Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes最新文献

Purpose: Use a tailored version of the Quality Assessment of Diagnostic Accuracy Studies tool to evaluate risk of bias and applicability across LIRADS related publications. Method: A tailored QUADAS-2 tool was created through consensus approach to assess risk of bias and applicability across 37 LI-RADS related publications. Studies were selected from 2017 to 2022 using the assistance of experienced hospital librarians to search for studies evaluating the diagnostic accuracy of CT, MRI, or contrast-enhanced ultrasound for HCC using LI-RADS through multiple different databases. QUADAS-2 assessments were performed in duplicate and independently by 2 authors with experience using the QUADAS-2 tool. Disagreements were resolved with a third expert reviewer. Consensus QUADAS-2 assessments were tabulated for each domain. Results: Using the tailored QUADAS-2 tool, 31 of the 37 included LI-RADS studies were assessed as high risk of bias, and 9 out of 37 studies demonstrated concerns for applicability. Patient selection (21 out of 37 studies) and flow/timing (24 out of 37 studies) domains demonstrated the highest risk of bias. 6 out of 37 studies in the index domain demonstrated high risk of bias. 2 out of 37 studies showed high risk of bias in the reference standard domain. Conclusion: A significant proportion of LI-RADS research is at risk of bias with concerns for applicability. Identifying risk of bias in such research is essential to recognize limitations of a study that may affect the validity of the results. Areas for improvement in LI-RADS research include reducing selection bias, avoiding inappropriate exclusions, and decreasing verification bias.

In tandem with the ever-increasing global population, the demand for diagnostic radiology service provision is on the rise and at a disproportionate rate compared to the number of radiologists available to practice. The current "revolution in robotics" promises to alleviate personnel shortages in many sectors of industry, including medicine. Despite negative depictions of robots in popular culture, their multiple potential benefits cannot be overlooked, in particular when it comes to health service provision. The type of robots used for interventional procedures are largely robotic-assistance devices, such as the Da Vinci surgical robot. Advances have also been made with regards to robots for image-guided percutaneous needle placement, which have demonstrated superior accuracy compared to manual methods. It is likely that artificial intelligence will come to play a key role in the field of robotics and will result in an increase in the levels of robotic autonomy attainable. However, this concept is not without ethical and legal considerations, most notably who is responsible should an error occur; the physician, the robot manufacturer, software engineers, or the robot itself? Efforts have been made to legislate in order to protect against the potentially harmful effects of unexplainable "black-box" decision outputs of artificial intelligence systems. In order to be accepted by patients, studies have shown that the perceived level of trustworthiness and predictability of robots is crucial. Ultimately, effective, widespread implementation of medical robotic systems will be contingent on developers remaining cognizant of factors that increase human acceptance, as well as ensuring compliance with regulations.

Radiology in France has made major advances in recent years through innovations in research and clinical practice. French institutions have developed innovative imaging techniques and artificial intelligence applications in the field of diagnostic imaging and interventional radiology. These include, but are not limited to, a more precise diagnosis of cancer and other diseases, research in dual-energy and photon-counting computed tomography, new applications of artificial intelligence, and advanced treatments in the field of interventional radiology. This article aims to explore the major research initiatives and technological advances that are shaping the landscape of radiology in France. By highlighting key contributions in diagnostic imaging, artificial intelligence, and interventional radiology, we provide a comprehensive overview of how these innovations are improving patient outcomes, enhancing diagnostic accuracy, and expanding the possibilities for minimally invasive therapies. As the field continues to evolve, France's position at the forefront of radiological research ensures that these innovations will play a central role in addressing current healthcare challenges and improving patient care on a global scale.

