Signal, Noise, and Contrast

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145413/1/cpmib0600.pd

Signal‐to‐Noise Ratio as a Function of Imaging Parameters

Signal‐to‐Noise Ratio as a Function of Imaging Parameters (Azim Celik, General Electric Company, Milwaukee, Wisconsin and Weili Lin, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina). The degree to which noise affects a measurement is generally characterized by the signal‐to‐noise ratio (SNR, as measured by the ratio of the voxel signal to the noise standard deviation). This unit describes the importance of SNR in describing image quality. SNR is the key parameter for determining the quality of any given imaging experiment. If the SNR is not high enough, it becomes impossible to differentiate tissues from one another or the background. The dependence of SNR on imaging parameters such as the number of repetitions, the number of k‐space samples (Nx, Ny, and Nz), the readout bandwidth, and voxel dimensions (Dx, Dy, and Dz) is explained in detail.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145331/1/cpmib0602.pd

Contrast Agents

Contrast agents in general are exogeneous substances employed to alter natural tissue contrast. The motivation behind the use of contrast agents in MR imaging is to further enhance contrast between normal and diseased tissue types and indicate functionality of an organ. The focus of this unit is to give to the basic mechanisms of contrast agents in MR without going into their clinical applications.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145201/1/cpmib0604.pd

Contrast

Contrast (Azim Celik, General Electric Company, Milwaukee, Wisconsin and Weili Lin, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina). SNR (signal‐to‐noise ratio) determines the effectiveness of an imaging experiment. However, even the highest SNR does not guarantee the usefulness of an image. An important aim of imaging for diagnostic purposes is to be able to distinguish between diseased and neighboring normal tissues. If the imaging method used does not have a signal‐manipulating mechanism which produces different signals for the diseased and normal tissues, then distinguishing the two tissues is not possible. This unit provides a detailed discussion of the contrast‐producing mechanisms that arise from the signal dependence on a wide variety of tissue parameters.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145270/1/cpmib0603.pd

Effect of imaging parameters on the accuracy of apparent diffusion coefficient and optimization strategies

PURPOSEWe aimed to investigate the effect of key imaging parameters on the accuracy of apparent diffusion coefficient (ADC) maps using a phantom model combined with ADC calculation simulation and propose strategies to improve the accuracy of ADC quantification.METHODSDiffusion-weighted imaging (DWI) sequences were acquired on a phantom model using single-shot echo-planar imaging DWI at 1.5 T scanner by varying key imaging parameters including number of averages (NEX), repetition time (TR), echo time (TE), and diffusion preparation pulses. DWI signal simulations were performed for varying TR and TE.RESULTSMagnetic resonance diffusion signal and ADC maps were dependent on TR and TE imaging parameters as well as number of diffusion preparation pulses, but not on the NEX. However, the choice of a long TR and short TE could be used to minimize their effects on the resulting DWI sequences and ADC maps.CONCLUSIONThis study shows that TR and TE imaging parameters affect the diffusion images and ADC maps, but their effect can be minimized by utilizing diffusion preparation pulses. Another key imaging parameter, NEX, is less relevant to DWI and ADC quantification as long as DWI signal-to-noise ratio is above a certain level. Based on the phantom results and data simulations, DWI acquisition protocol can be optimized to obtain accurate ADC maps in routine clinical application for whole body imaging

Quantitative measurements of cerebral metabolic rate of oxygen utilization using MRI: a volunteer study

Quantitative estimates of cerebral metabolic rate of oxygen utilization using magnetic resonance imaging can have profound implications for the understanding of brain metabolic activity as well as the investigation of cerebrovascular disease. In this study, five normal volunteers were studied. All images were acquired on a Siemens 1.5 T scanner (Siemens Medical Systems Inc, Erlangen, Germany). Cerebral blood flow (CBF) was obtained in vivo with a dynamic imaging approach and the acquired images were post-processed with the singular value decomposition method (SVD). In addition, a multi-echo gradient echo/spin echo sequence was employed to provide MR estimates of oxygen extraction fraction (MR_OEF) in vivo. Subsequently, an absolute measure of MR cerebral metabolic rate of oxygen utilization (MR_CMRO2) was obtained in all subjects by taking the product of CBF and MR_OEF. A mean MR_CMRO2 of 28.94 ± 3.26 ml/min/100 g and 12.57 ± 3.11 ml/min/100 g was obtained for gray matter and white matter, respectively, suggesting that the gray matter utilizes more oxygen than white matter under normal physiological conditions. These results yield a gray matter to white matter CMRO2 ratio of 2.37 ± 0.37, which is comparable to the reported values in the literature. More studies are needed to further improve on the accuracy as well as shortening the required data acquisition time so that the proposed approaches can be utilized in a routine clinical setting

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

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Signal and Noise

Signal and Noise (Azim Celik and Weili Lin, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina). This unit discusses the basic signal detection technique in magnetic resonance imaging based on quadrature (i.e., measured in two orthogonal channels) technique. The detected signal is demodulated with respect to the Larmor frequency and digitized. The measured MR signal also includes noise. The noise in MR generally derives from the random fluctuations in the receive coil electronics and from the sample. Even though there are other sources of signal fluctuations such as digitization noise and pseudo‐random ghosting due to moving spins, these sources are minimized in an ideal experiment. The effect of these noises in MRI image reconstruction is explained in this unit.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145348/1/cpmib0601.pd