General Radiologists Research Articles

Performance of RAPID noncontrast CT stroke platform in large vessel occlusion and intracranial hemorrhage detection.

Noncontrast CT (NCCT) is used to evaluate for intracerebral hemorrhage (ICH) and ischemia in acute ischemic stroke (AIS). Large vessel occlusions (LVOs) are a major cause of AIS, but challenging to detect on NCCT. The purpose of this study is to evaluate an AI software called RAPID NCCT Stroke (RAPID, iSchemaView, Menlo Park, CA) for ICH and LVO detection compared to expert readers. In this IRB approved retrospective, multicenter study, stand-alone performance of the software was assessed based on the consensus of 3 neuroradiologists and sensitivity and specificity were determined. The platform's performance was then compared to interpretation by readers comprised of eight general radiologists (GR) and three neuroradiologists (NR) in detecting ICH and hyperdense vessel sign (HVS) indicating LVO. A total of 244 cases were included. Of the 244, 115 were LVOs and 26 were ICHs. One hundred three cases did not have LVO nor ICH. Stand-alone performance of the software demonstrated sensitivities and specificities of 96.2 and 99.5% for ICH and 63.5 and 95.1% for LVO detection. Compared to all 11 readers and eight GR readers only respectively, the software demonstrated superiority, achieving significantly higher sensitivities (63.5% versus 43.6%, p < 0.0001 and 63.5% versus 40.9%, p = 0.001). The RAPID NCCT Stroke platform demonstrates superior performance to radiologists for detecting LVO from a NCCT. Use of this software platform could lead to earlier LVO detection and expedited transfer of these patients to a thrombectomy capable center.

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation

Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification problem. T1-CE, T2WI, and FLAIR 3D-segmented masks of 307 patients (157 GB and 150 BM) were generated post resampling, co-registration normalization and semi-automated 3D-segmentation and used for internal model development. Subsequent external validation was performed on 59 cases (27GB and 32 BM) from another institution. Four different mask-sequence combinations were evaluated using area under the curve (AUC), precision, recall and F1-scores. Diagnostic performance of a neuroradiologist and a general radiologist, both without and with the model output available, was also assessed. 3D-model using the T1-CE tumor mask (TM) showed the highest performance [AUC 0.93 (95% CI 0.858-0.995)] on the external test set, followed closely by the model using T1-CE TM and FLAIR mask of peri-tumoral region (PTR) [AUC of 0.91 (95% CI 0.834-0.986)]. Models using T2WI masks showed robust performance on the internal dataset but lower performance on the external set. Both neuroradiologist and general radiologist showed improved performance with model output provided [AUC increased from 0.89 to 0.968 (p=0.06) and from 0.78 to 0.965 (p=0.007) respectively], the latter being statistically significant. 3D-CNNs showed robust performance for differentiating GB from BMs, with T1-CE TM, either alone or combined with FLAIR-PTR masks. Availability of model output significantly improved the accuracy of the general radiologist.

Peritoneal Dialysis Catheter Complications after Insertion by Surgeons, Radiologists, or Nephrologists.

