• Journal of radiological science and technology
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• v.37 no.2
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• pp.75-84
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• 2014

In this study, we surveyed the current status, satisfaction and demand of radiologic technologist continuing education for 93 radiologic technologists who participated in the continuing education. To understand the current status and general evaluation and to find out the improvement direction, survey was conducted on 3 categories: participation, satisfaction and demand of continuing education. In addition, we analyzed the continuing education implementation status and the management system by collecting related regulations. As a result, the education completion rates of radiologic technologists from 2010 to 2012 were respectively 42.6%, 43.4% and 34.2%; the rates were similar to other medical technician's average education completion rates. According to the survey, in case of participation, the most frequent answer was 'more than five times less than 10 times per year' with 48.4% and in satisfaction section, the most common answer was 'Average(3)' with 34.4%. In demand of continuing education section, 32.8% of the respondents chose 'Clinical skill training in major field'. In the results of this research, continuing education needs to be managed in the direction of helping radiologists improve their personal ability and self development. Furthermore, to meet the demand of radiologists, the quality of continuing education should be improved to satisfy the educatee.

• Journal of Preventive Medicine and Public Health
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• v.29 no.4 s.55
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• pp.853-861
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• 1996

Pneumoconiosis is one of the major problem in the field of occupational health at Korea. Therefore, the efficient diagnosis of pneumoconiosis is a hot issue on the occupational health program. The author executed this study to estimate the diagnostic value of high resolution computed tomography(HRCT) compared with chest radiography for screening of welder's lung. HRCT was introduced very recently for the diagnosis of pneumoconiosis, however, the diagnostic value for screening of welder's lung - principally nonfibrogenic and reversible - has not been evaluated. The subjects were fifty cases of welder's lung or suspected cases who had been collected between 1989 and 1994 from one shipyard and continuously followed-up on the basis of in-plant periodic health check program. We applied both chest radiography and HRCT on the same subjects from May 1 to 30, 1996. The images were evaluated by two careered radiologists independently. The findings of chest radiography were classified into four category by ILO classification, and the findings of HRCT according to the criteria of Bergin et al. The concordance between two radiologists expressed with Kendall's tau-b was 0.72 by chest radiography and 0.44 by HRCT- that is, interobserver variation of HRCT was bigger than that of chest radiography. The concordance between the two different methods was highly variable as 0.44 by radiologist A and 0.06 by radiologist B - that is, interobserver variation was very big. However, HRCT looked more detectable for the minor parenchymal change. These findings suggested that it is not appropriate to use HRCT routinely for screening of welder's lung due to lack of diagnostic criteria, and feasibility, acceptability and economic aspects. Nevertheless, HRCT might be recommendable in the case of equivocal parenchymal features on the chest radiography, unexplained respiratory symptoms, and/or lung function abnormalities suggestive of interstitial fibrosis.

• Journal of the Korean Society of Radiology
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• v.12 no.7
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• pp.861-868
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• 2018

As the research about supplementary education of radiological technologist who works in medical clinics, this study was conducted to draw the improvements by analyzing the satisfaction level and problems of the supplementary education. During November 01, 2016 to April 30, 2017, after we distributed a total of 150 questionnaires for the survey to radiological technologists working at medical clinics located in Changwon-si, Gyoungsangnam province, 106 questionnaires suitable for research were analysis by using SPSS 18.0 statistical analysis software. As the sociodemographic characteristics, the age, gender, working period, level of education, and working department were used. And As the welfare factors, working environment, financial support, educational opportunity, medical support, working culture, etc. were used. As the satisfaction factors, 21 items such as system, subject, help, appropriateness of lecturer selection, professionalism were used. And as the problem factors, 18 items such as place, transportation, diversity, administrative treatment, education promotion, proceed method were used. Consequentially, the satisfaction level(3.02 point) of the supplementary education were confirmed as normal level. And the problems(3.18 point) of the supplementary education was analyzed a little higher. The supplementary education is the mandatory education that any health and medical service personnel must complete every three years for license re-issuance. There were many opinions that the supplementary education for radiologists working in various medical institutions did not meet the education level of radiologists working in the medical clinics. In order to improve the satisfaction of the supplementary education of medical clinic's radiological technologist, it should be improved the quality of education through a practical education program that reflects various opinions and improvements on conservative education.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.281-290
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• 2021

