Kostas Marias - Profile on Academia.edu (original) (raw)

Papers by Kostas Marias

A supportive environment for the long term management of knee osteoarthritis condition

Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare - "Transforming healthcare through innovations in mobile and wireless technologies", 2015

Objectives: MyHealthAvatar (MHA) platform aims towards a collaborative partnership among patients... more Objectives: MyHealthAvatar (MHA) platform aims towards a collaborative partnership among patients and healthcare providers [1]. Nowadays, in silico clinical trials (ISCTs), population pharmacokinetics, pharmacogenomics and information communication technologies have provided several tools towards stratified and personalized medicine approaches [2-4]. In this work a methodology of potential fitting of results generated through ISCTs with real life patients through virtual profiles of MHA is presented. To this respect, we use a simple example of discontinuation of warfarin administration during pre-operative period for a 55 year’s old male patient with a MHA profile. Methods: MHA’s architecture is based on integration of multiscale data gained from several sources (i.e. demographic, biomedical, genomics, lifestyle) and transform them into a representation of health status as a “virtual twin” or avatar [1]. The integration of these information from different avatars can lead in a creat...

Digital patient: Personalized and translational data management through the MyHealthAvatar EU project

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015

The advancements in healthcare practice have brought to the fore the need for flexible access to ... more The advancements in healthcare practice have brought to the fore the need for flexible access to health-related information and created an ever-growing demand for the design and the development of data management infrastructures for translational and personalized medicine. In this paper, we present the data management solution implemented for the MyHealthAvatar EU research project, a project that attempts to create a digital representation of a patient&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s health status. The platform is capable of aggregating several knowledge sources relevant for the provision of individualized personal services. To this end, state of the art technologies are exploited, such as ontologies to model all available information, semantic integration to enable data and query translation and a variety of linking services to allow connecting to external sources. All original information is stored in a NoSQL database for reasons of efficiency and fault tolerance. Then it is semantically uplifted through a semantic warehouse which enables efficient access to it. All different technologies are combined to create a novel web-based platform allowing seamless user interaction through APIs that support personalized, granular and secure access to the relevant information.

Digital patient: Personalized and translational data management through the MyHealthAvatar EU project

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015

The advancements in healthcare practice have brought to the fore the need for flexible access to ... more The advancements in healthcare practice have brought to the fore the need for flexible access to health-related information and created an ever-growing demand for the design and the development of data management infrastructures for translational and personalized medicine. In this paper, we present the data management solution implemented for the MyHealthAvatar EU research project, a project that attempts to create a digital representation of a patient&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s health status. The platform is capable of aggregating several knowledge sources relevant for the provision of individualized personal services. To this end, state of the art technologies are exploited, such as ontologies to model all available information, semantic integration to enable data and query translation and a variety of linking services to allow connecting to external sources. All original information is stored in a NoSQL database for reasons of efficiency and fault tolerance. Then it is semantically uplifted through a semantic warehouse which enables efficient access to it. All different technologies are combined to create a novel web-based platform allowing seamless user interaction through APIs that support personalized, granular and secure access to the relevant information.

This paper presents a novel framework for assessing tumor changes based on histogram analysis of ... more This paper presents a novel framework for assessing tumor changes based on histogram analysis of temporal Magnetic Resonance Image (MRI) data. The proposed method detects the distribution of tumor and quantitatively models its growth or shrinkage offering the potential to assist clinicians in objectively assessing subtle changes during therapy. The presented work and the initial validation refer to the glioma case but can be generalized to any type of cancer where medical imaging is routinely used to characterize tumor response over time.

Patient Empowerment through Personal Medical Recommendations

Studies in health technology and informatics, 2015

Patients today have ample opportunities to inform themselves about their disease and possible tre... more Patients today have ample opportunities to inform themselves about their disease and possible treatments using the Internet. While this type of patient empowerment is widely regarded as having a positive influence on the treatment, there exists the problem that the quality of information that can be found on online is very diverse. This paper presents a platform which empowers patients by allowing searching in a high quality document repository. In addition, it automatically provides intelligent and personalized recommendations according to the individual preferences and medical conditions.

Magnetic relaxation measurements on tissue mimicking phantoms: comparison between different fitting algorithms in MRI T2 calculations

Physica Medica, 2014

Assessing Treatment Response Through Generalized Pharmacokinetic Modeling of DCE-MRI Data

Cancer Informatics, 2015

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the quantification of cont... more Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the quantification of contrast leakage from the vascular tissue by using pharmacokinetic (PK) models. Such quantitative analysis of DCE-MRI data provides physiological parameters that are able to provide information of tumor pathophysiology and therapeutic outcome. Several assumptive PK models have been proposed to characterize microcirculation in the tumoral tissue. In this paper, we present a comparative study between the well-known extended Tofts model (ETM) and the more recent gamma capillary transit time (GCTT) model, with the latter showing initial promising results in the literature. To enhance the GCTT imaging biomarkers, we introduce a novel method for segmenting the tumor area into subregions according to their vascular heterogeneity characteristics. A cohort of 11 patients diagnosed with glioblastoma multiforme with known therapeutic outcome was used to assess the predictive value of both models in terms of correctly classifying responders and nonresponders based on only one DCE-MRI examination. The results indicate that GCTT model&amp;amp;amp;amp;amp;#39;s PK parameters perform better than those of ETM, while the segmentation of the tumor regions of interest based on vascular heterogeneity further enhances the discriminatory power of the GCTT model.