The Advancing American Kidney Health Initiative aims to increase rates of utilization of peritoneal dialysis (PD) in the United States. One of the first steps to PD is successful catheter placement, which can be performed by surgeons, interventional radiologists, or nephrologists. We examined the association between operator subspecialty and risk of needing a follow-up procedure in the first 90 days after initial PD catheter implantation. Overall, we found that 15.5% of catheters required revision, removal, or a second catheter placement within 90 days. The odds of requiring a follow-up procedure was 36% higher for interventional radiologists and 86% higher for interventional nephrologists compared with general surgeons. Further research is needed to understand how to optimize the function of catheters across different operator types. The US government has implemented incentives to increase the use of PD. Successful placement of PD catheters is an important step to increasing PD utilization rates. Our objective was to compare initial outcomes after PD catheter placement by different types of operators. We included PD-naïve patients insured by Medicare who had a PD catheter inserted between 2010 and 2019. We examined the association between specialty of the operator (general surgeon, vascular surgeon, interventional radiologist, or interventional nephrologist) and odds of needing a follow-up procedure, which we defined as catheter removal, replacement, or revision within 90 days of the initial procedure. Mixed logistic regression models clustered by operator were used to examine the association between operator type and outcomes. We included 46,973 patients treated by 5205 operators (71.1% general surgeons, 17.2% vascular surgeons, 9.7% interventional radiologists, 2.0% interventional nephrologists). 15.5% of patients required a follow-up procedure within 90 days of the initial insertion, of whom 2.9% had a second PD catheter implanted, 6.6% underwent PD catheter removal, and 5.9% had a PD catheter revision within 90 days of the initial insertion. In models adjusted for patient and operator characteristics, the odds of requiring a follow-up procedure within 90 days were highest for interventional nephrologists (HR, 1.86; 95% confidence interval [CI], 1.56 to 2.22) and interventional radiologists (odds ratio, 1.36; 95% CI, 1.17 to 1.58) followed by vascular surgeons (odds ratio, 1.06; 95% CI, 0.97 to 1.14) compared with general surgeons. The probability of needing a follow-up procedure after initial PD catheter placement varied by operator specialty and was higher for interventionalists and lowest for general surgeons.

The 2021 ACR/RBMA Workforce Survey: Practice Types, Employment Trends, and Hiring Needs

PurposeThe aim of this study was to analyze current radiology practice types, specific subspecialty needs, employment trends, and retirement trends. MethodsACR members, nonmembers, and Radiology Business Management Association members were surveyed using predominantly structured closed-ended questions about a variety of current and recent radiology practice characteristics. Responses were group practice deduplicated and weighted. ResultsOf 1,702 survey respondents, 64% were men, with a median age of 51 years. In 2021, 62% of responding practices hired radiologists, with the average practice hiring 2 radiologists and academic practices on average hiring the most (3.5). Most radiologists (87%) were hired for full-time positions, with independent practices hiring the largest proportion of part-time positions. Body and breast imagers represented the largest numbers of hired radiologists (17% each). Practices anticipated similar hiring patterns in 2022, prioritizing breast (37%) and body (35%) imaging. Of all practice types, academic groups were least likely to prioritize general radiologist hiring. A large majority (82%) of radiology practices permit remote work (teleradiology), more common at academic than other practices. Of currently employed radiologists, 16% plan to seek new employment in the next year; early-career radiologists indicated the highest likelihood (92%) and academic radiologists the lowest (66%) of remaining in the same practice for at least 5 years. A large majority of practices (80%) reported no radiologist retirements in 2021. Of those retiring, the average age was 75 years, and 66% worked full-time until retirement. ConclusionsRadiologist recruiting remains robust. Current information on practice characteristics may help inform radiology practice leaders seeking to right-size their groups.

EMBOLIZATION FOR THE TREATMENT OF DELAYED HEMATURIA RENAL ARTERY PSEUDOANEURYSM FOLLOWING BLUNT TRAUMA

Background: The occurrence of a renal artery pseudoaneurysm after blunt renal trauma is an infrequent complication. The occurrence of delayed bleeding is typically observed within a period of 2 to 3 weeks following an injury and is commonly attributed to the presence of an arteriovenous malformation (AVM) or pseudoaneurysm. They are frequently observed in cases of injuries of greater severity or trauma that penetrates the body. The application of angiographic catheterization is efficacious in the detection of pseudoaneurysms in the renal artery. The management of renal pseudoaneurysms necessitates the consideration of distinct clinical associations, including the location and size of the lesion as well as the presence of symptoms.&#x0D; Objective: The objective of this study is to provide a detailed account of the use of an angiographic catheter and embolization in the treatment of a patient afflicted with a post-traumatic renal artery pseudoaneurysm.&#x0D; Materials and Methods: Conducting a literature review and medical records.&#x0D; Results: A case of renal artery pseudoaneurysm is presented. A male individual aged 33 sought medical attention at the emergency department following a motorcycle collision and exhibited symptoms of pain in the right flank region. The individual underwent a medical intervention involving the placement of a double J stent. After a period of nearly fourteen days, the individual reported experiencing hematuria. The abdominal CT scan revealed a renal injury on the right side with an AAST grade of 4, while the renal CTA demonstrated the presence of a pseudoaneurysm. A pseudoaneurysm was observed at the renal poles on the right side through the use of an angiographic catheter. The procedure of selective embolization utilising coils was executed on the renal arteries located at the lower and middle poles of the right kidney.&#x0D; Conclusion: The occurrence of renal artery pseudoaneurysms is infrequent; however, it is a grave complication that may arise from renal trauma. The accurate diagnosis and effective management of pseudoaneurysms are of paramount importance due to their potential to cause severe and potentially fatal complications if left untreated. The diagnostic process for pseudoaneurysms heavily relies on the involvement of the general radiologist. Interventional radiology provides alternative minimally invasive procedures that are linked to reduced morbidity and mortality rates and have replaced surgical interventions in the management of certain conditions.&#x0D; Keywords: pseudoaneurysm, angiographic catheter, embolization

