American Journal of Roentgenology最新文献

{"title":"Photon-Counting Detector CTA in Standard- and Ultrahigh-Resolution Modes for Diagnosing Coronary Artery Stenosis Using Invasive Angiography as the Reference: A Prospective Study.","authors":"Mengzhen Wang, Xinrui Li, Zhihan Xu, Rui Chang, Wentao Han, Fuhua Yan, Mi Zhou, Wenjie Yang","doi":"10.2214/AJR.25.33021","DOIUrl":"10.2214/AJR.25.33021","url":null,"abstract":"<p><p><b>BACKGROUND</b>. The literature reports excellent diagnostic performance of coronary CTA using photon-counting detector (PCD) CT, albeit obtained using various acquisition and reconstruction protocols. <b>OBJECTIVE</b>. The purpose of this study was to assess the diagnostic performance for detecting significant stenosis of coronary CTA performed by PCD CT with various standard-resolution (SR) and ultrahigh-resolution (UHR) protocols, using invasive coronary angiography (ICA) as the reference standard. <b>METHODS</b>. This prospective study enrolled inpatients undergoing coronary CTA between October 2023 and October 2024. Participants underwent coronary CTA by PCD CT, sequentially alternating between SR (collimation: 144 × 0.4 mm) and UHR (collimation: 120 × 0.2 mm) modes across participants. SR examinations were reconstructed into normal (SR_normal) and virtual noncalcium (SR_VNCa) image sets, both using 0.6-mm slice thickness and Bv40 kernel. UHR examinations were reconstructed into normal (UHR_normal [0.6-mm slice thickness, Bv40 kernel]) and thin (UHR_thin [0.2-mm slice thickness, Bv64 kernel]) image sets. Two radiologists independently measured the diameter of stenoses. The final analysis included patients who underwent ICA after CTA; a cardiologist reviewed the ICA images to determine the reference standard. Stenoses were considered significant at a threshold of 50% or greater. <b>RESULTS</b>. The SR group included 61 patients (mean age, 67 ± 9 [SD] years; 46 men, 15 women; 788 segments analyzed). The UHR group included 61 patients (67 ± 11 years; 43 men, 18 women; 825 segments analyzed). Per-segment sensitivity, specificity, and accuracy for reader 1 were 92.9%, 89.9%, and 90.5% for SR_normal, respectively; 92.9%, 91.6%, and 91.8% for SR_VNCa; 96.0%, 92.4%, and 93.0% for UHR_normal; and 100.0%, 98.6%, and 98.8% for UHR_thin; and for reader 2 were 92.9%, 88.8%, and 89.6% for SR_normal; 93.5%, 92.3%, and 92.5% for SR_VNCa; 96.0%, 91.6%, and 92.2% for UHR_normal; and 100.0%, 98.9%, and 99.0% for UHR_thin. Significant (<i>p</i> < .05) differences included SR_VNCa versus SR_normal for specificity for both readers and accuracy for reader 2; UHR_thin versus UHR_normal for sensitivity, specificity, and accuracy for both readers; and UHR_thin versus SR_VNCa for sensitivity, specificity, and accuracy for both readers. <b>CONCLUSION</b>. Coronary CTA performed by PCD CT achieved high diagnostic performance in the SR or UHR mode. Performance was higher for SR_VNCa than SR_normal and for UHR_thin than either UHR_normal or SR_VNCa. <b>CLINICAL IMPACT</b>. The findings will help to optimize protocols for coronary CTA performed by PCD CT.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":"1-13"},"PeriodicalIF":6.1,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144546277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>AJR</i> Forum on Quantitative Ultrasound.","authors":"David T Fetzer, Ivan M Rosado-Mendez, Bryan Bunnell, Theodore Pierce, Michelle L Robbin","doi":"10.2214/AJR.25.33979","DOIUrl":"https://doi.org/10.2214/AJR.25.33979","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145253964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lessons in Longevity-From Training to Practice, an <i>AJR</i> Podcast Series (Episode 4).","authors":"Surbhi Raichandani, Desiree E Morgan","doi":"10.2214/AJR.25.33956","DOIUrl":"https://doi.org/10.2214/AJR.25.33956","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bone Scintigraphy in the Era of PSMA PET: Counterpoint-The Page Has Turned.","authors":"Sidney M Levy, Michael S Hofman","doi":"10.2214/AJR.25.33755","DOIUrl":"https://doi.org/10.2214/AJR.25.33755","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bone Scintigraphy in the Era of PSMA PET: Point-Still a Valuable Tool and Not Yet Dead.","authors":"Adrien Holzgreve, Oliver Sartor","doi":"10.2214/AJR.25.33724","DOIUrl":"https://doi.org/10.2214/AJR.25.33724","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lung MRI: Indications, Capabilities, and Techniques-<i>AJR</i> Expert Panel Narrative