RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.232750
Anand K Narayan, Nia Foster, Nadja Kadom, Jinel A Scott, Efren J Flores, Jennifer C Broder, Charlotte J Yong-Hing, Dania Daye, Nolan J Kagetsu, Helen Burstin
{"title":"Six Steps to Improving Health Equity Using Quality Improvement and Patient Safety Tools.","authors":"Anand K Narayan, Nia Foster, Nadja Kadom, Jinel A Scott, Efren J Flores, Jennifer C Broder, Charlotte J Yong-Hing, Dania Daye, Nolan J Kagetsu, Helen Burstin","doi":"10.1148/radiol.232750","DOIUrl":"10.1148/radiol.232750","url":null,"abstract":"<p><p>Health equity is a foundational principle for providing high-quality care. The COVID-19 pandemic has increased the urgency of health systems and regulatory agencies to address longstanding health disparities. Imaging disparities have been documented in the imaging literature for decades, but there is paucity of published interventions to successfully reduce disparities in imaging. Quality and safety approaches can be successfully employed to catalyze and rigorously evaluate interventions to reduce imaging disparities. Emerging from the Toyota Production System, the lean management framework focuses on continuous quality improvement to improve efficiency and reduce waste. Lean approaches have been successfully adopted by quality and safety experts in health care for problem-solving and process improvement. This article provides readers with step-by-step guidance on how to address health equity issues by adapting selected lean tools for quality improvement and patient safety. Core steps include <i>(a)</i> problem identification, <i>(b)</i> team building, <i>(c)</i> creation of a data infrastructure, <i>(d)</i> problem analysis, <i>(e)</i> development and testing of solutions, and <i>(f)</i> change management strategies to help organizations sustain successful health equity initiatives. Readers can use these six core steps to catalyze data-driven quality improvement initiatives to reduce imaging disparities within their health systems.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e232750"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868847/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.232996
Gregory J DiGirolamo, Federico Sorcini, Zachary Zaniewski, Jonathan B Kruskal, Max P Rosen
{"title":"Non-Conscious Detection of \"Missed\" Lung Nodules by Radiologists: Expanding the Boundaries of Successful Processing During the Visual Assessment of Chest CT Scans.","authors":"Gregory J DiGirolamo, Federico Sorcini, Zachary Zaniewski, Jonathan B Kruskal, Max P Rosen","doi":"10.1148/radiol.232996","DOIUrl":"10.1148/radiol.232996","url":null,"abstract":"<p><p><i>\"Just Accepted\" papers have undergone full peer review and have been accepted for publication in <i>Radiology: Artificial Intelligence</i>. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content.</i> Background Diagnostic error rates for detecting small lung nodules on chest CT scans remain high at 50%, despite advances in imaging technology and radiologist training. These failure rates may stem from limitations in conscious recognition processes. However, successful visual processes may be detecting the nodule independent of the radiologist's report. Purpose To investigate visual processing in radiologists during the assessment of chest nodules to determine if radiologists have successful non-conscious processes that detect lung nodules on chest CT examinations even when not consciously recognized or considered, as evidenced by changes in how long they look (dwell time) and pupil size to missed nodules. Materials and Methods This prospective study, conducted from [8/14] to [09/23], compared 6 experienced radiologists with 6 medically naïve control participants. Participants viewed 18 chest CTs (9 abnormal with 16 nodules, 9 normal) to detect lung nodules. High-speed video eye-tracking measured gaze duration and pupil size (indicating physiological arousal) at missed nodule locations and same locations on normal CTs. The reference standard was the known presence or absence of nodules (as determined by a 4-radiologist consensus panel) in abnormal and normal CTs, respectively. Primary outcome measures were detection rates of nodules, dwell time and pupil size at nodule locations versus normal tissue. Paired t-tests were used for statistical analysis. Results Twelve participants (6 radiologists [9.3 average years of radiological experience]) 6 controls (with no radiological experience) were evaluated. Radiologists missed on average 59% of these lung nodules. For missed nodules, radiologists exhibited longer dwell times (Mean: 228 milliseconds vs 175 milliseconds, <i>P</i>=.005) and larger pupil area (Mean: 1446 pixels vs. 1349 pixels, <i>P</i>=.04.) than normal tissue. Control participants showed no differences in dwell time (Mean: 197 milliseconds vs 180 milliseconds, <i>P</i>= .64) or pupil size (Mean: 1426 pixels vs. 1714 pixels, <i>P</i>=.23) for missed nodules than normal tissue locations. Conclusion Radiologists non-conscious processes during visual assessment of a CT examination can detect lung nodules on chest CTs even when conscious recognition fails, as evidenced by increased dwell time and larger pupil size. This successful non-conscious detection is a result of general radiology training.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e232996"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11868848/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143190257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.250127
