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

{"title":"Evaluation of Imaging Research Adherence to the STARD 2015 Reporting Guideline: Update 9 Years After Implementation and Baseline Assessment.","authors":"Mohammed Kashif Al-Ghita, Haben Dawit, Sakib Kazi, Robert G Adamo, Nabil Islam, Sebastian Karpinski, Jean-Paul Salameh, Eric Lam, Hoda Osman, Danyaal Ansari, Daniël A Korevaar, Patrick M Bossuyt, Matthew D F McInnes","doi":"10.1177/08465371251324090","DOIUrl":"https://doi.org/10.1177/08465371251324090","url":null,"abstract":"<p><p><b>Background:</b> Adherence of diagnostic accuracy imaging research to the STARD 2015 reporting guideline was assessed at baseline in 2016; on average, only 55% of 30 items were reported. Several knowledge translation strategies have since been implemented by the STARD group. <b>Purpose:</b> The purpose of this study was to evaluate the adherence of diagnostic accuracy studies recently published in imaging journals to STARD 2015, to assess for changes in the level of adherence relative to the baseline study. <b>Methods:</b> We performed an electronic search on MEDLINE for diagnostic accuracy studies, published between May and June of 2024, from a select group of imaging journals. The timespan was modulated to achieve a sample size of 100 to 150 included studies. Overall and item-specific adherence to STARD 2015 was evaluated, in addition to associations with journal of publication, imaging modality, study design, country of corresponding author, imaging subspecialty area, journal impact factor, and journal STARD adoption. Statistical comparison to the baseline study from 2016 was also performed. Poisson Regression and two-tailed student's tests were used to compare STARD adherence relative to variables included in subgroup analysis. <b>Results:</b> In the 126 included studies, average adherence to STARD 2015 was 61% (18.3/30 items; SD = 3.1), improved compared to the baseline study (55%; 16.6/30 items; SD = 2.2; <i>P</i> < .0001). Studies published in higher impact factor journals reported more items than those in lower impact factor journals (20.6 vs 18.4 items, <i>P</i>-value <.0001). There was no significant association between reporting completeness and journal of publication (<i>P</i> = .7), imaging modality (<i>P</i> = .21), country of corresponding author (<i>P</i> = .46), imaging subspecialty (<i>P</i> = .31), and journal STARD adoption status (<i>P</i> = .55). <b>Conclusion:</b> Recently published diagnostic accuracy studies reported more STARD 2015 items than studies published in 2016, but completeness of reporting is still not optimal.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251324090"},"PeriodicalIF":2.9,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143651890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planetary Health and Climate Action in Radiology.","authors":"Tyler D Yan, Bruce B Forster, Alison Harris, Maura J Brown","doi":"10.1177/08465371251322733","DOIUrl":"https://doi.org/10.1177/08465371251322733","url":null,"abstract":"<p><p>Climate change, biodiversity loss, and pollution are disrupting earth's biophysical systems, with adverse effects on local and global human health. Planetary health describes the inextricable link between human health and the health of earth's biophysical systems. There is urgent need for a stronger focus on planetary health among healthcare systems and radiology departments. Medical imaging is a substantial contributor to climate change, responsible for 0.8% to 1% of global greenhouse gas emissions. As demands for medical imaging continue to grow, so will the need for radiologists to provide leadership in environmentally sustainable medical imaging. Mitigation strategies targeting overall reductions in environmental impact are pivotal including reducing the energy consumption of medical imaging equipment and establishing a circular supply chain to reduce unnecessary waste. In addition, radiology departments will need to focus on adaptative measures which build resiliency to the impacts of climate change, some of which will be unavoidable. This review aims to define planetary healthcare in the context of radiology and provide a framework within which to consider specific actions to reduce the environmental footprint of medically necessary medical imaging.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251322733"},"PeriodicalIF":2.