Review.","authors":"Lea Azour, Yoshiharu Ohno, Jürgen Biederer, Bruno Hochhegger, Grzegorz Bauman, Hiroto Hatabu, Mark L Schiebler, Jeanne B Ackman","doi":"10.2214/AJR.25.32637","DOIUrl":"10.2214/AJR.25.32637","url":null,"abstract":"<p><p>Lung MRI provides both structural and functional information across a spectrum of parenchymal and airway pathologies. MRI, using current widely available conventional sequences, provides high-quality diagnostic images that allow tissue characterization and delineation of lung lesions; dynamic evaluation of expiratory central airway collapse, diaphragmatic or chest wall motion, and the relation of lung masses to the chest wall; oncologic staging; surveillance of chronic lung pathologies; and differentiation of inflammation and fibrosis in interstitial lung disease. Ongoing technologic advances, including deep learning acceleration methods, may enable future applications in longitudinal lung cancer screening without ionizing radiation exposure and in the regional quantification of ventilation and perfusion without hyperpolarized gas or IV contrast media. Although society statements highlight appropriate indications for lung MRI and the modality has performed favorably relative to CT or FDG PET/CT in various indications, the examination's clinical utilization remains extremely low. Ongoing barriers to adoption include limited awareness by referring physicians, as well as insufficient proficiency and experience by radiologists and technologists. In this <i>AJR</i> Expert Panel Narrative Review, we review the clinical indications for lung MRI, describe the examination's current capabilities, provide guidance on protocols comprising widely available pulse sequences, introduce emerging techniques, and issue consensus recommendations.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":"1-19"},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144121538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence Versus Radiologist False Positives on Digital Breast Tomosynthesis Examinations in a Population-Based Screening Program.","authors":"Tara Shahrvini, Erika J Wood, Melissa M Joines, Hillary Nguyen, Anne C Hoyt, James S Chalfant, Nina M Capiro, Cheryce P Fischer, James Sayre, William Hsu, Hannah S Milch","doi":"10.2214/AJR.25.33412","DOIUrl":"https://doi.org/10.2214/AJR.25.33412","url":null,"abstract":"<p><p><b>Background:</b> Insights into the nature of false-positive findings flagged by contemporary mammography artificial intelligence (AI) systems could inform the potential use of AI to reduce false-positive recall rates. <b>Objective:</b> To compare AI and radiologists in terms of characteristics of false-positive digital breast tomosynthesis (DBT) examinations in a breast cancer screening population. <b>Methods:</b> This retrospective study included 2977 women (mean age, 58 years) participating in an observational population-based screening study who underwent 3183 screening DBT examinations from January 2013 to June 2017. A commercial AI tool analyzed DBT examinations. Positive examinations were defined for AI as an elevated-risk result and for interpreting radiologists as BI-RAD category 0. False-positive examinations were defined as the absence of a breast cancer diagnosis within 1 year. Radiologists re-reviewed the imaging for AI-flagged false-positive findings. <b>Results:</b> The false-positive rate was 10% for both AI (308/3183) and radiologists (304/3183). Of 541 total false-positive examinations, 233 (43%) were false positives for AI only, 237 (44%) for radiologists only, and 71 (13%) for both. AI-only versus radiologist-only false positives were associated with greater mean patient age (60 vs 52 years, p<.001), lower frequency of dense breasts (24% vs 57%, p<.001), and greater frequencies of a personal history of breast cancer (13% vs 4%, p<.001), prior breast imaging studies (95% vs 78%, p<.001), and prior breast surgical procedures (37% vs 11%, p<.001). The false-positive examinations included 932 AI-only flagged findings, 315 radiologist-only flagged findings, and 49 flagged findings concordant between AI and radiologists. AI-only flagged findings were most commonly benign calcifications (40%), asymmetries (13%), and benign postsurgical change (12%); radiologist-only flagged findings were most commonly masses (47%), asymmetries (19%), and indeterminate calcifications (15%). Of 18 concordant flagged findings undergoing biopsy, 44% yielded high-risk lesions. <b>Conclusion:</b> Imaging and patient-level differences were observed between AI and radiologist false-positive DBT examinations. Although only a small fraction of false-positive examinations overlapped between AI and radiologists, concordant flagged findings had a high rate of representing high-risk lesions. <b>Clinical Impact:</b> The findings may help guide strategies for using AI to improve DBT recall specificity. In particular, concordant findings may represent an enriched subset of actionable abnormalities.