Computational and Mathematical Methods in Medicine

Computational and Mathematical Modeling of Tumor Kinetics and Response to Radiation and Chemotherapy


Publishing date
13 Jul 2012
Status
Published
Submission deadline
24 Feb 2012

Lead Editor

1Department of Medical Physics, Royal Adelaide Hospital, School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000, Australia

2Faculty of Science, University of Oradea, 410087 Oradea, Romania

3Department of Medical Physics, Royal Adelaide Hospital, North Terrace, SA 5000, Australia


Computational and Mathematical Modeling of Tumor Kinetics and Response to Radiation and Chemotherapy

Description

Over the last few decades, computational and mathematical modeling of tumor behavior and response to treatment has become an integral part of oncological research, transitioning from a preclinical tool status to a clinical aid in advanced treatment planning and biological optimization. While models in cancer research will not replace the need for in vitro studies or clinical trials, the advantages presented by theoretical models complement the limitations imposed by other techniques.

Advancements in molecular biology, treatment techniques, and imaging modalities, as well as the better understanding of the underlying radiobiology, initiated branching developments in computational and mathematical modeling of biological processes concerning spatial/temporal tumor growth, angiogenesis, bystander effects, low-dose response, tumor response to treatment, normal tissue toxicity, risk of second cancer, and several more.

Advances in micro- and nanodosimetry have also led to the utilization of radiation-transport-based radiobiology simulations. Such work allows for low-cost feasibility investigations into the effectiveness of novel treatment modalities, based on the physical properties of the radiation.

Models in cancer research are simplified illustrations of biological reality. Yet, due to their flexible structure, models can answer the “what if” question encountered by clinical scenarios without the confrontation of trials.

This special issue aims to publish novel articles on various aspects of modeling in oncology including, but not limited to, analytical, statistical, combinatorial modeling techniques, and transport codes solutions. Potential topics include, but are not limited to:

  • Modeling of cellular kinetics and tumor growth
  • Modeling hypoxia and angiogenesis
  • Tumor response to chemo- and radiotherapy
  • Altered/novel treatment schedules in chemical, radiation, and combined therapies
  • Modeling of response to treatment modifiers
  • Modeling of normal tissue toxicities
  • Tumor resistance to chemo- and radiotherapy
  • Modeling of radiation transport, radiation damage, and dose accumulation
  • Novel therapies: nanoparticles, high LET therapy, targeted therapies, and Auger electron therapy
  • Biological optimization for RT treatment planning
  • Modeling of bystander effects

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