• 대한한의학방제학회지
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• 제31권3호
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• pp.133-144
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• 2023

Ureteral obstruction can be causes of renal dysfunction and renal injury at late period of kidney pathology. The purpose of this study was to determine the protective effects of Oryeongsan (ORS), Geumgwe-sinkihwan (GSH), and Jwagwieum (JGE) in rats with unilateral ureteral obstruction (UUO). The animal models were divided into five groups randomly at the age of 5 weeks; Control group: SD male rats (n=10), UUO group: SD male rats with UUO surgery (n=10), ORS group: SD male rats with UUO surgery + ORS 200 mg/kg/day (n=10), GSH group: SD male rats with UUO surgery + GSH 200 mg/kg/day (n=10), JGE group: SD male rats with UUO surgery + JGE 200 mg/kg/day (n=10). Treatment with ORS, GSH, and JGE significantly ameliorate creatinine clearance(Ccr). The present results also showed that ORS, GSH, and JGE improved the morphological aspects of renal tissues. These prescriptions also reduced the expression levels of cytokines such as TNF-α, IL-1β, and IL-6. In Kidney, UUO increased the expression levels of inflamasome markers such as NLRP3, ASC, and Caspase-1. However, ORS, GSH, and JGE suppressed these levele. Treatment with these prescriptions reduced kidney inflammation markers such as Neutrophil Gelatinase Associated Lipocalin (NGAL) and kidney injury molecule -1 (KIM-1). Therefore, these findings suggest that ORS, GSH, and JGE has a protective effect on renal injury by alleviating renal inflammation and improving renal function in rats with UUO.

• 대한치과교정학회지
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• 제52권2호
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• pp.150-160
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• 2022

Objective: To provide reliable prediction models based on dentoskeletal and soft tissue variables for customizing maxillary incisor positions and to optimize digitalized orthodontic treatment planning. Methods: This study included 244 Chinese women (age, 18-40 years old) with esthetic profiles after orthodontic treatment with fixed appliances (133 in group I: 1° ≤ The angle between the nasion [N]-A point [A] plane and the N-B point [B] plane [ANB] ≤ 4°; 111 in group II: 4° < ANB ≤ 7°). Dental, skeletal, and soft tissue measurements were performed on lateral cephalograms of the participants. Correlation and multiple linear regression analyses were used to determine the influence of dentoskeletal and soft tissue variables on maxillary incisor position. Results: The ideal anteroposterior position of the maxillary incisor varied between sagittal skeletal patterns. The position of the maxillary incisor correlated with the sagittal discrepancy between the maxilla and the mandible (ANB), protrusion of the midface, nasal tip projection, development of the chin, and inclination of both the maxillary and mandibular incisors. Distance from the maxillary central incisor to nasion-pogonion plane predicted using multiple linear regression analysis was accurate and could be a practical measurement in orthodontic treatment planning. Conclusions: Instead of using an average value or norm, orthodontists should customize a patient's ideal maxillary incisor position using dentoskeletal and soft tissue evaluations.

• 한국방사선학회논문지
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• 제17권3호
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• pp.423-431
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• 2023