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Based Contrast Boosting in Low-Contrast Media Pre-TAVR CT Imaging.","authors":"Jeaneun Park, Jung Im Jung, Kyunghwa Han, Suyon Chang","doi":"10.1177/08465371251322054","DOIUrl":"10.1177/08465371251322054","url":null,"abstract":"<p><p><b>Purpose:</b> This study investigates the impact of deep learning-based contrast boosting (DL-CB) on image quality and measurement reliability in low-contrast media (low-CM) CT for pre-transcatheter aortic valve replacement (TAVR) assessment. <b>Methods:</b> This retrospective study included TAVR candidates with renal dysfunction who underwent low-CM (30-mL: 15-mL bolus of contrast followed by 50-mL of 30% iomeprol solution) pre-TAVR CT between April and December 2023, along with matched standard-CM controls (n = 68). Low-CM images were reconstructed as conventional, 50-keV, and DL-CB images. Qualitative and quantitative image quality were compared among image sets. The aortic annulus was measured by 2 independent readers on low-CM CT images, and interobserver reliability was assessed. <b>Results:</b> DL-CB significantly improved contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) compared to conventional and 50-keV images (CNR: 12.5-13.4, 18-19.8, and 21.9-24; SNR: 10.8-15.5, 10.7-15.5, and 16.8-26.7 on conventional, 50-keV, and DL-CB images, respectively; <i>P</i> < .001). DL-CB achieved comparable CNR (21.9-24 vs 27-27.7, <i>P</i> = .39-.61) and comparable to slightly higher SNR (16.8-26.7 vs 15.7-20.2, <i>P</i> = .003-.80) to standard-CM images. For aortic annular measurement, DL-CB demonstrated high interobserver reliability, with an intraclass correlation coefficient (ICC) of .96 and small mean differences (area: 0.01 cm², limits of agreement [LoA]: -0.52 to 0.55 cm²; perimeter: 0.02 mm, LoA: -4.49 to 4.53 mm). <b>Conclusions:</b> DL-CB improves image quality and provides high measurement reliability in low-CM CT for pre-TAVR assessment in patients with renal dysfunction, without requiring dual-energy CT.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251322054"},"PeriodicalIF":2.9,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging Climate-Related Environmental Exposures: Impact and Opportunity.","authors":"Felipe Castillo, Omar Taboun, John Farag Alla, Karyna Yankova, Kate Hanneman","doi":"10.1177/08465371251322762","DOIUrl":"https://doi.org/10.1177/08465371251322762","url":null,"abstract":"<p><p>Climate change is the most important challenge of this century. Global surface temperature is continuously rising to new record highs, adversely affecting the health of the planet and humans. The purpose of this article is to review the impact of climate related environmental exposures on human health, healthcare delivery, and medical imaging and explore the potential to leverage medical imaging as a non-invasive tool to advance our understanding of climate related health effects. Radiology departments and healthcare systems must focus on building resilience to the effects of climate change while ensuring that the delivery of care is environmentally sustainable. Further research is needed to refine our understanding of the effects of climate change on human health and to forecast the expected changes in the demand for healthcare and radiology services.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251322762"},"PeriodicalIF":2.9,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in Interventional Radiology: A Bibliometric Analysis of the Canadian Association of Radiologists Journal.","authors":"Ali Helmi, Sabreena Moosa, Sebastian Charles Mafeld","doi":"10.1177/08465371251324099","DOIUrl":"https://doi.org/10.1177/08465371251324099","url":null,"abstract":"","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251324099"},"PeriodicalIF":2.9,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental Sustainability and Cancer Imaging.","authors":"Parthiv Amin, Aleena Malik, Matthew D F Mcinnes, Maura J Brown, Andrew Szava-Kovats","doi":"10.1177/08465371251323107","DOIUrl":"https://doi.org/10.1177/08465371251323107","url":null,"abstract":"<p><p>The rising global burden of cancer drives increased demands for medical imaging, which is essential throughout cancer care. However, delivering medical imaging presents significant environmental challenges including high energy use, reliance on single-use supplies, and the production of environmental pollutants. Environmental factors, such as ultraviolet radiation, wildfire smoke, and carcinogenic pollutants contribute to rising cancer rates, while extreme weather events driven by climate change disrupt cancer care delivery-highlighting the close connection between patient and planetary health. This review explores opportunities to improve the environmental sustainability of oncologic imaging, emphasizing the importance of patient-relevant outcomes-such as quality of life and overall survival-as a guiding principle in cancer care. Key strategies include optimizing imaging schedules to reduce low-value imaging, selecting modalities with lower environmental impact where clinically appropriate, minimizing waste streams, and adopting energy-efficient practices. Artificial intelligence offers the potential to personalize imaging schedules and improve efficiency, though its benefits must be weighed against energy use. Mobile imaging programs and integrated scheduling reduce patient travel-related emissions while promoting health equity, particularly in underserved communities. Future research should focus on optimizing imaging intervals to address patient-relevant outcomes better, expanding the use of abbreviated imaging protocols, and the judicious deployment of artificial intelligence, ensuring its benefits justify energy use.