Spontaneous Intracranial Hypotension: A Review of Neuroimaging and Current Concepts.

Spontaneous intracranial hypotension (SICH) is the emerging cause of orthostatic headache as it has been better recognized in recent years. SICH happens due to spinal cerebrospinal fluid (CSF) leak; however, the manifestations are predominantly cranial and hence imaging in SICH includes brain and spine. There are few characteristic brain imaging features to be concerned about to diagnose SICH in patients with vague symptoms or low clinical suspicion. Spine screening is recommended in these patients to assess spinal CSF leaks. While neuroradiologists play a significant role from the time of diagnosis to treatment of SICH, there is a need for all the general radiologists to be aware of the condition. Computed tomography myelogram and digital subtraction myelogram are performed for diagnostic and therapeutic management of SICH. There is a known risk for SICH recurrence in patients with sagittal longitudinal epidural collection and hence, targeted blood patch should be used instead of blind patch. Most importantly, slow mobilization is recommended following the patch to avoid recurrence.

Introducing Paediatric Radiology As A Subspecialty In Pakistan: Bridging The Gap In Healthcare.

Madam, Radiology is a rapidly progressing field that significantly contributes to disease diagnosis and treatment monitoring. Recent advancements in the field have improved evidence-based medicine for patient care. Despite substantial growth in Pakistan, limited opportunities for sub-specialisation training in radiology are available in Pakistan. Just a few institutions offer training in sub-specialties such as women's imaging, neurologic radiology, interventional radiology, and body imaging. There has been significant evolution in pediatric radiology, which has now emerged as a distinct field requiring solid foundations. Unfortunately, due to undefined training opportunities, pediatric radiology is being neglected in Pakistan. Pediatric radiology requires specialized training due to anatomical variations and unique disease presentations in children. Even senior general radiologists may lack confidence when reporting pediatric cases. Radiology demands updated knowledge and expertise in diagnostic tools, making it challenging to keep up. Reporting pitfalls in pediatrics differ from adults due to varying growth patterns and myelination making expert knowledge essential for accurate reporting in multiple conditions. The acceptable radiation doses and protocols for imaging studies are also different, considering children’s susceptibility to ionizing radiation3. The European Society of Radiology highlighted the importance of integrating pediatric radiology training4. Many other countries, including the USA and Europe, have sub-specializations and accreditations despite having lower proportions of children in their populations compared to Pakistan. Advocacy movements for pediatric radiology have also emerged in other developing nations like Nigeria5. Pakistan is a largely populated country, with approximately 35% being pediatric population and multiple radiological cases being reported daily. It seems a gross neglect not to cater specifically to such a large proportion of the people. Therefore, there is a dire need to recognize pediatric radiology as a formal subspeciality that requires redrafting of the curriculum. The subspecialty should focus on a particular area and offer comprehensive and consistent training to interested individuals.

