Encapsulated Contrast Agent Markers for MRI-based Post-implant Dosimetry

Low-dose-rate prostate brachytherapy involves the implantation of tiny radioactive seeds into the prostate to treat prostate cancer. The current standard post-implant imaging modality is computed tomography (CT). On CT images, the radioactive seeds can be distinctively localized but delineation of the prostate and surrounding soft tissue is poor. Magnetic resonance imaging (MRI) provides better prostate and soft tissue delineation, but seed localization is difficult. To aid with seed localization, MRI markers with encapsulated contrast agent that provide positive-contrast on MRI images (Sirius MRI markers; C4 Imaging, Houston, TX) have been proposed to be placed adjacent to the negative-contrast seeds. This dissertation describes the development of the Sirius MRI markers for prostate post-implant dosimetry. First, I compared the dose-volume histogram and other dosimetry parameters generated by MIM Symphony (a brachytherapy treatment planning system that allow the use of MRI images for treatment planning; MIM Software Inc., Cleveland, OH) and VariSeed (a widely used brachytherapy treatment planning system; Varian Medical Systems, Inc., Palo Alto, CA), and found the dosimetry between both brachytherapy treatment planning systems to be comparable. To gain more insight into the MRI contrast characteristics of the Sirius MRI markers, I measured the Sirius MRI marker contrast agent\u27s spin-lattice and spin-spin relaxivities, and studied the relaxation characteristics\u27 dependence on MRI field strength, temperature, and orientation. From the Sirius MRI marker\u27s contrast agent relaxation characteristics, I systematically studied the effect of varying MRI scan parameters such as flip angle, number of excitations, bandwidth, field of view, slice thickness, and encoding steps, on the Sirius MRI markers\u27 signal and contrast, as well as image noise, artifact and scan time. On patients implanted with Sirius MRI markers, I evaluated the visibility of the Sirius MRI markers and image artifacts. Lastly, I semi-automated the localization of markers and seeds to more enable the efficient incorporation of Sirius MRI markers as part of the clinical post-implant workflow. Ultimately, the Sirius MRI markers may change the paradigm from CT-based to MRI-based post-implant dosimetry, for a more accurate understanding of dose-response relationships in patients undergoing low dose rate prostate brachytherapy

Patient-based quality control for glucometers: using the moving sum of positive patient results and moving average

Introduction: The capability of glucometer internal quality control (QC) in detecting varying magnitude of systematic error (bias), and the potential use of moving sum of positive results (MovSum) and moving average (MA) techniques as potential alternatives were evaluated. Materials and methods: The probability of error detection using routine QC and manufacturer’s control limits were investigated using historical data. Moving sum of positive results and MA algorithms were developed and optimized before being evaluated through numerical simulation for false positive rate and probability of error detection. Results: When the manufacturer’s default control limits (that are multiple times higher than the running standard deviation (SD) of the glucometer) was used, they had 0-75% probability of detecting small errors up to 0.8 mmol/L. However, the error detection capability improved to 20-100% when the running SD of the glucometer was used. At a binarization threshold of 6.2 mmol/L and block sizes of 200 to 400, MovSum has a 100% probability of detecting a bias that is greater than 0.5 mmol/L. Compared to MovSum, the MA technique had lower probability of bias detection, especially for smaller bias magnitudes; MA also had higher false positive rates. Conclusions: The MovSum technique is suited for detecting small, but clinically significant biases. Point of care QC should follow conventional practice by setting the control limits according to the running mean and SD to allow proper error detection. The glucometer manufacturers have an active role to play in liberalizing QC settings and also enhancing the middleware to facility patient-based QC practices

Impact of combining data from multiple instruments on performance of patient-based real-time quality control

It is unclear what is the best strategy for applying patient-based real-time quality control (PBRTQC) algorithm in the presence of multiple instruments. This simulation study compared the error detection capability of applying PBRTQC algorithms for instruments individually and in combination using serum sodium as an example. Four sets of random serum sodium measurements were generated with differing means and standard deviations to represent four simulated instruments. Moving median with winsorization was selected as the PBRTQC algorithm. The PBRTQC parameters (block size and control limits) were optimized and applied to the four simulated laboratory data sets individually and in combination. When the PBRTQC algorithm were individually optimized and applied to the data of the individual simulated instruments, it was able to detect bias several folds faster than when they were combined. Similarly, the individually applied algorithms had perfect error detection rates across different magnitudes of bias, whereas the error detection rates of the algorithm applied on the combined data missed smaller biases. The performance of the individually applied PBRTQC algorithm performed more consistently among the simulated instruments compared to when the data were combined. While combining data from different instruments can increase the data stream and hence, increase the speed of error detection, it may widen the control limits and compromising the probability of error detection. The presence of multiple instruments in the data stream may dilute the effect of the error when it only affects a selected instrument

The p7 protein of the hepatitis C virus induces cell death differently from the influenza A virus viroporin M2

