Georgios S Stamatakos

National Technical University of Athens | NTUA · Institute of Communication and Computer Systems School of Electrical and Computer Engineering

The concept of in silica radiation oncology is clarified in this paper. A brief literature review points out the principal domains in which experimental, mathematical, and three-dimensional (3-D) computer simulation models of tumor growth and response to radiation therapy have been developed. Two paradigms of 3-D simulation models developed by our...

This paper outlines the major components and function of the Technologically Integrated Oncosimulator developed primarily within the ACGT (Advancing Clinico Genomic Trials on Cancer) project. The Oncosimulator is defined as an information technology system simulating in vivo tumor response to therapeutic modalities within the clinical trial context...

Cancer is a complex disease process that spans multiple scales in space and time. Driven by cutting-edge mathematical and computational techniques, in silico biology provides powerful tools to investigate the mechanistic relationships of genes, cells, and tissues. It enables the creation of experimentally testable hypotheses, the integration of dat...

Apart from offering insight into the biomechanisms involved in cancer, many recent mathematical modeling efforts aspire to the ultimate goal of clinical translation, wherein models are designed to be used in the future as clinical decision support systems in the patient-individualized context. Most significant challenges are the integration of mult...

We aimed to (a) investigate the interplay between depression, symptoms and level of functioning, and (b) understand the paths through which they influence health related quality of life (QOL) during the first year of rehabilitation period of early breast cancer. A network analysis method was used. The population consisted of 487 women aged 35–68 ye...

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the dat...

The massive amount of human biological, imaging, and clinical data produced by multiple and diverse sources necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of t...

We aimed to (a) investigate the interplay between depression, symptoms and level of functioning, and (b) understand the paths through which they influence health related quality of life (QOL) during the first year of rehabilitation period of early breast cancer. A network analysis method was used. The population consisted of 487 women aged 35-68 ye...

The massive amount of human biological, imaging and clinical data produced by multiple and diverse sources, necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of t...

Objective This study aimed to describe distinct trajectories of anxiety/depression symptoms and overall health status/quality of life over a period of 18 months following a breast cancer diagnosis, and identify the medical, socio‐demographic, lifestyle, and psychological factors that predict these trajectories. Methods 474 females (mean age = 55.7...

Objective: This study aimed to examine whether self-efficacy to cope with cancer changes over time in patients with breast cancer and whether these potential changes are similar across patients. It also aimed to examine whether these trajectories are related to patient psychological well-being and overall quality of life. Methods: Participants (...

The current study aimed to track the trajectory of quality of life (QoL) among subgroups of women with breast cancer in the first 12 months post-diagnosis. We also aimed to assess the number and portion of women classified into each distinct trajectory and the sociodemographic, clinical, and psychosocial factors associated with these trajectories....

In silico (computational) medicine (ISM) is an emergent scientific and technological domain aiming at transforming medicine into an exact quantitative scientific discipline with parsimonious overarching mathematical principles, methods, computational and artificial intelligence (AI) models and in-silico simulations – i.e. simulations on the compute...

Background: Identifying and understanding modifiable factors for the well-being of cancer patients is critical in survivorship research. We studied variables associated with the exercise habits of breast cancer patients and investigated if the achievement of exercise recommendations was associated with enhanced quality of life and/or psychological...

Background: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient’s sociodemographic and psychological characteri...

1. Introduction Coping with breast cancer has been acknowledged as a major socio-economic challenge. There is a growing need for novel in silico approaches to predict and enhance the resilience of women to the variety of stressful experiences and practical challenges related to breast cancer [1,2,3]. In this context, a prospective clinical study ha...

1. Introduction The Nephroblastoma Oncosimulator (NO) is a digital twin for Wilms tumour that is based on a mechanistic multiscale simulation model of tumour growth and response to treatment. It exploits the patient’s imaging, cellular, molecular and clinical data [1,2]. The NO maps the patient’s imaging and other data into a 3D discretization mesh...

Machine Learning (ML) represents a computer science capable of generating predictive models, by exposure to raw, training data, without being rigidly programmed. Over the last few years, ML has gained attention within the field of oncology, with considerable strides in both diagnostic, predictive, and prognostic spectrum of malignancies, but also a...

The role of self-efficacy to cope with breast cancer as a mediator and/or moderator in the relationship of trait resilience to quality of life and psychological symptoms was examined in this study. Data from the BOUNCE Project (https://www.bounce-project.eu/) were used. Women diagnosed with and in treatment for breast cancer (N = 484), from four co...

BACKGROUND Despite the continued progress of medicine, dealing with breast cancer is becoming a major socio-economic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer, but also on the patient's socio-demographic and psychological characte...

Background: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient's sociodemographic and psychological character...

A brief historical tracing of the global emergence of the new scientific, technological and progressively clinical domain of in silico medicine in Greece is presented.

