Eng Sci Med        ISSN: 0158-9938            Impact factor:   1.430


  9 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.  Influence of stem-cell cycle time on accelerated re-population during radiotherapy in head and neck cancer.

Authors:  L G Marcu; E Bezak
Journal:  Cell Prolif       Date:  2012-07-07       Impact factor: 6.831

3.  Tumour repopulation and the role of abortive division in squamous cell carcinomas during chemotherapy.

Authors:  L G Marcu
Journal:  Cell Prolif       Date:  2014-05-13       Impact factor: 6.831

Review 4.  Integrated PK-PD and agent-based modeling in oncology.

Authors:  Zhihui Wang; Joseph D Butner; Vittorio Cristini; Thomas S Deisboeck
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-01-15       Impact factor: 2.745

5.  In silico study of the impact of cancer stem cell dynamics and radiobiological hypoxia on tumour response to hyperfractionated radiotherapy.

Authors:  L G Marcu; D Marcu; S M Filip
Journal:  Cell Prolif       Date:  2016-04-15       Impact factor: 6.831

6.  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

7.  Radiobiological modeling of interplay between accelerated repopulation and altered fractionation schedules in head and neck cancer.

Authors:  Loredana G Marcu; Eva Bezak
Journal:  J Med Phys       Date:  2009-10

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

9.  In silico modelling of a cancer stem cell-targeting agent and its effects on tumour control during radiotherapy.

Authors:  Loredana G Marcu; David Marcu
Journal:  Sci Rep       Date:  2016-08-30       Impact factor: 4.379

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.