Reporting of Participant Demographics in Clinical Trials Published in General Radiology Journals

The reporting of research participant demographics provides insights into study generalizability. Our study aimed to determine the frequency at which participant age, sex/gender, race/ethnicity, and socioeconomic status (SES) are reported and used for subgroup analyses in radiology randomized controlled trials (RCTs) and their secondary analyses; as well as the study characteristics associated with, and the classification systems used for demographics reporting. RCTs and their secondary analyses published in 8 leading radiology journals between 2013 and 2021 were included. Associations between study characteristics and demographic reporting were tested with the chi-square goodness of fit test for categorical variables, Wilcoxon-Mann-Whitney test for impact factor, and logistic regression for publication year. Among 432 included articles, 89.4% (386) reported age, 90.3% (390) sex/gender, 5.6% (24) race/ethnicity, and 3.0% (13) SES. Among articles that reported these demographics and were not specific to a subgroup, results were analyzed by age in 14.2% (55/386), sex/gender in 19.4% (66/340), race/ethnicity in 13.6% (3/22), and SES in 46.2% (6/13).Journal, impact factor, and last author continent were predictors of race/ethnicity and SES reporting. Funding was associated with race/ethnicity reporting. No study reported sex and gender separately, or documented transgender, nonbinary gender spectrum or intersex participants. A single category for race/ethnicity was used in 37.5% (9/24) of studies, consisting of either "White" or "Caucasian." The reporting of participant demographics in radiology trials is variable and not always representative of the population diversity. Editorial guidelines on the reporting and analysis of participant demographics could help standardize practices.

ThTP5.5 The Emergency laparotomy – “scans, tubes and scalpels”. A report from the UK’s first collaborative National Emergency Laparotomy Audit (NELA) training meeting

Abstract Background &amp; Aims Time-critical emergency laparotomies are routinely performed nationally. These complex patients often require multi-disciplinary discussion of pre-operative imaging and intra-operative and post-operative status. NELA is designed to improve patient outcomes, encouraging regular audit and quality improvement. We report the outcomes of the UK’s first collaborative NELA training meeting from a Major Trauma Centre in London This unique meeting aimed to: Methods Three complex laparotomy patients were discussed using case-based discussions involving General Surgery, Anaesthetics and Radiology and involving imaging, intra-operative photographs and anaesthetic information. Pre- and post-meeting participant questionnaires were disseminated for comparative analysis. Results 39 attended the evening (50% radiologists, 25% surgeons, 25% anaesthetists); two thirds’ trainees. 100% attendee satisfaction rate was recorded. 46% of attendees were not aware of NELA prior to the meeting. Post meeting, 95% of attendees were confident in their understanding of the NELA process. There was a 25% increase in the knowledge of NELA reporting outcome measures (to 95%) and 90% correctly named the specialities involved. 96% of attendees reported interest in attending a subsequent meeting. Conclusion Complex emergency patients require expert cross-specialty input to drive improvements in patient outcomes. We believe this to be the first multidisciplinary NELA education meeting. Improvement in attendee understanding demonstrates the success of shared learning via case-based discussion to improve patient care. We aim to continue local meetings with aspirations to future national events.

Neurologic pathologies of the vertebral spine.

At some institutions, musculoskeletal and general radiologists rather than neuroradiologists are responsible for reading magnetic resonance imaging (MRI) of the spine. However, neurological findings, especially intrathecal ones, can be challenging. Intrathecal neurological findings in the spine can be classified by location (epidural, intradural extramedullary, and intramedullary) or etiology (tumor, infection, inflammatory, congenital). In this paper, we provide a succinct review of the intrathecal neurological findings that can be seen on MRI of the spine, primarily by location and secondarily by etiology, in order that this may serve as a helpful guide for musculoskeletal and general radiologists when encountering intrathecal neurological pathologies.

Investigation of the Radiographic Imaging Volume and Occupational Dose of Radiologic Technologists before and during the COVID-19 Pandemic.

