• Title/Summary/Keyword: ROC(Receiver operating characteristic)

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Comparison of 3D Volumetric Subtraction Technique and 2D Dynamic Contrast Enhancement Technique in the Evaluation of Contrast Enhancement for Diagnosing Cushing's Disease

  • Park, Yae Won;Kim, Ha Yan;Lee, Ho-Joon;Kim, Se Hoon;Kim, Sun-Ho;Ahn, Sung Soo;Kim, Jinna;Lee, Seung-Koo
    • Investigative Magnetic Resonance Imaging
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    • v.22 no.2
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    • pp.102-109
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    • 2018
  • Purpose: The purpose of this study is to compare the performance of the T1 3D subtraction technique and the conventional 2D dynamic contrast enhancement (DCE) technique in diagnosing Cushing's disease. Materials and Methods: Twelve patients with clinically and biochemically proven Cushing's disease were included in the study. In addition, 23 patients with a Rathke's cleft cyst (RCC) diagnosed on an MRI with normal pituitary hormone levels were included as a control, to prevent non-blinded positive results. Postcontrast T1 3D fast spin echo (FSE) images were acquired after DCE images in 3T MRI and image subtraction of pre- and postcontrast T1 3D FSE images were performed. Inter-observer agreement, interpretation time, multiobserver receiver operating characteristic (ROC), and net benefit analyses were performed to compare 2D DCE and T1 3D subtraction techniques. Results: Inter-observer agreement for a visual scale of contrast enhancement was poor in DCE (${\kappa}=0.57$) and good in T1 3D subtraction images (${\kappa}=0.75$). The time taken for determining contrast-enhancement in pituitary lesions was significantly shorter in the T1 3D subtraction images compared to the DCE sequence (P < 0.05). ROC values demonstrated increased reader confidence range with T1 3D subtraction images (95% confidence interval [CI]: 0.94-1.00) compared with DCE (95% CI: 0.70-0.92) (P < 0.01). The net benefit effect of T1 3D subtraction images over DCE was 0.34 (95% CI: 0.12-0.56). For Cushing's disease, both reviewers misclassified one case as a nonenhancing lesion on the DCE images, while no cases were misclassified on T1 3D subtraction images. Conclusion: The T1 3D subtraction technique shows superior performance for determining the presence of enhancement on pituitary lesions compared with conventional DCE techniques, which may aid in diagnosing Cushing's disease.

THE CHANGES OF SERUM C-REACTIVE PROTEIN IN THE HEAD AND NECK INFECTION (두경부 감염 환자에서 혈청 내 C-Reactive Protein의 변화)

  • Lee, Ju-Hyun;Kim, Chin-Soo;Lee, Sang-Han;Kim, Chul-Hwan
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.29 no.1
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    • pp.5-13
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    • 2003
  • The purpose of this study is to determine the value of serum concentration of C-reactive protein(CRP) in comparison with ESR and leukocyte as the tools for diagnosis and follow-up study of infection. For this study, thirty-one patients with head and neck infection and thirty-two patients performed the orthognathic surgery were selected for experimental and control groups each other. we analyzed the blood sample daily to measure CRP, ESR and leukocytosis. The results of this study are as the following : 1. Serum C-Reactive Protein levels in the experimental group were higher than control group and the pattern of CRP changes continued to decline in both groups(P<0.001). 2. ESR changes in both groups were scattered without any special pattern. 3. Correlation between CRP and Leukocyte was higher than others(r=0.664, P<0.01). 4. In the Receiver Operating Characteristic(ROC) Curve of experimental group, rapid increase of CRP curve and Area under the curve(AUC) value, 0.774, indicate the high accuracy of estimation. 5. In experimental group, sensitivity of CRP, ESR, and Leukocytosis on recovery day were 83%, 17% and 71%. Based on the results of this study, we could conclude that determination of CRP is more useful method to diagnosis and follow-up study of infection than other commonly used variables in oral and maxillofacial region.

