Inflammatory myofibroblastic tumor is an uncommon tumor composed of myoblasts and various types of inflammatory infiltrates. Inflammatory myofibroblastic tumor is most common in the lungs but can be rarely found in the nasal cavity. Inflammatory myofibroblastic tumor is a rare entity that represents a diverse histologic pattern that can mimic malignant tumors. We report a case of inflammatory myofibroblastic tumor of the nasal septum in a 45-year-old man who presented with a tumor-like lesion of the nasal septum after two rounds of septoplasty.

Chronic expanding organizing hematoma (CEH) occasionally mimics a soft tissue tumor on MRI, which becomes more problematic in patients with a history of surgical resection for musculoskeletal malignancy. Herein, we present a case of CEH which we were able to differentiate from recurrent tumor through MRI follow-up, including diffusion-weighted imaging (DWI) and dynamic contrast enhanced (DCE) imaging. A 66-year-old male visited our institution under suspicion of recurrent leiomyosarcoma of the thigh, 19 months after surgery and radiation therapy. Due to inconclusive results, three US-guided biopsies and 6 MRI examinations were performed over 2 years. In the end, we could diagnose a CEH using conventional and functional MRI techniques, and it was histopathologically confirmed after surgical resection. A CEH may occur remotely after an initiating event, and it may persist and expand over several years. Functional MR sequences, in addition to conventional sequences, are helpful in differentiating CEH from malignant neoplasms.
Aged ; Biopsy ; Follow-Up Studies ; Hematoma* ; Humans ; Leiomyosarcoma ; Magnetic Resonance Imaging* ; Male ; Thigh

Extranodal NK/T cell lymphoma, nasal type, is a rare non-Hodgkin lymphoma originating in the nasal cavity or in the paranasal sinuses. Atrophic rhinitis is a debilitating chronic nasal mucosal disease of unknown etiology. However, there have not been any reports on the occurrence of nasal NK/T cell lymphoma in patients with atrophic rhinitis. We experienced a case of the extranodal NK/T cell lymphoma in the left nasal cavity, which had been misdiagnosed as atrophic rhinitis in a 39-year-old female. Thus, we report this rare case with a review of the literature.
Adult ; Female ; Humans ; Lymphoma* ; Lymphoma, Non-Hodgkin ; Nasal Cavity ; Paranasal Sinuses ; Rhinitis, Atrophic*

BACKGROUND AND OBJECTIVES: Tinnitus, a common complaint of workers who are exposed to noise, can cause substantial negative effects on the quality of life of these workers. The aim of this study was to analyze the characteristics of tinnitus in patients with noise-induced hearing loss and the relationship between tinnitus and the duration of noise exposure. SUBJECTS AND METHOD: Thirty-three patients with subjective tinnitus and noise-induced hearing loss were included in this study. Tinnitus questionnaire, Tinnitus Handicap Inventory (THI) and audiological examinations were investigated according to the duration of noise exposure. RESULTS: There was a significant correlation between the tinnitus loudness and the duration of noise exposure. Patients who had longer periods of noise exposure had a louder tinnitus and higher THI score. However, there is no significant correlation between the characteristics of tinnitus and aging process. CONCLUSION: The duration of noise exposure influences the loudness and distress of tinnitus. An awareness of tinnitus should be considered as part of hearing conservation program.
Aging ; Hearing ; Hearing Loss ; Hearing Loss, Noise-Induced* ; Humans ; Methods ; Noise* ; Quality of Life ; Tinnitus*

Objective: Data processing in analysis of circadian rhythm was performed in various ways. However, there was a lack of evidence for the optimal analysis of circadian rest-activity rhythm. Therefore, we aimed to perform mathematical simulations of data processing to investigate proper evidence for the optimal analysis of circadian rest-activity rhythm. Methods: Locomotor activities of 20 ICR male mice were measured by infrared motion detectors. The data of locomotor activities was processed using data summation, data average, and data moving average methods for cosinor analysis. Circadian indices were estimated according to time block, respectively. Also, statistical F and p-values were calculated by zero-amplitude test. Results: The data moving average result showed well-fitted cosine curves independent of data processing time. Meanwhile, the amplitude, MESOR, and acrophase were properly estimated within 800 seconds in data summation and data average methods. Conclusion These findings suggest that data moving average would be an optimal method for data processing in a cosinor analysis and data average within 800-second data processing time might be adaptable. The results of this study can be helpful to analyze circadian restactivity rhythms and integrate the results of the studies using different data processing methods.