Grace Parraga, Sarah Svenningsen
{"title":"Seeing the Unseen: Pulmonary MRI in Children with Post-COVID-19 Condition.","authors":"Grace Parraga, Sarah Svenningsen","doi":"10.1148/radiol.250127","DOIUrl":"https://doi.org/10.1148/radiol.250127","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e250127"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.241158
Noam Nissan, Varadan Sevilimedu, Jill Gluskin, Yuki Arita, Delia M Keating, Donna D'Alessio, Hila Fruchtman-Brot, R Elena Ochoa-Albiztegui, Janice S Sung, Maxine S Jochelson
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.241941
Filippo Crimì, Giovanni Sussan, Carlo D'Alessandro
{"title":"ChatGPT versus Radiology Institutional Websites: What Is the Patients' Point of View?","authors":"Filippo Crimì, Giovanni Sussan, Carlo D'Alessandro","doi":"10.1148/radiol.241941","DOIUrl":"https://doi.org/10.1148/radiol.241941","url":null,"abstract":"","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e241941"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143391632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.232961
Frederik Abel, Ek T Tan, Yenpo Lin, J Levi Chazen, Darren R Lebl, Darryl B Sneag
{"title":"MRI after Cervical Spine Decompression and Fusion Surgery: Technical Considerations, Expected Findings, and Complications.","authors":"Frederik Abel, Ek T Tan, Yenpo Lin, J Levi Chazen, Darren R Lebl, Darryl B Sneag","doi":"10.1148/radiol.232961","DOIUrl":"https://doi.org/10.1148/radiol.232961","url":null,"abstract":"<p><p>Cervical spine MRI is essential for evaluating potential complications and symptomatic degenerative changes following cervical decompression and fusion surgery. High-yield diagnostic interpretation considers the underlying surgical approach (anterior vs posterior), the time elapsed since surgery, and the clinical status of the patient to reliably differentiate expected postoperative changes from surgical complications. As cervical anatomy, such as the foramina and nerve roots, is smaller than that of the lumbar spine, MRI acquisition challenges include the demand for higher spatial resolution. Another unique challenge for cervical spine MRI is susceptibility to motion artifacts from swallowing, breathing, and cerebrospinal fluid pulsation. Modified MRI protocols, including the use of metal artifact suppression techniques, can help mitigate susceptibility artifacts from metallic implants. This focused review of postoperative cervical spine MRI discusses common cervical surgery decompression and fusion approaches and recommended MRI acquisition and interpretation algorithms, briefly considers radiofrequency coil selection, and illustrates complications in both early and delayed phases.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e232961"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143391638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
RadiologyPub Date : 2025-02-01DOI: 10.1148/radiol.241452
Maira Hameed, Shankar Kumar, Stuart A Taylor
{"title":"How I Do It: Cross-sectional Imaging in Small-Bowel Crohn Disease and Ulcerative Colitis.","authors":"Maira Hameed, Shankar Kumar, Stuart A Taylor","doi":"10.1148/radiol.241452","DOIUrl":"https://doi.org/10.1148/radiol.241452","url":null,"abstract":"<p><p>Cross-sectional imaging, especially MR enterography (MRE) and intestinal US, plays an increasingly important role in the diagnosis and monitoring of Crohn disease. In this article, the authors share their approach to imaging Crohn disease, drawing on their clinical and research experience. They consider how to select the most appropriate modality for different clinical indications and discuss technical aspects to maximize diagnostic accuracy. The focus then shifts to how to use imaging to assess disease activity and treatment response in day-to-day clinical practice and the clinical potential of disease activity scores from MRE and intestinal US. The authors finish by discussing the benefits of intestinal US in ulcerative colitis.</p>","PeriodicalId":20896,"journal":{"name":"Radiology","volume":"314 2","pages":"e241452"},"PeriodicalIF":12.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143391636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}