Background: Image-guided tumour ablation is a minimally invasive treatment for early stage hepatocellular carcinoma (HCC). Our study reviews the complications and long term outcomes in patients treated at a tertiary referral centre. Methods: Retrospective study. All patients with HCC who underwent microwave ablation (MWA) or radiofrequency ablation (RFA) from 1st January 2014 to 31st December 2022 were identified. Treatment response of target lesion, complications, and survival were recorded. Results: One hundred seventy ablations were performed in 118 patients; 70% MWA, 30% RFA. Median radiological follow-up 21 months (range 3-107). Follow-up imaging was reported using LI-RADS and mRECIST. At first follow-up imaging, 94 patients had complete response (primary efficacy rate 80.3%) while 19.7% (n = 23) had residual disease. Fifteen of these had repeat ablation; 10 had complete response (secondary efficacy rate 85.6%). By end of study duration, 70.5% (n = 79) achieved sustained local complete response from single ablation without documented recurrence. 14.3% (n = 16) required more than one ablation of target lesion. Overall, 84.8% (n = 95) demonstrated long term local complete response to ablation. Complication occurred in 5.9% (n = 10); 40.0% Grade I, 40.0% Grade II, 10.0% Grade III, 10.0% Grade IV as per the CIRSE Classification. 1-, 3-, and 5-year overall survival (OS) rate was 97%, 68%, and 61% respectively. Mean OS was 5.3 years (median 4.7). No difference in OS (P = .7) or local progression free survival (P = .5) between patients treated with MWA versus RFA. Conclusion: This study demonstrates excellent long-term response to TA, with acceptable complication profile. No difference in survival between RFA versus MWA.

Purpose: To evaluate the clinical performance of a Protocol Recommendation System (PRS) automatic protocolling of chest CT imaging requests. Materials and Methods: 322 387 consecutive historical imaging requests for chest CT between 2017 and 2022 were extracted from a radiology information system (RIS) database containing 16 associated patient information values. Records with missing fields and protocols with <100 occurrences were removed, leaving 18 protocols for training. After freetext pre-processing and applying CLEVER terminology word replacements, the features of a bag-of-words model were used to train a multinomial logistic regression classifier. Four readers protocolled 300 clinically executed protocols (CEP) based on all clinically available information. After their selection was made, the PRS and CEP were unblinded, and the readers were asked to score their agreement (1 = severe error, 2 = moderate error, 3 = disagreement but acceptable, 4 = agreement). The ground truth was established by the readers' majority selection, a judge helped break ties. For the PRS and CEP, the accuracy and clinical acceptability (scores 3 and 4) were calculated. The readers' protocolling reliability was measured using Fleiss' Kappa. Results: Four readers agreed on 203/300 protocols, 3 on 82/300 cases, and in 15 cases, a judge was needed. PRS errors were found by the 4 readers in 1%, 2.7%, 1%, and 0.7% of the cases, respectively. The accuracy/clinical acceptability of the PRS and CEP were 84.3%/98.6% and 83.0%/99.3%, respectively. The Fleiss' Kappa for all readers and all protocols was 0.805. Conclusion: The PRS achieved similar accuracy to human performance and may help radiologists master the ever-increasing workload.

The health of Canadians is already impacted by climate change due to wildfire smoke, heat domes, floods, droughts, and the changing distribution of vector borne disease. The healthcare sector contributes to climate change, accounting for approximately 4.6% of annual greenhouse gas emissions in Canada. Healthcare teams have a responsibility and opportunity to reduce harm by limiting emissions and waste, and engaging the public in understanding the planetary health links between clean air and water, a stable climate, a healthy planet and human health. Transformation of Canadian healthcare to a low carbon, climate resilient system will be enhanced by physician engagement and leadership. Cornerstones to physician participation include knowledge of the anthropogenic etiology of the climate crisis, the human health impacts, and the contribution providing healthcare makes to the climate crisis. Integration of climate change knowledge into the Canadian Radiology educational curricula is essential to position radiologists to lead transformative change in mitigation and adaptation of the healthcare system to the climate crisis. This statement is intended to provide guidelines to optimize education and research for current and future Canadian radiologists, and builds on existing planetary healthcare education publications and the Canadian Association of Radiologists Statement on Environmental Sustainability in Medical Imaging.

Virtual reality (VR) and augmented reality (AR) technology hold potential across many disciplines in medicine to expand the delivery of education and healthcare. VR-AR applications in radiology, in particular, have gained prominence and have demonstrated advantages in many areas within the field. Recently, VR software has emerged to redesign the physical radiology workstation (ie, reading room) to expand the possibilities of diagnostic interpretation. Given the novelty of this technology, there is limited research investigating the potential applications of a simulated radiology workstation. In this review article, we explore VR-simulated reading room technology in its current form and illustrate the practical applications this technology will bring to future radiologists and learners. We also discuss the limitations and barriers to adopting this technology that must be overcome to truly understand its potential benefits. VR reading room technology offers great potential in radiology, but further research is needed to appreciate its benefits and identify areas for improvement. The findings and insights presented in this review contribute to the ongoing discourse on future technological advancements in radiology and healthcare, offering valuable recommendations for further research and practical implementation.