Neutrophil-to-lymphocyte Ratio as A Predictor of Aspiration Pneumonia in Drug Intoxication Patients (약물중독 환자에서 Neutrophil Lymphocyte Ratio의 흡인성폐렴 발생 예측인자로서의 고찰)

  • Lee, Jeong Beom;Lee, Sun Hwa;Yun, Seong Jong;Ryu, Seokyong;Choi, Seung Woon;Kim, Hye Jin;Kang, Tae Kyung;Oh, Sung Chan;Cho, Suk Jin;Seo, Beom Sok
    • Journal of The Korean Society of Clinical Toxicology
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    • v.16 no.2
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    • pp.61-67
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    • 2018
  • Purpose: To evaluate the association between neutrophil-to-lymphocyte ratio (NLR) and occurrence of aspiration pneumonia in drug intoxication (DI) patients in the emergency department (ED) and to evaluate the relationship between NLR and length of hospital admission/intensive care unit (ICU) admission Methods: A total of 466 patients diagnosed with DI in the ED from January 2016 to December 2017 were included in the analysis. The clinical and laboratory results, including NLR, were evaluated as variables. NLR was calculated as the absolute neutrophil count/absolute lymphocyte count. To evaluate the prognosis of DI, data on the development of aspiration pneumonia were obtained. Also, we evaluated the relationship between NLR and length of hospital admission and between NLR and length of ICU admission. Statistically, multivariate logistic regression analyses, receiver-operating characteristic (ROC) curve analysis, and Pearson's correlation (${\rho}$) were performed. Results: Among the 466 DI patients, 86 (18.5%) developed aspiration pneumonia. Multivariate logistic regression analysis revealed NLR as an independent factor in predicting aspiration pneumonia (odds ratio, 1.7; p=0.001). NLR showed excellent predictive performance for aspiration pneumonia (areas under the ROC curves, 0.815; cut-off value, 3.47; p<0.001) with a sensitivity of 86.0% and a specificity of 72.6%. No correlations between NLR and length of hospital admission (${\rho}=0.195$) and between NLR and length of ICU admission (${\rho}=0.092$) were observed. Conclusion: The NLR is a simple and effective marker for predicting the occurrence of aspiration pneumonia in DI patients. Emergency physicians should be alert for aspiration pneumonia in DI patients with high NLR value (>3.47).

Initial D-dimer level as early prognostic tool in blunt trauma patients without significant brain injury (중증 뇌손상이 없는 둔상 환자에서 초기 중증도 예측인자로서 D-dimer의 역할)

  • Sohn, Seok Woo;Lee, Jae Baek;Jin, Young Ho;Jeong, Tae Oh;Jo, Si On;Lee, Jeong Moon;Yoon, Jae Chol;Kim, So Eun
    • Journal of The Korean Society of Emergency Medicine
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    • v.29 no.5
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    • pp.430-436
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    • 2018
  • Objective: The purpose of this study was to evaluate whether or not the d-dimer level indicating hyperfibrinolysis could be a predictor of early poor outcome (massive transfusion, death within 24 hours) associated with trauma-induced coagulopathy in blunt trauma without significant brain injury. Methods: This study was a retrospective observational study using 516 blunt trauma patients without significant brain injury. The poor outcome group, including patients receiving massive transfusion and those who died within 24 hours, consisted of 33 patients (6.4%). The variables were compared between the poor outcome group and good outcome group, and logistic regression analysis was performed using statistically significant variables. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the poor outcome prediction ability of the initial d-dimer level. Results: The poor outcome group showed more serious anatomical, physiological, and laboratory data than the good outcome group. In the ROC curve analysis for evaluation of the poor outcome prediction of the d-dimer level, the area under the curve value was 0.87 (95% confidence interval [CI], 0.84-0.90) while the cut-off value was 27.35 mg/L. In the logistic regression analysis, the high d-dimer level was shown to be an independent predictor of poor outcome (adjusted odds ratio, 14.87; 95% CI, 2.96-74.67). Conclusion: The high d-dimer level (>27.35 mg/L) can be used as a predictor for the poor outcome of patients with blunt trauma without significant brain injury.

Assessment of Mild Cognitive Impairment in Elderly Subjects Using a Fully Automated Brain Segmentation Software

  • Kwon, Chiheon;Kang, Koung Mi;Byun, Min Soo;Yi, Dahyun;Song, Huijin;Lee, Ji Ye;Hwang, Inpyeong;Yoo, Roh-Eul;Yun, Tae Jin;Choi, Seung Hong;Kim, Ji-hoon;Sohn, Chul-Ho;Lee, Dong Young
    • Investigative Magnetic Resonance Imaging
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    • v.25 no.3
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    • pp.164-171
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    • 2021
  • Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

Development of Cerebral Amyloid Positivity Predicting Models Using Clinical Indicators (임상적 지표를 이용한 대뇌 아밀로이드 단백 축적 여부 예측모델 개발)