Digital Mammography, 2003

We present an update of our investigations into the potential role of quantitative measures of br... more We present an update of our investigations into the potential role of quantitative measures of breast density for characterising breast changes, and, in particular, changes due to Hormone Replacement Therapy (HRT). It has been established that long-term use of HRT can increase the risk of breast cancer, a fact that enforces the belief that objective measures of tissue density can be an important development in breast cancer image analysis. A set of 59 mammogram temporal HRT sequences (2 images per patient) were used in our experiments. The clinician's assessment of density changes constituted the ground truth for evaluating the proposed quantitative measures of density change. The measures are based on the h int representation of interesting tissue and their performance (agreement with the expert's description) is also compared to the "interactive thresholding" method that has been used in the past to characterise mammographic density.

Lecture Notes in Computer Science, 2000

Increasing use is being made of contrast-enhanced Magnetic Resonance Imaging (Gd-DTPA) for breast... more Increasing use is being made of contrast-enhanced Magnetic Resonance Imaging (Gd-DTPA) for breast cancer assessment since it provides 3D functional information via pharmacokinetic interaction between contrast agent and tumour vascularity, and because it is applicable to women of all ages. Contrast-enhanced MRI (CE-MRI) is complimentary to conventional Xray mammography since it is a relatively low-resolution functional counterpart of a comparatively high-resolution 2D structural representation. However, despite the additional information provided by MRI, mammography is still an extremely important diagnostic imaging modality, particularly for several common conditions such as ductal carcinoma in-situ (DCIS) where it has been shown that there is a strong correlation between microcalcification clusters and malignancy . Pathological indicators such as calcifications and fine spiculations are not visible in CE-MRI and therefore there is clinical and diagnostic value to fusing the high-resolution structural information available from mammography with the functional data acquired from MRI imaging. This paper presents a novel data fusion technique whereby medio-lateral (ML) and cranio-caudal (CC) mammograms (2D data) are registered to 3D contrastenhanced MRI volumes. We utilise a combination of pharmacokinetic modelling, projection geometry, wavelet-based landmark detection and thinplate spline non-rigid registration to transform the coordinates of regions of interest (ROIs) from the 2D mammograms to the spatial reference frame of the contrast-enhanced MRI volume.

The effects of near optimal growth solutions in genome-scale human cancer metabolic model

2012 IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), 2012

ABSTRACT Cancer cells inefficiently produce energy through glycolysis even in ample oxygen, a phe... more ABSTRACT Cancer cells inefficiently produce energy through glycolysis even in ample oxygen, a phenomenon known as “aerobic glycolysis”. A characteristic of the rapid and incomplete catabolism of glucose is the secretion of lactate. Genome-scale metabolic models have been recently employed to describe the glycolytic phenotype of highly proliferating human cancer cells. Genome-scale models describe genotype-phenotype relations revealing the full extent of metabolic capabilities of genotypes under various environmental conditions. The importance of these approaches in understanding some aspects of cancer complexity, as well as in cancer diagnostics and individualized therapeutic schemes related to metabolism is evident. Based on previous metabolic models, we explore the metabolic capabilities and rerouting that occur in cancer metabolism when we apply a strategy that allows near optimal growth solution while maximizing lactate secretion. The simulations show that slight deviations around the optimal growth are sufficient for adequate lactate release and that glucose uptake and lactate secretion are correlated at high proliferation rates as it has been observed. Inhibition of lactate dehydrogenase-A, an enzyme involved in the conversion of pyruvate to lactate, substantially reduces lactate release. We also observe that activating specific reactions associated with the migration-related PLCγ enzyme, the proliferation rate decreases. Furthermore, we incorporate flux constraints related to differentially expressed genes in Glioblastoma Multiforme in an attempt to construct a Glioblastoma-specific metabolic model and investigate its metabolic capabilities across different glucose uptake bounds.

