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1.
BMC Health Serv Res ; 22(1): 398, 2022 Mar 26.
Article in English | MEDLINE | ID: covidwho-1793948

ABSTRACT

BACKGROUND: Artificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologists. The goal was to generate insights for tool providers and policymakers regarding the development and funding of ideally designed and priced tools. Ultimately, healthcare systems can only benefit from quality enhancing AI when provider adoption is considered. METHODS: Since there is no established market for AI-based assistance tools in radiology yet, a discrete choice experiment was conducted. Respondents from the two major German professional radiology associations chose between hypothetical tools composed of five attributes and a no-choice option. The attributes included: provider, application, quality impact, time savings and price. A conditional logit model was estimated identifying preferences for attribute levels, the no-choice option, and significant subject-related interaction effects. RESULTS: 114 respondents were included for analysis of which 46% were already using an AI-based assistance tool. Average adoption probability for an AI-based tool was 81% (95% CI 77.1% - 84.4%). Radiologists preferred a tool that assists in routine diagnostics performing at above-radiologist-level quality and saves 50% in diagnostics time at a price-point of €3 per study. The provider is not a significant factor in the decisions. Time savings were considered more important than quality improvements (i.e., detecting more anomalies). CONCLUSIONS: Radiologists are overall willing to invest in AI-based assistance tools. Development, funding, and research regarding these tools should, however, consider providers' preferences for features of immediate everyday and economic relevance like time savings to optimize adoption.


Subject(s)
Artificial Intelligence , Radiology , Humans , Income , Quality Improvement , Radiologists
2.
Pediatr Radiol ; 52(4): 613-615, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1787803

ABSTRACT

The field of radiology has benefited greatly from the technological boom that has brought greater precision, efficiency and utilization amid an exponential growth in medical science. The downside is that the same technology that has allowed the field to grow is contributing to an erosion of interpersonal communication and connection with patients and referring physicians. Remote reading has displaced us from the communal reading room, where much interaction and teaching used to take place. The "invisible" radiologist must transcend these barriers in order to preserve and strengthen the role of radiology in medical care. With modest adaptation, radiologists can regain their identity as consultants, where they have the greatest chance to show their value and thwart the drive toward commoditization.


Subject(s)
Radiology , Referral and Consultation , Communication , Humans , Radiography , Radiologists , Radiology/education
3.
Indian J Public Health ; 66(1): 74-76, 2022.
Article in English | MEDLINE | ID: covidwho-1776449

ABSTRACT

During the COVID-19 pandemic, differences in health-care system and policies among countries worldwide meant that each country had to come up with their own strategies for containment, diagnosis, and treatment of the disease - "no one size fits all." India being the second populous country in the world with modern and traditional systems of health care has its own challenges to face during the pandemic. Among the increased cacophony of information regarding the COVID-19 disease and controversies surrounding the usage of various radiological modalities for its diagnosis, we are trying to present a sane perspective from an Indian radiologist viewpoint. Knowing the strengths and shortcomings of the Indian health-care system, we have suggested plausible solutions which may be the answers to the issues raised by the Indian media.


Subject(s)
COVID-19 , Pandemics , Humans , India/epidemiology , Radiologists , SARS-CoV-2
4.
Radiol Med ; 127(4): 369-382, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1739408

ABSTRACT

During the coronavirus disease 19 (COVID-19) pandemic, extracorporeal membrane oxygenation (ECMO) has been proposed as a possible therapy for COVID-19 patients with acute respiratory distress syndrome. This pictorial review is intended to provide radiologists with up-to-date information regarding different types of ECMO devices, correct placement of ECMO cannulae, and imaging features of potential complications and disease evolution in COVID-19 patients treated with ECMO, which is essential for a correct interpretation of diagnostic imaging, so as to guide proper patient management.


Subject(s)
COVID-19 , Extracorporeal Membrane Oxygenation , Respiratory Distress Syndrome , Extracorporeal Membrane Oxygenation/methods , Humans , Radiologists , Respiratory Distress Syndrome/diagnostic imaging , Respiratory Distress Syndrome/etiology , Respiratory Distress Syndrome/therapy , SARS-CoV-2
5.
Eur J Radiol ; 144: 110002, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1605018

ABSTRACT

PURPOSE: To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens. METHODS: Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia. RESULTS: The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% ± 4 (SD), 79% ± 6 (SD), and 90% ± 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively. CONCLUSIONS: Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.


