• Korean Journal of Radiology
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• v.22 no.6
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• pp.959-969
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• 2021

Objective: This study aimed to evaluate the role of preoperative two-dimensional (2D) shear wave elastography (SWE) in assessing the stages of liver fibrosis in patients with suspected biliary atresia (BA) and compared its diagnostic performance with those of serum fibrosis biomarkers. Materials and Methods: This study was approved by the ethical committee, and written informed parental consent was obtained. Two hundred and sixteen patients were prospectively enrolled between January 2012 and October 2018. The 2D SWE measurements of 69 patients have been previously reported. 2D SWE measurements, serum fibrosis biomarkers, including fibrotic markers and biochemical test results, and liver histology parameters were obtained. 2D SWE values, serum biomarkers including, aspartate aminotransferase to platelet ratio index (APRi), and other serum fibrotic markers were correlated with the stages of liver fibrosis by METAVIR. Receiver operating characteristic (ROC) curves and area under the ROC (AUROC) curve analyses were used. Results: The correlation coefficient of 2D SWE value in correlation with the stages of liver fibrosis was 0.789 (p < 0.001). The cut-off values of 2D SWE were calculated as 9.1 kPa for F1, 11.6 kPa for F2, 13.0 kPa for F3, and 15.7 kPa for F4. The AUROCs of 2D SWE in the determination of the stages of liver fibrosis ranged from 0.869 to 0.941. The sensitivity and negative predictive value of 2D SWE in the diagnosis of ≥ F3 was 93.4% and 96.0%, respectively. The diagnostic performance of 2D SWE was superior to that of APRi and other serum fibrotic markers in predicting severe fibrosis and cirrhosis (all p < 0.005) and other serum biomarkers. Multivariate analysis showed that the 2D SWE value was the only statistically significant parameter for predicting liver fibrosis. Conclusion: 2D SWE is a more effective non-invasive tool for predicting the stage of liver fibrosis in patients with suspected BA, compared with serum fibrosis biomarkers.

• The Korean Society of Law and Medicine
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• v.25 no.1
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• pp.149-192
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• 2024

People with mental illness are generally either unaware of their illness or unwilling to voluntarily seek treatment, which makes treatment difficult and the pain mainly passed on to their families. Accordingly, non-face-to-face treatment, in which the patient is diagnosed by interviews with the family and unannounced medication, in which medication is secretly administered through the family, can be performed, and this has been considered a necessary evil. Even considering realistic aspects such as the special nature of mental health care and families' suffer, not-informed treatment without consent violates not only medical laws, but also human rights of mentally ill patients. Above all, if the patient finds out about this late, the trust between the patient, family, and doctor is completely broken, and a treatment is absolutely refused. Japan's Chiba decision, which presents exceptional conditions for allowance might be a solution. However, it would not be a right solution, considering that it could lead to long-term unannounced medication and completely cut off treatment through therapeutic dialogue. Ultimately, it need to approach this problem and seek alternatives through restoration of therapeutic dialogue.

• Clinical and Experimental Vaccine Research
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• v.12 no.1
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• pp.25-31
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• 2023

Purpose: Since late 2019, the novel coronavirus disease has been a global concern, and alongside preventive strategies, including social distancing and personal hygiene, vaccination is now the primary hope for controlling the pandemic. Sputnik V is an adenovirus vector vaccine used against coronavirus disease 2019 (COVID-19) among Iranian health care providers, and there is a lack of information regarding the Adverse Events Following Immunisation (AEFI) by Sputnik V among the Iranian population. The present study aimed to evaluate AEFI by Sputnik V vaccine among Iranian population. Materials and Methods: Every member of the Islamic Republic of Iran Medical Council received their first dose of the Sputnik V vaccine in Mashhad (Iran) and was referred to receive their second dose enrolled in the present study and asked to fill an English language checklist asking about development of any AEFI following immunization with the first dose of Sputnik V vaccine. Results: A total number of 1,347 with a mean±standard deviation age of 56.2±9.6 years filled the checklist. Most of the participants were male (838 [62.2%]). The present study demonstrated that immunization with the first dose of Sputnik V results in at least one AEFI in 32.8% of the Iranian medical council members. Most of the AEFI was related to musculoskeletal symptoms, including myalgia. By considering the age of 55 years as a cut-off point, individuals younger than 55 had a higher rate of AEFI (41.3% vs. 22.5%, p=0.0001). Male gender, use of analgesics, beta-blockers, and previous COVID-19 infection have a lower chance of developing AEFI (p<0.05). Conclusion: The present study demonstrated that most of the AEFI was related to musculoskeletal symptoms, including myalgia, and older individuals, male gender and those receiving analgesics and beta-blockers were less likely to develop AEFI following immunization with the first dose of Sputnik V.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.610-619
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• 2020