  • Chun, Young Jae;Joo, Soo Hyun
    • Korean Journal of Biological Psychiatry
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    • v.27 no.2
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    • pp.94-100
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    • 2020
  • Objectives Amyloid β positron emission tomography (Aβ PET) is widely used as a diagnostic tool in patients who have symptoms of cognitive impairment, however, this diagnostic examination is too expensive. Thus, predicting the positivity of Aβ PET before patients undergo the examination is essential. We aimed to analyze clinical predictors of patients who underwent Aβ PET retrospectively, and to develop a predicting model of Aβ PET positivity. Methods 468 patients who underwent Aβ PET with cognitive impairment were recruited and their clinical indicators were analyzed retrospectively. We specified the primary outcome as Aβ PET positivity, and included variables such as age, sex, body mass index, diastolic blood pressure, systolic blood pressure, education, dementia family history, Mini Mental Status Examination (MMSE), Clinical Dementia Rating (CDR), Clinical Dementia Rating-Sum of Box (CDR-SB), hypertension (HTN), diabetes mellitus (DM) and presence of apolipoprotein E (ApoE) E4 as potential predictors. We developed three final models of amyloid positivity prediction for total subjects, mild cognitive impairment (MCI) and Alzheimer's disease (AD) dementia using a multivariate stepwise logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) value was calculated for the ROC curve. Results Aβ PET negative patients were 49.6% (n = 232), and Aβ PET positive patients were 50.4% (n = 236). In the final model of all subjects, older age, female sex, presence of ApoE E4 and lower MMSE are associated with Aβ PET positivity. The AUC value was 0.296. In the final model of MCI subjects (n = 244), older age and presence of ApoE E4 are associated with Aβ PET positivity. The AUC value was 0.725. In the final model of AD subjects (n = 173), lower MMSE scores, the presence of ApoE E4 and history of HTN are associated with Aβ PET positivity. The AUC value was 0.681. Conclusions The cerebral amyloid positivity model, which was based on commonly available clinical indicators, can be useful for prediction of amyloid PET positivity in MCI or AD patients.

The Korean Repeatable Battery for the Assessment of Neuropsychological Status-Update : Psychiatric and Neurosurgery Patient Sample Validity

  • Park, Jong-Ok;Koo, Bon-Hoon;Kim, Ji-Yean;Bai, Dai-Seg;Chang, Mun-Seon;Kim, Oh-Lyong
    • Journal of Korean Neurosurgical Society
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    • v.64 no.1
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    • pp.125-135
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    • 2021
  • Objective : This study aimed to validate the Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status Update (K-RBANS). Methods : We performed a retrospective analysis of 283 psychiatric and neurosurgery patients. To investigate the convergent validity of the K-RBANS, correlation analyses were performed for other intelligence and neuropsychological test results. Confirmatory factor analysis was used to test a series of alternative plausible models of the K-RBANS. To analyze the various capabilities of the K-RBANS, we compared the area under the receiver operating characteristic (ROC) curves (AUC). Results : Significant correlations were observed, confirming the convergent validity of the K-RBANS among the Total Scale Index (TSI) and indices of the K-RBANS and indices of intelligence (r=0.47-0.81; p<0.001) and other neuropsychological tests at moderate and above significance (r=0.41-0.63; p<0.001). Additionally, the results testing the construct validity of the K-RBANS showed that the second-order factor structure model (model 2, similar to an original factor structure of RBANS), which includes a first-order factor comprising five index scores (immediate memory, visuospatial capacity, language, attention, delayed memory) and one higher-order factor (TSI), was statistically acceptable. The comparative fit index (CFI) (CFI, 0.949) values and the goodness of fit index (GFI) (GFI, 0.942) values higher than 0.90 indicated an excellent fit. The root mean squared error of approximation (RMSEA) (RMSEA, 0.082) was considered an acceptable fit. Additionally, the factor structure of model 2 was found to be better and more valid than the other model in χ2 values (Δχ2=7.69, p<0.05). In the ROC analysis, the AUCs of the TSI and five indices were 0.716-0.837, and the AUC of TSI (AUC, 0.837; 95% confidence interval, 0.760-0.896) was higher than the AUCs of the other indices. The sensitivity and specificity of TSI were 77.66% and 78.12%, respectively. Conclusion : The overall results of this study suggest that the K-RBANS may be used as a valid tool for the brief screening of neuropsychological patients in Korea.

