EMJ. Radiology最新文献_第4页

Left Hemicolectomy for Intussusception of the Transverse Colon Caused by a Giant Benign Lipoma 巨大良性脂肪瘤所致横结肠肠套叠的左半结肠切除术

EMJ. Radiology Pub Date : 2021-04-15 DOI: 10.33590/emjradiol/20-00279

Kevin P. Birmingham

引用次数: 0

Artificial Intelligence in Radiology: An Exciting Future, but Ethically Complex 放射学中的人工智能：一个激动人心但伦理复杂的未来

EMJ. Radiology Pub Date : 2021-04-15 DOI: 10.33590/emjradiol/21f10415

A. Brady

{"title":"Artificial Intelligence in Radiology: An Exciting Future, but Ethically Complex","authors":"A. Brady","doi":"10.33590/emjradiol/21f10415","DOIUrl":"https://doi.org/10.33590/emjradiol/21f10415","url":null,"abstract":"“Let me start by saying a few things that seem obvious. I think if you work as a radiologist, you’re like the coyote that’s already over the edge of the cliff but hasn’t yet looked down, so doesn’t know there’s no ground underneath him. People should stop training radiologists now. It’s just completely obvious that within 5 years, deep learning is going to do better than radiologists, because it’s going to be able to get a lot more experience. It might be 10 years, but we’ve got plenty of radiologists already. I said this at a hospital, and it didn’t go down too well.”\u0000\u0000With those words at a 2016 Creative Destruction Lab (CDL) seminar on ‘Machine Learning and the Market for Intelligence’ in Toronto, Canada, Dr Geoff Hinton provided radiologists the world over with an uncomfortable prediction of their obsolescence (and provided a piece of video that always gets attention from audiences during speeches about artificial intelligence [AI] and radiology). Dr Hinton, an English/Canadian cognitive psychologist and computer scientist, is, fittingly, the great-great-grandson of George Boole.\u0000\u0000There have been many other such predictions in recent years, some from sources that know less about the subject than Dr Hinton. In October 2020, the Dutch Finance Minister, Wopke Hoekstra, said: “The work of the radiologist to a significant extent has become redundant, because […] a machine can read the images better than humans who studied 10 years for it.” He also commented that the same changes were occurring with supermarket checkout operators.","PeriodicalId":93747,"journal":{"name":"EMJ. Radiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44730481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Breast Lesion Characterisation with Diffusion Weighted Imaging Versus Dynamic Contrast Enhanced-MRI: A Prospective Observational Study in a Tertiary Care Hospital 扩散加权成像与动态对比增强MRI对乳腺病变的表征：一项在三级护理医院的前瞻性观察研究

EMJ. Radiology Pub Date : 2021-04-15 DOI: 10.33590/emjradiol/21-00053

Amandeep Singh, J. Purewal, K. Gupta, Gauravdeep Singh

{"title":"Breast Lesion Characterisation with Diffusion Weighted Imaging Versus Dynamic Contrast Enhanced-MRI: A Prospective Observational Study in a Tertiary Care Hospital","authors":"Amandeep Singh, J. Purewal, K. Gupta, Gauravdeep Singh","doi":"10.33590/emjradiol/21-00053","DOIUrl":"https://doi.org/10.33590/emjradiol/21-00053","url":null,"abstract":"Purpose: Dynamic contrast-enhanced (DCE)-MRI has a promising role in breast cancer detection and lesion characterisation. Diffusion-weighted imaging (DWI) acts as an adjunct in the differentiation between benign and malignant lesions. The purpose of the study was to evaluate the efficacy of DCE-MRI and DWI in differentiating benign and malignant lesions.\u0000\u0000Methods: In a prospective study conducted between March 2019 and February 2020, 60 patients with breast lesions underwent DWI combined with DCE-MRI of the breast. The time–intensity curves were plotted. Lesions were classified according to the latest American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS; 5th edition). The results were compared with the histopathological diagnosis. The sensitivity and specificity of DWI, DCE-MRI, and combined DWI and DCE-MRI were calculated for detection of benign and malignant breast lesions.\u0000\u0000Results: Sixty patients underwent breast MRI in which 78 lesions were detected, out of which 28 were benign and 50 were malignant. Quantitative apparent diffusion coefficient measurement revealed 96% sensitivity and 82% specificity, with a positive predictive value of 92% and negative predictive value of 96%, for differentiating benign from malignant lesions. DCE-MRI findings showed 96% sensitivity and 78.5% specificity. The sensitivity of combined DWI and DCE-MRI was 98% and specificity was 86%, which was higher than DWI and DCE-MRI alone.\u0000\u0000Conclusion: Multiparametric MRI of the breast has very high sensitivity for detecting and characterising breast lesions as benign or malignant lesions. DWI had higher specificity than DCE-MRI, and the combined use of DWI and DCE-MRI had greater efficacy than DWI and DCE-MRI alone.","PeriodicalId":93747,"journal":{"name":"EMJ. Radiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49062785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Pairing CT and Laboratory Data to Predict Prognosis in COVID-19 配对CT和实验室数据预测COVID-19预后

EMJ. Radiology Pub Date : 2021-04-01 DOI: 10.33590/emjradiol/21f20415

K. Colvin

引用次数: 0

Artificial Intelligence and the Future of Radiography 人工智能与放射摄影的未来

EMJ. Radiology Pub Date : 2020-09-01 DOI: 10.33590/emjradiol/20f0901

引用次数: 2

New Frontiers in Placenta Tissue Imaging. 胎盘组织成像的新领域。

EMJ. Radiology Pub Date : 2020-09-01 DOI: 10.33590/emjradiol/19-00210

Christopher D Nguyen, Ana Correia-Branco, Nimish Adhikari, Ezgi Mercan, Srivalleesha Mallidi, Mary C Wallingford

{"title":"New Frontiers in Placenta Tissue Imaging.","authors":"Christopher D Nguyen, Ana Correia-Branco, Nimish Adhikari, Ezgi Mercan, Srivalleesha Mallidi, Mary C Wallingford","doi":"10.33590/emjradiol/19-00210","DOIUrl":"https://doi.org/10.33590/emjradiol/19-00210","url":null,"abstract":"<p><p>The placenta is a highly vascularized organ with unique structural and metabolic complexities. As the primary conduit of fetal support, the placenta mediates transport of oxygen, nutrients, and waste between maternal and fetal blood. Thus, normal placenta anatomy and physiology is absolutely required for maintenance of maternal and fetal health during pregnancy. Moreover, impaired placental health can negatively impact offspring growth trajectories as well as increase the risk of maternal cardiovascular disease later in life. Despite these crucial roles for the placenta, placental disorders, such as preeclampsia, intrauterine growth restriction (IUGR), and preterm birth, remain incompletely understood. Effective noninvasive imaging and image analysis are needed to advance the obstetrician's clinical reasoning toolkit and improve the utility of the placenta in interpreting maternal and fetal health trajectories. Current paradigms in placental imaging and image analysis aim to improve the traditional imaging techniques that may be time-consuming, costly, or invasive. In concert with conventional clinical approaches such as ultrasound (US), advanced imaging modalities can provide insightful information on the structure of placental tissues. Herein we discuss such imaging modalities, their specific applications in structural, vascular, and metabolic analysis of placental health, and emerging frontiers in image analysis research in both preclinical and clinical contexts.</p>","PeriodicalId":93747,"journal":{"name":"EMJ. Radiology","volume":"1 1","pages":"54-62"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361653/pdf/nihms-1824475.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40601572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3