Objective: To assess the performance of content-based image retrieval (CBIR) of chest CT for diffuse interstitial lung disease (DILD). Materials and Methods: The database was comprised by 246 pairs of chest CTs (initial and follow-up CTs within two years) from 246 patients with usual interstitial pneumonia (UIP, n = 100), nonspecific interstitial pneumonia (NSIP, n = 101), and cryptogenic organic pneumonia (COP, n = 45). Sixty cases (30-UIP, 20-NSIP, and 10-COP) were selected as the queries. The CBIR retrieved five similar CTs as a query from the database by comparing six image patterns (honeycombing, reticular opacity, emphysema, ground-glass opacity, consolidation and normal lung) of DILD, which were automatically quantified and classified by a convolutional neural network. We assessed the rates of retrieving the same pairs of query CTs, and the number of CTs with the same disease class as query CTs in top 1-5 retrievals. Chest radiologists evaluated the similarity between retrieved CTs and queries using a 5-scale grading system (5-almost identical; 4-same disease; 3-likelihood of same disease is half; 2-likely different; and 1-different disease). Results: The rate of retrieving the same pairs of query CTs in top 1 retrieval was 61.7% (37/60) and in top 1-5 retrievals was 81.7% (49/60). The CBIR retrieved the same pairs of query CTs more in UIP compared to NSIP and COP (p = 0.008 and 0.002). On average, it retrieved 4.17 of five similar CTs from the same disease class. Radiologists rated 71.3% to 73.0% of the retrieved CTs with a similarity score of 4 or 5. Conclusion: The proposed CBIR system showed good performance for retrieving chest CTs showing similar patterns for DILD.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.363-373
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• 2024

Objective: To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI. Materials and Methods: We included whole spine MRI scans of adult patients with bone metastasis: 662 MRI series from 302 patients (63.5 ± 11.5 years; male:female, 151:151) from three study centers obtained between January 2015 and August 2021 for training and internal testing (random split into 536 and 126 series, respectively) and 49 MRI series from 20 patients (65.9 ± 11.5 years; male:female, 11:9) from another center obtained between January 2018 and August 2020 for external testing. Three sagittal MRI sequences, including non-contrast T1-weighted image (T1), contrast-enhanced T1-weighted Dixon fat-only image (FO), and contrast-enhanced fat-suppressed T1-weighted image (CE), were used. Seven models trained using the 2D and 3D U-Nets were developed with different combinations (T1, FO, CE, T1 + FO, T1 + CE, FO + CE, and T1 + FO + CE). The segmentation performance was evaluated using Dice coefficient, pixel-wise recall, and pixel-wise precision. The detection performance was analyzed using per-lesion sensitivity and a free-response receiver operating characteristic curve. The performance of the model was compared with that of five radiologists using the external test set. Results: The 2D U-Net T1 + CE model exhibited superior segmentation performance in the external test compared to the other models, with a Dice coefficient of 0.699 and pixel-wise recall of 0.653. The T1 + CE model achieved per-lesion sensitivities of 0.828 (497/600) and 0.857 (150/175) for metastases in the internal and external tests, respectively. The radiologists demonstrated a mean per-lesion sensitivity of 0.746 and a mean per-lesion positive predictive value of 0.701 in the external test. Conclusion: The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.259-270
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• 2023