Objective: Even though studies using machine learning on sleep-wake states have been performed, studies in various conditions are still necessary. This study aimed to examine the performance of the prediction model of locomotor activities on sleep-wake states using machine learning algorithms. Methods: The processed data using moving average of locomotor activities were used as predicting features. The sleep-wake states were used as true labels. The prediction models were established by machine learning classifiers such as support vector machine with radial basis function (SVM-RBF), linear discriminant analysis (LDA), naïve Bayes, and random forest (RF). The prediction model was evaluated by a six-fold cross validation. Results: The SVM-RBF and RF showed acceptable performance within a window of moving average from 480 to 1,200 seconds. The highest accuracy (0.869) was shown by the RF at the interval of 480 seconds. Meanwhile, the highest area under the curve (0.939) was shown by LDA at the interval of 870 seconds. Conclusion This study suggested that the prediction model on sleep-wake state using machine learning could show an improvement of the model performance when using moving average with raw data. The prediction model using locomotor activity can be useful in research on sleep-wake state.

Objective: Behavioral assessments that effectively predict sleep-wake states were tried in animal research. This study aimed to examine the prediction power of an infrared locomotion detector on the sleep-wake states in ICR (Institute Cancer Research) mice. We also explored the influence of the durations and ways of data processing on the prediction power. Methods: The locomotor activities of seven male mice in home cages were recorded by infrared detectors. Their sleep-wake states were assessed by video analysis. Using the receiver operating characteristic curve analysis, the cut-off score was determined, then the area under the curve (AUC) values of the infrared motion detector that predicted sleep-wake states were calculated. In order to improve the prediction power, the four ways of data processing on the prediction power were performed by Matlab 2013b. Results: In the initial analysis of raw data, the AUC value was 0.785, but it gradually reached to 0.942 after data summation. The simple data averaging and summation among four different methods showed the maximal AUC value. The 10-minute data summation improved sensitivity (0.889) and specificity (0.901) significantly from the baseline value (sensitivity 0.615; specificity 0.936) (p ＜ 0.001). Conclusion This study suggests that the locomotor activity measured by an infrared motion detector might be useful to predict the sleep-wake states in ICR mice. It also revealed that only simple data summation may improve the predictive power. Using daily locomotor activities measured by an infrared motion detector is expected to facilitate animal research related to sleep-wake states.

Objective: Behavioral assessments that effectively predict sleep-wake states were tried in animal research. This study aimed to examine the prediction power of an infrared locomotion detector on the sleep-wake states in ICR (Institute Cancer Research) mice. We also explored the influence of the durations and ways of data processing on the prediction power. Methods: The locomotor activities of seven male mice in home cages were recorded by infrared detectors. Their sleep-wake states were assessed by video analysis. Using the receiver operating characteristic curve analysis, the cut-off score was determined, then the area under the curve (AUC) values of the infrared motion detector that predicted sleep-wake states were calculated. In order to improve the prediction power, the four ways of data processing on the prediction power were performed by Matlab 2013b. Results: In the initial analysis of raw data, the AUC value was 0.785, but it gradually reached to 0.942 after data summation. The simple data averaging and summation among four different methods showed the maximal AUC value. The 10-minute data summation improved sensitivity (0.889) and specificity (0.901) significantly from the baseline value (sensitivity 0.615; specificity 0.936) (p ＜ 0.001). Conclusion This study suggests that the locomotor activity measured by an infrared motion detector might be useful to predict the sleep-wake states in ICR mice. It also revealed that only simple data summation may improve the predictive power. Using daily locomotor activities measured by an infrared motion detector is expected to facilitate animal research related to sleep-wake states.

