Colonic lesions by irritant laxative abuse are devided into melanosis coli, cathartic colon, soap or chemical colitis. Melanosis coli is the brownish or black discoloration of the colon because of the accumulation of lipofuscin pigment in macrophages located in lamina propria and associated with anthraquinone containing laxative abuse. The site of this lesion is more common in cecum and proximal colon, but whole colon can be involved. This lesion is occurred between 4 months and 13 months from initiation of drug medication, and the lesion is benign because the pigments disappear by withdrawning the laxatives. A number of cases were reported in our country, all of the cases were associated with prolonged administration of anthraquinone type laxatives. We presents two cases of melanosis eoli that had administrated aloe to treat the chronic constipation during long terms, and one case of melanosis coli that had not administrated laxatives or a specific drug with chronic constipation. All of three cases were confirmed by colonoscopy.
Aloe ; Cecum ; Colitis ; Colon ; Colonoscopy ; Constipation ; Laxatives ; Lipofuscin ; Macrophages ; Melanosis* ; Mucous Membrane ; Soaps

BACKGROUND: Hepatitis A is an acute infectious disease of the liver caused by the hepatitis A virus (HAV). The purpose of this study was to investigate the HAV vaccination status and related factors among college students. METHODS: The study subjects were 503 students conveniently sampled from C university located in one district of Jeollanamdo. General characteristics and HAV vaccination related factors were collected by a self-reported questionnaire in October 2013. Chi-square tests and multiple logistic regression analyses were used to evaluate related factors with HAV vaccination. RESULTS: Of the 503 subjects without a history of HAV infection, 65 subjects (12.9%) reported that they were vaccinated. In multiple analyses, subjects who have had health screening (adjusted odds ratio, aOR=2.44 and 95% confidence interval, 95% CI=1.26-4.73) and those who were aware of HAV infection (aOR=6.00, 95% CI=1.81-19.91) or who perceived the benefits of HAV vaccine (aOR=2.05, 95% CI=1.07-3.93) were more likely to be vaccinated than those not involved in these factors. With regard to intention for HAV vaccine, 314 subjects (71.9%) reported that they have the intention to be vaccinated against HAV. In multiple analyses, higher grade level, high monthly allowance, awareness of HAV vaccine, perceived susceptibility of HAV, perceived seriousness of HAV and perceived benefits of HAV vaccine were significantly associated with the intention for HAV vaccination. CONCLUSIONS: The vaccination rate for HAV was found to be low in our sample of college students. To reduce health risks related with HAV, prevention efforts should consider these results.
Communicable Diseases ; Hepatitis A ; Hepatitis A virus* ; Humans ; Intention ; Jeollanam-do ; Liver ; Logistic Models ; Mass Screening ; Odds Ratio ; Risk Factors ; Vaccination* ; Surveys and Questionnaires

Fetal bilateral renal agenesis is a lethal congenital anomaly. An early and reliable prenatal diagnosis is extremely important as it may offer options for pregnancy termination as early as possible. The criteria for the ultrasonographic diagnosis of bilateral renal agenesis are severe oligohydramnios, nonvisualization of the bladder, and the empty renal fossa. However, severe oligohydramnios makes it difficult to diagnose the disease because of poor sonographic resolution. We present two cases of bilateral renal agenesis, one is diagnosed by ultrasonography after amnioinfusion at 24 weeks gestation, the other is diagnosed postnatally after term delivery.
Diagnosis ; Female ; Oligohydramnios ; Pregnancy ; Prenatal Diagnosis ; Ultrasonography ; Urinary Bladder

No abstract available.
Bilirubin* ; Humans ; Infant, Newborn*

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

Purpose: Multi-echo gradient echo (mGRE) images are used to acquire and analyze multiple echo signals. As the number of acquired echoes increases, more information on the voxel decay changes can be obtained, facilitating myelin water fraction (MWF) mapping.However, an increase in the acquired echoes leads to an increase in scan time. In this study, we developed a workflow to reduce the scan time using a two-stage neural network approach, which extrapolates additional echo images using mGRE data. Materials and Methods: In Stage 1, a pseudo-T1 map was estimated using a U-net network combined with a simple signal model to correct the bias between two mGRE acquired with different scan parameters. The pseudo-T1 map was used to generate an initial echo time (TE) image from the mGRE images. In Stage 2, subsequent TE images were predicted from the initial echo image generated using a trained prediction network. The results were quantitatively compared with those obtained using a fitting algorithm. The MWF mapping results were then compared. Results: The proposed model exhibited better root mean square error, structural similarity index measure, and peak signal-to-noise ratio, as well as a higher correlation with the MWF analysis compared to the fitting algorithm. Conclusion These results demonstrate that the proposed network can effectively reduce the scan time for mGRE image acquisition.

No abstract available.
Mitral Valve* ; Quinidine*

No abstract available.
Dermatitis, Seborrheic* ; Lice Infestations*

No abstract available.
Dermatitis, Seborrheic* ; Lice Infestations*