10.1016/j.virusres.2012.12.005Virus Research 1721-224-3

MRI characterization of cobalt dichloride-N-acetyl cysteine (C4) contrast agent marker for prostate brachytherapy

Brachytherapy, a radiotherapy technique for treating prostate cancer, involves the implantation of numerous radioactive seeds into the prostate. While the implanted seeds can be easily identified on a CT image, distinguishing the prostate and surrounding soft tissues is not as straightforward. Magnetic Resonance Imaging (MRI) offers superior anatomical delineation, but the seeds appear as dark voids and are difficult to identify, thus creating a conundrum. Cobalt dichloride-N-acetylcysteine (C4) has previously been shown to be promising as an encapsulated contrast agent marker. We performed spin-lattice relaxation time (T1) and spin-spin relaxation time (T2) measurements of C4 solutions with varying cobalt dichloride concentrations to determine the corresponding relaxivities, r1 and r2. These relaxation parameters were investigated at different field strengths, temperatures and orientations. T1 measurements obtained at 1.5 T and 3.0 T, as well as at room and body temperature, showed that r1 is field-independent and temperatureindependent. Conversely, the T2 values at 3.0 T were shorter than at 1.5 T, while the T2 values at body temperature were slightly higher than at room temperature. By examining the relaxivities with the C4 vials aligned in three different planes, we found no orientation-dependence. With these relaxation characteristics, we aim to develop pulse sequences that will enhance the C4 signal against prostatic stroma. Ultimately, the use of C4 as a positive contrast agent marker will encourage the use of MRI to obtain an accurate representation of the radiation dose delivered to the prostate and surrounding normal anatomical structures

On-demand priority traffic optimizer with fuzzy logic microcontroller

Current traffic control system in Malaysia is developed based on predetermined setup, where the system is not able to analyse the surrounding condition to optimize the green time. When there is an unusual traffic flow, the control system fails to control traffic flow efficiently, causing delays and requiring the assistance of traffic police. The main objective of this project is to explore the potential of fuzzy logic embedded control system in optimizing the traffic congestion corresponding to the priority traffic signal. The developed real time traffic-adaptive control system operates by prioritising the green light based on the received priority signals such as high flow rate phases and the emergency vehicles. A microcontroller-based traffic controller with computed algorithm was developed. The performance of the controller in reducing average waiting time and average vehicle queue length at a traffic intersection was evaluated. In overall, Fuzzy Logic managed to reduce 23% of average waiting time and 11% of average vehicles in queue at the intersection as compared to the conventional control

NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool

<p>Abstract</p> <p>Background</p> <p>Classifying the fungal and viral content of a sample is an important component of analyzing microbial communities in environmental media. Therefore, a method to classify any fragment from these organisms' DNA should be implemented.</p> <p>Results</p> <p>We update the näive Bayes classification (NBC) tool to classify reads originating from viral and fungal organisms. NBC classifies a fungal dataset similarly to Basic Local Alignment Search Tool (BLAST) and the Ribosomal Database Project (RDP) classifier. We also show NBC's similarities and differences to RDP on a fungal large subunit (LSU) ribosomal DNA dataset. For viruses in the training database, strain classification accuracy is 98%, while for those reads originating from sequences not in the database, the order-level accuracy is 78%, where order indicates the taxonomic level in the tree of life.</p> <p>Conclusions</p> <p>In addition to being competitive to other classifiers available, NBC has the potential to handle reads originating from any location in the genome. We recommend using the Bacteria/Archaea, Fungal, and Virus databases separately due to algorithmic biases towards long genomes. The tool is publicly available at: <url>http://nbc.ece.drexel.edu</url>.</p

Zika virus infection preferentially counterbalances human peripheral monocyte and/or NK cell activity

Zika virus (ZIKV) has reemerged in the population and caused unprecedented global outbreaks. Here, the transcriptomic consequences of ZIKV infection were studied systematically first in human peripheral blood CD14+ monocytes and monocyte-derived macrophages with high-density RNA sequencing. Analyses of the ZIKV genome revealed that the virus underwent genetic diversification, and differential mRNA abundance was found in host cells during infection. Notably, there was a significant change in the cellular response, with cross talk between monocytes and natural killer (NK) cells as one of the highly identified pathways. Immunophenotyping of peripheral blood from ZIKV-infected patients further confirmed the activation of NK cells during acute infection. ZIKV infection in peripheral blood cells isolated from healthy donors led to the induction of gamma interferon (IFN-γ) and CD107a—two key markers of NK cell function. Depletion of CD14+ monocytes from peripheral blood resulted in a reduction of these markers and reduced priming of NK cells during infection. This was complemented by the immunoproteomic changes observed. Mechanistically, ZIKV infection preferentially counterbalances monocyte and/or NK cell activity, with implications for targeted cytokine immunotherapies

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London