Subject(s)
COVID-19 , Influenza, Human , Humans , Lung , Radiologists , Retrospective Studies , SARS-CoV-2
6.
Eur Radiol ; 32(4): 2235-2245, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1606144

ABSTRACT

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.


Subject(s)
Artificial Intelligence , COVID-19 , Algorithms , Humans , Radiologists , Tomography, X-Ray Computed/methods
7.
Clin Imaging ; 82: 77-82, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1574394

ABSTRACT

BACKGROUND: Chest radiographs (CXR) are frequently used as a screening tool for patients with suspected COVID-19 infection pending reverse transcriptase polymerase chain reaction (RT-PCR) results, despite recommendations against this. We evaluated radiologist performance for COVID-19 diagnosis on CXR at the time of patient presentation in the Emergency Department (ED). MATERIALS AND METHODS: We extracted RT-PCR results, clinical history, and CXRs of all patients from a single institution between March and June 2020. 984 RT-PCR positive and 1043 RT-PCR negative radiographs were reviewed by 10 emergency radiologists from 4 academic centers. 100 cases were read by all radiologists and 1927 cases by 2 radiologists. Each radiologist chose the single best label per case: Normal, COVID-19, Other - Infectious, Other - Noninfectious, Non-diagnostic, and Endotracheal Tube. Cases labeled with endotracheal tube (246) or non-diagnostic (54) were excluded. Remaining cases were analyzed for label distribution, clinical history, and inter-reader agreement. RESULTS: 1727 radiographs (732 RT-PCR positive, 995 RT-PCR negative) were included from 1594 patients (51.2% male, 48.8% female, age 59 ± 19 years). For 89 cases read by all readers, there was poor agreement for RT-PCR positive (Fleiss Score 0.36) and negative (Fleiss Score 0.46) exams. Agreement between two readers on 1638 cases was 54.2% (373/688) for RT-PCR positive cases and 71.4% (679/950) for negative cases. Agreement was highest for RT-PCR negative cases labeled as Normal (50.4%, n = 479). Reader performance did not improve with clinical history or time between CXR and RT-PCR result. CONCLUSION: At the time of presentation to the emergency department, emergency radiologist performance is non-specific for diagnosing COVID-19.


Subject(s)
COVID-19 , Adult , Aged , COVID-19 Testing , Emergency Service, Hospital , Female , Humans , Male , Middle Aged , Radiography, Thoracic , Radiologists , Retrospective Studies , SARS-CoV-2
9.
Abdom Radiol (NY) ; 46(12): 5485-5488, 2021 12.
Article in English | MEDLINE | ID: covidwho-1520333

ABSTRACT

As in any field, radiologists may face a number of challenges as they navigate their early careers. Because with experience comes wisdom, early-career radiologists may find helpful the advice and perspectives of mid- and late-career radiologists. The Society of Abdominal Radiology recognizes the value of this pool of knowledge and experience, prompting the establishment of the Early Career Committee. This group is designed to support early-career radiologists by sharing the experiences and insights of leaders in the field. In this series, the authors interview trailblazers Matthew S. Davenport, MD; Jonathan B. Kruskal, MD, PhD; Katherine E. Maturen, MD, MS; David B. Larson, MD, MBA; and Desiree E. Morgan, MD. This perspective explores a wide range of subjects, including personal values in medicine, the role of teleradiology, diversity of backgrounds in radiology, how to navigate workplace conflict, and lifelong learning in medicine. Beyond conveying these pearls of wisdom, the aim of this perspective is to highlight for early-career radiologists the value that mid- and late-career mentors can provide in navigating careers in medicine.


