ライフサイエンスコーパス: radiology

1 post-baseline disease assessment by central radiology.

2 to the success of artificial intelligence in radiology.

3 -related racial and/or ethnic disparities in radiology.

4 ored using virtual and augmented reality for radiology.

5 as related to or unrelated to interventional radiology.

6 trends and their potential implications for radiology.

7 7 of 78; 73%) were related to interventional radiology.

8 imaging modality in the field of diagnostic radiology.

9 is widely adopted for image and metadata in radiology.

10 sus automated volumetric methods in clinical radiology.

11 ures in natural images such as those used in radiology.

12 nes in the applications of DECT in abdominal radiology.

13 and diagnosis occurring offsite, similar to radiology.

14 s and the health-care value contributions of radiology.

15 07 and 2017 in 12 journals, with the most in Radiology (12 articles).

16 care unit (46.9% vs 22.4%) or interventional radiology (22.8% vs 12.8%).

17 % stool culture, P = 0.008) or any abdominal radiology (29.4% GI panel versus 31.7%, P = 0.002).

18 s performance to that of 4 American Board of Radiology (ABR) certified radiologists on an independent

19 ved retrospectively from American College of Radiology accreditation data (January 1, 2015, to Decemb

20 oped and endorsed by the American College of Radiology (ACR) and the National Kidney Foundation to im

21 The American College of Radiology (ACR) BI-RADS classification is the applicable

22 classified them with the American College of Radiology (ACR) classification.

23 In 2017, the American College of Radiology (ACR) created a classification system based on

24 sk calculator (VRC) with American College of Radiology (ACR) Lung Imaging Reporting and Data System (

25 The recently revised American College of Radiology (ACR) recommendations define PCN measurement a

26 nce (AI) to optimize the American College of Radiology (ACR) Thyroid Imaging Reporting and Data Syste

27 diologists who adhere to American College of Radiology (ACR) Thyroid Imaging Reporting and Data Syste

28 Background The American College of Radiology (ACR) Thyroid Imaging Reporting and Data Syste

29 rted and endorsed by the American College of Radiology (ACR), the system has been developed by a comm

30 For the market overview, a list of radiology AI companies was aggregated from the Radiologi

31 The radiology AI marketplace is rapidly maturing, with an in

32 However, as radiology AI matures to become fully integrated into the

33 e of the art of interpretability methods for radiology AI.

34 mbers from ASCO and the Society of Abdominal Radiology, American College of Radiology, Society of Nuc

35 ologic changes and secondly SM with atypical radiology and a more aggressive clinical course.

36 mmittee sponsored by the American College of Radiology and applies the standardized reporting tool fo

37 possibilities that were once limited only to radiology and cardiology.

38 iles were re-examined, including laboratory, radiology and clinical examinations.

39 nt, but the adjudication panel that reviewed radiology and endoscopy was masked to allocation and vis

40 adult nephrology, human genetics, paediatric radiology and ethics specialties together with patient r

41 nce (AI) is becoming increasingly present in radiology and health care.

42 quirements for implementing continuous AI in radiology and illustrate them with examples from emergin

43 recently proposed by the American College of Radiology and include eight distinct diagnostic categori

44 ticle is a simultaneous joint publication in Radiology and Kidney Medicine.

45 y advancing scientific fields-interventional radiology and nanotechnology.

46 zation schema for the practices of pediatric radiology and nuclear medicine.

47 prognostication of diseases in the fields of radiology and oncology, renal pathology is just entering

48 Radiology and pathology data bases were searched for pat

49 Radiology and posttransplant histopathology reports were

50 sary endoscopic expertise and interventional radiology and surgical backup.

51 c Health of the Netherlands asked a group of radiology and vascular medicine experts to provide guida

52 2709], nephrology; and 31.1% [1108 of 3562], radiology) and anesthesia (19.9% [377 of 1895], surgery;

53 10% residents in either nuclear medicine or radiology, and 5% medical physicists, radiographers, or

54 n in the utilization of endoscopy, abdominal radiology, and antibiotic prescribing.