Differences in Static Lower Extremity Alignment according to the History of Lateral Ankle Sprain: Efficacy and Limitation of Static Lower Limb Alignment Measurement as a Predictor of Lateral Ankle Sprain (외측 발목 염좌 병력에 따른 정적 하지 정렬 차이: 외측 발목 염좌의 예측인자로서 정적 하지 정렬 검사의 효용성과 한계점)

  • Jeon, Hyung Gyu;Ha, Sunghe;Lee, Inje;Kang, Tae Kyu;Kim, Eun Sung;Lee, Sae Yong
    • Korean Journal of Applied Biomechanics
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    • v.31 no.1
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    • pp.1-15
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    • 2021
  • Objective: The aim of this study was to investigate 1) the difference in static lower extremity alignment (SLEA) according to a history of lateral ankle sprain (LAS), 2) to identify SLEA factors affecting LAS, and 3) to present the cut-off value and 4) the usefulness and limitations of the SLEA measurement. Method: This case-control study recruited 88 men (age: 27.78±4.69 yrs) and 39 women (age: 24.62±4.20 yrs) subjects with and without LAS. SLEA measurement protocol included Q angle, tibiofemoral angle, genu recurvatum, rear foot (RF) angle, tibal varum and torsion, navicular drop, ankle dorsiflexion range of motion (DF ROM). Independent t-test, logistic regression and receiver operating characteristic (ROC) curve were used for statistical analysis. Results: Men with a history of LAS had significantly smaller Q angles both in standing and in supine position, while women with a history of LAS had significantly greater DF ROM in non-weight bearing (NWB; p < 0.05). Logistic regression model suggests tibial varum (OR = 0.779, p = 0.021) and WB DF ROM (OR = 1.067, p = 0.045) were associated with LAS in men. In case of women, there were no significant SLEA factors for LAS, however, ROC curve analysis revealed standing RF angle (AUC = 0.647, p = 0.028) and NWB DF ROM (AUC = 0.648, p = 0.026) could be affecting factors for LAS. Conclusion: There are differences in SLEA according to the history of LAS, furthermore, the identified items were different by sex. In case of men, tibial varum and WB DF ROM affect LAS occurrence. Standing RF angle and NWB DF ROM of women could be a predictor for LAS. However, since the sensitivity and specificity in most of the SLEA measurements are low, kinematic in dynamic tasks should be considered together for a more accurate evaluation of LAS risk.

Drought evaluation using unstructured data: a case study for Boryeong area (비정형 데이터를 활용한 가뭄평가 - 보령지역을 중심으로 -)

  • Jung, Jinhong;Park, Dong-Hyeok;Ahn, Jaehyun
    • Journal of Korea Water Resources Association
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    • v.53 no.12
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    • pp.1203-1210
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    • 2020
  • Drought is caused by a combination of various hydrological or meteorological factor, so it is difficult to accurately assess drought event, but various drought indices have been developed to interpret them quantitatively. However, the drought indexes currently being used are calculated from the lack of a single variable, which is a problem that does not accurately determine the drought event caused by complex causes. Shortage of a single variable may not be a drought, but it is judged to be a drought. On the other hand, research on developing indices using unstructured data, which is widely used in big data analysis, is being carried out in other fields and proven to be superior. Therefore, in this study, we intend to calculate the drought index by combining unstructured data (news data) with weather and hydrologic information (rainfall and dam inflow) that are being used for the existing drought index, and to evaluate the utilization of drought interpretation through verification of the calculated drought index. The Clayton Copula function was used to calculate the joint drought index, and the parameter estimation was used by the calibration method. The analysis showed that the drought index, which combines unstructured data, properly expresses the drought period compared to the existing drought index (SPI, SDI). In addition, ROC scores were calculated higher than existing drought indices, making them more useful in drought interpretation. The joint drought index calculated in this study is considered highly useful in that it complements the analytical limits of the existing single variable drought index and provides excellent utilization of the drought index using unstructured data.

Seismic Vulnerability Assessment and Mapping for 9.12 Gyeongju Earthquake Based on Machine Learning (기계학습을 이용한 지진 취약성 평가 및 매핑: 9.12 경주지진을 대상으로)

  • Han, Jihye;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.36 no.6_1
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    • pp.1367-1377
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    • 2020
  • The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.