Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal

박지은,한경화,성유섭,정미선,구현정,윤희망,최영준,이승수,김경원,신영빈,안수아,조효민,박성호 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.6

Objective: To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods: Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results: Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion: Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary.

영역 기반 영상 검출 기술을 이용한 반도체 불량 원인 진단용 컴퓨터 보조 진단 시스템의 개발

허경석,이영주,성유섭,강석호 한국경영과학회 2009 한국경영과학회 학술대회논문집 Vol.2009 No.5

Influence of B1-Inhomogeneity on Pharmacokinetic Modeling of Dynamic Contrast-Enhanced MRI: A Simulation Study

박범우,최병세,성유섭,우동철,심우현,김경원,최윤석,배상훈,서지연,조형준,김정곤 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.4

Objective: To simulate the B1-inhomogeneity-induced variation of pharmacokinetic parameters on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Materials and Methods: B1-inhomogeneity-induced flip angle (FA) variation was estimated in a phantom study. Monte Carlo simulation was performed to assess the FA-deviation-induced measurement error of the pre-contrast R1, contrast-enhancement ratio, Gd-concentration, and two-compartment pharmacokinetic parameters (Ktrans, ve, and vp). Results: B1-inhomogeneity resulted in -23–5% fluctuations (95% confidence interval [CI] of % error) of FA. The 95% CIs of FA-dependent % errors in the gray matter and blood were as follows: -16.7–61.8% and -16.7–61.8% for the pre-contrast R1, -1.0–0.3% and -5.2–1.3% for the contrast-enhancement ratio, and -14.2–58.1% and -14.1–57.8% for the Gd-concentration, respectively. These resulted in -43.1–48.4% error for Ktrans, -32.3–48.6% error for the ve, and -43.2–48.6% error for vp. The pre-contrast R1 was more vulnerable to FA error than the contrast-enhancement ratio, and was therefore a significant cause of the Gd-concentration error. For example, a -10% FA error led to a 23.6% deviation in the pre-contrast R1, -0.4% in the contrast-enhancement ratio, and 23.6% in the Gd-concentration. In a simulated condition with a 3% FA error in a target lesion and a -10% FA error in a feeding vessel, the % errors of the pharmacokinetic parameters were -23.7% for Ktrans, -23.7% for ve, and -23.7% for vp. Conclusion: Even a small degree of B1-inhomogeneity can cause a significant error in the measurement of pharmacokinetic parameters on DCE-MRI, while the vulnerability of the pre-contrast R1 calculations to FA deviations is a significant cause of the miscalculation.

영역 기반 영상 검출 기술을 이용한 반도체 불량 원인 진단용 컴퓨터 보조 진단 시스템의 개발

허경석,이영주,성유섭,강석호 대한산업공학회 2009 대한산업공학회 춘계학술대회논문집 Vol.2009 No.5

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Xiao Quan Xu,최영준,성유섭,윤라경,장승원,박지은,허영진,백정환,이정현 대한영상의학회 2016 Korean Journal of Radiology Vol.17 No.5

Objective: To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. Materials and Methods: We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D* and model-free parameters from the DCE-MRI (wash-in, Tmax, Emax, initial AUC60, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson’s correlation test was used for statistical analysis. Results: No correlation was found between f or D* and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D* (p > 0.05, respectively). Conclusion: Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Recent Issues on Body Composition Imaging for Sarcopenia Evaluation

이고은,신용빈,허지미,성유섭,In-Seob Lee,Kwon-Ha Yoon,김경원 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.2

Recently, sarcopenia has garnered renewed interest. Sarcopenia is a disease characterized by decreased skeletal muscle mass and strength/function, which can impair the quality of life and increase physical disability, adverse metabolic effects, and mortality. Imaging tools for evaluating and diagnosing sarcopenia have developed rapidly. Radiologists should be aware of sarcopenia and its clinical implications. We review current knowledge about sarcopenia, its pathophysiological impact, and advantages and disadvantages of methods for evaluation of sarcopenia focusing on body composition imaging modalities such as whole-body dual-energy X-ray absorptiometry, CT, and MRI. Controversial issues are discussed, including the lack of consensus and standardization of the disease definition, imaging modality, measurement methods, and diagnostic cutoff points.