55 each case, we reviewed clinical, pathology, radiology, and endoscopy findings.

56 sts; senior residents in emergency medicine, radiology, and orthopedics.

57 y opportunities for research in the field of radiology, and these are accessible at any level.

58 cal oncology, pathology, radiation oncology, radiology, and translational research to develop recomme

59 ) are increasingly treated by interventional radiology approaches.

60 Uniform phantom and American College of Radiology-approved phantom results between scanner manuf

61 s, including uniform and American College of Radiology-approved phantoms, PET/CT images, and examples

62 ubjects was retrospectively collected from a radiology archive of CT examinations of the head perform

63 Although this review focuses on Radiology articles, key articles from high-impact clinic

64 cid is classified by the American College of Radiology as a group III gadolinium-based contrast agent

65 henomenon-like reactions), lung function, or radiology attributable to vaccine were observed.

66 asing neural network performance for various radiology-based machine learning tasks.

67 f this examination that may be applicable to radiology-based practice.

68 Conclusion American College of Radiology baseline size category of 15-25-mm pancreatic

69 culated according to the American College of Radiology Breast Imaging Reporting and Data System, 5th

70 lus DBT images using the American College of Radiology Breast Imaging Reporting and Data Systems crit

71 ent the use of chest radiography in clinical radiology, but challenges include poor generalizability,

72 increase efficiency and accuracy throughout radiology, but it also carries inherent pitfalls and bia

73 -based intelligent and autonomous systems in radiology can increase the risk of systemic errors with

74 adiology, Journal of the American College of Radiology, Canadian Association of Radiologists Journal,

75 om interventional cardiology, interventional radiology, cardiac surgery, cardiac imaging, and critica

76 article is being published synchronously in Radiology: Cardiothoracic Imaging, Journal of Cardiovasc

77 residual breast tissue (American College of Radiology categories A-D) and normal conventional imagin

78 ad a complication (Society of Interventional Radiology class A, two of 41 [4.9%]; class B, two of 41

79 The American College of Radiology classification system was used to characterize

80 c resonance of 58 patients, performed in the radiology clinic of our hospital between 2015 and 2017 w

81 Patients, investigators, independent radiology committee members, and the sponsor were masked

82 Hodgkin lymphoma, assessed by an independent radiology committee.

83 In Singapore, early experiences of the radiology community on managing this pandemic was shaped

84 atment and imaging will help ensure that the radiology community remains relevant and central in the

85 The radiology community should start now to develop codes of

86 recently gained particular attention in the radiology community.

87 be aware of the support that interventional radiology could provide in the case of iatrogenic vascul

88 patient population, the American College of Radiology created the Liver Imaging Reporting and Data S

89 rate, or severe by using American College of Radiology criteria.

90 aterials and Methods The American College of Radiology CT accreditation phantom was scanned by using

91 and the common good and should block use of radiology data and algorithms for financial gain without

92 as performed by using data from the National Radiology Data Registry (year range, 2016-2017) (n = 239

93 We systematically searched a local radiology database for patients with PTEN variants who h

94 A search of the radiology database revealed 2180 pediatric patients who

95 CT and MRI scanners in a university hospital radiology department and to estimate energy- and cost-sa

96 admitted from the emergency room (ER) to the Radiology Department due to suspected stroke.

97 he outside institution were submitted to our radiology department for interpretation.

98 aging studies from outside of the diagnostic radiology department may need to be requested through th

99 Overuse of urgent brain CT increases the radiology department's workload and exposes patients to

100 c survey to assess patient experience in the radiology department, to identify improvement opportunit

101 ng in patient experience in a large academic radiology department.

102 cused on improving patient experience in the radiology department.

103 e to an aneurysm in four neurointerventional radiology departments between January 2018 and July 2019

104 al of 118 patients underwent brain CT at two radiology departments equipped with 64-slice CT scanners

105 ions of the oral cavity and were referred to radiology departments for MRI.