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attrition of the National Radiologist Workforce: Associations with Radiologist and Practice Characteristics.","authors":"Eric W Christensen, Chi-Mei Liu, Elizabeth Y Rula, Jay R Parikh","doi":"10.2214/AJR.25.33587","DOIUrl":"https://doi.org/10.2214/AJR.25.33587","url":null,"abstract":"<p><p><b>Background:</b> Ongoing radiologist workforce trends, including increasing subspecialization and practice consolidation, could have implications regarding radiologists' rate of workforce exit. <b>Objective:</b> The purpose of this study was to quantify relationships of radiologist workforce attrition with radiologist and practice characteristics. <b>Methods:</b> CMS National Downloadable Files (NDFs) from 2014 to 2022 were used to identify a national sample of radiologists, extracting individual radiologist-year observations. CMS research identifiable files, containing Medicare fee-for-service claims, and a commercial, Medicaid, and Medicare Advantage claims dataset (Inovalon Insights, LLC) were used to identify radiologists no longer clinically active after a given year (i.e., workforce attrition). Multiple CMS datasets (NDFs; Physician and Other Supplier Public Use Files; Provider Enrollment, Chain, and Ownership System) were used to determine characteristics of radiologists (practice pattern [subspecialist vs generalist], gender, years of practice [YOP], geographic region) and affiliated practices (type [based on specialty composition], size [based on number of members], academic status, urbanicity). Multivariable logistic regression analysis was used to identify associations of attrition with radiologist and practice characteristics. Nonlinear regression analyses were used to model attrition as a function of YOP and thereby estimate radiologists' YOP over their careers. <b>Results:</b> The analysis included 298,396 radiologist-year observations in 41,432 radiologists. Unadjusted attrition rates increased from 1.1% in 2014 to 2.5% in 2022. Adjusted odds of attrition were higher for subspecialists versus generalists (OR=1.37), female versus male radiologists (OR=1.26), radiologists in the Midwest versus the Northeast (OR=1.19), nonacademic versus academic radiologists (OR=1.34), and radiologists in practices with at least one rural site versus with no rural sites (OR=1.16); lower for radiologists in radiology-majority (OR=0.81) or other-specialty majority (OR=0.78) practices versus no-majority-specialty practices; and not significantly associated with practice size. Based on nonlinear models, estimated mean YOP for subspecialists, generalists, academic radiologists, and nonacademic radiologists were, among female radiologists, 34.3, 37.2, 38.2, and 34.3, and, among male radiologists, 37.8, 39.3, 40.1, and 37.8. <b>Conclusion:</b> Radiologist workforce attrition increased from 2014 to 2022, being higher for female radiologists, subspecialists, nonacademic radiologists, and radiologists in practices with rural sites. <b>Clinical Impact:</b> The findings suggest potential secondary impacts of radiologist workforce trends on the national workforce shortage.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciding Whether to Adopt Artificial Intelligence for Screening Mammography Interpretation.","authors":"Joo Hee Cha, Niketa Chotai, Eva M Fallenberg, January Lopez, Simone Schiaffino","doi":"10.2214/AJR.25.33946","DOIUrl":"https://doi.org/10.2214/AJR.25.33946","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145202153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidentally Detected Parathyroid Glands on CT: Comparison of Size Thresholds for Defining Enlargement-A Secondary Analysis.","authors":"Karol L Cardenas, Kevin D Hiatt, Joseph Rigdon, Leon Lenchik, Matthew A Gorris, Reese W Randle, Paul M Bunch","doi":"10.2214/AJR.25.33066","DOIUrl":"10.2214/AJR.25.33066","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":" ","pages":"1-4"},"PeriodicalIF":6.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}