EEG Based Biomarker Identification Using Graph-Theoretic Concepts: Case Study in Alcoholism

Fields Institute Communications, 2012

ABSTRACT

Imaging of brain tumors

Surgical oncology clinics of North America, 2014

Neuroimaging plays a crucial role in diagnosis of brain tumors and in the decision-making process... more Neuroimaging plays a crucial role in diagnosis of brain tumors and in the decision-making process for therapy. Functional imaging techniques can reflect cellular density (diffusion imaging), capillary density (perfusion techniques), and tissue biochemistry (magnetic resonance [MR] spectroscopy). In addition, cortical activation imaging (functional MR imaging) can identify various loci of eloquent cerebral cortical function. Combining these new tools can increase diagnostic specificity and confidence. Familiarity with conventional and advanced imaging findings facilitates accurate diagnosis, differentiation from other processes, and optimal patient treatment. This article is a practical synopsis of pathologic, clinical, and imaging spectra of most common brain tumors.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2009

This paper describes a flexible and easy-to-use annotation platform (GUI) for quick and precise i... more This paper describes a flexible and easy-to-use annotation platform (GUI) for quick and precise identification and delineation of tumors in medical images. The design of the platform is clinically driven in order to ensure that the clinician can efficiently and intuitively annotate large number of 3D tomographic datasets. Both manual and well-known semiautomatic segmentation techniques are available in the platform allowing clinician to annotate multiple regions of interest at the same session. Additionally, it includes contour drawing, refinement and labeling tools that can effectively assist in the delineation of tumors. Furthermore, segmented tumor regions can be annotated, labeled, deleted, added and redefined. The platform has been tested over several MRI datasets to assess usability, extensibility and robustness with promising results.

PLoS ONE, 2014

Tumor is characterized by extensive heterogeneity with respect to its microenvironment and its ge... more Tumor is characterized by extensive heterogeneity with respect to its microenvironment and its genetic composition. We extend a previously developed monoclonal continuous spatial model of tumor growth to account for polyclonal cell populations and investigate the interplay between a more proliferative and a more invasive phenotype under different conditions. The model simulations demonstrate a transition from the dominance of the proliferative to the dominance of the invasive phenotype resembling malignant tumor progression and show a time period where both subpopulations are abundant. As the dominant phenotype switches from proliferative to invasive, the geometry of tumor changes from a compact and almost spherical shape to a more diffusive and fingered morphology with the proliferative phenotype to be restricted in the tumor bulk and the invasive to dominate at tumor edges. Different micro-environmental conditions and different phenotypic properties can promote or inhibit invasion demonstrating their mutual importance. The model provides a computational framework to investigate tumor heterogeneity and the constant interplay between the environment and the specific characteristics of phenotypes that should be taken into account for the prediction of tumor evolution, morphology and effective treatment.

Current awareness in NMR in biomedicine

... Biol Psychiatry 57, (8) 873-884 (2005) Lu M, Mitsias PD, Ewing JR, Soltanian-Zadeh H,Bagher-E... more ... Biol Psychiatry 57, (8) 873-884 (2005) Lu M, Mitsias PD, Ewing JR, Soltanian-Zadeh H,Bagher-Ebadian H, Zhao QM, Oja-Tebbe N, Patel SC, Chopp M. Henry Ford Hlth Sci Ctr, Dept Biostat &amp;amp;amp;amp;amp;amp;amp; Res Epidemiol, 1 Ford Pl 3E, Detroit, Mi 48202, USA. ...

Multi-Level Image Analysis for Extracting Pathophysiological Parameters Related to Cancer Modeling

ABSTRACT

Stress and anxiety act as psycho-physical factors that increase the risk of developing several ch... more Stress and anxiety act as psycho-physical factors that increase the risk of developing several chronic diseases. Since they appear as early indicators, it is very important to be able to perform their evaluation in a contactless and non-intrusive manner in order to avoid inducing artificial stress or anxiety to the individual in question. For these reasons, this paper analyses the methodologies for the extraction of respective facial signs from images or videos, their classification and techniques for coding these signs into appropriate psycho-physical statuses. A review of existing datasets for the assessment of the various methodologies for facial expression analysis is reported. Finally, a short summary of the most interesting findings in the various stages of the procedure are indicated with the aim of achieving new contactless methods for the promotion of an individual's well-being.

Temporal mass detection

ABSTRACT

An innovative mathematical analysis of routine MRI scans in patients with glioblastoma using DoctorEye

IEEE 12th International Conference on BioInformatics and BioEngineering, BIBE 2012, 2012

ABSTRACT Improving the initial diagnosis and the assessment of response to treatment in malignant... more ABSTRACT 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 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. Better methods are needed for a reliable interpretation of follow-up studies in single patients. Histograms of signal intensities might serve as a method adding quantitative data to the description of a tumor. Using DoctorEye software, tumors can be easily rendered and histograms of the signal intensities within a tumor as well as mean and median signal intensities are possible to calculate. Our results in glioblastoma suggest that these histograms are an innovative method of gaining new tumor-specific information without performing additional investigations in a patient. It can be an additional diagnostic tool in differentiating various intracranial lesions from each other, as well as in assessing response to treatment or progression of malignant glioma.