106 article surveys the operational responses of radiology departments from six public hospitals in Singa

107 Radiology departments have begun exploring the use of th

108 survey (NCT04339686) was sent to 26 hospital radiology departments in France between March 2, 2020, a

109 ides detailed recommendations for organizing radiology departments in the case of new outbreaks of CO

110 -19 infection and explains the measures that radiology departments need to adopt during the pandemic.

111 Radiology departments play a critical role in policy and

112 Radiology departments play a fundamental role in the man

113 Results Twenty-six of 26 hospital radiology departments responded to the survey, with 7500

114 Radiology departments were selected to reflect the estim

115 ich may provide important guidance for other radiology departments who are in the early stages of pre

116 safety measures that should be introduced in radiology departments, as well as indications for imagin

117 irst authors but one primarily affiliated to radiology departments.

118 Background The American College of Radiology Dose Index Registry for CT enables evaluation

119 a were obtained from the American College of Radiology dose registry for CT examinations submitted fr

120 g the use of these technologies to help with radiology education and clinical care.

121 utions is presented, which includes clinical radiology education, infrastructure implementation, and

122 paper focuses on the role of interventional radiology embolisations in a series of patients presenti

123 lticenter European Society of Cardiovascular Radiology (ESCR) MR/CT Registry collected between Januar

124 an Society of Gastrointestinal and Abdominal Radiology (ESGAR) and European Society of Pediatric Radi

125 gy (ESGAR) and European Society of Pediatric Radiology (ESPR); however, MRI for non-IBD conditions wa

126 between mass spectrometry imaging (MSI) and radiology-established modalities such as magnetic resona

127 The European Society of Urogenital Radiology (ESUR) updated its guidelines for prophylaxis

128 om six BCSC registries (418 radiologists, 92 radiology facilities).

129 is, or both ("body CT studies") committed by radiology fellows working off-hours based on day or nigh

130 have lasting effects on the structure of the radiology field.

131 relative difficulty of identifying different radiology findings.

132 usion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to

133 In this issue of Radiology, Gade et al ( 1 ) describe a unique mechanism

134 e learning has created inroads in pathology, radiology, genomics, and the analysis of electronic heal

135 imilar safety profile to American College of Radiology group 2 gadolinium-based contrast agents for h

136 h colleagues and leaders of private-practice radiology groups from across the United States.

137 esult in decreased health care expenditures, radiology groups have never experienced an economic shoc

138 region sequencing, including iliac crest and radiology-guided focal lesion specimens from 51 patients

139 Radiology has the chance to leverage AI to become a cent

140 and the barriers to patient access of their radiology images.

141 a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high p

142 he clinical trial by the American College of Radiology Imaging Network (ACRIN) and the Gynecology Onc

143 operative Oncology Group-American College of Radiology Imaging Network (ECOG-ACRIN) affiliates in Eur

144 operative Oncology Group-American College of Radiology Imaging Network (ECOG-ACRIN) E2491 (intergroup

145 operative Oncology Group-American College of Radiology Imaging Network and the National Cancer Instit

146 ative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 mu

147 cohort of women from the American College of Radiology Imaging Network Pennsylvania 4006 trial was re

148 om multicenter Merck and American College of Radiology Imaging Network trials was performed.

149 ed analysis of ACRIN-PA (American College of Radiology Imaging Network-Pennsylvania) 4005 and the ROM

150 ctively enrolled from 23 American College of Radiology Imaging Network-qualified institutions.

151 led by a department separate from diagnostic radiology in 47 of 80 (59%) hospitals.

152 It has been widely accepted in practice in radiology in academic and hospital settings and included

153 non-diabetic mother and discuss the role of radiology in early diagnosis and timely management.

154 reed that promoting awareness of the role of radiology in patients' overall health care is important

155 ience as a nonprofit organization developing radiology in resource-poor health institutions, both in

156 ecisions that influence the effectiveness of radiology in the care of patients on a daily basis.

