• Tuberculosis and Respiratory Diseases
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• v.61 no.2
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• pp.129-136
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• 2006

Background: To interpret lung function tests, it is necessary to determine the lower limits of normal (LLN) and to derive a consensus on the interpretative algorithm. '0.7 of LLN for the $FEV_1$/FVC' was suggested by the COPD International Guideline (GOLD) for defining obstructive disease. A consensus on a new interpretative algorithm was recently achieved by ATS/ERS in 2005. We evaluated the accuracy of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases, and we also determined the effect of the new algorithm on diagnosing ventilatory defects. Methods: We obtained the age, gender, height, weight, $FEV_1$, FVC, and $FEV_1$/FVC from 7362 subjects who underwent spirometry in 2005 at the Asan Medical Center, Korea. For diagnosing obstructive diseases, the accuracy of '0.7 of LLN for the $FEV_1$/FVC' was evaluated in reference to the $5^{th}$ percentile of the LLN. By applying the new algorithm, we determined how many more subjects should have lung volumes testing performed. Evaluation of 1611 patients who had lung volumes testing performed as well as spirometry during the period showed how many more subjects were diagnosed with obstructive diseases according to the new algorithm. Results: 1) The sensitivity of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases increased according to age, but the specificity was decreased according to age; the positive predictive value decreased, but the negative predictive value increased. 2) By applying the new algorithm, 34.5% (2540/7362) more subjects should have lung volumes testing performed. 3) By applying the new algorithm, 13% (205/1611) more subjects were diagnosed with obstructive diseases; these subjects corresponded to 30% (205/681) of the subjects who had been diagnosed with restrictive diseases by the old interpretative algorithm. Conclusion: The sensitivity and specificity of '0.7 of LLN for the $FEV_1$/FVC' for diagnosing obstructive diseases changes according to age. By applying the new interpretative algorithm, it was shown that more subjects should have lung volumes testing performed, and there was a higher probability of being diagnosed with obstructive diseases.

• Journal of Preventive Medicine and Public Health
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• v.34 no.4
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• pp.427-436
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• 2001

Objective : To estimate the prevalence of congenital heart disease from the 1990 student heart disease screening program. Methods : The heart disease screening program for elementary students was conducted in Kyonggi-do, in 1998. The subjects of the present study comprised the 40,402 students who attended the schools in the catchment area of a collaborative university hospital and who participated in the primary examination. The congenital heart disease (CHD) patients were initially identified through a questionnaire about prior medical history, and further through diagnostic tests & medical examinations in the secondary & the tertiary examinations. Certain assumptions were used in the estimation of the number of CHD cases among non-participants of the secondary & tertiary examinations. The overall prevalence of CHD was estimated by adding the CHD detection rates of the participants and the estimated prevalence of the non-participants. Results : Among the 40,402 primary participants, 1,655 were referred further, of whom 79.1% (1,309) participated in the secondary examination. Of these, 121 were referred to the tertiary examination, with a participation rate at this last stage of 80.2%. The positive predictive value (PPV) of the screening tools was the highest when the results of both EKG and the questionnaire were positive. Because 85.9% of the detected cases had a past history of CHD, PPV was higher when the selection criteria in the questionnaire included past CHD history than when it didnt. The CHD defection rate among the participants was 1.76 cases/1,000 and the presumed number of cases among the non-participants was 31; giving an estimated final CHD prevalence of 2.52 cases/1,000 (95% CI : 2.06-3.06). Among the identified cases of CHD, VSD (52.8%) was the most common, followed by PDA (9.7%), TOF (9.7%) & PS (9.7%). Conclusion : Because the characteristics of the non-participants differed from those of the participants, the estimation of prevalence was influenced by the participation rate. Of the detected cases, 85.9% had a past history of diagnosis or operation for CMD. These findings suggested that the prevalence estimated in this study may be an underestimation of the actual condition. Therefore, a birth cohort study is required in order to more accurately estimate the prevalence and the effects of the program.