본 연구의 목적은 환자의 신체정보와 인공지능 기법을 활용하여 부작용에 영향을 미치는 인자들을 분석하고 조영제 부작용의 정도를 예측하여 이를 완화하는 기초자료로 활용되고자 한다. 연구에 사용한 데이터는 서울 소재 종합병원의 검진을 시행한 CT 검사 58,000건 중 조영제 부작용이 발생한 1,235건 중 과거력 조사에서 조영제 부작용이 없었던 606명의 검사자를 대상자로 하였다. 606개 샘플 중 70%는 훈련 셋으로 사용하고 나머지 30%는 검증을 위한 테스트 셋으로 사용하였다. 나이, BMI(Body Mass Index), GFR(Glomerular Filtration Rate), BUN(Blood Urea Nitrogen), GGT(Gamma Glutamyl Transgerase), AST(Aspartate Amino Transferase,), and ALT(Alanine Amiono Transferase)의 feature를 독립변수로 조영제 중증도를 목표변수로 사용하였다. AdaBoost, Tree, Neural network, SVM, Random foest 알고리즘을 통해 AUC(Area under curve), CA(Classification Accuracy), F1, Precision, Recall을 파악하였다. 분류 예측에 사용된 알고리즘 중 가장 높은 평가지표를 나타내 것은 AdaBoost와 Random Forest이다. 모든 모델의 예측에서 가장 큰 요인은 GFR, BMI, GGT 이였다. 이는 신장 여과 기능, 비만에 따라 주입되는 조영제 양의 차이와 대사증후군의 여부에 따라 조영제 부작용 중증도에 영향을 미치는 것을 알 수 있었다.

• Korean Journal of Radiology
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• 제22권12호
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• pp.1985-1995
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• 2021

Objective: Although the liver-to-spleen volume ratio (LSVR) based on CT reflects portal hypertension, its prognostic role in cirrhotic patients has not been proven. We evaluated the utility of LSVR, automatically measured from CT images using a deep learning algorithm, as a predictor of hepatic decompensation and transplantation-free survival in patients with hepatitis B viral (HBV)-compensated cirrhosis. Materials and Methods: A deep learning algorithm was used to measure the LSVR in a cohort of 1027 consecutive patients (mean age, 50.5 years; 675 male and 352 female) with HBV-compensated cirrhosis who underwent liver CT (2007-2010). Associations of LSVR with hepatic decompensation and transplantation-free survival were evaluated using multivariable Cox proportional hazards and competing risk analyses, accounting for either the Child-Pugh score (CPS) or Model for End Stage Liver Disease (MELD) score and other variables. The risk of the liver-related events was estimated using Kaplan-Meier analysis and the Aalen-Johansen estimator. Results: After adjustment for either CPS or MELD and other variables, LSVR was identified as a significant independent predictor of hepatic decompensation (hazard ratio for LSVR increase by 1, 0.71 and 0.68 for CPS and MELD models, respectively; p < 0.001) and transplantation-free survival (hazard ratio for LSVR increase by 1, 0.8 and 0.77, respectively; p < 0.001). Patients with an LSVR of < 2.9 (n = 381) had significantly higher 3-year risks of hepatic decompensation (16.7% vs. 2.5%, p < 0.001) and liver-related death or transplantation (10.0% vs. 1.1%, p < 0.001) than those with an LSVR ≥ 2.9 (n = 646). When patients were stratified according to CPS (Child-Pugh A vs. B-C) and MELD (< 10 vs. ≥ 10), an LSVR of < 2.9 was still associated with a higher risk of liver-related events than an LSVR of ≥ 2.9 for all Child-Pugh (p ≤ 0.045) and MELD (p ≤ 0.009) stratifications. Conclusion: The LSVR measured on CT can predict hepatic decompensation and transplantation-free survival in patients with HBV-compensated cirrhosis.

• Korean Journal of Radiology
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• 제22권3호
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• pp.476-488
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• 2021