Purpose The study aimed to investigate the role of Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) in predicting incidental prostate cancer (PCa) or urothelial carcinoma (UCa) extension in urinary bladder (UB) cancer patients. Materials and Methods A total of 72 UB cancer patients who underwent radical cystoprostatectomy and 3 Tesla multiparametric MRI before surgery were enrolled. PI-RADS v2 ratings were assigned by two independent radiologists. All prostate specimens were examined by a single pathologist. We compared the multiparametric MRI findings rated using PI-RADS v2 with the pathologic data. Results Of the 72 UB cancer patients, 29 had incidental PCa (40.3%) and 20 showed UCa extension (27.8%), with an overlap for 3 patients. With a score of 4 as the cut-off value for predicting incidental PCa, the diagnostic accuracy was 65.3%, specificity was 90.7%, and positive predictive value (PPV) was 66.7%. The diagnostic accuracy for incidental UCa extension was 47.2%, specificity was 92.3%, and PPV was 83.3%. Conclusion Despite the low diagnostic accuracy, the PPV and specificity were relatively high. Therefore, PI-RADS v2 scores of 1, 2, or 3 may help exclude the probability of incidental PCa or UCa extension.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.1009-1018
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• 2022

Objective: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment. Materials and Methods: This retrospective simulation study was conducted using the CXRs of 5887 adults (mean age ± standard deviation, 55.4 ± 11.8 years; male, 4329) from three health screening centers in South Korea using a commercial AI (Lunit INSIGHT CXR3, version 3.5.8.8). Three board-certified thoracic radiologists reviewed CXR images for referable thoracic abnormalities and grouped the images into those with visible referable abnormalities (identified as abnormal by at least one reader) and those with clearly visible referable abnormalities (identified as abnormal by at least two readers). With AI-based simulated exclusion of normal CXR images, the percentages of normal images sorted and abnormal images erroneously removed were analyzed. Additionally, in a random subsample of 480 patients, the ability to identify visible referable abnormalities was compared among AI-unassisted reading (i.e., all images read by human readers without AI), AI-assisted reading (i.e., all images read by human readers with AI assistance as concurrent readers), and reading with AI triage (i.e., human reading of only those rendered abnormal by AI). Results: Of 5887 CXR images, 405 (6.9%) and 227 (3.9%) contained visible and clearly visible abnormalities, respectively. With AI-based triage, 42.9% (2354/5482) of normal CXR images were removed at the cost of erroneous removal of 3.5% (14/405) and 1.8% (4/227) of CXR images with visible and clearly visible abnormalities, respectively. In the diagnostic performance study, AI triage removed 41.6% (188/452) of normal images from the worklist without missing visible abnormalities and increased the specificity for some readers without decreasing sensitivity. Conclusion: This study suggests the feasibility of sorting and removing normal CXRs using AI with a tailored cut-off to increase efficiency and reduce the workload of radiologists.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.77-88
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• 2022

Objective: Our study aimed to evaluate the quality of radiomics studies on brain metastases based on the radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, and the Image Biomarker Standardization Initiative (IBSI) guidelines. Materials and Methods: PubMed MEDLINE, and EMBASE were searched for articles on radiomics for evaluating brain metastases, published until February 2021. Of the 572 articles, 29 relevant original research articles were included and evaluated according to the RQS, TRIPOD checklist, and IBSI guidelines. Results: External validation was performed in only three studies (10.3%). The median RQS was 3.0 (range, -6 to 12), with a low basic adherence rate of 50.0%. The adherence rate was low in comparison to the "gold standard" (10.3%), stating the potential clinical utility (10.3%), performing the cut-off analysis (3.4%), reporting calibration statistics (6.9%), and providing open science and data (3.4%). None of the studies involved test-retest or phantom studies, prospective studies, or cost-effectiveness analyses. The overall rate of adherence to the TRIPOD checklist was 60.3% and low for reporting title (3.4%), blind assessment of outcome (0%), description of the handling of missing data (0%), and presentation of the full prediction model (0%). The majority of studies lacked pre-processing steps, with bias-field correction, isovoxel resampling, skull stripping, and gray-level discretization performed in only six (20.7%), nine (31.0%), four (3.8%), and four (13.8%) studies, respectively. Conclusion: The overall scientific and reporting quality of radiomics studies on brain metastases published during the study period was insufficient. Radiomics studies should adhere to the RQS, TRIPOD, and IBSI guidelines to facilitate the translation of radiomics into the clinical field.

• Korean Journal of Radiology
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• v.20 no.4
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• pp.621-630
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• 2019