Objective The main objective of this prospective multicenter study was to examine whether illness representations of control, affect, and coping behaviors mediate the effects of self‐efficacy to cope with cancer on psychological symptoms and overall quality of life, in breast cancer patients. Method Data from 413 women (Mean age=54.87; SD=8.01), c...

Abstract Background the aim of this study is to perform an external validation for the Candiolo nomogram, a predictive algorithm of biochemical and clinical recurrences in prostate cancer patients treated by radical Radiotherapy, published in 2016 on the journal “Radiation Oncology”. Methods 561 patients, treated by Radiotherapy with curative inten...

A brief outline of the mission and the research and teaching activities of the In Silico Oncology and In Silico Medicine Group (ISO&ISM_G) , Institute of Communication and Computer Systems (ICCS), School of Electrical and Computer Engineering (SECE), National Technical University of Athens (NTUA) that I direct.

Background the aim of this study is to perform an external validation for the Candiolo nomogram, a predictive algorithm of biochemical and clinical recurrences in prostate cancer patients treated by radical Radiotherapy, published in 2016 on the journal “Radiation Oncology”. Methods 561 patients, treated by Radiotherapy with curative intent between...

Our study uses AI methodologies to explore a retroscpective data set of 200 breast cancer survivors from the the Davidoff Center at Rabin Medical Center, Israel, focusing on two different tasks: A. To identify subgroups of patients regarding their Mental Status, Quality of Life and Functionality, using measurements of indicative psychosocial variab...

The practical goal of this work is to develop a “bottomup” multiscale (tri-scale) mathematical model of glioma growth, invasion and survival of cells following radiation that would serve as the core of the “Continuous Mathematics Based GBM Oncosimulator.”. It is an extension of the model for untreated glioma growth, described in previous papers to...

Following publication of the original article [1], the authors noticed that the following errors were introduced by pdf/html formatting issues.

Background: Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the m...

Background/aim: The need for more effective treatment modalities that can improve the clinical outcome of patients with glioblastoma multiforme remains imperative. Dendritic cell vaccination is a fast-developing treatment modality, currently under exploration. Functional immune cell subpopulations may play a role in the final outcome. Materials a...

Development, clinical adaptation and partial clinical validation of multiscale cancer hypermodels developed by different modelling groups were three of the major tasks of the recently completed large scale EU-US research project CHIC on in silico oncology. The main goal of the project, of which the outcome was rated as “excellent” by the European C...

Introduction - Medicine is undergoing a paradigm shift from phenotyping to genotyping. In parallel system approaches to disease, new computational and mathematical tools, modelling and visualization technologies together with heterogeneous data from clinical and basic science are able to path the way to precision and predictive medicine

We are very pleased to introduce the proceedings of the Virtual Physiological Human Conference (VPH2018), which collect the abstracts of all the presentations involved in the Conference. The Conference held its 5th meeting in Zaragoza, Spain, during September 5-7th, 2018. This scientific conference focused on "VPH for InSilico Medicine", dealing wi...

Glioblastoma remains a clinical challenge in spite of years of extensive research. Novel approaches are needed in order to integrate the existing knowledge. This is the potential role of mathematical oncology. This paper reviews mathematical models on glioblastoma from the clinical doctor’s point of view, with focus on 3D modeling approaches of rad...

Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combinati...

DC-vaccination integrated in multimodal temozolomid-based treatment for patients with GBM prolong OS in a fraction of patients. Biomarkers predicting outcome after active specific immunotherapy, however, fail. Blood samples from 134 adults, randomized for DC-vaccination during or after TMZ maintenance (TMZm), were taken before and after radiochemot...

Glioblastoma (GB) implies a devastating prognosis with an average survival of 14–16 months using the current standard of care treatment [1]. GB is the most frequent malignant tumour originating from the brain parenchyma, and it is characterised by a marked intratumoural heterogeneity, proneness to infiltrate throughout the brain parenchyma, robust...

Georgios Stamatakos is interviewed by J.Lyons-Weiler, Editor in Chief, Cancer Informatics in 2006. Georgios briefly formulates his philosophical view and vision regarding the extension of the Newtonian approach to the mathematical description of nature so as to include multiscale living matter phenomena and in particular cancer. The interview cover...

The present paper aims at demonstrating clinically oriented applications of the multiscale four dimensional in vivo tumor growth simulation model previously developed by our research group. To this end the effect of weekend radiotherapy treatment gaps and p53 gene status on two virtual glioblastoma tumors differing only in p53 gene status is invest...

A novel explicit triscale reaction-diffusion numerical model of glioblastoma multiforme tumor growth is presented. The model incorporates the handling of Neumann boundary conditions imposed by the cranium and takes into account both the inhomogeneous nature of human brain and the complexity of the skull geometry. The finite-difference time-domain m...

The plethora of available disease prediction models and the ongoing process of their application into clinical practice – following their clinical validation – have created new needs regarding their efficient handling and exploitation. Consolidation of software implementations, descriptive information, and supportive tools in a single place, offeri...