Objective: We aimed to develop a deep neural network for segmenting lung parenchyma with extensive pathological conditions on non-contrast chest computed tomography (CT) images. Materials and Methods: Thin-section non-contrast chest CT images from 203 patients (115 males, 88 females; age range, 31-89 years) between January 2017 and May 2017 were included in the study, of which 150 cases had extensive lung parenchymal disease involving more than 40% of the parenchymal area. Parenchymal diseases included interstitial lung disease (ILD), emphysema, nontuberculous mycobacterial lung disease, tuberculous destroyed lung, pneumonia, lung cancer, and other diseases. Five experienced radiologists manually drew the margin of the lungs, slice by slice, on CT images. The dataset used to develop the network consisted of 157 cases for training, 20 cases for development, and 26 cases for internal validation. Two-dimensional (2D) U-Net and three-dimensional (3D) U-Net models were used for the task. The network was trained to segment the lung parenchyma as a whole and segment the right and left lung separately. The University Hospitals of Geneva ILD dataset, which contained high-resolution CT images of ILD, was used for external validation. Results: The Dice similarity coefficients for internal validation were 99.6 ± 0.3% (2D U-Net whole lung model), 99.5 ± 0.3% (2D U-Net separate lung model), 99.4 ± 0.5% (3D U-Net whole lung model), and 99.4 ± 0.5% (3D U-Net separate lung model). The Dice similarity coefficients for the external validation dataset were 98.4 ± 1.0% (2D U-Net whole lung model) and 98.4 ± 1.0% (2D U-Net separate lung model). In 31 cases, where the extent of ILD was larger than 75% of the lung parenchymal area, the Dice similarity coefficients were 97.9 ± 1.3% (2D U-Net whole lung model) and 98.0 ± 1.2% (2D U-Net separate lung model). Conclusion: The deep neural network achieved excellent performance in automatically delineating the boundaries of lung parenchyma with extensive pathological conditions on non-contrast chest CT images.

• Korean Journal of Radiology
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• 제22권7호
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• pp.1066-1076
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• 2021

Objective: To evaluate the performance of the 2018 Korean Liver Cancer Association-National Cancer Center (KLCA-NCC) Practice Guidelines (hereafter, PG) for the diagnosis of hepatocellular carcinoma (HCC) using gadoxetic acid-enhanced MRI, compared to the Liver Imaging-Reporting and Data System (LI-RADS) version 2018 (hereafter, v2018). Materials and Methods: From January 2013 to October 2015, treatment-naïve hepatic lesions (≥ 1 cm) on gadoxetic acid-enhanced MRI in consecutive patients with chronic hepatitis B or cirrhosis were retrospectively evaluated. For each lesion, three radiologists independently analyzed the imaging features and classified the lesions into categories according to the 2018 KLCA-NCC PG and LI-RADS v2018. The imaging features and categories were determined by consensus. Generalized estimating equation (GEE) models were used to compare the per-lesion diagnostic performance of the 2018 KLCA-NCC PG and LI-RADS v2018 using the consensus data. Results: In total, 422 lesions (234 HCCs, 45 non-HCC malignancies, and 143 benign lesions) from 387 patients (79% male; mean age, 59 years) were included. In all lesions, the definite HCC (2018 KLCA-NCC PG) had a higher sensitivity and lower specificity than LR-5 (LI-RADS v2018) (87.2% [204/234] vs. 80.8% [189/234], p < 0.001; 86.2% [162/188] vs. 91.0% [171/188], p = 0.002). However, in lesions of size ≥ 2 cm, the definite HCC had a higher sensitivity than the LR-5 (86.8% [164/189] vs. 82.0 (155/189), p = 0.002) without a reduction in the specificity (80.0% [48/60] vs. 83.3% [50/60], p = 0.15). In all lesions, the sensitivity and specificity of the definite/probable HCC (2018 KLCA-NCC PG) and LR-5/4 did not differ significantly (89.7% [210/234] vs. 91.5% [214/234], p = 0.204; 83.5% [157/188] vs. 79.3% [149/188], p = 0.071). Conclusion: For the diagnosis of HCC of size ≥ 2 cm, the definite HCC (2018 KLCA-NCC PG) had a higher sensitivity than LR-5, without a reduction in specificity. The definite/probable HCC (2018 KLCA-NCC PG) had a similar sensitivity and specificity to that those of the LR-5/4.

