Associations of chronotype and insomnia with menstrual problems in newly employed nurses at university hospitals in the Republic of Korea.

Background: Dysmenorrhea and menstrual cycle changes occur in women working shifts. Circadian rhythm disruption and sleep disturbances associated with shift work leads to health problems. We identified chronotypes and the occurrence of insomnia among newly employed university hospital nurses and investigated the association of these factors with menstrual problems. Methods: We conducted pre-placement health examinations for shift workers using self-reported questionnaires between 2018 and 2020. A total of 463 nurses were included in the study. Sociodemographic data, shift work experience, and information on insomnia were collected from health examination data. In addition, details regarding chronotype, dysmenorrhea, irregular and abnormal menstrual cycles, amenorrhea, and contraceptive use were obtained from the questionnaire. Multiple logistic regression analysis was performed to study the association between chronotype, insomnia, and menstrual problems after controlling for age, body mass index, contraceptive use, amenorrhea, and prior shift work. Results: The prevalence rates of dysmenorrhea, irregular menstrual cycles, and longer menstrual cycles were 23.8%, 14.9%, and 4.1%, respectively. The risk of dysmenorrhea increased in the evening-type (odds ratio [OR]: 3.209; 95% confidence interval [CI]: 1.685-6.113) and those with insomnia (OR: 1.871; 95% CI: 1.074-3.261). Additionally, the risk of an irregular menstrual cycle (OR: 2.698; 95% CI: 1.167-6.237) increased in the evening-type, and the risk of a longer menstrual cycle (OR: 4.008; 95% CI: 1.354-11.864) increased in individuals with insomnia. Conclusions: Our findings suggest that dysmenorrhea is promoted in the evening-type and insomnia individuals. There may be an increased risk of irregular menstrual cycles among evening-type nurses and an increased risk of longer menstrual cycles among those with insomnia. Therefore, factors such as evening-type and insomnia should be considered for the prevention of menstrual problems in women performing shift work.

Who has sustained psychological symptoms nine years after the Hebei Spirit oil spill?: The Health Effect Research on Hebei Spirit oil spill (HEROS) study.

This study evaluated risk factors for sustained psychological symptoms in affected residents, nine years after the Hebei Spirit oil spill in Korea in 2007. The participants included residents of high-exposure areas, living within 2 km from the contaminated coast (n = 2013), among the cohort of the Health Effect Research on Hebei Spirit oil spill study from 2009 to 2016. Symptoms for post-traumatic stress disorder (PTSD), depression, psychosocial distress, and anxiety, as well as sociodemographic information were assessed through questionnaire interviews. Trajectory analysis was conducted to identify the group with sustained symptoms over time and logistic regression analysis was performed to identify risk factors for sustained symptoms adjusted for covariates. A longer duration of clean-up work, lower household income, and presence of a chronic disease in all type of symptoms, and being female, younger age, and higher educational level in all symptoms but PTSD, showed a significant association with increased risk of sustained symptoms. The highest risk was found in the subgroup with a longer clean-up together with offshore and maritime occupations or lower income in PTSD, depression, and anxiety, compared with those with a shorter clean-up and other occupation or higher income. Increased risk of sustained PTSD in relation to a longer clean-up was limited to those with a lower educational level (p-interaction = 0.009). The results suggested that participating longer in clean-up work increased sustained psychological symptoms, synergistically with socioeconomic factors such as offshore and maritime occupations, lower household income, or economic losses related to educational level.

Health effect research on Hebei Spirit Oil Spill (HEROS) in Korea: a cohort profile.