During the last decades, medical observations and multiscale data concerning tumor growth are mounting. At the same time, contemporary imaging techniques well established in clinical practice, provide a variety of information on real-time, in-vivo tumor growth. Mathematical and in-silico modeling has been widely recruited to provide means for furth...

The large scale integrating Euro-American research project CHIC (“Computational Horizons in Cancer: Developing Meta- and Hyper-Multiscale Models and Respositories for In Silico Oncology”) [1] which is funded by the European Commission aims at developing an efficient and robust scientific and technological framework able to support the development o...

The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on...

Background: The adoption in oncology of Clinical Decision Support (CDS) may help clinical users to efficiently deal with the high complexity of the domain, lead to improved patient outcomes, and reduce the current knowledge gap between clinical research and practice. While significant effort has been invested in the implementation of CDS, the upta...

Background Antiangiogenic agents have been recently added to the oncological armamentarium with bevacizumab probably being the most popular representative in current clinical practice. The elucidation of the mode of action of these agents is a prerequisite for personalized prediction of antiangiogenic treatment response and selection of patients wh...

As in many cancer types, the G1/S restriction point (RP) is deregulated in Acute Lymphoblastic Leukemia (ALL). Hyper-phosphorylated retinoblastoma protein (hyper-pRb) is found in high levels in ALL cells. Nevertheless, the ALL lymphocyte proliferation rate for the average patient is surprisingly low compared to its normal counterpart of the same ma...

Intensive glioma tumor infitration into the surrounding normal brain tissues is one of the most critical causes of glioma treatment failure.To quantitatively understand and mathematically simulate this phenomenon, several diffsion-based mathematical models have appeared in the literature.The majority of them ignore the anisotropic character of diff...

Over the previous years, semantic metadata have largely contributed to the management, exchange and querying of health-related data, including mathematical and computational disease simulation model descriptions, implementations and output results. In this paper, we present a proposal for an abstract semantic metadata infrastructure layout, indicat...

The goal of this article is to present basic scientific principles and core algorithms of the simulation module of the CERvical cancer ONCOsimulator (CERONCO) developed within the context of the DrTherapat project (FP7-ICT-600852). CERONCO simulates the response of cervical tumours to radiotherapy treatment (external beam radiotherapy followed by b...

A couple of multiscale spatiotemporal simulation models of glioblastoma multiforme (GBM) growth and invasion into the surrounding normal brain tissue is presented. Both models are based on a continuous and subsequently finite mathematical approach centered around the non-linear partial differential equation of diffusion-reaction referring to glioma...

This paper briefly outlines the aim, the objectives, the architecture and the main building blocks of the ongoing large scale integrating transatlantic research project CHIC (http://chic-vph.eu/).

The aim of this paper is to present the development of a multi-scale and multiphysics approach to tumor growth. An existing biomodel used for clinical tumor growth and response to treatment has been coupled with a biomechanical model. The macroscopic mechanical model is used to provide directions of least pressure in the tissue, which drives the ge...

Significant Virtual Physiological Human (VPH) efforts and projects have been concerned with cancer modeling, especially in the European Commission Seventh Framework research programme, with the ambitious goal to approach personalized cancer simulation based on patient-specific data and thereby optimize therapy decisions in the clinical setting. How...

This paper presents a brief outline of the notion and the system of oncosimulator in conjunction with a high level description of the basics of its core multiscale model simulating clinical tumor response to treatment. The exemplary case of lung cancer preoperatively treated with a combination of chemotherapeutic agents is considered. The core onco...

This paper discusses the need for interconnecting computational cancer models from different sources and scales within clinically relevant scenarios to increase the accuracy of the models and speed up their clinical adaptation, validation, and eventual translation. We briefly review current interoperability efforts drawing upon our experiences with...

This short VIDEO demonstrates a four dimensional, discrete mathematics based, top-down simulation of tumor response to two radiation therapy scenarios according to the predictions of an in silico model described mainly in the following two publications: 1.G S Stamatakos, V P Antipas, N K Uzunoglu, R G Dale, “A four-dimensional computer simulation...

Improving the initial diagnosis and the assessment of response to treatment in malignant gliomas, while avoiding invasive methods as much as justifiable, is one major aspect actual research is focusing on. Imaging studies are used to calculate tumor volume and define vital, necrotic and cystic areas within a tumor. Though the visual interpretation...

I. INTRODUCTION Cancer is a natural phenomenon and consequently is amenable to mathematical and computational description. Clinically driven complex multi-scale cancer models are capable of producing realistic spatio-temporal and patient-specific simulations of commonly-used clinical interventions such as radio-chemotherapy. Clinical data-processi...

In this paper, a previous continuum approach describing vascular tumor growth under angiogenic signaling is developed and extended via the inclusion of bevacizumab pharmacokinetics. The modeling approach to the problem addressed includes inter alia the building of the model (selection of equations, related assumptions, coupling with a pharmacokinet...