Korean Journal of Radiology最新文献

{"title":"Automated Detection and Segmentation of Bone Metastases on Spine MRI Using U-Net: A Multicenter Study.","authors":"Dong Hyun Kim, Jiwoon Seo, Ji Hyun Lee, Eun-Tae Jeon, DongYoung Jeong, Hee Dong Chae, Eugene Lee, Ji Hee Kang, Yoon-Hee Choi, Hyo Jin Kim, Jee Won Chai","doi":"10.3348/kjr.2023.0671","DOIUrl":"10.3348/kjr.2023.0671","url":null,"abstract":"<p><strong>Objective: </strong>To develop and evaluate a deep learning model for automated segmentation and detection of bone metastasis on spinal MRI.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>The deep learning models proposed for automated segmentation and detection of bone metastases on spinal MRI demonstrated high diagnostic performance.</p>","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"363-373"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT Vision for Radiological Interpretation: An Investigation Using Medical School Radiology Examinations.","authors":"Hyungjin Kim, Paul Kim, Ijin Joo, Jung Hoon Kim, Chang Min Park, Soon Ho Yoon","doi":"10.3348/kjr.2024.0017","DOIUrl":"10.3348/kjr.2024.0017","url":null,"abstract":"","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"403-406"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT Demonstration of Local Cytokine-Release Syndrome Involving the Head and Neck Following Chimeric Antigen Receptor T Cell Infusion Therapy.","authors":"Ji Su Ko, Jeong Hyun Lee, Dok Hyun Yoon, Chong Hyun Suh, Sae Rom Chung, Young Jun Choi, Jung Hwan Baek","doi":"10.3348/kjr.2023.1100","DOIUrl":"10.3348/kjr.2023.1100","url":null,"abstract":"","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"399-402"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.","authors":"Tong Su, Zhe Zhang, Yu Chen, Yun Wang, Yumei Li, Min Xu, Jian Wang, Jing Li, Xinping Tian, Zhengyu Jin","doi":"10.3348/kjr.2023.1078","DOIUrl":"10.3348/kjr.2023.1078","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize the cervical artery wall in patients with Takayasu arteritis (TAK).</p><p><strong>Materials and methods: </strong>This prospective study continuously recruited 53 patients with TAK (mean age: 33.8 ± 10.2 years; 49 females) between January and July 2022 who underwent head-neck CTA scans. The arterial- and delayed-phase images were reconstructed using HIR and DLR. Subtracted images of the arterial-phase from the delayed-phase were then added to the original delayed-phase using a denoising filter to generate the final-dark-blood images. Qualitative image quality scores and quantitative parameters were obtained and compared among the three groups of images: Delayed-HIR, Dark-blood-HIR, and Dark-blood-DLR.</p><p><strong>Results: </strong>Compared to Delayed-HIR, Dark-blood-HIR images demonstrated higher qualitative scores in terms of vascular wall visualization and diagnostic confidence index (all <i>P</i> < 0.001). These qualitative scores further improved after applying DLR (Dark-blood-DLR compared to Dark-blood-HIR, all <i>P</i> < 0.001). Dark-blood DLR also showed higher scores for overall image noise than Dark-blood-HIR (<i>P</i> < 0.001). In the quantitative analysis, the contrast-to-noise ratio (CNR) values between the vessel wall and lumen for the bilateral common carotid arteries and brachiocephalic trunk were significantly higher on Dark-blood-HIR images than on Delayed-HIR images (all <i>P</i> < 0.05). The CNR values were significantly higher for Dark-blood-DLR than for Dark-blood-HIR in all cervical arteries (all <i>P</i> < 0.001).</p><p><strong>Conclusion: </strong>Compared with Delayed-HIR CTA, the dark-blood method combined with DLR improved CTA image quality and enhanced visualization of the cervical artery wall in patients with TAK.</p>","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"384-394"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973741/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncover This Tech Term: Uncertainty Quantification for Deep Learning.","authors":"Shahriar Faghani, Cooper Gamble, Bradley J Erickson","doi":"10.3348/kjr.2024.0108","DOIUrl":"10.3348/kjr.2024.0108","url":null,"abstract":"","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"395-398"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretation of Complete Tumor Response on MRI Following Chemoradiotherapy of Rectal Cancer: Inter-Reader Agreement and Associated Factors in Multi-Center Clinical Practice.","authors":"Hae Young Kim, Seung Hyun Cho, Jong Keon Jang, Bohyun Kim, Chul-Min Lee, Joon Seok Lim, Sung Kyoung Moon, Soon Nam Oh, Nieun Seo, Seong Ho Park","doi":"10.3348/kjr.2023.1213","DOIUrl":"10.3348/kjr.2023.1213","url":null,"abstract":"<p><strong>Objective: </strong>To measure inter-reader agreement and identify associated factors in interpreting complete response (CR) on magnetic resonance imaging (MRI) following chemoradiotherapy (CRT) for rectal cancer.