PURPOSE: The Hebei Spirit Oil Spill occurred on 7 December 2007 and resulted in the spillage of 12 547 kl of crude oil on the coastline near Taean. Historically, this was the largest oil spill in Korean water. The health effect research on Hebei Spirit Oil Spill (HEROS) is a prospective cohort study that aimed to evaluate the long-term health effects of oil spill exposure on residents in the affected community. PARTICIPANTS: The Taean Environmental Health Center initially enrolled adults, adolescents and children living in Taean in 2009 and 2010. Follow-up surveys of participating adults and children were conducted every other year. By 2017, a total of 9585 adults and 2216 children and adolescents were enrolled. Of these, 294 adults and 102 children and adolescents were included in all subsequent surveys. FINDINGS TO DATE: Children who lived closer to the oil spill site exhibited a lower level of pulmonary function and higher prevalence of allergic rhinitis, than those who lived further away from the oil spill site. Adults who lived in a highly exposed area or participated in clean-up work had higher urine levels of the oxidative stress biomarkers malondialdehyde and 8-hydroxydeoxyguanosine. Changes in haematological parameters during a 3-year period were observed in residents of both sexes in highly exposed areas, in addition to increases in respiratory diseases and mental health problems in female and male participants, respectively. FUTURE PLANS: The findings of this study will better enable policy makers to develop environmental health policies intended to prevent adverse health effects in residents of communities affected by oil spills, as well as policies regarding the management of future oil accidents. The HEROS study will continue to follow participants in future and will be updated to enable an investigation of long-term health effects.

Combined exposure of emotional labor and job insecurity on depressive symptoms among female call-center workers: A cross-sectional study.

Call-center workers work under unfavorable psychosocial working conditions, including, emotional labor and job insecurity, which might be linked to depressive symptoms.The purpose of this study was to explore the link between emotional labor and depressive symptoms and to investigate the influence of combined exposure to emotional labor and job insecurity on depressive symptoms.A health survey was conducted among female call-center workers in Geumcheon-gu (a district in Seoul), South Korea, in November 2012. The short form of the Korean occupational stress scale was used to measure occupational stressors. A questionnaire with 8 items was employed to assess emotional labor. Depressive symptoms were estimated using the Korean Version of the Centre for Epidemiologic Studies Depression Scale (CES-D). The association of emotional labor and occupational stressors with depressive symptoms was assessed using multilevel mixed-effects logistic regression.Overall, 699 female call-center workers were enrolled into this study. The odds ratios of experiencing depressive symptoms in workers exposed to emotional labor and job insecurity were 5.45 (95% confidence interval [CI]: 3.38-8.80) and 2.37 (95% CI: 0.86-6.50), respectively. When workers were simultaneously exposed to excessive emotional labor and high job insecurity levels, the odds ratio of experiencing depressive symptoms was 10.13 (95% CI: 3.51-29.23). The Relative Excess Risk due to the Interaction (RERI) of job insecurity and emotional labor was 3.30 (95% CI: -5.50 to 12.11); however, this was not statistically significant (P = .46).Although a causal relationship could not be established due to the cross-sectional study design, the combined effect of emotional labor and job insecurity might have a serious influence on behavioral health among call-center female workers.

Anisotropic Conductivity Tensor Imaging of In Vivo Canine Brain Using DT-MREIT.

We present in vivo images of anisotropic electrical conductivity tensor distributions inside canine brains using diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT). The conductivity tensor is represented as a product of an ion mobility tensor and a scale factor of ion concentrations. Incorporating directional mobility information from water diffusion tensors, we developed a stable process to reconstruct anisotropic conductivity tensor images from measured magnetic flux density data using an MRI scanner. Devising a new image reconstruction algorithm, we reconstructed anisotropic conductivity tensor images of two canine brains with a pixel size of 1.25 mm. Though the reconstructed conductivity values matched well in general with those measured by using invasive probing methods, there were some discrepancies as well. The degree of white matter anisotropy was 2 to 4.5, which is smaller than previous findings of 5 to 10. The reconstructed conductivity value of the cerebrospinal fluid was about 1.3 S/m, which is smaller than previous measurements of about 1.8 S/m. Future studies of in vivo imaging experiments with disease models should follow this initial trial to validate clinical significance of DT-MREIT as a new diagnostic imaging modality. Applications in modeling and simulation studies of bioelectromagnetic phenomena including source imaging and electrical stimulation are also promising.

A method for MREIT-based source imaging: simulation studies.