This study aimed to assess occupational radiation doses for radiologic technologists (RTs) in Saudi Arabia shortly before and during the COVID-19 pandemic, considering changes in imaging volume during that time. This retrospective study included the imaging volume data and the RTs' occupational dose records from a central hospital for 2019 and 2020. The occupational dose-in terms of annual and quarterly mean effective doses (AMEDs and QMEDs)-was estimated for 115 RTs using thermoluminescent dosimeter records. There was a 22% increase in the AMED in 2020 compared with 2019, though the overall imaging volume decreased by 9% in 2020. The percentage changes in AMEDs between 2019 and 2020 for general radiography (GR), computed tomography (CT), interventional radiology (IR), nuclear medicine (NM), and mammography (MG) were 45%, 56%, 9%, 18% and -2%, respectively. The highest contribution to AMEDs in 2020 for modalities was due to GR and CT procedures, accounting for 0.50 mSv and 0.58 mSv, respectively. The percentage change in imaging volumes between 2019 and 2020 depicted a slight decrease in Q2 (-1%) and a substantial decrease in Q1 (-10%), Q3 (-12%), and Q4 (-11%) for 2020. The overall percentage changes in imaging volumes in 2020 for GR (conventional and mobile), CT, IR, NM, and MG were -7% (-19% and 48%), -11%, 13%, -26%, and -46%, respectively. Investigating the changes in 2020 by comparing Q1 of 2020 (before the pandemic restrictions) with Q2 (during the pandemic restrictions and changes in workflow) revealed that the QMED during Q2 increased by 5% with a 17.4% decrease in the imaging volume. However, CT procedures were increased by 11.1% during the pandemic restrictions in Q2 of 2020, with an increase in the corresponding QMED of 66%. Moreover, mobile GR procedures increased by 21% in Q2 of 2020 compared to Q1. This study indicated the impact of the COVID-19 pandemic on imaging volume and occupational dose. Overall, the study observed a decrease in the imaging volume and an increase in RTs' effective doses by 2020. However, there was an increase in mobile GR and CT examinations during the COVID-19 pandemic restrictions in 2020. This study suggested that the increased mobile GR and CT examinations contributed to greater effective doses for RTs in 2020.

Real world validation of an AI-based CT hemorrhage detection tool.

Intracranial hemorrhage (ICH) is a potentially life-threatening medical event that requires expedited diagnosis with computed tomography (CT). Automated medical imaging triaging tools can rapidly bring scans containing critical abnormalities, such as ICH, to the attention of radiologists and clinicians. Here, we retrospectively investigated the real-world performance of VeriScout™, an artificial intelligence-based CT hemorrhage detection and triage tool. Ground truth for the presence or absence of ICH was iteratively determined by expert consensus in an unselected dataset of 527 consecutively acquired non-contrast head CT scans, which were sub-grouped according to the presence of artefact, post-operative features and referral source. The performance of VeriScout™ was compared with the ground truths for all groups. VeriScout™ detected hemorrhage with a sensitivity of 0.92 (CI 0.84-0.96) and a specificity of 0.96 (CI 0.94-0.98) in the global dataset, exceeding the sensitivity of general radiologists (0.88) with only a minor relative decrement in specificity (0.98). Crucially, the AI tool detected 13/14 cases of subarachnoid hemorrhage, a potentially fatal condition that is often missed in emergency department settings. There was no decrement in the performance of VeriScout™ in scans containing artefact or postoperative change. Using an integrated informatics platform, VeriScout™ was deployed into the existing radiology workflow. Detected hemorrhage cases were flagged in the hospital radiology information system (RIS) and relevant, annotated, preview images made available in the picture archiving and communications system (PACS) within 10 min. AI-based radiology worklist prioritization for critical abnormalities, such as ICH, may enhance patient care without adding to radiologist or clinician burden.

Chromosomal Aberrations, Micronuclei, Blood Parameters and Received Doses in Workers Exposed to Ionizing Radiation.