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251323107"},"PeriodicalIF":2.9,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating Adherence to Canadian Radiology Guidelines for Incidental Hepatobiliary Findings Using RAG-Enabled LLMs.","authors":"Nicholas Dietrich, Brett Stubbert","doi":"10.1177/08465371251323124","DOIUrl":"https://doi.org/10.1177/08465371251323124","url":null,"abstract":"<p><p><b>Purpose:</b> Large language models (LLMs) have the potential to support clinical decision-making but often lack training on the latest clinical guidelines. Retrieval-augmented generation (RAG) may enhance guideline adherence by dynamically integrating external information. This study evaluates the performance of two LLMs, GPT-4o and o1-mini, with and without RAG, in adhering to Canadian radiology guidelines for incidental hepatobiliary findings. <b>Methods:</b> A customized RAG architecture was developed to integrate guideline-based recommendations into LLM prompts. Clinical cases were curated and used to prompt models with and without RAG. Primary analyses assessed the rate of guideline adherence with comparisons made between LLMs with and without RAG. Secondary analyses evaluated reading ease, grade level, and response times for generated outputs. <b>Results:</b> A total of 319 clinical cases were evaluated. Adherence rates were 81.7% for GPT-4o without RAG, 97.2% for GPT-4o with RAG, 79.3% for o1-mini without RAG, and 95.1% for o1-mini with RAG. Model performance differed significantly across groups, with RAG-enabled configurations outperforming their non-RAG counterparts (<i>P</i> < .05). RAG-enabled models demonstrated improved reading ease and lower grade level scores; however, all model outputs remained at advanced comprehension levels. Response times for RAG-enabled models increased slightly due to additional retrieval processing but remained clinically acceptable. <b>Conclusions:</b> RAG-enabled LLMs significantly improved adherence to Canadian radiology guidelines for incidental hepatobiliary findings without compromising readability or response times. This approach holds promise for advancing evidence-based care and warrants further validation across broader clinical settings.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251323124"},"PeriodicalIF":2.9,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CAR/CSTR Practice Guideline on CT Screening for Lung Cancer.","authors":"Jana Lyn Taylor, Scott J Adams, Carole Dennie, Robert Lim, Micheal McInnis, Daria Manos","doi":"10.1177/08465371251317179","DOIUrl":"https://doi.org/10.1177/08465371251317179","url":null,"abstract":"<p><p>Lung cancer is the second-most diagnosed cancer and the leading cause of cancer-related death in Canada. The updated CAR/CSTR Practice Guideline on CT Screening for Lung Cancer reflects advancements in evidence since the 2016 guideline, including findings from the NELSON trial and preliminary data from multiple provincial lung cancer screening programs, and aims to support Canadian diagnostic imaging departments in implementing organized lung cancer screening programs. The guideline emphasizes screening with the use of low-dose CT (LDCT) to reduce lung cancer mortality in appropriately selected individuals with increased risk of lung cancer, using eligibility criteria based on risk prediction models such as the PLCO_m2012. It outlines training requirements for radiologists, standardized CT and reporting protocols, quality assurance measures, and the integration of AI tools for nodule risk stratification. The document also highlights emerging areas for investigation, including the potential for biennial screening and equitable access to programs across Canada.