• Korean Journal of Radiology
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• v.24 no.10
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• pp.1028-1037
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• 2023

Objective: To evaluate the computed tomography (CT) features for diagnosing metastatic cervical lymph nodes (LNs) in patients with differentiated thyroid cancer (DTC) and validate the CT-based risk stratification system suggested by the Korean Thyroid Imaging Reporting and Data System (K-TIRADS) guidelines. Materials and Methods: A total of 463 LNs from 399 patients with DTC who underwent preoperative CT staging and ultrasound-guided fine-needle aspiration were included. The following CT features for each LN were evaluated: absence of hilum, cystic changes, calcification, strong enhancement, and heterogeneous enhancement. Multivariable logistic regression analysis was performed to identify independent CT features associated with metastatic LNs, and their diagnostic performances were evaluated. LNs were classified into probably benign, indeterminate, and suspicious categories according to the K-TIRADS and the modified LN classification proposed in our study. The diagnostic performance of both classification systems was compared using the exact McNemar and Kosinski tests. Results: The absence of hilum (odds ratio [OR], 4.859; 95% confidence interval [CI], 1.593-14.823; P = 0.005), strong enhancement (OR, 28.755; 95% CI, 12.719-65.007; P < 0.001), and cystic changes (OR, 46.157; 95% CI, 5.07-420.234; P = 0.001) were independently associated with metastatic LNs. All LNs showing calcification were diagnosed as metastases. Heterogeneous enhancement did not show a significant independent association with metastatic LNs. Strong enhancement, calcification, and cystic changes showed moderate to high specificity (70.1%-100%) and positive predictive value (PPV) (91.8%-100%). The absence of the hilum showed high sensitivity (97.8%) but low specificity (34.0%). The modified LN classification, which excluded heterogeneous enhancement from the K-TIRADS, demonstrated higher specificity (70.1% vs. 62.9%, P = 0.016) and PPV (92.5% vs. 90.9%, P = 0.011) than the K-TIRADS. Conclusion: Excluding heterogeneous enhancement as a suspicious feature resulted in a higher specificity and PPV for diagnosing metastatic LNs than the K-TIRADS. Our research results may provide a basis for revising the LN classification in future guidelines.

• Journal of Conservation Science
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• v.32 no.4
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• pp.491-500
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• 2016

Fog is atmospheric in which tiny drops of water vapor are suspended in the air near the ground. Its form, occurrence, etc., change according to the temperature, relative humidity, wind and geographical features of the space around it. In particular, fog tends to occur near a source of water because of temperature and relative humidity difference. These days, climate change is increasingly affecting the occurrence of fog. Therefore the purpose of this study was to investigate how fog affects materials that are part of our cultural properties through outdoor exposure tests and artificial degradation. The degradation evaluation of materials as a function of fog occurrence frequency, showed that the color of metals changed noticeably, whereas dyed silk and Dancheong showed degradation on the surface and color differences but no particular tendencies. Therefore, damage prediction by color differences as a function of fog occurrence frequency was based on metal samples, which showed constant color differences. Through a comparison of the predictive value and color difference by outdoor exposure, the accuracy and applicability of the damage prediction formula was confirmed. If a more complex damage prediction formula is created, it is expected that prediction of the degree of material damage in the field would be possible.

• Journal of Korean Neurosurgical Society
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• v.29 no.6
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• pp.778-785
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• 2000

Objectives : Intraoperative neurophysiologic monitoring(INM) is a well known useful method to reduce intraoperative neurological complications during neurosurgical procedures. Furthermore, INM is required in most cerebellopontine angle(CPA) surgery because cranial nerves or brain stem injuries can result in serious complications. Object of this study is to the correlation between the changes of intraoperative monitoring modalities during cerebellopontine angle tumor surgery and post-operative functional outcomes in auditory and facial functions. Material and Methods : Fifty-seven patients who underwent intraoperative neurophysiologic monitoring during CPA tumor surgery were retrospectively reviewed. Their lesions were as follows ; vestibular schwannomas in 42, other cranial nerve schwannomas in seven, meningiomas in five and cysts in three cases. Pre- and postoperative audiologic examinations and facial nerve function tests were performed in all patients. Intraoperative neurophysiologic monitoring modalities includes brainstem auditory evoked potentials(BAEP) and facial electromyographies(EMG). We compared the events of INM during CPA tumor surgeries with the outcomes of auditory and facial nerve functions. Results : The subjects who had abnormal changes during CPA tumor surgery were twenty cases with BAEP changes and facial EMG changes in twenty one cases. The changes of intraoperative neurophysiologic monitoring did not always result in poor functional outcomes. However, most predictable intraoperative monitoring changes were wave III-V complex losses in BAEP and continuous neurotonic activities in facial EMG. Conclusion : These results indicate that intraoperative neurophysiologic monitoring in CPA tumor surgery usually provide predictive value for postoperative functional outcomes.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4409-4413
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• 2016