• Korean Journal of Radiology
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• 제22권4호
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• pp.559-567
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• 2021

Objective: To evaluate the impact of multiparametric magnetic resonance imaging (mpMRI) before confirmatory prostate biopsy in patients under active surveillance (AS). Materials and Methods: This retrospective study included 170 patients with Gleason grade 6 prostate cancer initially enrolled in an AS program between 2011 and 2019. Prostate mpMRI was performed using a 1.5 tesla (T) magnetic resonance imaging system with a 16-channel phased-array body coil. The protocol included T1-weighted, T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging sequences. Uroradiology reports generated by a specialist were based on prostate imaging-reporting and data system (PI-RADS) version 2. Univariate and multivariate analyses were performed based on regression models. Results: The reclassification rate at confirmatory biopsy was higher in patients with suspicious lesions on mpMRI (PI-RADS score ≥ 3) (n = 47) than in patients with non-suspicious mpMRIs (n = 61) and who did not undergo mpMRIs (n = 62) (66%, 26.2%, and 24.2%, respectively; p < 0.001). On multivariate analysis, presence of a suspicious mpMRI finding (PI-RADS score ≥ 3) was associated (adjusted odds ratio: 4.72) with the risk of reclassification at confirmatory biopsy after adjusting for the main variables (age, prostate-specific antigen density, number of positive cores, number of previous biopsies, and clinical stage). Presence of a suspicious mpMRI finding (adjusted hazard ratio: 2.62) was also associated with the risk of progression to active treatment during the follow-up. Conclusion: Inclusion of mpMRI before the confirmatory biopsy is useful to stratify the risk of reclassification during the biopsy as well as to evaluate the risk of progression to active treatment during follow-up.

• Korean Journal of Radiology
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• 제24권5호
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• pp.434-443
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• 2023

Objective: To investigate the association between pelvic bone computed tomography (CT)-derived body composition and patient outcomes in older adult patients who underwent surgery for proximal femur fractures. Materials and Methods: We retrospectively identified consecutive patients aged ≥ 65 years who underwent pelvic bone CT and subsequent surgery for proximal femur fractures between July 2018 and September 2021. Eight CT metrics were calculated from the cross-sectional area and attenuation of the subcutaneous fat and muscle, including the thigh subcutaneous fat (TSF) index, TSF attenuation, thigh muscle (TM) index, TM attenuation, gluteus maximus (GM) index, GM attenuation, gluteus medius and minimus (Gmm) index, and Gmm attenuation. The patients were dichotomized using the median value of each metric. Multivariable Cox regression and logistic regression models were used to determine the association between CT metrics with overall survival (OS) and postsurgical intensive care unit (ICU) admission, respectively. Results: A total of 372 patients (median age, 80.5 years; interquartile range, 76.0-85.0 years; 285 females) were included. TSF attenuation above the median (adjusted hazard ratio [HR], 2.39; 95% confidence interval [CI], 1.41-4.05), GM index below the median (adjusted HR, 2.63; 95% CI, 1.33-5.26), and Gmm index below the median (adjusted HR, 2.33; 95% CI, 1.12-4.55) were independently associated with shorter OS. TSF index (adjusted odds ratio [OR], 6.67; 95% CI, 3.13-14.29), GM index (adjusted OR, 3.45; 95% CI, 1.49-7.69), GM attenuation (adjusted OR, 2.33; 95% CI, 1.02-5.56), Gmm index (adjusted OR, 2.70; 95% CI, 1.22-5.88), and Gmm attenuation (adjusted OR, 2.22; 95% CI, 1.01-5.00) below the median were independently associated with ICU admission. Conclusion: In older adult patients who underwent surgery for proximal femur fracture, low muscle indices of the GM and gluteus medius/minimus obtained from their cross-sectional areas on preoperative pelvic bone CT were significant prognostic markers for predicting high mortality and postsurgical ICU admission.

