Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...最新文献

{"title":"Dendritic cell vaccination for glioblastoma multiforme: Clinical experience and future directions","authors":"J. Dejaegher, L. Solie, S. Vleeschouwer, S. Gool","doi":"10.1109/IARWISOCI.2014.7034631","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034631","url":null,"abstract":"Dendritic cell vaccination is an experimental treatment for malignant gliomas, and has been subject of a translational program for more than ten years in our center. In vitro research, animal models and clinical trials for relapsed and newly diagnosed patients have been conducted. In this paper, we give an overview of the mechanism and rationale of this treatment for brain cancer. We also briefly discuss recently updated results of our clinical trials. Finally, we mention strategies to select patients for this therapy and additional immunotherapeutic strategies to further enhance the antitumor immune responses.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"23 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2015-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73439366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The importance of grid size and boundary conditions in discrete tumor growth modeling","authors":"G. Tzedakis, Giorgos Grekas, E. Tzamali, K. Marias, V. Sakkalis","doi":"10.1109/IARWISOCI.2014.7034635","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034635","url":null,"abstract":"Modeling tumour growth has proven a very challenging problem, mainly due to the fact that cancer is a very complex process that spans multiple scales both in time and space. The desire to describe interactions in multiple scales has given rise to modeling approaches that use both continuous and discrete variables, called hybrid. The biochemical processes occurring in tumour environment are usually described by continuous variables. Cancer cells tend to be described as discrete agents interacting with their local neighborhood, which is comprised of their extracellular environment and nearby cancer cells. These interactions shape the microenvironment, which in turn acts as a selective force on clonal emergence and evolution. In this work, we study the effects of grid size and boundary conditions of the continuous processes on the discrete populations. We perform various tests on a simplified hybrid model with the aim of achieving faster execution runtimes. We conclude that we can reduce the grid size while maintaining the same dynamics of a larger domain by manipulating the boundary conditions.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"72 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74134103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Legal and ethical aspects of In Silico medicine","authors":"Iheanyi Nwankwo, M. Stauch, Alan Dahi, N. Forgó","doi":"10.1109/IARWISOCI.2014.7034647","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034647","url":null,"abstract":"The following paper considers some of the novel ethical and legal issues that may arise in the context of in silico-based medicine, with particular reference to the development of hypermodels to optimize treatment decisions for specific diseases.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"105 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79231049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A model of tumor growth coupling a cellular biomodel with biomechanical simulations","authors":"Farhad Rikhtegar, E. Kolokotroni, G. Stamatakos, P. Büchler","doi":"10.1109/IARWISOCI.2014.7034638","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034638","url":null,"abstract":"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 geometrical evolution of the tumor predicted at the cellular level. The combined model has been applied to the case of brain and lung tumors. Results indicated that the coupled approach provides additional morphological information on the realistic tumor shape when the tumor is located in regions of tissue inhomogeneity. The approach might be used in oncosimulators for tumor types where the morphometry information plays a major role in the treatment and surgical planning.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"116 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80624670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling glioblastoma growth and inhomogeneous tumor invasion with explicitly numerically treated neumann boundary conditions","authors":"S. Giatili, G. Stamatakos","doi":"10.1109/IARWISOCI.2014.7034634","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034634","url":null,"abstract":"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 tumour cells. A novel explicit, strict and thorough numerical treatment of the three dimensional adiabatic Neumann boundary conditions imposed by the skull is also included in both models. The first model assumes a homogeneous representation of normal brain tissue whereas the second one, assuming an inhomogeneous representation of normal brain tissue, distinguishes between white matter, grey matter and cerebrospinal fluid. The predictions of the tumour doubling time by both models are compared for specific data sets. Clinical observational data regarding the range of the GBM doubling time values are utilized in order to ensure the realism of both models and their predictions. We assume that the inhomogeneous normal brain tissue representation is a virtual rendering of reality more credible than its homogeneous counterpart. The simulation results for the cases considered show that using the homogeneous