The aim of this study was to analyze the impact of low doses of ionizing radiation on healthcare workers using dosimeter data and several biomarkers of effects, and to asses the suitability of those tests. Data from the last medical examinations, obtained from the medical records of 148 employees were analysed. They were divided into three groups: nuclear medicine, interventional radiology and general radiology. The examination included hematological parameters and cytogenetical tests: unstable chromosomal aberrations (UCA) and micronucleus test (MNT). The received cumulative 5-year dose was calibrated into personal dose equivalents Hp(10). A statistically significant difference was found between the groups in the UCAs (c2=6.634, p=0.036) with the highest UCA frequency in nuclear medicine. The ANOVA showed a statistically significant difference in the values of erythrocytes (F(2,140)=3.715, p=0.027), monocytes (F(2,127)=3.326, p=0.039) and platelets (F(2,135)=4.209, p=0.017), with higher erythrocytes and lower platelets in interventional radiology and lower monocytes in nuclear medicine, all with small effect size. The dose was significantly different among the groups (c2 =22,191; p<0.001). The nuclear medicine workers received a higher dose compared to interventional radiology (U=458, p<0.001) and general radiology (U=510.5, p<0.001). Nuclear medicine employees are at a higher risk of developing neoplastic and blood-related diseases due to consistent exposure to low doses of ionizing radiation. Results suggest that UCA test might be more suitable for detecting radiation-induced damage at low doses than MNT. Compulsory monitoring of the health status at periodic examinations is required to prevent occupational diseases, esp. among the nuclear medicine workers.

Information extraction from weakly structured radiological reports with natural language queries

ObjectivesProvide physicians and researchers an efficient way to extract information from weakly structured radiology reports with natural language processing (NLP) machine learning models.MethodsWe evaluate seven different German bidirectional encoder representations from transformers (BERT) models on a dataset of 857,783 unlabeled radiology reports and an annotated reading comprehension dataset in the format of SQuAD 2.0 based on 1223 additional reports.ResultsContinued pre-training of a BERT model on the radiology dataset and a medical online encyclopedia resulted in the most accurate model with an F1-score of 83.97% and an exact match score of 71.63% for answerable questions and 96.01% accuracy in detecting unanswerable questions. Fine-tuning a non-medical model without further pre-training led to the lowest-performing model. The final model proved stable against variation in the formulations of questions and in dealing with questions on topics excluded from the training set.ConclusionsGeneral domain BERT models further pre-trained on radiological data achieve high accuracy in answering questions on radiology reports. We propose to integrate our approach into the workflow of medical practitioners and researchers to extract information from radiology reports.Clinical relevance statementBy reducing the need for manual searches of radiology reports, radiologists’ resources are freed up, which indirectly benefits patients.Key Points• BERT models pre-trained on general domain datasets and radiology reports achieve high accuracy (83.97% F1-score) on question-answering for radiology reports.• The best performing model achieves an F1-score of 83.97% for answerable questions and 96.01% accuracy for questions without an answer.• Additional radiology-specific pretraining of all investigated BERT models improves their performance.Graphical

A Context-based Chatbot Surpasses Trained Radiologists and Generic ChatGPT in Following the ACR Appropriateness Guidelines.

Background Radiological imaging guidelines are crucial for accurate diagnosis and optimal patient care as they result in standardized decisions and thus reduce inappropriate imaging studies. Purpose In the present study, we investigated the potential to support clinical decision-making using an interactive chatbot designed to provide personalized imaging recommendations from American College of Radiology (ACR) appropriateness criteria documents using semantic similarity processing. Methods We utilized 209 ACR appropriateness criteria documents as specialized knowledge base and employed LlamaIndex, a framework that allows to connect large language models with external data, and the ChatGPT 3.5-Turbo to create an appropriateness criteria contexted chatbot (accGPT). Fifty clinical case files were used to compare the accGPT's performance against general radiologists at varying experience levels and to generic ChatGPT 3.5 and 4.0. Results All chatbots reached at least human performance level. For the 50 case files, the accGPT performed best in providing correct recommendations that were "usually appropriate" according to the ACR criteria and also did provide the highest proportion of consistently correct answers in comparison with generic chatbots and radiologists. Further, the chatbots provided substantial time and cost savings, with an average decision time of 5 minutes and a cost of 0.19 € for all cases, compared to 50 minutes and 29.99 € for radiologists (both p < 0.01). Conclusion ChatGPT-based algorithms have the potential to substantially improve the decision-making for clinical imaging studies in accordance with ACR guidelines. Specifically, a context-based algorithm performed superior to its generic counterpart, demonstrating the value of tailoring AI solutions to specific healthcare applications.