This paper aims to provide a method for using magnetic resonance electrical impedance tomography (MREIT) to visualize local conductivity changes associated with evoked neuronal activities in the brain. MREIT is an MRI-based technique for conductivity mapping by probing the magnetic flux density induced by an externally injected current through surface electrodes. Since local conductivity changes resulting from evoked neural activities are very small (less than a few %), a major challenge is to acquire exogenous magnetic flux density data exceeding a certain noise level. Noting that the signal-to-noise ratio is proportional to the square root of the number of averages, it is important to reduce the data acquisition time to get more averages within a given total data collection time. The proposed method uses a sub-sampled k-space data set in the phase-encoding direction to significantly reduce the data acquisition time. Since the sub-sampled data violates the Nyquist criteria, we only get a nonlinearly wrapped version of the exogenous magnetic flux density data, which is insufficient for conductivity imaging. Taking advantage of the sparseness of the conductivity change, the proposed method detects local conductivity changes by estimating the time-change of the Laplacian of the nonlinearly wrapped data.

Alternating steady state free precession for estimation of current-induced magnetic flux density: A feasibility study.

PURPOSE: To develop a novel, current-controlled alternating steady-state free precession (SSFP)-based conductivity imaging method and corresponding MR signal models to estimate current-induced magnetic flux density (Bz ) and conductivity distribution. METHODS: In the proposed method, an SSFP pulse sequence, which is in sync with alternating current pulses, produces dual oscillating steady states while yielding nonlinear relation between signal phase and Bz . A ratiometric signal model between the states was analytically derived using the Bloch equation, wherein Bz was estimated by solving a nonlinear inverse problem for conductivity estimation. A theoretical analysis on the signal-to-noise ratio of Bz was given. Numerical and experimental studies were performed using SSFP-FID and SSFP-ECHO with current pulses positioned either before or after signal encoding to investigate the feasibility of the proposed method in conductivity estimation. RESULTS: Given all SSFP variants herein, SSFP-FID with alternating current pulses applied before signal encoding exhibits the highest Bz signal-to-noise ratio and conductivity contrast. Additionally, compared with conventional conductivity imaging, the proposed method benefits from rapid SSFP acquisition without apparent loss of conductivity contrast. CONCLUSION: We successfully demonstrated the feasibility of the proposed method in estimating current-induced Bz and conductivity distribution. It can be a promising, rapid imaging strategy for quantitative conductivity imaging.

Current Density Imaging During Transcranial Direct Current Stimulation Using DT-MRI and MREIT: Algorithm Development and Numerical Simulations.

OBJECTIVE: Transcranial direct current stimulation (tDCS) is a neuromodulatory technique for neuropsychiatric diseases and neurological disorders. In the tDCS treatment, dc current is injected into the head through a pair of electrodes attached on the scalp over a target region. A current density imaging method is needed to quantitatively visualize the internal current density distribution during the tDCS treatment. METHODS: We developed a novel current density image reconstruction algorithm using 1) a subject specific segmented 3-D head model, 2) diffusion tensor data, and 3) magnetic flux density data induced by the tDCS current. We acquired T1 weighted and diffusion tensor images of the head using the MRI scanner before the treatment. During the treatment, we can measure the induced magnetic flux density data using a magnetic resonance electrical impedance tomography (MREIT) pulse sequence. In this paper, the magnetic flux density data were numerically generated. RESULTS: Numerical simulation results show that the proposed method successfully recovers the current density distribution including the effects of the anisotropic, as well as isotropic conductivity values of different tissues in the head. CONCLUSION: The proposed current density imaging method using DT-MRI and MREIT can reliably recover cross-sectional images of the current density distribution during the tDCS treatment. SIGNIFICANCE: Success of the tDCS treatment depends on a precise determination of the induced current density distribution within different anatomical structures of the brain. Quantitative visualization of the current density distribution in the brain will play an important role in understanding the effects of the electrical stimulation.

Frequency-dependent conductivity contrast for tissue characterization using a dual-frequency range conductivity mapping magnetic resonance method.

