• Korean Journal of Radiology
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• 제22권1호
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• pp.131-138
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• 2021

Objective: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). Materials and Methods: This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. Results: Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). Conclusion: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.

• Journal of Korean Neurosurgical Society
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• 제67권4호
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• pp.451-457
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• 2024

Objective : Exploring protein requirements for critically ill patients has become prominent. On the other hand, considering the significant impact of coma therapy and targeted temperature management (TTM) on the brain as well as systemic metabolisms, protein requirements may plausibly be changed by treatment application. However, there is currently no research on protein requirements following the application of these treatments. Therefore, the aim of this study is to elucidate changes in patients' protein requirements during the application of TTM and coma therapy. Methods : This study is a retrospective analysis of prospectively collected data from March 2019 to May 2022. Among the patients admitted to the intensive care unit, those receiving coma therapy and TTM were included. The patient's treatment period was divided into two phases (phase 1, application and maintenance of coma therapy and TTM; phase 2, tapering and cessation of treatment). In assessing protein requirements, the urine urea nitrogen (UUN) method was employed to estimate the nitrogen balance, offering insight into protein utilization within the body. The patient's protein requirement for each phase was defined as the amount of protein required to achieve a nitrogen balance within ±5, based on the 24-hour collection of UUN. Changes in protein requirements between phases were analyzed. Results : Out of 195 patients, 107 patients with a total of 214 UUN values were included. The mean protein requirement for the entire treatment period was 1.84±0.62 g/kg/day, which is higher than the generally recommended protein supply of 1.2 g/kg/day. As the treatment was tapered, there was a statistically significant increase in the protein requirement from 1.49±0.42 to 2.18±0.60 in phase 2 (p<0.001). Conclusion : Our study revealed a total average protein requirement of 1.84±0.62 g during the treatment period, which falls within the upper range of the preexisting guidelines. Nevertheless, a notable deviation emerged when analyzing the treatment application period separately. Hence, it is recommended to incorporate considerations for the type and timing of treatment, extending beyond the current guideline, which solely accounts for the severity by disease.

• Korean Journal of Radiology
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• 제25권5호
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• pp.414-425
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• 2024

Objective: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct value elements offered by AI, with a specific focus on patient-centered outcomes (PCOs). PCOs are distinguished from traditional clinical outcomes and focus on patient-reported experiences and values such as quality of life, functionality, well-being, physical or emotional status, and convenience. Materials and Methods: We classified the value elements provided by AI into four dimensions: clinical outcomes, economic aspects, organizational aspects, and non-clinical PCOs. The survey comprised three sections: 1) experiences with PCOs in evaluating AI, 2) opinions on the coverage of AI by the National Health Insurance of the Republic of Korea when AI demonstrated benefits across the four value elements, and 3) respondent characteristics. The opinions regarding AI insurance coverage were assessed dichotomously and semi-quantitatively: non-approval (0) vs. approval (on a 1-10 weight scale, with 10 indicating the strongest approval). The survey was conducted from July 4 to 26, 2023, using a web-based method. Responses to PCOs and other value elements were compared. Results: Among 200 respondents, 44 (22%) were patients/patient representatives, 64 (32%) were industry/developers, 60 (30%) were medical practitioners/doctors, and 32 (16%) were government health personnel. The level of experience with PCOs regarding AI was low, with only 7% (14/200) having direct experience and 10% (20/200) having any experience (either direct or indirect). The approval rate for insurance coverage for PCOs was 74% (148/200), significantly lower than the corresponding rates for other value elements (82.5%-93.5%; P ≤ 0.034). The approval strength was significantly lower for PCOs, with a mean weight ± standard deviation of 5.1 ± 3.5, compared to other value elements (P ≤ 0.036). Conclusion: There is currently limited demand for insurance coverage for AI that demonstrates benefits in terms of non-clinical PCOs.