Preventing lost-to-follow up diagnostic imaging in ambulatory care: evaluation of an electronic notification tool

ObjectiveMissed or cancelled imaging tests may be invisible to the ordering clinician and result in diagnostic delay. We developed an outpatient results notification tool (ORNT) to alert physicians of patients’...

Navigating Minority and Gender Discrimination, Substance Use Disorder, Financial Distress, and Workplace Politics: Lessons for Work-Life Wellness in Academic Medicine: Part 2 of 3.

In this second of three manuscripts addressing a range of complex work and personal issues, the authors explore case scenarios with characters who work in the fields of general surgery, orthopedic surgery, anesthesiology, neurology, radiology, and otolaryngology. The medical specialty identifiers help inform some baseline understanding of the demands of that particular profession but are less pertinent than the specifics of each case. In this manuscript, the authors dive into the topics of navigating a lawsuit and professional burnout, personal finances, substance use disorder, demands of clinical work and workplace politics, diversity and inclusion, and dealing with major personal illness. The authors provide practical steps to help the readers deal with similar situations and provide insight to support persons on how to improve support structures.

The peer review process: A survey among scientists in radiology

PurposeTo map the experience and view of scientists in radiology on the peer review process. MethodA survey with 12 closed-ended questions and 5 conditional sub-questions was conducted among corresponding authors who published in general radiology journals. Results244 corresponding authors participated. In considering a peer review invitation, most respondents found the topic and the availability of time very important (62.1% [144/132] and 57.8% [134/232], respectively), the quality of the abstract, the prestige/impact factor of the journal, and the sense of professional duty important (43.7% [101/231], 42.2% [98/232], and 53.9% [125/232], respectively), and were indifferent about a reward (35.3% [82/232]). However, 61.1% (143/234) believed that a reviewer should be rewarded. Direct financial compensation (27.6% [42/152]), discounted fees for society memberships, conventions, and/or journal subscriptions (24.3% [37/152]), and Continuing Medical Education credits (23.0% [35/152]) were the most frequently desired rewards. 73.4% (179/244) of respondents never received formal peer review training, of whom 31.2% (54/173) would like to, particularly less experienced researchers (Chi-Square P = 0.001). The median reported review time per article was 2.5 h. 75.2% (176/234) of respondents found it acceptable that a manuscript is rejected by an editor without formal peer review. The double-blinded peer review model was preferred by most respondents (42.3% [99/234]). A median of 6 weeks was considered the maximum acceptable time from manuscript submission to initial decision by a journal. ConclusionPublishers and journal editors may use the experiences and views of authors that were provided in this survey to shape the peer review process.

Chest Radiography of Tuberculosis: Determination of Activity Using Deep Learning Algorithm.

Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

Global hemodialysis vascular access care: Three decades of evolution.

The development of vascular access for hemodialysis has come a long way since 1943 when the first hemodialysis treatment was performed in humans by connecting an artery and vein using an external glass canula. Since then, vascular access care has evolved robustly through contributions from numerous countries and professional nephrology societies, worldwide. To understand the global distribution and contribution of different specialties to medical literature on dialysis vascular access care, we performed a literature search from 1991 to 2021 and identified 2768 articles from 74 countries. The majority of publications originated from the United States (41.5%), followed by China (5.1%) and the United Kingdom (4.6%). Our search results comprise of observational studies (43%), case reports/series (27%), review articles (16.5%) and clinical trials (12%). A large proportion of articles were published in Nephrology journals (49%), followed by General Medicine (14%), Surgery (10%), Vascular Medicine (8%), and Interventional Radiology journals (4%). With the introduction of interventional nephrology, nephrologists will be able to assume the majority of the responsibility for dialysis vascular access care and above all maintain a close interdisciplinary collaboration with other specialties to provide optimum patient care. In this review article, we discuss the history, evolving knowledge, challenges, educational opportunities, and future directions of dialysis vascular access care, worldwide.