Subject(s)
Mentors , Radiology , Humans , Radiography , Radiologists
10.
J Thorac Imaging ; 37(2): 90-99, 2022 Mar 01.
Article in English | MEDLINE | ID: covidwho-1494141

ABSTRACT

PURPOSE: To assess the potential of a transfer learning strategy leveraging radiologist supervision to enhance convolutional neural network-based (CNN) localization of pneumonia on radiographs and to further assess the prognostic value of CNN severity quantification on patients evaluated for COVID-19 pneumonia, for whom severity on the presenting radiograph is a known predictor of mortality and intubation. MATERIALS AND METHODS: We obtained an initial CNN previously trained to localize pneumonia along with 25,684 radiographs used for its training. We additionally curated 1466 radiographs from patients who had a computed tomography (CT) performed on the same day. Regional likelihoods of pneumonia were then annotated by cardiothoracic radiologists, referencing these CTs. Combining data, a preexisting CNN was fine-tuned using transfer learning. Whole-image and regional performance of the updated CNN was assessed using receiver-operating characteristic area under the curve and Dice. Finally, the value of CNN measurements was assessed with survival analysis on 203 patients with COVID-19 and compared against modified radiographic assessment of lung edema (mRALE) score. RESULTS: Pneumonia detection area under the curve improved on both internal (0.756 to 0.841) and external (0.864 to 0.876) validation data. Dice overlap also improved, particularly in the lung bases (R: 0.121 to 0.433, L: 0.111 to 0.486). There was strong correlation between radiologist mRALE score and CNN fractional area of involvement (ρ=0.85). Survival analysis showed similar, strong prognostic ability of the CNN and mRALE for mortality, likelihood of intubation, and duration of hospitalization among patients with COVID-19. CONCLUSIONS: Radiologist-supervised transfer learning can enhance the ability of CNNs to localize and quantify the severity of disease. Closed-loop systems incorporating radiologists may be beneficial for continued improvement of artificial intelligence algorithms.


Subject(s)
COVID-19 , Pneumonia , Artificial Intelligence , Humans , Machine Learning , Pneumonia/diagnostic imaging , Radiologists , Retrospective Studies , SARS-CoV-2
11.
Clin Imaging ; 80: 16-18, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1491864

ABSTRACT

Breastfeeding has medical and economic benefits and providing an environment supportive of breastfeeding should be a priority in radiology to promote diversity, equity and inclusion. Most breastfeeding radiologists do not meet their breastfeeding goals and inadequate time for pumping is the most commonly cited barrier. The UCSF lactation credit model sets the standard for breastfeeding support in medicine by providing protected time without productivity penalties and it should be adapted and implemented across radiology practices to more fully support breastfeeding radiologists and radiation oncologists.


Subject(s)
Breast Feeding , Radiology , Female , Humans , Lactation , Radiography , Radiologists
12.
Rofo ; 194(2): 141-151, 2022 02.
Article in English, German | MEDLINE | ID: covidwho-1467161

ABSTRACT

BACKGROUND: Since its outbreak in December 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has infected more than 151 million people worldwide. More than 3.1 million have died from Coronavirus Disease 2019 (COVID-19), the illness caused by SARS-CoV-2. The virus affects mainly the upper respiratory tract and the lungs causing pneumonias of varying severity. Moreover, via direct and indirect pathogenetic mechanisms, SARS-CoV-2 may lead to a variety of extrapulmonary as well as vascular manifestations. METHODS: Based on a systematic literature search via PubMed, original research articles, meta-analyses, reviews, and case reports representing the current scientific knowledge regarding diagnostic imaging of COVID-19 were selected. Focusing on the imaging appearance of pulmonary and extrapulmonary manifestations as well as indications for imaging, these data were summarized in the present review article and correlated with basic pathophysiologic mechanisms. RESULTS AND CONCLUSION: Typical signs of COVID-19 pneumonia are multifocal, mostly bilateral, rounded, polycyclic or geographic ground-glass opacities and/or consolidations with mainly peripheral distribution. In severe cases, peribronchovascular lung zones are affected as well. Other typical signs are the "crazy paving" pattern and the halo and reversed halo (the latter two being less common). Venous thromboembolism (and pulmonary embolism in particular) is the most frequent vascular complication of COVID-19. However, arterial thromboembolic events like ischemic strokes, myocardial infarctions, and systemic arterial emboli also occur at higher rates. The most frequent extrapulmonary organ manifestations of COVID-19 affect the central nervous system, the heart, the hepatobiliary system, and the gastrointestinal tract. Usually, they can be visualized in imaging studies as well. The most important imaging modality for COVID-19 is chest CT. Its main purpose is not to make the primary diagnosis, but to differentiate COVID-19 from other (pulmonary) pathologies, to estimate disease severity, and to detect concomitant diseases and complications. KEY POINTS: · Typical signs of COVID-19 pneumonia are multifocal, mostly peripheral ground-glass opacities/consolidations.. · Imaging facilitates differential diagnosis, estimation of disease severity, and detection of complications.. · Venous thromboembolism (especially pulmonary embolism) is the predominant vascular complication of COVID-19.. · Arterial thromboembolism (e. g., ischemic strokes, myocardial infarctions) occurs more frequently as well.. · The most common extrapulmonary manifestations affect the brain, heart, hepatobiliary system, and gastrointestinal system.. CITATION FORMAT: · Gross A, Albrecht T. One year of COVID-19 pandemic: what we Radiologists have learned about imaging. Fortschr Röntgenstr 2022; 194: 141 - 151.