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251317179"},"PeriodicalIF":2.9,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective External Validation of an AI-Based Emergency Department Pneumonia Disposition Prediction Tool.","authors":"Aaditeya Jhaveri, Farbod Abolhassani, Benjamin Fine","doi":"10.1177/08465371251320938","DOIUrl":"https://doi.org/10.1177/08465371251320938","url":null,"abstract":"<p><p><b>Purpose:</b> This shadow deployment evaluated an externally-developed AI tool to predict disposition using chest X-rays (CXR) in patients with community-acquired pneumonia (CAP) in the Emergency Department (ED). Retrospective and prospective external validations were conducted to assess differences between the 2 evaluations and across subgroups to inform deployment decisions. <b>Methods:</b> The CNN was retrospectively validated (n = 17 689) from November 1, 2020, to June 30, 2021, and prospectively validated on \"suspected-CAP\" patients (n = 3062) from Jan 1 to Jan 31, 2023. Calibration and standard metrics, including AUC, accuracy, sensitivity, specificity, PPV, and NPV, were calculated. Subgroup analyses were conducted for age, sex, modality, and CXR projection (PA vs AP). <b>Results:</b> The model's AUC was 67% in both validations. The prospective evaluation showed a non-significant increase in sensitivity (65% vs 59%) and PPV (64% vs 63%), while specificity (68% vs 73%) and NPV (69% vs 70%) slightly decreased. NPV was very high for younger patients in the prospective evaluation (95%); PPV was moderately high for older patients (81%). Sensitivity dropped significantly in females under 31 years (50%), and specificity was reduced in females over 86 years (38%). <b>Conclusion:</b> This study showed moderate, consistent performance in both retrospective and prospective validations. While this consistency is encouraging, further direct comparisons are needed to determine whether both validation approaches are necessary in different clinical settings. Subgroup analysis suggests the tool may be helpful to accelerate discharge in younger patients (high NPV) and possibly for admission in older patients (high PPV).</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251320938"},"PeriodicalIF":2.9,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainability in radiology: Position paper and call to action from ACR, AOSR, ASR, CAR, CIR, ESR, ESRNM, ISR, IS3R, RANZCR, and RSNA.","authors":"Andrea G Rockall, Bibb Allen, Maura J Brown, Tarek El-Diasty, Jan Fletcher, Rachel F Gerson, Stacy Goergen, Amanda P Marrero González, Thomas M Grist, Kate Hanneman, Christopher P Hess, Evelyn Lai Ming Ho, Dina H Salama, Julia Schoen, Sarah Sheard","doi":"10.1177/08465371251321390","DOIUrl":"https://doi.org/10.1177/08465371251321390","url":null,"abstract":"<p><p>The urgency for climate action is recognised by international government and healthcare organisations, including the United Nations (UN) and World Health Organisation (WHO). Climate change, biodiversity loss, and pollution negatively impact all life on earth. All populations are impacted but not equally; the most vulnerable are at highest risk, an inequity further exacerbated by differences in access to healthcare globally.The delivery of healthcare exacerbates the planetary health crisis through greenhouse gas emissions, largely due to combustion of fossil fuels for medical equipment production and operation, creation of medical and non-medical waste, and contamination of water supplies.As representatives of radiology societies from across the globe who work closely with industry, and both governmental and non-governmental leaders in multiple capacities, we advocate together for urgent, impactful, and measurable changes to the way we deliver care by further engaging our members, policymakers, industry partners, and our patients. Simultaneous challenges including global health disparities, resource allocation, and access to care must inform these efforts.Climate literacy should be increasingly added to radiology training programmes. More research is required to understand and measure the environmental impact of radiological services and inform mitigation, adaptation and monitoring efforts. Deeper collaboration with industry partners is necessary to support innovations in the supply chain, energy utilization, and circular economy. Many solutions have been proposed and are already available, but we must understand and address barriers to implementation of current and future sustainable innovations. Finally, there is a compelling need to partner with patients, to ensure that trust in the excellence of clinical care is maintained during the transition to sustainable radiology.By fostering a culture of global cooperation and rapid sharing of solutions amongst the broader imaging community, we can transform radiological practice to mitigate its environmental impact, adapt and develop resilience to current and future climate and environmental threats, and simultaneously improve access to care.</p>","PeriodicalId":55290,"journal":{"name":"Canadian Association of Radiologists Journal-Journal De L Association Canadienne Des Radiologistes","volume":" ","pages":"8465371251321390"},"PeriodicalIF":2.9,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}