• Korean Journal of Radiology
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• 제23권8호
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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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• 제23권5호
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• pp.548-554
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• 2022

Objective: To evaluate the safety and feasibility of prostatic artery embolization (PAE) via transradial access (TRA) compared with transfemoral access (TFA). Materials and Methods: This retrospective study included 53 consecutive men with lower urinary tract symptoms (LUTS) who underwent PAE between September 2018 and September 2021. Thirty-one patients (mean age ± standard deviation: 70.6 ± 8.4 years) were treated with TFA, including 14 patients treated before adopting TRA. Since December 2019, TRA has also been attempted with the procedure's selection criteria of patent carpal circulation and a height ≤ 172 cm, with 22 patients treated via TRA (69.1 ± 9.6 years). Parameters of technical success (defined as successful bilateral embolization), clinical success (defined as LUTS improvement), procedural time, radiation dose, and adverse events were compared between the two groups using the Fisher's exact test, independent sample t test, Wilcoxon signed-rank test, or Mann-Whitney test. Results: All patients received at least one-side PAE. Technical success of PAE was achieved in most patients (TRA, 21/22; TFA, 30/31; p > 0.999). No technical problem-related conversion from TRA to TFA occurred. The clinical success rate was 85% (11/13) in patients with TRA, and 89% (16/18) in patients with TFA for follow-up > 2 weeks post-PAE (median, 3 months) (p > 0.999). The median procedure time was similar in both groups (TRA, 81 minutes vs. TFA, 94 minutes; p = 0.570). No significant dose differences were found between the TRA and TFA groups in the dose-area product (median Gycm², 95 [range, 44-255] for TRA and 84 [34-255] for TFA; p = 0.678) or cumulative air kerma (median mGy, 609 [236-1584] for TRA and 634 [217-1594] for TFA; p = 0.551). No major adverse events occurred in either of the groups. Conclusion: PAE via TRA is a safe and feasible method comparable to conventional TFA. It can be safely implemented by selecting patients with patent carpal circulation and adequate height.

• Korean Journal of Radiology
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• 제23권12호
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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.

• Korean Journal of Radiology
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• 제23권3호
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• pp.370-380
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• 2022

Objective: To compare pneumonic-type invasive mucinous adenocarcinoma (pIMA) confined to a single lobe with clinical T2, T3, and T4 stage lung cancer without pathological node metastasis regarding survival after curative surgery and to identify prognostic factors for pIMA. Materials and Methods: From January 2010 to December 2017, 41 patients (15 male; mean age ± standard deviation, 66.0 ± 9.9 years) who had pIMA confined to a single lobe on computed tomography (CT) and underwent curative surgery were identified in two tertiary hospitals. Three hundred and thirteen patients (222 male; 66.3 ± 9.4 years) who had non-small cell lung cancer (NSCLC) without pathological node metastasis and underwent curative surgery in one participating institution formed a reference group. Relapse-free survival (RFS) and overall survival (OS) were calculated using the Kaplan-Meier method. Cox proportional hazard regression analysis was performed to identify factors associated with the survival of patients with pIMA. Results: The 5-year RFS and OS rates in patients with pIMA were 33.1% and 56.0%, respectively, compared with 74.3% and 91%, 64.3% and 71.8%, and 46.9% and 49.5% for patients with clinical stage T2, T3, and T4 NSCLC in the reference group, respectively. The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 NSCLC and significantly worse than that of patients with clinical stage T3 NSCLC (p = 0.012). The differences in OS between patients with pIMA and those with clinical stage T3 or T4 NSCLC were not significant (p = 0.11 and p = 0.37, respectively). In patients with pIMA, the presence of separate nodules was a significant factor associated with poor RFS and OS {unadjusted hazard ratio (HR), 4.66 (95% confidence interval [CI], 1.95-11.11), p < 0.001 for RFS; adjusted HR, 4.53 (95% CI, 1.59-12.89), p = 0.005 for OS}. Conclusion: The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 lung cancer. Separate nodules on CT were associated with poor RFS and OS in patients with pIMA.

• 문화기술의 융합
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• 제10권3호
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• pp.313-319
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• 2024

본 연구는 대학생들의 공동체 의식과 심리적 안녕감에서 정서지능의 매개효과를 살펴보고자 하였다. 이에 부산·경남 지역의 대학교에 재학중인 대학생 267명을 대상으로 설문조사를 진행하였다. 자료분석은 SPSS 21 프로그램을 활용하여 조사대상자의 일반적 특성, 주요변인의 평균, 표준편차, 왜도 및 첨도를 확인하였고 주요 변인들간에 다중공선성을 확인하고자 상관관계 분석을 실시하였으며 매개효과를 살펴보기 위해 Barron과 Kenny가 제안한 3단계 검증 방식에 따라 회귀분석을 실시하였다. 본 연구의 결과는 다음과 같다. 첫째, 대학생의 공동체 의식은 심리적 안녕감에 유의미한 영향을 주는 것으로 나타났다. 둘째, 대학생이 인식하는 공동체 의식이 정서지능에 유의미한 영향을 미치는 것으로 나타났다. 셋째, 정서지능이 심리적 안녕감에 유의미한 영향을 주는 것으로 나타났다. 마지막으로 대학생의 공동체 의식과 심리적 안녕감 간의 관계에서 정서지능은 부분 매개 효과가 있는 것으로 확인되었다. 이에 우리는 대학이라는 특수 상황에서 대학생들의 정서지능 기술과 사회적 참여에 밀접한 관련이 있는 공동체 의식을 높이는 다양한 방안을 찾아보고 실행하려는 노력을 통해 대학생들이 보다 행복하고 만족스러운 자신의 삶을 형성하고 지속해 나갈 수 있도록 도와야 할 것이다.

