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Comparison between Different ESI Methods on Refractory Epilepsy Patients Shows a High Sensitivity for Bayesian Model Averaging

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Journal of Biomedical Science and Engineering 2014年第9期7卷 662-674页

作者： Danilo Maziero agustin lage castellanos Carlos Ernesto Garrido Salmon Tonicarlo Rodrigues Velasco Cuba Neuroscience Center Havana Cuba Department of Physics FFLCRP University of S&atilde o Paulo Ribeir&atilde o Preto Brazil Epilepsy Surgery Center Department of Neuroscience Faculty of Medicine University of S&atilde o Paulo Ribeir&atilde o Preto Brazil

Electrical Source Imaging (ESI) is a non-invasive technique of reconstructing brain activities using EEG data. This technique has been applied to evaluate epilepsy patients being evaluated for epilepsy surgery, showing encouraging results for mapping interictal epileptiform discharges (IED). However, ESI is underused in planning epilepsy surgery. This is basically due to the wide availability of methods for solving the electromagnetism inverse problem (e-IP) associated to few studies using EEG setups similar to those most commonly used in clinical setting. In this study, we applied six different methods of solving the e-IP based on IEDs of 20 focal epilepsy patients that presented abnormalities in their MRI. We compared the ESI maps obtained by each method with the location of the abnormality, calculating the Euclidian distances from the center of the lesion to the closest border of the method solution (CL-BM) and also to the solution’s maxima (CL-MM). We also applied a score system in order to allow us to evaluate the sensitivity of each method for temporal and extra temporal patients. In our patients, the Bayesian Model Averaging method had a sensitivity of 86% and the shortest CL-MM. This method also had more restricted solutions that were more representative of epileptogenic activities than those obtained by the other methods.

关键词： EEG Epilepsy Electrical Source Imaging Bayesian Model Averaging

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Current Algorithm for Treatment of Advanced NSCLC Patients: How to Include Active Immunotherapy?

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Journal of Cancer Therapy 2013年第8期4卷 59-75页

作者： Gisela Gonzalez Arlhee Diaz-Miqueli Tania Crombet Luis E. Raez agustin lage Center of Molecular Immunology Havana Cuba Memorial Cancer Institute Memorial Health Care System Florida International University Miami USA

Despite the availability of different treatments for advanced NSCLC, all of them have a palliative intention and a cure for the disease is unlikely. Thus, advanced lung cancer remains as an unmet medical need. Chemotherapy has been used as the therapy of choice for advanced NSCLC patients, but it is mainly limited by the patient’s performance status. More recently, targeted therapies have introduced more specific treatment options that show efficacy in specific niche of patients, but precisely due to their target specificity, they usually provoke early resistance. In addition to these limitations, most of the best drugs currently used for treatment of advanced NSCLC show small increases in patient survival with severe associated toxicity. Novel drugs with low toxicity that could be given chronically to control the advanced disease can make a difference. They could allow the management of advanced cancer as a chronic disease that, even when not cured, it can be controlled for long periods of time offering patients a good quality of life. Active-specific immunotherapy is an area of oncology that is rapidly expanding with encouraging results. Cancer vaccines against many potential targets have shown to increase patient survival in clinical trials at all stages NSCLC, when included as first-line, maintenance, or second-line therapy. Safety of cancer vaccines supposes a new hope for cancer therapy, and this unique characteristic makes it possible to be used in sub-sets of patients that cannot receive other approved treatments because of their high toxicity. In this paper, authors propose how active immunotherapy could be included in the current algorithm for treatment of advanced NSCLC patients.

关键词： Lung Cancer Therapy Active Immunotherapy Cancer Vaccines

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