157 All students had taken a class in basic radiology in the previous year.

158 sider the fundamental role of interventional radiology in the treatment of pseudotumor cerebri becaus

159 lia, and New Zealand, describes the place of radiology in VBH models and the health-care value contri

160 ist members of the Society of Interventional Radiology, including attending-level physicians and trai

161 able phantoms for diagnostic and therapeutic radiology, including the reproduction of individual pati

162 asurements, the scanners' log files, and the radiology information system from the entire year 2015 w

163 ly verified disease but had uncharacteristic radiology involving multiple compartments of the abdomen

164 The risk of infection from interventional radiology (IR) procedures is not well documented.

165 n patients undergoing cardiac interventional radiology (IR) procedures.

166 s a complement to an existing interventional radiology (IR) service.

167 Interventional radiology (IR) team was successful with their conservati

168 d use of moderate sedation in interventional radiology (IR), patient reactions to moderate sedation a

169 Radiology is a major contributor to patient and societal

170 icacy of traditional computational models in radiology is a matter of debate.

171 ticle is a simultaneous joint publication in Radiology, Journal of the American College of Radiology,

172 ric Working Group within American College of Radiology LI-RADS was created to provide consensus for i

173 in the measurements and American College of Radiology Lung CT Screening Reporting and Data System (L

174 hich is a promising subspecialty of clinical radiology mainly for psychiatric disorders.

175 psychoradiology, an evolving subspecialty of radiology mainly for psychiatry and clinical psychology.

176 Imaging and interventional radiology management are described in detail.

177 analysis, performed in the II Department of Radiology, Medical University Hospital in Warsaw, includ

178 nsiders uncertainty of tumor location in the radiology mMRI image sub-regions, to obtain tumor segmen

179 t the ability to identify NDDs from combined radiology, morphology, and CNV assessments may be possib

180 istorical divides between the NM and nuclear radiology (NR) communities.

181 ucted in the Department of Oral Medicine and Radiology of the Dental Institute after obtaining approv

182 train deep learning algorithms in published radiology, ophthalmology, dermatology, pathology, gastro

183 any complex visual tasks in medicine such as radiology or pathology.

184 dical oncology, surgery, radiation oncology, radiology, pathology, and advocacy experts to conduct a

185 tric intensive care, nephrology, hepatology, radiology, pathology, and transfusion medicine; HSCT adv

186 ology, medical oncology, radiation oncology, radiology, pathology, translational research, health eco

187 aset of the Computational Precision Medicine Radiology-Pathology (CPM-RadPath) Challenge on Brain Tum

188 y MSERg are found to be more appropriate for radiology-pathology co-registration.

189 l experts in pediatric nephrology, pediatric radiology, pediatric US, and adult nephrology prepared s

190 ey fit with the current dominant approach to radiology peer review.

191 Local radiology personnel expertise is augmented through compr

192 luate trained readers' (nuclear medicine and radiology physicians) visual assessments of FA from soli

193 k factors for needlesticks in interventional radiology physicians, as well as the attitudes, behavior

194 gical treatment combined with interventional radiology played a decisive role in the final result.

195 The Polish Medical Society of Radiology (PLTR) and the Polish Society of Neurology (PT

196 ystems begin to make their way into clinical radiology practice, it is crucial to assure that they fu

197 t STTs are infrequent in routine orthopaedic radiology practice, musculoskeletal radiologists must be

198 -19) pandemic will have a profound impact on radiology practices across the country.