Feasibility of Automated Quantification of Regional Disease Patterns Depicted on High-Resolution Computed Tomography in Patients with Various Diffuse Lung Diseases

박상옥,서준범,김남국,박성훈,이영경,박범우,성유섭,이영주,이정진,강석호 대한영상의학회 2009 Korean Journal of Radiology Vol.10 No.5

Objective: This study was designed to develop an automated system for quantification of various regional disease patterns of diffuse lung diseases as depicted on high-resolution computed tomography (HRCT) and to compare the performance of the automated system with human readers. Materials and Methods: A total of 600 circular regions-of-interest (ROIs), 10 pixels in diameter, were utilized. The 600 ROIs comprised 100 ROIs that represented six typical regional patterns (normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). The ROIs were used to train the automated classification system based on the use of a Support Vector Machine classifier and 37 features of texture and shape. The performance of the classification system was tested with a 5-fold cross-validation method. An automated quantification system was developed with a moving ROI in the lung area, which helped classify each pixel into six categories. A total of 92 HRCT images obtained from patients with different diseases were used to validate the quantification system. Two radiologists independently classified lung areas of the same CT images into six patterns using the manual drawing function of dedicated software. Agreement between the automated system and the readers and between the two individual readers was assessed. Results: The overall accuracy of the system to classify each disease pattern based on the typical ROIs was 89%. When the quantification results were examined, the average agreement between the system and each radiologist was 52% and 49%, respectively. The agreement between the two radiologists was 67%. Conclusion: An automated quantification system for various regional patterns of diffuse interstitial lung diseases can be used for objective and reproducible assessment of disease severity. Objective: This study was designed to develop an automated system for quantification of various regional disease patterns of diffuse lung diseases as depicted on high-resolution computed tomography (HRCT) and to compare the performance of the automated system with human readers. Materials and Methods: A total of 600 circular regions-of-interest (ROIs), 10 pixels in diameter, were utilized. The 600 ROIs comprised 100 ROIs that represented six typical regional patterns (normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation). The ROIs were used to train the automated classification system based on the use of a Support Vector Machine classifier and 37 features of texture and shape. The performance of the classification system was tested with a 5-fold cross-validation method. An automated quantification system was developed with a moving ROI in the lung area, which helped classify each pixel into six categories. A total of 92 HRCT images obtained from patients with different diseases were used to validate the quantification system. Two radiologists independently classified lung areas of the same CT images into six patterns using the manual drawing function of dedicated software. Agreement between the automated system and the readers and between the two individual readers was assessed. Results: The overall accuracy of the system to classify each disease pattern based on the typical ROIs was 89%. When the quantification results were examined, the average agreement between the system and each radiologist was 52% and 49%, respectively. The agreement between the two radiologists was 67%. Conclusion: An automated quantification system for various regional patterns of diffuse interstitial lung diseases can be used for objective and reproducible assessment of disease severity.

Development and Validation of a Simple Index Based on Non-Enhanced CT and Clinical Factors for Prediction of Non-Alcoholic Fatty Liver Disease

안유라,윤성철,이승수,손정희,조소라,변지은,성유섭,김호성,유은실 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.4

Objective: A widely applicable, non-invasive screening method for non-alcoholic fatty liver disease (NAFLD) is needed. We aimed to develop and validate an index combining computed tomography (CT) and routine clinical data for screening for NAFLD in a large cohort of adults with pathologically proven NAFLD. Materials and Methods: This retrospective study included 2218 living liver donors who had undergone liver biopsy and CT within a span of 3 days. Donors were randomized 2:1 into development and test cohorts. CTL-S was measured by subtracting splenic attenuation from hepatic attenuation on non-enhanced CT. Multivariable logistic regression analysis of the development cohort was utilized to develop a clinical-CT index predicting pathologically proven NAFLD. The diagnostic performance was evaluated by analyzing the areas under the receiver operating characteristic curve (AUC). The cutoffs for the clinical-CT index were determined for 90% sensitivity and 90% specificity in the development cohort, and their diagnostic performance was evaluated in the test cohort. Results: The clinical-CT index included CTL-S, body mass index, and aspartate transaminase and triglyceride concentrations. In the test cohort, the clinical-CT index (AUC, 0.81) outperformed CTL-S (0.74; p < 0.001) and clinical indices (0.73–0.75; p < 0.001) in diagnosing NAFLD. A cutoff of ≥ 46 had a sensitivity of 89% and a specificity of 41%, whereas a cutoff of ≥ 56.5 had a sensitivity of 57% and a specificity of 89%. Conclusion: The clinical-CT index is more accurate than CTL-S and clinical indices alone for the diagnosis of NAFLD and may be clinically useful in screening for NAFLD.