• 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.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1317-1325
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• 2020

Objective: The aim of this study was to prospectively evaluate whether liver stiffness (LS) assessments, obtained by two-dimensional (2D)-shear wave elastography (SWE) with a propagation map, can evaluate liver fibrosis stage using histopathology as the reference standard. Materials and Methods: We prospectively enrolled 123 patients who had undergone percutaneous liver biopsy from two tertiary referral hospitals. All patients underwent 2D-SWE examination prior to biopsy, and LS values (kilopascal [kPa]) were obtained. On histopathologic examination, fibrosis stage (F0-F4) and necroinflammatory activity grade (A0-A4) were assessed. Multivariate linear regression analysis was performed to determine the significant factors affecting the LS value. The diagnostic performance of the LS value for staging fibrosis was assessed using receiver operating characteristic (ROC) analysis, and the optimal cut-off value was determined by the Youden index. Results: Reliable measurements of LS values were obtained in 114 patients (92.7%, 114/123). LS values obtained from 2D-SWE with the propagation map positively correlated with the progression of liver fibrosis reported from histopathology (p < 0.001). According to the multivariate linear regression analysis, fibrosis stage was the only factor significantly associated with LS (p < 0.001). The area under the ROC curve of LS from 2D-SWE with the propagation map was 0.773, 0.865, 0.946, and 0.950 for detecting F ≥ 1, F ≥ 2, F ≥ 3, and F = 4, respectively. The optimal cut-off LS values were 5.4, 7.8, 9.4, and 12.2 kPa for F ≥ 1, F ≥ 2, F ≥ 3, and F = 4, respectively. The corresponding sensitivity and specificity of the LS value for detecting cirrhosis were 90.9% and 88.4%, respectively. Conclusion: The LS value obtained from 2D-SWE with a propagation map provides excellent diagnostic performance in evaluating liver fibrosis stage, determined by histopathology.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.670-683
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• 2020

Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.620-631
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• 2022

Purpose This study aimed to investigate the diagnostic performance of features suggestive of nodal metastasis on preoperative MRI in patients with invasive breast cancer. Materials and Methods We retrospectively reviewed the preoperative breast MRI of 192 consecutive patients with surgically proven invasive breast cancer. We analyzed MRI findings of axillary lymph nodes with regard to the size, long/short ratio, cortical thickness, shape and margin of the cortex, loss of hilum, asymmetry, signal intensity (SI) on T2-weighted images (T2WI), degree of enhancement in the early phase, and enhancement kinetics. Receiver operating characteristic (ROC) analysis, chi-square test, t test, and McNemar's test were used for statistical analysis. Results Increased shorter diameter, uneven cortical shape, increased cortical thickness, loss of hilum, asymmetry, irregular cortical margin, and low SI on T2WI were significantly suggestive of metastasis. ROC analysis revealed the cutoff value for the shorter diameter and cortical thickness as 8.05 mm and 2.75 mm, respectively. Increased cortical thickness (> 2.75 mm) and uneven cortical shape showed significantly higher sensitivity than other findings in McNemar's test. Irregular cortical margins showed the highest specificity (100%). Conclusion Cortical thickness > 2.75 mm and uneven cortical shape are more sensitive parameters than other findings, and an irregular cortical margin is the most specific parameter for predicting axillary metastasis in patients with invasive breast cancer.

• Korean Journal of Radiology
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• v.25 no.2
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• pp.189-198
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• 2024