normal brain based model may lead to an error of up to 10% for the first 25 simulated days in relation to the predictions of the inhomogeneous model. However, the error drops to less than 7% afterwards. This observation suggests that even by using a homogeneous brain based model and a realistic weighted average value of its diffusion coefficient, a rough but still informative estimate of the expected tumour doubling time can be achieved. Additional in silico experimentation aiming at statistically testing and eventually further supporting the validity of this hypothesis is in progress. It is noted that the values of the diffusion coefficients and the cell birth and death rates of the model are amenable to refinement and personalization by exploiting the histological and molecular profile of the patient. Work on this aspect is in progress.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"146 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A collaborative central reviewing platform for cancer detection in digital microscopy images","authors":"Ioannis Karatzanis, A. Iliopoulos, M. Tsiknakis, V. Sakkalis, K. Marias","doi":"10.1109/IARWISOCI.2014.7034639","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034639","url":null,"abstract":"Telepathology, the practice of pathology at a long distance, has advanced continuously since 1986. Today, almost 3 decades later, virtual slide telepathology has become a promising tool for providing re-review of surgical pathology cases as part of a quality assurance program but also for educational purposes. In this paper we present the Central Review for Pathology images platform (CRP), developed by the Computational Medicine Laboratory at FORTH-ICS. The CRP is a secure cloud platform, which tries to address current issues that hamper the wider use of virtual pathology. The system offers an easy upgradable multi-format support for virtual slide files from different slide scanner vendors, enhanced collaboration capabilities and scheduling tools, a sophisticated mechanism for defining custom templates for reporting forms which adapts to all user needs and a virtual microscope viewer for the digital slides.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"15 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86490506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incorporating data protection in In Silico research: A case of the CHIC project","authors":"Elias Neri, Wouter Dhaeze","doi":"10.1109/IARWISOCI.2014.7034643","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034643","url":null,"abstract":"This is a case study of the solution provided by the CHIC project (http://chic-vph.eu) for the processing of sensitive retrospective and prospective patient data in a research environment. The case study focuses on the de-identification aspects of the CHIC data protection solution.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"37 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87473173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Predictions of Cancer Driver Mutations.","authors":"E Joseph Jordan,&nbsp;Ravi Radhakrishnan","doi":"10.1109/iarwisoci.2014.7034632","DOIUrl":"10.1109/iarwisoci.2014.7034632","url":null,"abstract":"<p><p>A method to predict the activation status of kinase domain mutations in cancer is presented. This method, which makes use of the machine learning technique support vector machines (SVM), has applications to cancer treatment, as well as numerous other diseases that involve kinase misregulation.</p>","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"2014 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/iarwisoci.2014.7034632","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39499086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intellectual property rights issues in multiscale cancer modeling","authors":"I. Lishchuk, M. Stauch, N. Forgó","doi":"10.1109/IARWISOCI.2014.7034646","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034646","url":null,"abstract":"In silico hyper-modeling is a complex process which requires interdisciplinary effort. Scientists from biology, medicine, bio-informatics, mathematics, engineering and other fields collaborate and contribute their knowledge and expertise. Researchers deserve recognition, intellectual input deserves protection and investments deserve reward. This paper investigates several IP regimes which may apply to cancer models and seeks to find solutions which would guarantee protection and reward.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"70 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85735976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A modular semantic infrastructure layout for the management of hypermodel-pertinent metadata in the context of In Silico oncology","authors":"N. Christodoulou, G. Stamatakos","doi":"10.1109/IARWISOCI.2014.7034640","DOIUrl":"https://doi.org/10.1109/IARWISOCI.2014.7034640","url":null,"abstract":"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, indicating its modularity, and thus its capability to operate with different combinations of software tools. Its potential contribution for the purposes of the CHIC project is also reported.","PeriodicalId":93358,"journal":{"name":"Proceedings of the 2014 6th International Advanced Research Workshop on In Silico Oncology and Cancer Investigation : the CHIC Project Workshop (IARWISOCI) : Athens, Greece, 3-4 November 2014. International Advanced Research Workshop on...","volume":"38 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85898294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}