• Korean Journal of Radiology
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• 제24권2호
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• pp.133-144
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• 2023

Objective: Cyclin-dependent kinase inhibitor (CDKN)2A/B homozygous deletion is a key molecular marker of isocitrate dehydrogenase (IDH)-mutant astrocytomas in the 2021 World Health Organization. We aimed to investigate whether qualitative and quantitative MRI parameters can predict CDKN2A/B homozygous deletion status in IDH-mutant astrocytomas. Materials and Methods: Preoperative MRI data of 88 patients (mean age ± standard deviation, 42.0 ± 11.9 years; 40 females and 48 males) with IDH-mutant astrocytomas (76 without and 12 with CDKN2A/B homozygous deletion) from two institutions were included. A qualitative imaging assessment was performed. Mean apparent diffusion coefficient (ADC), 5th percentile of ADC, mean normalized cerebral blood volume (nCBV), and 95th percentile of nCBV were assessed via automatic tumor segmentation. Logistic regression was performed to determine the factors associated with CDKN2A/B homozygous deletion in all 88 patients and a subgroup of 47 patients with histological grades 3 and 4. The discrimination performance of the logistic regression models was evaluated using the area under the receiver operating characteristic curve (AUC). Results: In multivariable analysis of all patients, infiltrative pattern (odds ratio [OR] = 4.25, p = 0.034), maximal diameter (OR = 1.07, p = 0.013), and 95th percentile of nCBV (OR = 1.34, p = 0.049) were independent predictors of CDKN2A/B homozygous deletion. The AUC, accuracy, sensitivity, and specificity of the corresponding model were 0.83 (95% confidence interval [CI], 0.72-0.91), 90.4%, 83.3%, and 75.0%, respectively. On multivariable analysis of the subgroup with histological grades 3 and 4, infiltrative pattern (OR = 10.39, p = 0.012) and 95th percentile of nCBV (OR = 1.24, p = 0.047) were independent predictors of CDKN2A/B homozygous deletion, with an AUC accuracy, sensitivity, and specificity of the corresponding model of 0.76 (95% CI, 0.60-0.88), 87.8%, 80.0%, and 58.1%, respectively. Conclusion: The presence of an infiltrative pattern, larger maximal diameter, and higher 95th percentile of the nCBV may be useful MRI biomarkers for CDKN2A/B homozygous deletion in IDH-mutant astrocytomas.

• Korean Journal of Radiology
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• 제23권12호
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• pp.1269-1280
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• 2022

Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD). Materials and Methods: We included patients who underwent baseline and 1-year follow-up MRI from a prospective cohort that underwent gadoxetic acid-enhanced MRI for hepatocellular carcinoma surveillance between November 2011 and August 2012 at a tertiary medical center. Baseline liver condition was categorized as non-ACLD, compensated ACLD, and decompensated ACLD. The liver-to-spleen signal intensity ratio (LS-SIR) and liver-to-spleen volume ratio (LS-VR) were automatically measured on the HBP images using a deep learning algorithm, and their percentage changes at the 1-year follow-up (ΔLS-SIR and ΔLS-VR) were calculated. The associations of the MRI indices with hepatic decompensation and a composite endpoint of liver-related death or transplantation were evaluated using a competing risk analysis with multivariable Fine and Gray regression models, including baseline parameters alone and both baseline and follow-up parameters. Results: Our study included 280 patients (153 male; mean age ± standard deviation, 57 ± 7.95 years) with non-ACLD, compensated ACLD, and decompensated ACLD in 32, 186, and 62 patients, respectively. Patients were followed for 11-117 months (median, 104 months). In patients with compensated ACLD, baseline LS-SIR (sub-distribution hazard ratio [sHR], 0.81; p = 0.034) and LS-VR (sHR, 0.71; p = 0.01) were independently associated with hepatic decompensation. The ΔLS-VR (sHR, 0.54; p = 0.002) was predictive of hepatic decompensation after adjusting for baseline variables. ΔLS-VR was an independent predictor of liver-related death or transplantation in patients with compensated ACLD (sHR, 0.46; p = 0.026) and decompensated ACLD (sHR, 0.61; p = 0.023). Conclusion: MRI indices automatically derived from the deep learning analysis of gadoxetic acid-enhanced HBP MRI can be used as prognostic markers in patients with ACLD.