199 c imaging is becoming commonplace throughout radiology practices and is increasingly important in lar

200 ologists working in various types of private radiology practices during the initial peak of the COVID

201 Reasons are considered for radiology practices on both sides of the Atlantic about

202 Anecdotal experience suggests that radiology practices should anticipate 50%-70% decreases

203 an abrupt and substantial impact on private radiology practices, which are heavily dependent on exam

204 mmendations of the Polish Medical Society of Radiology, presuming that our knowledge on COVID-19 will

205 acic surgery, radiation oncology, pulmonary, radiology, primary care, and advocacy experts to conduct

206 ith COVID-19 who underwent 21 interventional radiology procedures between March 13, 2020 and May 11,

207 es, respiratory compromise in interventional radiology procedures with moderate sedation contributes

208 V-2 testing before surgeries, interventional radiology procedures, and endoscopy.

209 on ethics of artificial intelligence (AI) in radiology produced by the ACR, European Society of Radio

210 edge about radiation exposure is crucial for radiology professionals.

211 r bundles of care advance the imperative for radiology providers to articulate their value.

212 f care provides an excellent opportunity for radiology providers to take a leading role within the he

213 by Elsevier Inc; and The American College of Radiology, published by Elsevier Inc.

214 process and were vetted through a consensus radiology quality assurance committee.

215 Nearly half of unplanned interventional radiology-related readmissions are potentially preventab

216 Interventional radiology-related readmissions were categorized as poten

217 Of unplanned interventional radiology-related readmissions, 16% (nine of 57) were re

218 doses were transferred automatically to the radiology report and a centralized dose database when th

219 RIAL/It is a retrospective study analyzing a radiology report database and MR images of 92 patients w

220 of recommending a follow-up examination in a radiology report, after adjusting for patient, examinati

221 the majority of PHI found in the dataset of radiology reports (n = 2755 [78%]).

222 s of suspicious microcalcifications from all radiology reports and pathologic outcome of recalled wom

223 Although radiology reports are stored for communication and docum

224 associated with follow-up recommendations in radiology reports from multiple modalities, patient care

225 pathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy

226 and natural language processing of text from radiology reports to identify acute respiratory distress

227 f protected health information (PHI) in 2503 radiology reports were annotated from a large multihospi

228 The free-text radiology reports were preprocessed by using an in-house

229 Electronic medical records and radiology reports were retrospectively evaluated for the

230 chieved limited performance on the corpus of radiology reports, suggesting the need for further advan

231 ext indicating the placement of catheters in radiology reports, thereby improving radiologists' effic

232 ere confirmed through review of clinical and radiology reports.

233 the following text features from qualifying radiology reports: 1) word representations (n-grams) and

234 followed by reflections about the future of radiology research in the wake of the COVID-19 pandemic.

235 of a diverse international group of academic radiology research programs in managing their response t

236 ailed in the design process of deep learning radiology research.

237 Radiology researchers are currently grappling with these

238 se developed rapidly in the initial years of radiology residency and leveled off in the 3rd and 4th t

239 ewed by 2 board-certified radiologists and a radiology resident individually; each reviewed 2D and th

240 terials and Methods Two radiologists and one radiology resident retrospectively measured lung nodules

241 llowship trained thoracic radiologists and 3 radiology resident trainees).

242 ted by two chest radiologists and a 5th-year radiology resident using the RSNA chest CT classificatio

243 mong the chest radiologists and the 5th-year radiology resident were 0.570 (95% CI: 0.443, 0.696) and

244 ists (86% correct; P = .20), and better than radiology residents (56%; P < .001), general radiologist

245 were evaluated by three radiologists and six radiology residents (blinded to final diagnosis) for the

246 d 64% for TDx, which was better than that of radiology residents (n = 4; 56% for T3DDx, 36% for TDx;

247 To develop as leaders in AI-ML, radiology residents may seek a formative data science ex

248 Longitudinal test data of 577 of 2884 radiology residents who took semiannual progress tests d

249 Accuracy was compared with radiology residents, general radiologists, neuroradiolog

250 imaging interpretive errors have focused on radiology residents, not on the relative performance of

251 lored to the AI-ML interests of three senior radiology residents.

252 introductory experience in AI-ML for senior radiology residents.