Subject(s)
COVID-19 , Pandemics , Humans , Lung/diagnostic imaging , Radiologists , SARS-CoV-2 , Tomography, X-Ray Computed
13.
Abdom Radiol (NY) ; 46(11): 5095-5104, 2021 11.
Article in English | MEDLINE | ID: covidwho-1465846

ABSTRACT

PURPOSE: To assess inter-reader agreement of key features from the SAR-AGA recommendations for the interpretation and reporting of MRE in adult patients with CD, focusing on the impact of radiologist experience on inter-reader agreement of CD phenotypes. METHODS: Two experienced and two less-experienced radiologists retrospectively evaluated 99 MRE in CD patients (50 initial MRE, 49 follow-up MRE) performed from 1/1/2019 to 3/20/2020 for the presence of active bowel inflammation (stomach, proximal small bowel, ileum, colon), stricture, probable stricture, penetrating disease, and perianal disease. The MRE protocol did not include dedicated perianal sequences. Inter-rater agreement was determined for each imaging feature using prevalence-adjusted bias-adjusted kappa and compared by experience level. RESULTS: All readers had almost-perfect inter-reader agreement (κ > 0.90) for penetrating disease, abscess, and perianal abscess in all 99 CD patients. All readers had strong inter-reader agreement (κ: 0.80-0.90) in 99 CD patients for active ileum inflammation, proximal small bowel inflammation, and stricture. Less-experienced readers had significantly lower inter-reader agreement for active ileum inflammation on initial than follow-up MRE (κ 0.68 versus 0.96, p = 0.018) and for strictures on follow-up than initial MRE (κ 0.76 versus 1.0, p = 0.027). Experienced readers had significantly lower agreement for perianal fistula on follow-up than initial MRE (κ: 0.55 versus 0.92, p = 0.008). CONCLUSION: There was strong to almost-perfect inter-reader agreement for key CD phenotypes described in the SAR-AGA consensus recommendations including active ileum and proximal small bowel inflammation, stricture, penetrating disease, abscess, and perianal abscess. Areas of lower inter-reader agreement could be targeted for future education efforts to further standardize CD MRE reporting. Dedicated perianal sequences should be included on follow-up MRE.


Subject(s)
Crohn Disease , Radiology , Adult , Consensus , Crohn Disease/diagnostic imaging , Humans , Magnetic Resonance Imaging , Observer Variation , Phenotype , Radiologists , Reproducibility of Results , Retrospective Studies , United States
15.
Clin Imaging ; 81: 60-61, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1439947

ABSTRACT

From the more than 700,000 deaths from COVID-19 in the US and the nearly 5 million worldwide, there emerge even more stories than match the statistics when one considers all of the patients' relations. While the numbers are staggering, when we humanize the stories, we are left with even greater devastation, of course. One of the stories among so many that seemed particularly salient and poignant to us was the death of Dr. Susan Moore. Her plaintive Facebook post, which went viral in December 2020, was made a few weeks before she died at the age of 52 from COVID-19 and claimed that she was a victim of racially biased treatment at a hospital in Indiana. It was Dr. Moore's mentioning of CT scans that led us to reflect on the biases of some health care workers and the role of radiologists. Our initial interface with our patients is actually not with their faces, but with their films. This dynamic does not eliminate any biases we may harbor but shields practitioners and patients from potential glaring racial biases in this first and sometimes only stage of the relationship.