Electrical conductivities of biological tissues show frequency-dependent behaviors, and these values at different frequencies may provide clinically useful diagnostic information. MR-based tissue property mapping techniques such as magnetic resonance electrical impedance tomography (MREIT) and magnetic resonance electrical property tomography (MREPT) are widely used and provide unique conductivity contrast information over different frequency ranges. Recently, a new method for data acquisition and reconstruction for low- and high-frequency conductivity images from a single MR scan was proposed. In this study, we applied this simultaneous dual-frequency range conductivity mapping MR method to evaluate its utility in a designed phantom and two in vivo animal disease models. Magnetic flux density and B(1)(+) phase map for dual-frequency conductivity images were acquired using a modified spin-echo pulse sequence. Low-frequency conductivity was reconstructed from MREIT data by the projected current density method, while high-frequency conductivity was reconstructed from MREPT data by B(1)(+) mapping. Two different conductivity phantoms comprising varying ion concentrations separated by insulating films with or without holes were used to study the contrast mechanism of the frequency-dependent conductivities related to ion concentration and mobility. Canine brain abscess and ischemia were used as in vivo models to evaluate the capability of the proposed method to identify new electrical properties-based contrast at two different frequencies. The simultaneous dual-frequency range conductivity mapping MR method provides unique contrast information related to the concentration and mobility of ions inside tissues. This method has potential to monitor dynamic changes of the state of disease.

Fast conductivity imaging in magnetic resonance electrical impedance tomography (MREIT) for RF ablation monitoring.

PURPOSE: This study shows the potential of magnetic resonance electrical impedance tomography (MREIT) as a non-invasive RF ablation monitoring technique. MATERIALS AND METHODS: We prepared bovine muscle tissue with a pair of needle electrodes for RF ablation, a temperature sensor, and two pairs of surface electrodes for conductivity image reconstructions. We used the injected current non-linear encoding with multi-echo gradient recalled echo (ICNE-MGRE) pulse sequence in a series of MREIT scans for conductivity imaging. We acquired magnetic flux density data induced by externally injected currents, while suppressing other phase artefacts. We used an 8-channel RF head coil and 8 echoes to improve the signal-to-noise ratio (SNR) in measured magnetic flux density data. Using the measured data, we reconstructed a time series of 180 conductivity images at every 10.24 s during and after RF ablation. RESULTS: Tissue conductivity values in the lesion increased with temperature during RF ablation. After reaching 60 °C, a steep increase in tissue conductivity values occurred with relatively little temperature increase. After RF ablation, tissue conductivity values in the lesion decreased with temperature, but to values different from those before ablation due to permanent structural changes of tissue by RF ablation. CONCLUSION: We could monitor temperature and also structural changes in tissue during RF ablation by producing spatio-temporal maps of tissue conductivity values using a fast MREIT conductivity imaging method. We expect that the new monitoring method could be used to estimate lesions during RF ablation and improve the efficacy of the treatment.

Noise analysis in fast magnetic resonance electrical impedance tomography (MREIT) based on spoiled multi gradient echo (SPMGE) pulse sequence.

Magnetic resonance electrical impedance tomography (MREIT) is a promising non-invasive method to visualize a static cross-sectional conductivity and/or current density image by injecting low frequency currents. MREIT measures one component of the magnetic flux density caused by the injected current using a magnetic resonance (MR) scanner. For practical in vivo implementations of MREIT, especially for soft biological tissues where the MR signal rapidly decays, it is crucial to develop a technique for optimizing the magnetic flux density signal by the injected current while maintaining spatial-resolution and contrast. We design an MREIT pulse sequence by applying a spoiled multi-gradient-echo pulse sequence (SPMGE) to the injected current nonlinear encoding (ICNE), which fully injects the current at the end of the read-out gradient. The applied ICNE-SPMGE pulse sequence maximizes the duration of injected current almost up to a repetition time by measuring multiple magnetic flux density data. We analyze the noise level of measured magnetic flux density with respect to the pulse width of injection current and T*(2) relaxation time. In due consideration of the ICNE-SPMGE pulse sequence, using a reference information of T*(2) values in a local region of interest by a short pre-scan data, we predict the noise level of magnetic flux density to be measured for arbitrary repetition time TR. Results from phantom experiment demonstrate that the proposed method can predict the noise level of magnetic flux density for an appropriate TR = 40 ms using a reference scan for TR = 75 ms. The predicted noise level was compared with the noise level of directly measured magnetic flux density data.