</p><p><strong>Materials and methods: </strong>This retrospective study involved 10 readers from seven hospitals with experience of 80-10210 cases, and 149 patients who underwent surgery after CRT for rectal cancer. Using MRI-based tumor regression grading (mrTRG) and methods employed in daily practice, the readers independently assessed mrTRG, CR on T2-weighted images (T2WI) denoted as mrCR_T2W, and CR on all images including diffusion-weighted images (DWI) denoted as mrCR_overall. The readers described their interpretation patterns and how they utilized DWI. Inter-reader agreement was measured using multi-rater kappa, and associated factors were analyzed using multivariable regression. Correlation between sensitivity and specificity of each reader was analyzed using Spearman coefficient.</p><p><strong>Results: </strong>The mrCR_T2W and mrCR_overall rates varied widely among the readers, ranging 18.8%-40.3% and 18.1%-34.9%, respectively. Nine readers used DWI as a supplement sequence, which modified interpretations on T2WI in 2.7% of cases (36/1341 [149 patients × 9 readers]) and mostly (33/36) changed mrCR_T2W to non-mrCR_overall. The kappa values for mrTRG, mrCR_T2W, and mrCR_overall were 0.56 (95% confidence interval: 0.49, 0.62), 0.55 (0.52, 0.57), and 0.54 (0.51, 0.57), respectively. No use of rectal gel, larger initial tumor size, and higher initial cT stage exhibited significant association with a higher inter-reader agreement for assessing mrCR_overall (<i>P</i> ≤ 0.042). Strong negative correlations were observed between the sensitivity and specificity of individual readers (coefficient, -0.718 to -0.963; <i>P</i> ≤ 0.019).</p><p><strong>Conclusion: </strong>Inter-reader agreement was moderate for assessing CR on post-CRT MRI. Readers' varying standards on MRI interpretation (i.e., threshold effect), along with the use of rectal gel, initial tumor size, and initial cT stage, were significant factors associated with inter-reader agreement.</p>","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 4","pages":"351-362"},"PeriodicalIF":4.8,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10973736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140288462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical and Imaging Characteristics of SARS-CoV-2 Breakthrough Infection in Hospitalized Immunocompromised Patients.","authors":"Jong Eun Lee, Jinwoo Kim, Minhee Hwang, Yun-Hyeon Kim, Myung Jin Chung, Won Gi Jeong, Yeon Joo Jeong","doi":"10.3348/kjr.2023.0992","DOIUrl":"https://doi.org/10.3348/kjr.2023.0992","url":null,"abstract":"To evaluate the clinical and imaging characteristics of SARS-CoV-2 breakthrough infection in hospitalized immunocompromised patients in comparison with immunocompetent patients.","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"127 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140613268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.","authors":"Hoyol Jhang, So Jin Park, Ah-Ram Sul, Hye Young Jang, Seong Ho Park","doi":"10.3348/kjr.2023.1281","DOIUrl":"https://doi.org/10.3348/kjr.2023.1281","url":null,"abstract":"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.","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"40 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140613217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Announcement of New Breast Section Editor.","authors":"Seong Ho Park","doi":"10.3348/kjr.2024.0077","DOIUrl":"10.3348/kjr.2024.0077","url":null,"abstract":"","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 3","pages":"223"},"PeriodicalIF":4.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10912497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139983226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cerebellar, Hippocampal, and Basal Nuclei Transient Edema With Restricted Diffusion (CHANTER) Syndrome: Radiologic Features and Findings.","authors":"Renu Pandit, Omar Hamki, Siddhartha Gaddamanugu","doi":"10.3348/kjr.2023.1142","DOIUrl":"10.3348/kjr.2023.1142","url":null,"abstract":"","PeriodicalId":17881,"journal":{"name":"Korean Journal of Radiology","volume":"25 3","pages":"314-318"},"PeriodicalIF":4.8,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10912496/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139983227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}