Background: Cervical cancer is the second most common of malignancy found in Thai women. Human papillomavirus (HPV) infection is a major cause. The objective of the present study was to evaluate the prevalence of HPV infection and association with abnormal cervical cytology in Thai women. Materials and Methods: This study was conducted at the Gynecologic Clinic, Thammasat University, Pathum Thani, Thailand. A total of 2,144 cases who underwent annual cervical cancer screening by co-testing (liquid based cytology and HPV testing, DNA versus mRNA) during the priod from July 2013 to June 2016 were recruited in this study. Results: Prevalence of positive high risk (HR) HPV DNA and mRNA test were 19.7 and 8.4%, respectively with a statistically significant difference. Majority of cases of abnormal cytology in this study were atypical squamous cells of undetermined significance (ASC-US). In patients with ASC-US, positive HR HPV DNA was greater than in the mRNA group (10.1 and 4.5%, p<0.001). Nonetheless, there was no significant difference in participants with cervical intraepithelial neoplasia (CIN). HPV mRNA test had slightly lower sensitivity but higher negative predictive value (NPV) than the DNA test to detect abnormal cytology during cervical cancer screening (p<0.001). Both HPV test (DNA and mRNA) had equally efficacy to detect high grade precancerous lesion or higher (CIN 2+). Conclusions: Prevalence of HR HPV DNA and mRNA were 19.7 and 8.4 percent, respectively. NPV of HPV mRNA was higher than DNA test. Both tests had equal efficacy to detect CIN 2+ with sensitivity and specificity of 63% vs 55.7% and 83% vs 92%, respectively.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.681-689
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• 2023

Objective : Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm. Methods : A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant. Results : The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided. Conclusion : Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.

• The Korean Journal of Pain
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• v.19 no.1
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• pp.81-86
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• 2006

Background: Complex regional pain syndrome (CRPS) is a painful and disabling disease, yet the diagnosis of this can be difficult to confirm by purely objective measures. Therefore, we performed three-phasic bone scans and thermography as a work up in order to determine their predictive value and usefulness for making the diagnosis of CRPS. Methods: 44 patients who had been diagnosed with CRPS type-1, according to the modified criteria, were evaluated. All the patients were examined by performing a three-phasic bone scan and thermography as part of a work-up for diagnostic confirmation. The diffuse increased tracer uptake in the delayed image (phase III) was estimated by the positive findings. The findings were considered positive for CRPS if the thermographic findings showed temperature asymmetries between the affected and non- affected extremities of more than $1.00^{\circ}C$ Results: A review of the three-phasic bone scan for 44 patients indicated that 16 patients (36.4%) had diffusely positive scans, and thermographic abnormalities were noted in 35 of 44 patients (79.5%). Conclusions: The use of thermography in clinical settings can play an important role in the diagnosis of CRPS. However, a three-phasic bone scan alone cannot provide a completely accurate diagnosis, so it is imperative that the three-phasic bone scan data be integrated with the clinical evaluation and the other relevant tests.

• Journal of Microbiology and Biotechnology
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• v.28 no.4
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• pp.645-651
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• 2018

The carcinogenicity of chemicals in the environment is a major concern. Recently, numerous studies have attempted to develop methods for predicting carcinogenicity, including rodent and cell-based approaches. However, rodent carcinogenicity tests for evaluating the carcinogenic potential of a chemical to humans are time-consuming and costly. This study focused on the development of an alternative method for predicting carcinogenicity using quantitative PCR (qPCR) and colon cancer stem cells. A toxicogenomic method, mRNA profiling, is useful for predicting carcinogenicity. Using microarray analysis, we optimized 16 predictive gene sets from five carcinogens (azoxymethane, 3,2'-dimethyl-4-aminobiphenyl, N-ethyl-n-nitrosourea, metronidazole, 4-(n-methyl-n-nitrosamino)-1-(3-pyridyl)-1-butanone) used to treat colon cancer stem cell samples. The 16 genes were evaluated by qPCR using 23 positive and negative carcinogens in colon cancer stem cells. Among them, six genes could differentiate between positive and negative carcinogens with a p-value of ${\leq}0.05$. Our qPCR-based prediction system for colon carcinogenesis using colon cancer stem cells is cost- and time-efficient. Thus, this qPCR-based prediction system is an alternative to in vivo carcinogenicity screening assays.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.363-373
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• 2024

Objective: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. Materials and Methods: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. Results: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. Conclusion: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.