Objective: To investigate the prognostic utility of radiomics features extracted from ¹⁸F-fluorodeoxyglucose (FDG) PET/CT combined with clinical factors and metabolic parameters in predicting progression-free survival (PFS) and overall survival (OS) in individuals diagnosed with extranodal nasal-type NK/T cell lymphoma (ENKTCL). Materials and Methods: A total of 126 adults with ENKTCL who underwent ¹⁸F-FDG PET/CT examination before treatment were retrospectively included and randomly divided into training (n = 88) and validation cohorts (n = 38) at a ratio of 7:3. Least absolute shrinkage and selection operation Cox regression analysis was used to select the best radiomics features and calculate each patient's radiomics scores (RadPFS and RadOS). Kaplan-Meier curve and Log-rank test were used to compare survival between patient groups risk-stratified by the radiomics scores. Various models to predict PFS and OS were constructed, including clinical, metabolic, clinical + metabolic, and clinical + metabolic + radiomics models. The discriminative ability of each model was evaluated using Harrell's C index. The performance of each model in predicting PFS and OS for 1-, 3-, and 5-years was evaluated using the time-dependent receiver operating characteristic (ROC) curve. Results: Kaplan-Meier curve analysis demonstrated that the radiomics scores effectively identified high- and low-risk patients (all P < 0.05). Multivariable Cox analysis showed that the Ann Arbor stage, maximum standardized uptake value (SUVmax), and RadPFS were independent risk factors associated with PFS. Further, β2-microglobulin, Eastern Cooperative Oncology Group performance status score, SUVmax, and RadOS were independent risk factors for OS. The clinical + metabolic + radiomics model exhibited the greatest discriminative ability for both PFS (Harrell's C-index: 0.805 in the validation cohort) and OS (Harrell's C-index: 0.833 in the validation cohort). The time-dependent ROC analysis indicated that the clinical + metabolic + radiomics model had the best predictive performance. Conclusion: The PET/CT-based clinical + metabolic + radiomics model can enhance prognostication among patients with ENKTCL and may be a non-invasive and efficient risk stratification tool for clinical practice.

• Korean Journal of Radiology
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• v.23 no.8
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• pp.811-820
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• 2022

Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825-0.910) in the training cohort and 0.890 (0.844-0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcomes.

• Korean Journal of Radiology
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• v.23 no.6
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• pp.664-673
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• 2022

Objective: To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction. Materials and Methods: A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test. Results: Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013). Conclusion: An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.

• Korean Journal of Radiology
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• v.23 no.2
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• pp.180-188
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• 2022

Objective: To validate the performance of 3T spin-echo echo-planar imaging (SE-EPI) magnetic resonance elastography (MRE) for staging hepatic fibrosis in a large population, using surgical specimens as the reference standard. Materials and Methods: This retrospective study initially included 310 adults (155 undergoing hepatic resection and 155 undergoing donor hepatectomy) with histopathologic results from surgical liver specimens. They underwent 3T SE-EPI MRE ≤ 3 months prior to surgery. Demographic findings, underlying liver disease, and hepatic fibrosis pathologic stage according to METAVIR were recorded. Liver stiffness (LS) was measured by two radiologists, and inter-reader reproducibility was evaluated using the intraclass correlation coefficient (ICC). The mean LS of each fibrosis stage (F0-F4) was calculated in total and for each etiologic subgroup. Comparisons among subgroups were performed using the Kruskal-Wallis test and Conover post-hoc test. The cutoff values for fibrosis staging were estimated using receiver operating characteristic (ROC) curve analysis. Results: Inter-reader reproducibility was excellent (ICC, 0.98; 95% confidence interval, 0.97-0.99). The mean LS values were 1.91, 2.41, 3.24, and 5.41 kPa in F0-F1 (n = 171), F2 (n = 26), F3 (n = 38), and F4 (n = 72), respectively. The discriminating cutoff values for diagnosing ≥ F2, ≥ F3, and F4 were 2.18, 2.71, and 3.15 kPa, respectively, with the ROC curve areas of 0.97-0.98 (sensitivity 91.2%-95.9%, specificity 90.7%-99.0%). The mean LS was significantly higher in patients with cirrhosis (F4) of nonviral causes, such as primary biliary cirrhosis (9.56 kPa) and alcoholic liver disease (7.17 kPa) than in those with hepatitis B or C cirrhosis (4.28 and 4.92 kPa, respectively). There were no statistically significant differences in LS among the different etiologic subgroups in the F0-F3 stages. Conclusion: The 3T SE-EPI MRE demonstrated high interobserver reproducibility, and our criteria for staging hepatic fibrosis showed high diagnostic performance. LS was significantly higher in patients with non-viral cirrhosis than in those with viral cirrhosis.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.89-100
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• 2022