Objective: It is unknown whether artificial intelligence-based computer-aided detection (AI-CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical practice. We aimed to compare the accuracy of CR interpretation assisted by AI-CAD to that of conventional interpretation in patients who presented to the emergency department (ED) with acute respiratory symptoms using a pragmatic randomized controlled trial. Materials and Methods: Patients who underwent CRs for acute respiratory symptoms at the ED of a tertiary referral institution were randomly assigned to intervention group (with assistance from an AI-CAD for CR interpretation) or control group (without AI assistance). Using a commercial AI-CAD system (Lunit INSIGHT CXR, version 2.0.2.0; Lunit Inc.). Other clinical practices were consistent with standard procedures. Sensitivity and false-positive rates of CR interpretation by duty trainee radiologists for identifying acute thoracic diseases were the primary and secondary outcomes, respectively. The reference standards for acute thoracic disease were established based on a review of the patient's medical record at least 30 days after the ED visit. Results: We randomly assigned 3576 participants to either the intervention group (1761 participants; mean age ± standard deviation, 65 ± 17 years; 978 males; acute thoracic disease in 472 participants) or the control group (1815 participants; 64 ± 17 years; 988 males; acute thoracic disease in 491 participants). The sensitivity (67.2% [317/472] in the intervention group vs. 66.0% [324/491] in the control group; odds ratio, 1.02 [95% confidence interval, 0.70-1.49]; P = 0.917) and false-positive rate (19.3% [249/1289] vs. 18.5% [245/1324]; odds ratio, 1.00 [95% confidence interval, 0.79-1.26]; P = 0.985) of CR interpretation by duty radiologists were not associated with the use of AI-CAD. Conclusion: AI-CAD did not improve the sensitivity and false-positive rate of CR interpretation for diagnosing acute thoracic disease in patients with acute respiratory symptoms who presented to the ED.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1033-1052
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• 2021

Bladder cancer is a relatively common cancer type, with a high recurrence rate, that can be often encountered in the imaging study. Accurate diagnosis and staging have a significant impact on determining treatment and evaluating prognosis. Bladder cancer has been evaluated by transurethral resection of bladder tumor for clinical staging and treatment, but it is often understaged when compared with final pathologic result by radical cystectomy. If the location, size, presence of muscle invasion, lymph node metastasis, distant metastasis, and presence of upper urinary tract cancer can be accurately diagnosed and evaluated in an imaging study, it can be treated and managed more appropriately. For an accurate diagnosis, radiologists who evaluate the images must be aware of the characteristics of bladder cancer as well as its types, imaging techniques, and limitations of imaging studies. Recent developments in MRI with functional imaging have improved the quality of bladder imaging and the evaluation of cancer. In addition, the Vesical Imaging Reporting and Data System was published to objectively assess the possibility for muscle invasion of cancer. Radiologists need to know the types of bladder cancer treatment and how to evaluate the changes after treatment. In this article, the characteristics of bladder urothelial carcinoma, various imaging studies, and findings are reviewed.

• Korean Journal of Radiology
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• v.23 no.11
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• pp.1031-1043
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• 2022

Objective: To compare digital breast tomosynthesis (DBT) and MRI as an adjunct to full-field digital mammography (FFDM) for the preoperative evaluation of women with breast cancer based on mammographic density. Materials and Methods: This retrospective study enrolled 280 patients with breast cancer who had undergone FFDM, DBT, and MRI for preoperative local tumor staging. Three radiologists independently sought the index cancer and additional ipsilateral and contralateral breast cancers using either FFDM alone, DBT plus FFDM, or MRI plus FFDM. Diagnostic performances across the three radiologists were compared among the reading modes in all patients and subgroups with dense (n = 186) and non-dense breasts (n = 94) according to mammographic density. Results: Of 280 patients, 46 (16.4%) had 48 additional (39 ipsilateral and nine contralateral) cancers in addition to the index cancer. For index cancers, both DBT plus FFDM and MRI plus FFDM showed sensitivities of 100% in the non-dense group. In the dense group, DBT plus FFDM showed lower sensitivity than that of MRI plus FFDM (94.6% vs. 99.6%, p < 0.001). For additional ipsilateral cancers, DBT plus FFDM showed specificity and positive predictive value (PPV) of 100% in the non-dense group, but sensitivity and negative predictive value (NPV) were not statistically different from those of MRI plus FFDM (p > 0.05). In the dense group, DBT plus FFDM showed higher specificity (98.2% vs. 94.1%, p = 0.005) and PPV (83.1% vs. 65.4%; p = 0.036) than those of MRI plus FFDM, but lower sensitivity (59.9% vs. 75.3%; p = 0.049). For contralateral cancers, DBT plus FFDM showed higher specificity than that of MRI plus FFDM (99.0% vs. 96.7%, p = 0.014), however, the other values did not differ (all p > 0.05) in the dense group. Conclusion: DBT plus FFDM showed an overall higher specificity than that of MRI plus FFDM regardless of breast density, perhaps without substantial loss in sensitivity and NPV in the diagnosis of additional cancers. Thus, DBT may have the potential to be used as a preoperative breast cancer staging tool.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1241-1250
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• 2022

