ABSTRACT In silico oncology is anticipated to gain a more individualized treatment for patients with cancer. To run in silico oncology models data from individual patients are essential. The more and the more accurate these data are the... more
ABSTRACT In silico oncology is anticipated to gain a more individualized treatment for patients with cancer. To run in silico oncology models data from individual patients are essential. The more and the more accurate these data are the more precise the results of the in silico oncology models will be. Imaging studies are used to calculate tumor volume and define vital, necrotic and cystic areas within a tumor. Though the visual interpretation of magnetic resonance (MR) images is based on qualitative observation of variation in signal intensity a correlation of signal intensities with histological features of a tumor is not possible. Quantitative methods are needed for reliable follow-up or inter-individual studies. Using DoctorEye tumors can be easily rendered and histograms of the signal intensities within a tumor as well as mean and median signal intensities are calculated. In gliomas the histogram of signal intensities of cerebrospinal fluid is used as a reference for standardization of signal intensities. Our results in gliomas suggest that these histograms add value for a better description of tumors for the use in insilico oncology models.
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ABSTRACT This short communication briefly outlines the major components and the integration steps of the Oncosimulator that is being developed within the framework of the European Commission funded ContraCancrum project. The Oncosimulator... more
ABSTRACT This short communication briefly outlines the major components and the integration steps of the Oncosimulator that is being developed within the framework of the European Commission funded ContraCancrum project. The Oncosimulator is a technologically advanced multiscale tumor growth and treatment response system aiming at supporting patient individualized treatment decisions. An indicative example of the adopted mathematical approaches as well as a simple example of numerical code validation are provided. The document concludes with a short discussion on the characteristics of the major modeling approaches that refer to the cellular and higher biocomplexity levels since the latter constitute the basis for the entire Oncosimulator integration.
In the present paper, the dynamic behavior of a clinically-oriented simulation model of breast tumor response to chemotherapy is investigated. The model incorporates various biological processes such as cycling of proliferating cells,... more
In the present paper, the dynamic behavior of a clinically-oriented simulation model of breast tumor response to chemotherapy is investigated. The model incorporates various biological processes such as cycling of proliferating cells, quiescence, differentiation and cell death. Indicative results drawn from an extensive parametric analysis of the model are presented.
A brief introduction into the basics of a top-down multiscale tumour dynamics modelling method primarily based on the consideration and manipulation of discrete biological entities and events is presented. The method is clearly clinically... more
A brief introduction into the basics of a top-down multiscale tumour dynamics modelling method primarily based on the consideration and manipulation of discrete biological entities and events is presented. The method is clearly clinically oriented. One of its major goals is to support patient individualized treatment optimization through experimentation in silico (=on the computer). Therefore, modelling of the treatment response of clinical tumours lies at the epicenter of the approach. Macroscopic data, including i.a. anatomic and metabolic tomographic images of the tumour, provide the Virtual Physiological Human (VPH) framework for the integration of data and mechanisms pertaining to lower and lower biocomplexity levels such as clinically approved cellular and molecular biomarkers. The method also provides a powerful framework for the investigation of multiscale tumour biology in the generic investigational context. The Oncosimulator, a multiscale basic science and biomedical engi...
The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the... more
The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of in silico oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adapt...
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Research Interests: Algorithms, Clinical Trial, Cytokines, Multiscale Modeling, Personalized Medicine, and 19 moreSensitivity Analysis, Stem Cell, Multidisciplinary, Clinical Practice, Humans, Child, Computer Simulation, Computer Model, PLoS one, Clinical Data, Time Factors, Growth rate, Reproducibility of Results, Nutrient Availability, In Silico, Tumor Growth, Simulation Model, Translational Medical Research, and Wilms' tumor
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Research Interests: Information Systems, Computer Science, Computational Modeling, Systems Biology, Cancer, and 12 moreWeb Services, Personalized Medicine, Signal Transduction, Software, Humans, Computer Simulation, Computer User Interface Design, Mathematical Model, Data Models, Neoplasms, Individualized Medicine, and Internet
The "Oncosimulator" is at the same time a concept of multilevel integrative cancer and (treatment affected) normal tissue biology, an algorithmic construct and a software tool which aims at supporting the clinician in the... more
The "Oncosimulator" is at the same time a concept of multilevel integrative cancer and (treatment affected) normal tissue biology, an algorithmic construct and a software tool which aims at supporting the clinician in the process of optimizing cancer treatment on the patient individualized basis. Additionally it is a platform for better understanding and exploring the natural phenomenon of cancer as well as training doctors and interested patients alike. In order to achieve all of these goals it has to undergo a thorough clinical optimization and validation process. This is one of the goals of the European Commission funded integrated project "ACGT: Advancing Clinicogenomic Trials on Cancer". Nephroblastoma (Wilms' tumor) and breast cancer have been selected to serve as two paradigms to clinically specify and evaluate the "Oncosimulator" as well as the emerging domain of in silico oncology.
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Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to... more
Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.
Research Interests: Magnetic Resonance Imaging, Finite element method, Treatment Outcome, Systems Integration, Finite Element Analysis, and 17 moreHumans, Glioblastoma, PARTIAL DIFFERENTIAL EQUATION, Glioblastoma Multiforme, Biological Process, Moment of Inertia, Treatment planning, In Silico, Biological System Modeling, Diffusion Model, Mechanical Processes, Tumor Growth, Rule Based, Pressure Effect, Monte Carlo Method, Biochemistry and cell biology, and Biomechanical Phenomena
Research Interests: Algorithms, Clinical Trial, Breast Cancer, Cell Cycle, Treatment Outcome, and 29 moreSensitivity Analysis, Stem Cell, Apoptosis, Theoretical biology, Gene expression, Biological Sciences, Software Design, Humans, Computer Simulation, Mathematical Sciences, Female, Multiscale Simulation, Early Breast Cancer, Theoretical, Biological systems, Clinical Data, Necrosis, Neoplasms, Clinical Study, Discrete Event, Cell Proliferation, Individualized Medicine, In Silico, DNA binding proteins, Critical Parameter, Simulation Model, Time Course, National Technical University of Athens, and Adaptive Optimization
Abstract-This short paper provides a brief outline of the main components and the developmental and translational process of the ACGT Oncosimulator. The Oncosimulator is an integrated software system simulating in vivo tumor response to... more
Abstract-This short paper provides a brief outline of the main components and the developmental and translational process of the ACGT Oncosimulator. The Oncosimulator is an integrated software system simulating in vivo tumor response to therapeutic modalities within the clinical trial environment. It aims at supporting patient individualized optimization of cancer treatment. The four dimensional
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Grid-based system, under development within a 25-partner European-Japanese project, for patient-specific simulation of the response of a tumor and its surrounding tissue to various forms of therapy. The validation of the simulation code... more
Grid-based system, under development within a 25-partner European-Japanese project, for patient-specific simulation of the response of a tumor and its surrounding tissue to various forms of therapy. The validation of the simulation code is an activity requiring extensive human-driven visual investigation of the influence of each of the dozens of parameters to the code, initially by comparing results from simulations carried out with different parameter values. This activity requires that users be supported in specifying simulation runs based ...