Optimization of magnetic flux density measurement using multiple RF receiver coils and multi-echo in MREIT.

Magnetic Resonance Electrical Impedance Tomography (MREIT) is an MRI method that enables mapping of internal conductivity and/or current density via measurements of magnetic flux density signals. The MREIT measures only the z-component of the induced magnetic flux density B = (Bx, By, Bz) by external current injection. The measured noise of Bz complicates recovery of magnetic flux density maps, resulting in lower quality conductivity and current-density maps. We present a new method for more accurate measurement of the spatial gradient of the magnetic flux density gradient (∇ Bz). The method relies on the use of multiple radio-frequency receiver coils and an interleaved multi-echo pulse sequence that acquires multiple sampling points within each repetition time. The noise level of the measured magnetic flux density Bz depends on the decay rate of the signal magnitude, the injection current duration, and the coil sensitivity map. The proposed method uses three key steps. The first step is to determine a representative magnetic flux density gradient from multiple receiver coils by using a weighted combination and by denoising the measured noisy data. The second step is to optimize the magnetic flux density gradient by using multi-echo magnetic flux densities at each pixel in order to reduce the noise level of ∇ Bz and the third step is to remove a random noise component from the recovered ∇ Bz by solving an elliptic partial differential equation in a region of interest. Numerical simulation experiments using a cylindrical phantom model with included regions of low MRI signal to noise ('defects') verified the proposed method. Experimental results using a real phantom experiment, that included three different kinds of anomalies, demonstrated that the proposed method reduced the noise level of the measured magnetic flux density. The quality of the recovered conductivity maps using denoised ∇ Bz data showed that the proposed method reduced the conductivity noise level up to 3-4 times at each anomaly region in comparison to the conventional method.

Noise in hospital rooms and sleep disturbance in hospitalized medical patients.

OBJECTIVES: Hospitalized patients are vulnerable to sleep disturbances because of environmental stresses including noise. While most previous studies on hospital noise and sleep have been performed for medical machines in intensive care units, there is a limited data for patients hospitalized in medical wardrooms. The purpose of present study was to measure noise level of medical wardrooms, identify patient-perceived sources of noise, and to examine the association between noise levels and sleep disturbances in hospitalized patients. METHODS: Noise dosimeters were used to measure noise level in 29 inpatient wardrooms at a university hospital. Sleep pattern and disturbance were assessed in 103 hospitalized patients, using the Pittsburgh Sleep Quality Index (PSQI) and Leeds Sleep Evaluation Questionnaire. RESULTS: The mean equivalent continuous noise level for 24 hours was 63.5 decibel A (dBA), which was far higher than 30 dBA recommended by the World Health Organization for hospital wardrooms. Other patients sharing a room were perceived as the most common source of noise by the patients, which was usually preventable. Of the patients in the study, 86% had bad sleep as assessed by the PSQI. The sleep disturbance was significantly correlated with increasing noise levels in a dose response manner. CONCLUSIONS: Systemic organizational interventions are needed to keep wardrooms private and quiet to reduce sleep disturbance.

Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter.

BACKGROUND: In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality. METHODS: Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented. RESULTS: Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals. CONCLUSION: We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity contrast is of primary concern.

Focused current density imaging using internal electrode in magnetic resonance electrical impedance tomography (MREIT).

Magnetic resonance electrical impedance tomography (MREIT) is an imaging modality capable of visualizing cross-sectional current density and/or conductivity distributions inside an electrically conducting object. It uses an MRI scanner to measure one component of the magnetic flux density induced by an externally injected current through a pair of surface electrodes. For the cases of deep brain stimulation (DBS), electroporation, and radio frequency (RF) ablation, internal electrodes can be used to improve the quality of the MREIT images. In this paper, we propose a new MREIT imaging method using internal electrodes to visualize a current density distribution within a local region around them. To evaluate its performance, we conducted and analyzed a series of numerical simulations and phantom imaging experiments. We compared the reconstructed current density images using the internal electrodes with the obtained using only the external electrodes. We found that the proposed method using the internal electrodes stably determines the current density in the focused region with better accuracy.