Objective: To conduct a simulation study to determine whether artificial intelligence (AI)-aided mammography reading can reduce unnecessary recalls while maintaining cancer detection ability in women recalled after mammography screening. Materials and Methods: A retrospective reader study was performed by screening mammographies of 793 women (mean age ± standard deviation, 50 ± 9 years) recalled to obtain supplemental mammographic views regarding screening mammography-detected abnormalities between January 2016 and December 2019 at two screening centers. Initial screening mammography examinations were interpreted by three dedicated breast radiologists sequentially, case by case, with and without AI aid, in a single session. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and recall rate for breast cancer diagnosis were obtained and compared between the two reading modes. Results: Fifty-four mammograms with cancer (35 invasive cancers and 19 ductal carcinomas in situ) and 739 mammograms with benign or negative findings were included. The reader-averaged AUC improved after AI aid, from 0.79 (95% confidence interval [CI], 0.74-0.85) to 0.89 (95% CI, 0.85-0.94) (p < 0.001). The reader-averaged specificities before and after AI aid were 41.9% (95% CI, 39.3%-44.5%) and 53.9% (95% CI, 50.9%-56.9%), respectively (p < 0.001). The reader-averaged sensitivity was not statistically different between AI-unaided and AI-aided readings: 89.5% (95% CI, 83.1%-95.9%) vs. 92.6% (95% CI, 86.2%-99.0%) (p = 0.053), although the sensitivities of the least experienced radiologists before and after AI aid were 79.6% (43 of 54 [95% CI, 66.5%-89.4%]) and 90.7% (49 of 54 [95% CI, 79.7%-96.9%]), respectively (p = 0.031). With AI aid, the reader-averaged recall rate decreased by from 60.4% (95% CI, 57.8%-62.9%) to 49.5% (95% CI, 46.5%-52.4%) (p < 0.001). Conclusion: AI-aided reading reduced the number of recalls and improved the diagnostic performance in our simulation using women initially recalled for supplemental mammographic views after mammography screening.

• Korean Journal of Radiology
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• v.21 no.9
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• pp.1065-1076
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• 2020

Objective: To determine the prognostic value of MRI-based tumor regression grading (mrTRG) in rectal cancer compared with pathological tumor regression grading (pTRG), and to assess the effect of diffusion-weighted imaging (DWI) on interobserver agreement for evaluating mrTRG. Materials and Methods: Between 2007 and 2016, we retrospectively enrolled 321 patients (male:female = 208:113; mean age, 60.2 years) with rectal cancer who underwent both pre-chemoradiotherapy (CRT) and post-CRT MRI. Two radiologists independently determined mrTRG using a 5-point grading system with and without DWI in a one-month interval. Two pathologists graded pTRG using a 5-point grading system in consensus. Kaplan-Meier estimation and Cox-proportional hazard models were used for survival analysis. Cohen's kappa analysis was used to determine interobserver agreement. Results: According to mrTRG on MRI with DWI, there were 6 mrTRG 1, 48 mrTRG 2, 109 mrTRG 3, 152 mrTRG 4, and 6 mrTRG 5. By pTRG, there were 7 pTRG 1, 59 pTRG 2, 180 pTRG 3, 73 pTRG 4, and 2 pTRG 5. A 5-year overall survival (OS) was significantly different according to the 5-point grading mrTRG (p = 0.024) and pTRG (p = 0.038). The 5-year disease-free survival (DFS) was significantly different among the five mrTRG groups (p = 0.039), but not among the five pTRG groups (p = 0.072). OS and DFS were significantly different according to post-CRT MR variables: extramural venous invasion after CRT (hazard ratio = 2.259 for OS, hazard ratio = 5.011 for DFS) and extramesorectal lymph node (hazard ratio = 2.610 for DFS). For mrTRG, k value between the two radiologists was 0.309 (fair agreement) without DWI and slightly improved to 0.376 with DWI. Conclusion: mrTRG may predict OS and DFS comparably or even better compared to pTRG. The addition of DWI on T2-weighted MRI may improve interobserver agreement on mrTRG.