• Journal of Radiation Protection and Research
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• 제6권1호
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• pp.25-30
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• 1981

단일집진법(單一集塵法)을 써서 공기부유진중(空氣浮游塵中)에 존재(存在)하는 라돈 붕괴생성물(崩壞生成物), 즉, RaA, RaB 및 RaC 의 방사능(放射能)(또는 농도(濃度))을 측정(測定)하였다. 이것은 단일집진장치(單一集塵裝置)를 이용하여 평균공격(平均孔隔)(mean pore size)이 $0.8{\mu}m$인 membrane 노지(瀘紙)에 채취(採取)한 시료(試料)의 전(全) 알파방사능(放射能)을 시차별(時差別)로 측정(測定)한 후 그 결과(結果)로부터 라돈 붕괴생성물(崩壞生成物)의 농도(濃度)를 Ci 또는 WL(working level) 단위(單位)로 산출(算出)하는 방법(方法)이다. 여기서는 농도외(濃度外)에도 농도치(濃度値)의 표준편차(標準偏差) 및 라돈 붕괴생성물(崩壞生成物)의 방사평형상태(放射平衡狀態)를 나타내는 방사평형인자(放射平衡因子)와 방사평형비(放射平衡比)를 구(求)하였다. Ci 및 WL단위(單位)로 주어진 라돈 붕괴생성물(崩壞生成物)의 농도(濃度)는 실험기간중(實驗期間中) 각각 $0.30{\sim}2.36pCi/l$ 및 $0.89{\times}10^{-3}{\sim}6.57{\times}10^{-3}WL$로서 시간적(時間的) 요동이 심하였는데 대개 하루중(中) 오전(午前)에 높고 오후(午後)에 낮은 현상을 보여 주었다. RaA, RaB 및 RaC의 농도산출(濃度算出)에 따른 표준편차(標準偏差)는 각각 ${\pm}57.75%,\;{\pm}22.32%$ 및 ${\pm}31.29%$였으며 방사평형인자(放射平衡因子)는 평균(平均) 0.322였다. 그리고 RaA를 모핵종(母核種)으로 가정(假定)했을 때 각핵종간(各核種間)의 방사평형비(放射平衡比)는 대개 $C_1>C_2>C_3$인 것으로 나타났다. 여기서 $C_1,\;C_2$ 및 $C_3$는 각각 RaA, RaB 및 RaC의 농도(濃度)를 나타낸다.

• 지능정보연구
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• 제25권3호
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• pp.239-251
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• 2019

본 논문은 학습데이터의 크기에 따른 사례기반추론기법이 주가예측력에 어떻게 영향을 미치는지 살펴본다. 삼성전자 주가를 대상을 학습데이터를 2000년부터 2017년까지 이용한 경우와 2015년부터 2017년까지 이용한 경우를 비교하였다. 테스트데이터는 두 경우 모두 2018년 1월 1일부터 2018년 8월 31일까지 이용하였다. 시계 열데이터의 경우 과거데이터가 얼마나 유용한지 살펴보는 측면과 유사사례개수의 중요성을 살펴보는 측면에서 연구를 진행하였다. 실험결과 학습데이터가 많은 경우가 그렇지 않은 경우보다 예측력이 높았다. MAPE을 기준으로 비교할 때, 학습데이터가 적은 경우, 유사사례 개수와 상관없이 k-NN이 랜덤워크모델에 비해 좋은 결과를 보여주지 못했다. 그러나 학습데이터가 많은 경우, 일반적으로 k-NN의 예측력이 랜덤워크모델에 비해 좋은 결과를 보여주었다. k-NN을 비롯한 다른 데이터마이닝 방법론들이 주가 예측력 제고를 위해 학습데이터의 크기를 증가시키는 것 이외에, 거시경제변수를 고려한 기간유사사례를 찾아 적용하는 것을 제안한다.