Anisotropic conductivity tensor imaging in MREIT using directional diffusion rate of water molecules.

Magnetic resonance electrical impedance tomography (MREIT) is an emerging method to visualize electrical conductivity and/or current density images at low frequencies (below 1 KHz). Injecting currents into an imaging object, one component of the induced magnetic flux density is acquired using an MRI scanner for isotropic conductivity image reconstructions. Diffusion tensor MRI (DT-MRI) measures the intrinsic three-dimensional diffusion property of water molecules within a tissue. It characterizes the anisotropic water transport by the effective diffusion tensor. Combining the DT-MRI and MREIT techniques, we propose a novel direct method for absolute conductivity tensor image reconstructions based on a linear relationship between the water diffusion tensor and the electrical conductivity tensor. We first recover the projected current density, which is the best approximation of the internal current density one can obtain from the measured single component of the induced magnetic flux density. This enables us to estimate a scale factor between the diffusion tensor and the conductivity tensor. Combining these values at all pixels with the acquired diffusion tensor map, we can quantitatively recover the anisotropic conductivity tensor map. From numerical simulations and experimental verifications using a biological tissue phantom, we found that the new method overcomes the limitations of each method and successfully reconstructs both the direction and magnitude of the conductivity tensor for both the anisotropic and isotropic regions.

Experimental validations of in vivo human musculoskeletal tissue conductivity images using MR-based electrical impedance tomography.

Magnetic resonance (MR)-based electrical impedance tomography (MREIT) is a widely used imaging technique that provides high-resolution conductivity images at DC or below the 1 kHz frequency range. Using an MR scanner, this technique injects imaging currents into the human body and measures induced internal magnetic flux density data. By applying the recent progress of MREIT techniques, such as chemical shift artifact correction, multi-echo pulse sequence, and improved reconstruction algorithm, we can successfully reconstruct conductivity images of the human body. Meanwhile, numerous studies reported that the electrical conductivity of human tissues could be inferred from in vitro or ex vivo measurements of different species. However, in vivo tissues may differ from in vitro and/or ex vivo state due to the complicated tissue responses in living organs. In this study, we performed in vivo MREIT imaging of a human lower extremity and compared the resulting conductivity images with ex vivo biological tissue phantom images. The human conductivity images showed unique contrast between two different types of bones, muscles, subcutaneous adipose tissues, and conductive body fluids. Except for muscles and adipose tissues, the human conductivity images showed a similar pattern when compared with phantom results due to the anisotropic characteristic of muscle and the high conductive fluids in the adipose tissue.

Reconstruction of dual-frequency conductivity by optimization of phase map in MREIT and MREPT.

BACKGROUND: The spectroscopic conductivity distribution of tissue can help to explain physiological and pathological status. Dual frequency conductivity imaging by combining Magnetic Resonance Electrical Property Tomography (MREPT) and Magnetic Resonance Electrical Impedance Tomography (MREIT) has been recently proposed. MREIT can provide internal conductivity distributions at low frequency (below 1 kHz) induced by an external injecting current. While MREPT can provide conductivity at the Larmor frequency related to the strength of the magnetic field. Despite this potential to describe the membrane properties using spectral information, MREPT and MREIT techniques currently suffer from weak signals and noise amplification as they both reply on differentiation of measured phase data. METHODS: We proposed a method to optimize the measured phase signal by finding weighting factors according to the echo signal for MREPT and MREIT using the ICNE (Injected current nonlinear encoding) multi-echo pulse sequence. Our target weights are chosen to minimize the measured noise. The noise standard deviations were precisely analyzed for the optimally weighted magnetic flux density and the phase term of the positive-rotating magnetic field. To enhance the quality of dual-frequency conductivity images, we applied the denoising method based on the reaction-diffusion equation with the estimated noise standard deviations. A real experiment was performed with a hollow cylindrical object made of thin insulating film with holes to control the apparent conductivity using ion mobility and an agarose gel cylinder wrapped in an insulating film without holes to show different spectroscopic conductivities. RESULTS: The ability to image different conductivity characteristics in MREPT and MREIT from a single MR scan was shown by including the two objects with different spectroscopic conductivities. Using the six echo signals, we computed the optimized weighting factors for each echo. The qualities of conductivity images for MREPT and MREIT were improved by optimization of the phase map. The proposed method effectively reduced the random noise artifacts for both MREIT and MREPT. CONCLUSION: We enhanced the dual conductivity images using the optimally weighted magnetic flux density and the phase term of positive-rotating magnetic field based on the analysis of the noise standard deviations and applying the optimization and denoising methods.