253 Scarce or absent radiology resources impede adoption of artificial intell

254 based on anonymised clinical information and radiology results plus either molecular classifier or hi

255 disease as assessed by blinded, independent radiology review and by investigators) and locally asses

256 Confirmed ORRs per independent radiology review and investigator assessment were 43.5%

257 l, progression-free survival per independent radiology review committee (IRRC), and objective respons

258 ctive response rate (95% CI) per independent radiology review committee was 84% (71% to 93%), with 67

259 hed, retrospective cohort study with blinded radiology review for 133 patients with high-grade glioma

260 es to become fully integrated into the daily radiology routine, it needs to go beyond replicating sta

261 ogy produced by the ACR, European Society of Radiology, RSNA, Society for Imaging Informatics in Medi

262 ite this, some VBH models do not acknowledge radiology's central role; this may have future negative

263 Radiology's engagement across a broad spectrum of care p

264 ghts our consensus that ethical use of AI in radiology should promote well-being, minimize harm, and

265 lti-society paper, representing the views of Radiology Societies in Europe, the USA, Canada, Australi

266 eumonia is currently not recommended by most radiology societies.

267 of Abdominal Radiology, American College of Radiology, Society of Nuclear Medicine and Molecular Ima

268 ety of North America (RSNA) Patient-Centered Radiology Steering Committee survey were to (a) assess R

269 Conclusion Despite an increased focus on radiology subspecialization, most U.S. radiologists are

270 procedure carried out in the interventional radiology suite provides an advantage in the management

271 pic and nuclear images in the interventional radiology suite.

272 wing CVAP implantation in the interventional radiology suite.

273 g scores on knowledge and image questions on radiology tests, mediated by the training environment.

274 gy is a subspecialty field of interventional radiology that addresses the diagnosis and treatment of

275 promising clinical tool for use oncology and radiology that should be evaluated further in future lar

276 including microbiology, histopathology, and radiology, the etiology of intestinal perforation is fre

277 ndorsed by the European Society of Pediatric Radiology, the European Federation of Societies for Ultr

278 ce (AI) shows promise across many aspects of radiology, the use of AI to create differential diagnose

279 ternational Society for Strategic Studies in Radiology, this report outlines the effects of reforms a

280 ergy computed tomography (DECT) in abdominal radiology Thomson Reuters Web of Science All Databases w

281 rt radiologists who used American College of Radiology Thyroid Imaging and Reporting Data System guid

282 usion Use of the current American College of Radiology Thyroid Imaging Reporting and Data System crit

283 (TI-RADS) validates the American College of Radiology TI-RADS while slightly improving specificity a

284 ectify and quantify the value contributed by radiology to healthcare are outlined.

285 resentation varies from 8.6% (interventional radiology) to 63.1% (breast imaging); cardiothoracic ima

286 rated training experience for cardiology and radiology trainees in CCT.

287 e was strong concordance of findings between radiology training levels with agreement ranging from 60

288 describe our experience in an interventional radiology unit in a hospital in Spain that was severely

289 mmon nonsurgical procedure in interventional radiology used for the deliberate occlusion of blood ves

290 h articles with a primary focus on abdominal radiology using DECT were selected.

291 70 of 2709], nephrology; 4.7% [170 of 3562], radiology) varied by specialty and accounted for 407% an

292 s of cardiovascular medicine, interventional radiology, vascular medicine, and vascular surgery; onco

293 This group with typical radiology was labelled MP.

294 ion of the diagnostic and therapeutic use of radiology was slow and affected by peculiarities owing t

295 Psychoradiology, an emerging subspecialty of radiology, which seems primed to play a major clinical r

296 In this issue of Radiology, White et al ( 6 ) introduced their work on de

297 and experiences concerning patient-centered radiology, with specific attention paid to radiologist-t

298 e system that uses deep learning may improve radiology workflow for management of thyroid nodules.Pur

299 ologic and networking infrastructure enables radiology workflows incorporating AI.

300 In addition, radiology workflows, volumes, and access must be optimiz