Objective: To improve the N biomarker in the amyloid/tau/neurodegeneration system by radiomics and study its value for predicting cognitive progression in individuals with mild cognitive impairment (MCI). Materials and Methods: A group of 147 healthy controls (HCs) (72 male; mean age ± standard deviation, 73.7 ± 6.3 years), 197 patients with MCI (114 male; 72.2 ± 7.1 years), and 128 patients with Alzheimer's disease (AD) (74 male; 73.7 ± 8.4 years) were included. Optimal A, T, and N biomarkers for discriminating HC and AD were selected using receiver operating characteristic (ROC) curve analysis. A radiomics model containing comprehensive information of the whole cerebral cortex and deep nuclei was established to create a new N biomarker. Cerebrospinal fluid (CSF) biomarkers were evaluated to determine the optimal A or T biomarkers. All MCI patients were followed up until AD conversion or for at least 60 months. The predictive value of A, T, and the radiomics-based N biomarker for cognitive progression of MCI to AD were analyzed using Kaplan-Meier estimates and the log-rank test. Results: The radiomics-based N biomarker showed an ROC curve area of 0.998 for discriminating between AD and HC. CSF Aβ42 and p-tau proteins were identified as the optimal A and T biomarkers, respectively. For MCI patients on the Alzheimer's continuum, isolated A+ was an indicator of cognitive stability, while abnormalities of T and N, separately or simultaneously, indicated a high risk of progression. For MCI patients with suspected non-Alzheimer's disease pathophysiology, isolated T+ indicated cognitive stability, while the appearance of the radiomics-based N+ indicated a high risk of progression to AD. Conclusion: We proposed a new radiomics-based improved N biomarker that could help identify patients with MCI who are at a higher risk for cognitive progression. In addition, we clarified the value of a single A/T/N biomarker for predicting the cognitive progression of MCI.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1260-1268
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• 2022

Objective: To propose standardized MRI-proton density fat fraction (PDFF) cutoff values for diagnosing hepatic steatosis, evaluated using contemporary PDFF measuring methods in a large population of healthy adults, using histologic fat fraction (HFF) as the reference standard. Materials and Methods: A retrospective search of electronic medical records between 2015 and 2018 identified 1063 adult donor candidates for liver transplantation who had undergone liver MRI and liver biopsy within a 7-day interval. Patients with a history of liver disease or significant alcohol consumption were excluded. Chemical shift imaging-based MRI (CS-MRI) PDFF and high-speed T2-corrected multi-echo MR spectroscopy (HISTO-MRS) PDFF data were obtained. By temporal splitting, the total population was divided into development and validation sets. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of the MRI-PDFF method. Two cutoff values with sensitivity > 90% and specificity > 90% were selected to rule-out and rule-in, respectively, hepatic steatosis with reference to HFF ≥ 5% in the development set. The diagnostic performance was assessed using the validation set. Results: Of 921 final participants (624 male; mean age ± standard deviation, 31.5 ± 9.0 years), the development and validation sets comprised 497 and 424 patients, respectively. In the development set, the areas under the ROC curve for diagnosing hepatic steatosis were 0.920 for CS-MRI-PDFF and 0.915 for HISTO-MRS-PDFF. For ruling-out hepatic steatosis, the CS-MRI-PDFF cutoff was 2.3% (sensitivity, 92.4%; specificity, 63.0%) and the HISTO-MRI-PDFF cutoff was 2.6% (sensitivity, 88.8%; specificity, 70.1%). For ruling-in hepatic steatosis, the CS-MRI-PDFF cutoff was 3.5% (sensitivity, 73.5%; specificity, 88.6%) and the HISTO-MRI-PDFF cutoff was 4.0% (sensitivity, 74.7%; specificity, 90.6%). Conclusion: In a large population of healthy adults, our study suggests diagnostic thresholds for ruling-out and ruling-in hepatic steatosis defined as HFF ≥ 5% by contemporary PDFF measurement methods.