Simultaneous imaging of dual-frequency electrical conductivity using a combination of MREIT and MREPT.

PURPOSE: To propose a single magnetic resonance scan conductivity imaging technique providing dual-frequency characteristics of tissue conductivity. METHODS: Using a modified spin-echo pulse sequence, the magnetic flux density induced by externally injected currents and the B1+ phase map with injected current effects removed were acquired simultaneously. The low-frequency conductivity was reconstructed from the measured magnetic flux density by the projected current density method, while the high-frequency conductivity was reconstructed using the B1+ maps. Three different conductivity phantoms were used to demonstrate low- and high-frequency conductivity characteristics. RESULTS: A conductivity spectrum at two frequencies was successfully acquired with the proposed scheme. Magnetic resonance electrical impedance tomography is advantageous for seeing an anomaly itself wrapped with a thin insulating membrane. In addition, if the membrane is porous, the membrane property can be quantitatively visualized with magnetic resonance electrical impedance tomography. Magnetic resonance electrical properties tomography does not detect such membranes, which enable it to probe things inside an insulating membrane. CONCLUSION: Considering these pros and cons and also the fact that the conductivity of biological tissue changes with frequency, a dual-frequency conductivity imaging incorporating both magnetic resonance electrical impedance tomography and magnetic resonance electrical properties tomography in future animal and human experiments is suggested.

Respiratory effects of the hebei spirit oil spill on children in taean, Korea.

PURPOSE: The oil spill from the Heibei Spirit in December 2007 contaminated the Yellow Coast of South Korea. We evaluated the respiratory effects of that spill on children who lived along the Yellow Coast. METHODS: Of 662 children living in the area exposed to the oil spill, 436 (65.9%) were enrolled as subjects. All subjects completed a modified International Study of Asthma and Allergies in Childhood questionnaire. A health examination, including a skin prick test, pulmonary function test, and methacholine bronchial provocation test (MBPT), was administered. The children were assigned to two groups: those who lived close to the oil spill area and those who lived far from the oil spill area. RESULTS: The children who lived close to the oil spill area showed a significantly lower forced expiratory volume in one second (FEV1), an increased prevalence of 'asthma ever' (based on a questionnaire), and 'airway hyperresponsiveness' (based on the MBPT) than those who lived far from the oil spill area (FEV1; P=0.011, prevalence of 'asthma ever' based on a questionnaire; P=0.005, prevalence of 'airway hyperresponsiveness' based on the MBPT; P=0.001). The onset of wheezing after the oil spill was significantly higher in children who lived close to the oil spill area than in those who lived far from the oil spill area among the 'wheeze ever' group (P=0.002). In a multiple logistic regression analysis, male sex, family history of asthma, and residence near the oil spill area were significant risk factors for asthma (sex [male/female]: odds ratio [OR], 2.54; 95% confidence interval [CI], 1.31-4.91; family history of asthma [No/Yes]: OR, 3.77; 95% CI, 1.83-7.75; exposure group [low/high]; OR, 2.43; 95% CI, 1.27-4.65). CONCLUSIONS: This study suggests that exposure to an oil spill is a risk factor for asthma in children.