PURPOSE: The aim of this study was to evaluate the tissue stiffness of solid pancreatic lesions by using acoustic radiation force impulse (ARFI) elastography to differentiate benign from malignant pancreatic lesions. METHODS: ARFI elastography was performed in 26 patients who had 27 focal solid pancreatic lesions, including 8 benign lesions (mass-forming pancreatitis, 5; autoimmune pancreatitis, 3) and 19 malignant lesions (pancreatic adenocarcinoma, 16; metastasis from colorectal cancer, 2; malignant neuroendocrine tumor, 1). On the elastographic images of virtual touch tissue imaging (VTI), the echogenicity of the mass was categorized on a 5-grade scale. On the elastographic image of virtual touch tissue quantification (VTQ), the shear wave velocities (SWVs) of the lesion and surrounding parenchyma were measured. RESULTS: On the VTI images, the mean echogenicity score of the malignant lesions (3.7+/-1.0) was higher than that of the benign lesions (3.1+/-0.4; P=0.023). On the VTQ images, there were no statistical differences in the mean SWV between the benign (2.4+/-1.1 m/sec) and malignant (3.3+/-1.0 m/sec) lesions (P=0.101). However, the mean SWV difference values between the lesion and background parenchyma of the malignant lesions (1.5+/-0.8 m/sec) were higher than those of the benign lesions (0.4+/-0.3 m/sec; P=0.011). CONCLUSION: ARFI elastography can determine the relative stiffness between a lesion and the background pancreatic parenchyma using VTI and VTQ, which is helpful in the differentiation between benign and malignant solid pancreatic lesions.
Acoustics* ; Adenocarcinoma ; Colorectal Neoplasms ; Diagnosis, Differential* ; Elasticity Imaging Techniques* ; Humans ; Neoplasm Metastasis ; Neuroendocrine Tumors ; Pancreas ; Pancreatic Neoplasms ; Pancreatitis ; Ultrasonography

PURPOSE: Vitiligo prevalence and its associated comorbidities rate have been reported variably among different populations. We aimed to determine the prevalence of vitiligo in Korea along with the baseline rate of comorbidities and compared the risks to the general population using hospital visit information of the total population in Korea. MATERIALS AND METHODS: We assessed demographic characteristics of vitiligo patients in Korean population from 2009 to 2011 in a nationwide data from Health Insurance Review Assessment Service. Patients who had at least one visit to Korea's primary, secondary, or tertiary referral hospitals with International Classification of Diseases, 10th Revision, Clinical Modification diagnosis code for vitiligo were identified. As a supplementary study, comorbidities associated with vitiligo were selected for further review to calculate relative risks compared to the general population. RESULTS: The annual prevalence of vitiligo determined by hospital-visiting rate in Korea was 0.12% to 0.13% over a three year period. In sync with other previous epidemiological studies, there was bimodal distribution among the age groups and no difference between genders. Also, vitiligo in Korean population was associated with various autoimmune/non-autoimmune diseases such as thyroiditis, atopic dermatitis, and psoriasis. CONCLUSION: This study was by far the most comprehensive review on prevalence of vitiligo using a data of total population in Korea. The prevalence is within a range of those reported in previous literatures, and increased risk of comorbidities such as thyroid diseases and psoriasis in vitiligo might aid clinicians in the initial work up of vitiligo patients and concurrent follow ups.
Adult ; Aged ; Autoimmune Diseases/*epidemiology/immunology ; Comorbidity ; Diabetes Mellitus, Type 1/epidemiology ; Female ; Humans ; Male ; Middle Aged ; Population Surveillance ; Prevalence ; Republic of Korea/epidemiology ; Socioeconomic Factors ; Thyroid Diseases/epidemiology ; Vitiligo/*epidemiology