Subject(s)
Attitude of Health Personnel , COVID-19 , Bias , Female , Humans , Radiologists , SARS-CoV-2
16.
Can Assoc Radiol J ; 73(2): 427, 2022 May.
Article in English | MEDLINE | ID: covidwho-1436998
17.
Br J Radiol ; 94(1126): 20210327, 2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1406741

ABSTRACT

OBJECTIVE: To describe the restructuring of services by British radiologists in response to evolving national guidelines and highlight the impact of the COVID-19 pandemic on the treatment of musculoskeletal (MSK) conditions. METHODS: An online anonymised survey was distributed via the British Society of Skeletal Radiology (BSSR) members forum in November 2020. Responses were collated using a standardised Google form including 21 questions. RESULTS: 135 members of the BSSR completed the survey. 85% of respondents stopped performing corticosteroid injections (CSI) during the initial lockdown of the pandemic. This was primarily influenced by national guidelines. The majority of respondents initially abstained from offered CSI procedures, then by November 2020, 69% of respondents were providing CSI for high and low risk patients, 23% were only providing CSI for low-risk patients with 8% still not performing any CSI. 40% of respondents reported routinely obtaining specific written consent regarding the risk of COVID-19. Approximately, 11,000 CSI were performed by respondents between March and November 2020 with no reported significant COVID-19-related complications. Over 80% of BSSR members reported that the number of CSI procedures that they performed dropped by more than 80% compared to usual. 73% of respondents reported an increased backlog of patients awaiting treatment. The average waiting time for routine outpatient CSI treatment was > 12 weeks in 53% of responses, compared to 34% the previous year. CONCLUSION: The COVID-19 pandemic has had a significant impact on the clinical practices of MSK radiologists in the UK. Our survey highlights the rapid response of BSSR members as national guidelines evolved. Currently, the majority of respondents are performing CSI for musculoskeletal conditions when clinically indicated, with enhanced consent. However, the pandemic has resulted in increased waiting times - delaying the treatment of patients who may be suffering with significant pain and disability. Further research is warranted to provide guidance around both service recovery and provision of CSI around COVID-19 vaccination schedules. ADVANCES IN KNOWLEDGE: BSSR members responded rapidly to changing guidelines during the COVID-19 pandemic. The majority of respondents are currently performing CSI when clinically indicated. The pandemic has resulted in a significant increase in waiting times which will have a significant impact on UK musculoskeletal services.


Subject(s)
Adrenal Cortex Hormones/administration & dosage , COVID-19/epidemiology , Musculoskeletal Diseases/drug therapy , Practice Patterns, Physicians'/statistics & numerical data , Radiologists , England/epidemiology , Guideline Adherence , Humans , Pandemics , SARS-CoV-2 , Surveys and Questionnaires
18.
Acad Radiol ; 28(11): 1582-1585, 2021 11.
Article in English | MEDLINE | ID: covidwho-1404697

ABSTRACT

The fifth Association of University Radiologists (AUR) Academic Radiology and Leaders Roundtable took place the day after the conclusion of the AUR annual meeting in May 2021 and involved leaders in academic radiology departments across the United States, and industry from companies who provide quintessential services to radiology departments. The open-ended discussion identified the key challenges facing the practice and business of radiology as we jointly move forward after the COVID-19 pandemic. Particular attention was paid to the identification of viable solutions that radiology departments should embrace to sustain clinical productivity, innovation, and well-being, and the ways that industry could contribute significantly to that endeavor.


Subject(s)
COVID-19 , Radiology , Humans , Pandemics , Radiologists , Radiology/education , SARS-CoV-2 , United States , Universities
19.
AJR Am J Roentgenol ; 218(2): 370-374, 2022 02.
Article in English | MEDLINE | ID: covidwho-1399088

ABSTRACT

Physician burnout is increasingly recognized as a public health crisis given the impact of burnout on physicians, their families, patients, communities, and population health. The COVID-19 pandemic has superimposed a new set of challenges for physicians to navigate, including unique challenges presented to radiologists. Radiologists from a diversity of backgrounds, practice settings, and career stages were asked for their perspectives on burnout.


Subject(s)
Burnout, Professional/epidemiology , Burnout, Professional/psychology , COVID-19/psychology , Radiologists/psychology , Radiologists/statistics & numerical data , Humans , SARS-CoV-2 , Surveys and Questionnaires/statistics & numerical data , United States/epidemiology
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