Kostas Marias

Current trends in Electronic Family Resilience Tools: Implementing a tool for the cancer domain

It is well documented that the diagnosis of cancer affects the wellbeing of the whole family adding overwhelming stresses and uncertainties. As such, family education and enhancement of resilience is an important factor that should be promoted and facilitated in a holistic manner for addressing a severe and chronic condition such as cancer. In this paper, we review the notion of resilience in the literature identifying three tools that try to support it. Then we focus in the cancer domain and we describe a tool implemented to this direction. To our knowledge, this is the first time such a tool is used to complete patient profile with family resilience information, eventually leading to patient and family engagement and empowerment.

A correlative study between diffusion and perfusion MR imaging parameters on peripheral arterial disease data

PURPOSEnThe purpose of this study was to correlate diffusion and perfusion quantitative and semi-quantitative MR parameters, on patients with peripheral arterial disease. In addition, we investigated which perfusion model better describes the behavior of the dynamic contrast-enhanced (DCE) MR data signal on ischemic regions of the lower limb.nnnMETHODSnLinear and nonlinear least squares algorithms, were incorporated for the quantification of the parameters through a variety of widely used models, able to extract physiological information from each imaging technique. All numerical calculations were implemented in Python 3.5 and include the: Intra voxel incoherent motion for diffusion and Patlaks, Extended Tofts and Gamma Capillary Transit time (GCTT) models for perfusion MRI.nnnRESULTSnOur initial voxel by voxel correlation analysis didnt show any significant correlation based on the Pearsons Correlation metric between diffusion and perfusion parameters. To account for the inherited noise from the raw data, a Gaussian filter was applied to the parametric maps in order for the data to be comparable. By repeating our analysis in the filtered image maps, a good correlation (>0.5) of diffusion and perfusion parameters was achieved.nnnCONCLUSIONSnPerfusion and diffusion MRI quantitative and semi-quantitative parameters can be obtained through a variety of physiological-pharmacokinetic models. This paper compares most of the widely-known models and parameters in both techniques with data from patients with peripheral arterial disease. Initial analysis showed no correlation in the perfusion parametric maps of DWI and DCE MRI data but a good correlation was obtained after smoothing the parametric maps indicating that perfusion information could be obtained from diffusion MRI images in patients with peripheral arterial disease.

A Content-Aware Analytics Framework for Open Health Data

The vision of personalized medicine has led to an unprecedented demand for acquiring, managing and exploiting health related information, which in turn has led to the development of many e-Health systems and applications. However, despite this increasing trend only a limited set of information is currently being exploited for analysis and this has become a major obstacle towards the advancement of personalized medicine. To this direction, this paper presents the design and implementation of a content aware health data-analytics framework. The framework enables first the seamless integration of the available data and their efficient management through big data management systems and staging environments. Then the integrated information is further anonymized at run-time and accessed by the data analysis algorithms in order to provide appropriate statistical information, feature selection correlation and clustering analysis.

The impact of spin coupling signal loss on fat content characterization in multi-echo acquisitions with different echo spacing

PURPOSEnThis study aimed to assess the effect of echo spacing in transverse magnetization (T2) signal decay of gel and fat (oil) samples. Additionally, we assess the feasibility of using spin coupling as a determinant of fat content.nnnMETHODSnPhantoms of known T2 values, as well as vegetable oil phantoms, were scanned at 1.5T scanner with a multi echo FSE sequence of variable echo spacing above and below the empirical threshold of 20ms for echo train signal modulation (6.7, 13.6, 26.8, and 40ms). T2 values were calculated from monoexponential fitting of the data. Relative signal loss between the four acquisitions of different echo spacing was calculated.nnnRESULTSnAgreement in the T2 values of water gel phantom was observed in all acquisitions as opposed to fat phantom (oil) samples. Relative differences in signal intensity between two successive sequences of different echo spacing on composite fat/water regions of interest was found to be linearly correlated to fat fraction of the ROI.nnnCONCLUSIONnThe sample specific degree of signal loss that was observed between different fat samples (vegetable oils) can be attributed to the composition of each sample in J coupled fat components. Hence, spin coupling may be used as a determinant of fat content.