Objective: To study the prevalence and clinical characteristics of decreased myocardial blood flow (MBF) quantified by dynamic computed tomography (CT) myocardial perfusion imaging (MPI) in symptomatic patients without in-stent restenosis. Materials and Methods: Thirty-seven (mean age, 71.3 ± 10 years; age range, 48-88 years; 31 males, 6 females) consecutive symptomatic patients with patent coronary stents and without obstructive de novo lesions were prospectively enrolled to undergo dynamic CT-MPI using a third-generation dual-source CT scanner. The shuttle-mode acquisition technique was used to image the complete left ventricle. A bolus of contrast media (50 mL; iopromide, 370 mg iodine/mL) was injected into the antecubital vein at a rate of 6 mL/s, followed by a 40-mL saline flush. The mean MBF value and other quantitative parameters were measured for each segment of both stented-vessel territories and reference territories. The MBF_ratio was defined as the ratio of the mean MBF value of the whole stent-vessel territory to that of the whole reference territory. An MBF_ratio of 0.85 was used as the cut-off value to distinguish hypoperfused from non-hypoperfused segments. Results: A total of 629 segments of 37 patients were ultimately included for analysis. The mean effective dose of dynamic CT-MPI was 3.1 ± 1.2 mSv (range, 1.7-6.3 mSv). The mean MBF of stent-vessel territories was decreased in 19 lesions and 81 segments. Compared to stent-vessel territories without hypoperfusion, the mean MBF and myocardial blood volume were markedly lower in hypoperfused stent-vessel territories (77.5 ± 16.6 mL/100 mL/min vs. 140.4 ± 24.1 mL/100 mL/min [p < 0.001] and 6.4 ± 3.7 mL/100 mL vs. 11.5 ± 4 mL/100 mL [p < 0.001, respectively]). Myocardial hypoperfusion in stentvessel territories was present in 48.6% (18/37) of patients. None of clinical parameters differed statistically significantly between hypoperfusion and non-hypoperfusion subgroups. Conclusion: Decreased MBF is commonly present in patients who are symptomatic after percutaneous coronary intervention, despite patent stents and can be detected by dynamic CT-MPI using a low radiation dose.

• Journal of Veterinary Clinics
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• v.40 no.6
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• pp.399-407
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• 2023

Chronic kidney disease (CKD) occurs in more than 15% of the dogs over 10 years of age and causes irreversible renal function deterioration. Therefore, it is important to diagnose CKD early and treat the disease properly. The purpose of this study aimed to to evaluate the clinical utility of urine albumin/creatinine ratio (ACR) using POC (point-of-care) device as an early detection urinary biomarker in CKD dogs and to confirm the correlation between ACR and other known CKD biomarkers. Urine and serum samples were obtained from 50 healthy dogs and 50 dogs with CKD. Serum blood urea nitrogen (BUN), creatinine, and symmetric dimethylarginine (SDMA) concentrations, and urine protein creatinine ratio (UPC) were measured. Urine specific gravity (USG) was evaluated using refractometer, and ACR was measured using an i-SENS A1Care analyzer. The ACR values of dogs with CKD were significantly different from those of healthy dogs (p < 0.001), as with other renal biomarkers. ACR showed significant differences between healthy dogs and dogs with CKD at every IRIS stage (p < 0.005), whereas no significant differences were observed between dogs with CKD IRIS stage I and healthy dogs with UPC. There are significant positive correlation between ACR and BUN (r = 0.611, p < 0.001), creatinine (r = 0.788, p < 0.001), SDMA (r = 0.747, p < 0.001), and UPC (r = 0.784, p < 0.001), and significant negative correlation between ACR and USG (r = -0.700, p < 0.001). In receiver operator characteristic curve analysis, the area under the curve (AUC) was 0.982 (95% CI 0.963-1.000, p < 0.001), with an optimal cut-off value of 64.20 mg/g (94% sensitivity and 94% specificity). Thus, ACR is a useful urinary biomarker for the early diagnosis of proteinuria in CKD and combined use of ACR and other renal biomarkers may be helpful for early diagnosis and prevention of CKD in dogs.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.859-868
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• 2020

Objective: To investigate the value of initial CT quantitative analysis of ground-glass opacity (GGO), consolidation, and total lesion volume and its relationship with clinical features for assessing the severity of coronavirus disease 2019 (COVID-19). Materials and Methods: A total of 84 patients with COVID-19 were retrospectively reviewed from January 23, 2020 to February 19, 2020. Patients were divided into two groups: severe group (n = 23) and non-severe group (n = 61). Clinical symptoms, laboratory data, and CT findings on admission were analyzed. CT quantitative parameters, including GGO, consolidation, total lesion score, percentage GGO, and percentage consolidation (both relative to total lesion volume) were calculated. Relationships between the CT findings and laboratory data were estimated. Finally, a discrimination model was established to assess the severity of COVID-19. Results: Patients in the severe group had higher baseline neutrophil percentage, increased high-sensitivity C-reactive protein (hs-CRP) and procalcitonin levels, and lower baseline lymphocyte count and lymphocyte percentage (p < 0.001). The severe group also had higher GGO score (p < 0.001), consolidation score (p < 0.001), total lesion score (p < 0.001), and percentage consolidation (p = 0.002), but had a lower percentage GGO (p = 0.008). These CT quantitative parameters were significantly correlated with laboratory inflammatory marker levels, including neutrophil percentage, lymphocyte count, lymphocyte percentage, hs-CRP level, and procalcitonin level (p < 0.05). The total lesion score demonstrated the best performance when the data cut-off was 8.2%. Furthermore, the area under the curve, sensitivity, and specificity were 93.8% (confidence interval [CI]: 86.8-100%), 91.3% (CI: 69.6-100%), and 91.8% (CI: 23.0-98.4%), respectively. Conclusion: CT quantitative parameters showed strong correlations with laboratory inflammatory markers, suggesting that CT quantitative analysis might be an effective and important method for assessing the severity of COVID-19, and may provide additional guidance for planning clinical treatment strategies.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.