Medicine and Health Sciences | Open Access Articles

Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi

Electrical & Computer Engineering Faculty Publications

Plasma medicine refers to the application of nonequilibrium plasmas at approximately body temperature, for therapeutic purposes. Nonequilibrium plasmas are weakly ionized gases which contain charged and neutral species and electric fields, and emit radiation, particularly in the visible and ultraviolet range. Medically-relevant cold atmospheric pressure plasma (CAP) sources and devices are usually dielectric barrier discharges and nonequilibrium atmospheric pressure plasma jets. Plasma diagnostic methods and modelling approaches are used to characterize the densities and fluxes of active plasma species and their interaction with surrounding matter. In addition to the direct application of plasma onto living tissue, the treatment of liquids …

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Reduction Of Plasmid Vector Backbone Length Enhances Reporter Gene Expression, Carly Boye, Sezgi Arpag, Michael Francis, Scott Declemente, Aislin West, Richard Heller, Anna Bulysheva

Electrical & Computer Engineering Faculty Publications

Gene therapy has a wide range of applications for various types of pathologies. Viral methods of gene delivery provide high levels of gene expression but have various safety concerns. Non-viral methods are largely known to provide lower levels of expression. We aim to address this issue by using plasmid DNA with smaller backbones to increase gene expression levels when delivered using non-viral methods. In this study we compare gene expression levels between two vectors with firefly luciferase encoding gene insert using liposome complexes and gene electrotransfer as delivery methods. A 2-fold reduction in plasmid vector backbone size, disproportionately enhanced gene …

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Radiomic Texture Feature Descriptor To Distinguish Recurrent Brain Tumor From Radiation Necrosis Using Multimodal Mri, M. S. Sadique, A. Temtam, E. Lappinen, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Despite multimodal aggressive treatment with chemo-radiation-therapy, and surgical resection, Glioblastoma Multiforme (GBM) may recur which is known as recurrent brain tumor (rBT), There are several instances where benign and malignant pathologies might appear very similar on radiographic imaging. One such illustration is radiation necrosis (RN) (a moderately benign impact of radiation treatment) which are visually almost indistinguishable from rBT on structural magnetic resonance imaging (MRI). There is hence a need for identification of reliable non-invasive quantitative measurements on routinely acquired brain MRI scans: pre-contrast T1-weighted (T1), post-contrast T1-weighted (T1Gd), T2-weighted (T2), and T2 Fluid Attenuated Inversion Recovery (FLAIR) that can …

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Uncertainty Estimation In Classification Of Mgnt Using Radiogenomics For Glioblastoma Patients, W. Farzana, Z. A. Shboul, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Glioblastoma Multiforme (GBM) is one of the most malignant brain tumors among all high-grade brain cancers. Temozolomide (TMZ) is the first-line chemotherapeutic regimen for glioblastoma patients. The methylation status of the O6-methylguanine-DNA-methyltransferase (MGMT) gene is a prognostic biomarker for tumor sensitivity to TMZ chemotherapy. However, the standardized procedure for assessing the methylation status of MGMT is an invasive surgical biopsy, and accuracy is susceptible to resection sample and heterogeneity of the tumor. Recently, radio-genomics which associates radiological image phenotype with genetic or molecular mutations has shown promise in the non-invasive assessment of radiotherapeutic treatment. This study proposes a machine-learning framework …

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Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel

Electrical & Computer Engineering Faculty Publications

Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. …

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Gene Electrotransfer Of Fgf2 Enhances Collagen Scaffold Biocompatibility, Carly Boye, Kyle Cristensen, Kamal Asadipour, Scott Declemente, Michael Francis, Anna Bulysheva

Electrical & Computer Engineering Faculty Publications

Tendon injuries are a common athletic injury that have been increasing in prevalence. While there are current clinical treatments for tendon injuries, they have relatively long recovery times and often do not restore native function of the tendon. In the current study, gene electrotransfer (GET) parameters for delivery to the skin were optimized with monophasic and biphasic pulses with reporter and effector genes towards optimizing underlying tendon healing. Tissue twitching and damage, as well as gene expression and distribution were evaluated. Bioprinted collagen scaffolds, mimicking healthy tendon structure were then implanted subcutaneously for biocompatibility and angiogenesis analyses when combined with …

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Assessment Of Combined Modality Therapy For Non-Small-Cell Lung Carcinoma: A Simulation Study Concerning Concurrent Chemo-Brachytherapy, Hadi Rezaei, Hesameddin Mostaghimi, Ali Reza Mehdizadeh

Electrical & Computer Engineering Faculty Publications

Although surgery is the treatment of choice for early-stage non-small-cell lung carcinoma, almost two-thirds of patients do not have acceptable pulmonary function for extensive surgeries. The alternative approach for this large group of patients is sublobar resection along with low-dose-rate (LDR) brachytherapy (BT). However, patients with resected lungs have a high risk of recurrence and are often treated with platinum-based (Pt-based) chemotherapy (CT). In this study, we aimed to evaluate the absorbed doses of lung and other thoracic organs, considering concurrent chemo-BT with LDR sources in two modalities: conventional vs. unconventional Pt-based CT. We used the MCNPX code for simulations …

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Full-Text Articles in Medicine and Health Sciences

Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi

Electrical & Computer Engineering Faculty Publications

Reduction Of Plasmid Vector Backbone Length Enhances Reporter Gene Expression, Carly Boye, Sezgi Arpag, Michael Francis, Scott Declemente, Aislin West, Richard Heller, Anna Bulysheva

Electrical & Computer Engineering Faculty Publications

Radiomic Texture Feature Descriptor To Distinguish Recurrent Brain Tumor From Radiation Necrosis Using Multimodal Mri, M. S. Sadique, A. Temtam, E. Lappinen, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Uncertainty Estimation In Classification Of Mgnt Using Radiogenomics For Glioblastoma Patients, W. Farzana, Z. A. Shboul, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Electrical & Computer Engineering Faculty Publications

Gene Electrotransfer Of Fgf2 Enhances Collagen Scaffold Biocompatibility, Carly Boye, Kyle Cristensen, Kamal Asadipour, Scott Declemente, Michael Francis, Anna Bulysheva

Electrical & Computer Engineering Faculty Publications

Assessment Of Combined Modality Therapy For Non-Small-Cell Lung Carcinoma: A Simulation Study Concerning Concurrent Chemo-Brachytherapy, Hadi Rezaei, Hesameddin Mostaghimi, Ali Reza Mehdizadeh

Electrical & Computer Engineering Faculty Publications