Radiography最新文献

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Use of ChatGPT in radiological dose management. ChatGPT在放射剂量管理中的应用。
IF 2.8
Radiography Pub Date : 2025-09-17 DOI: 10.1016/j.radi.2025.103161
D E Tekcan Sanli, A N Sanli
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引用次数: 0
Evaluation of a method to predict positioning errors in orthopantomography using cephalography 评估一种利用头颅造影预测正体层摄影定位误差的方法。
IF 2.8
Radiography Pub Date : 2025-09-17 DOI: 10.1016/j.radi.2025.103174
S. Imajo , M. Honda , Y. Tanabe
{"title":"Evaluation of a method to predict positioning errors in orthopantomography using cephalography","authors":"S. Imajo ,&nbsp;M. Honda ,&nbsp;Y. Tanabe","doi":"10.1016/j.radi.2025.103174","DOIUrl":"10.1016/j.radi.2025.103174","url":null,"abstract":"<div><h3>Introduction</h3><div>Various radiographic examinations are used to diagnose diseases and determine treatment plans, and the quality of radiographic images affects diagnostic accuracy. This study assessed the relationship between orthopantomography and cephalometric analysis in predicting positioning errors before orthopantomography.</div></div><div><h3>Methods</h3><div>This study evaluated four human head phantom types and included 300 patients aged ≥18 years who underwent orthopantomography. The correlation between the Frankfort horizontal plane and occlusal plane angles in the orthopantomogram was analyzed. The occlusal plane angle at a Frankfort horizontal plane of 0° was estimated using a linear approximation formula. Frankfort horizontal plane and occlusal plane angles were measured on the cephalograms, and their differences were analyzed for correlation with the occlusal plane angle at a Frankfort horizontal plane of 0° in the corresponding orthopantomograms. The cephalogram’s condylar plane–corpus line angle was also compared with orthopantomogram measurements.</div></div><div><h3>Results</h3><div>Frankfort horizontal and occlusal plane angles demonstrated a strong negative correlation (r &lt; −0.9) in phantom studies and moderate negative correlation (r &lt; −0.4) in clinical orthopantomograms. In the phantoms, the occlusal plane at a Frankfort horizontal of 0° in the orthopantomogram strongly correlated with the difference between the Frankfort horizontal and condylar plane–corpus line angles in the cephalogram.</div></div><div><h3>Conclusion</h3><div>Adjusting patient positioning based on individual skeletal differences and angles may reduce positioning errors and improve image quality. Cephalogram analysis could help determine an appropriate Frankfort plane angle for each patient when acquiring orthopantomograms.</div></div><div><h3>Implications for practice</h3><div>Integrating cephalometric analysis into positioning protocols enhances radiographic accuracy, reduces retakes, and improves diagnostic reliability in clinical positioning. This research could improve image quality by identifying reference indicators for orthopantomography by incorporating data from images other than cephalograms, such as computed tomography and magnetic resonance imaging.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 6","pages":"Article 103174"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Apparent diffusion coefficient benchmarking and inter-scanner variability; preparing for biological image guided adaptive radiotherapy treatments. 视扩散系数基准和扫描仪间变异性;生物影像引导下的适应性放射治疗的准备。
IF 2.8
Radiography Pub Date : 2025-09-17 DOI: 10.1016/j.radi.2025.103168
S Manolopoulos, R Tulip, J Wyatt
{"title":"Apparent diffusion coefficient benchmarking and inter-scanner variability; preparing for biological image guided adaptive radiotherapy treatments.","authors":"S Manolopoulos, R Tulip, J Wyatt","doi":"10.1016/j.radi.2025.103168","DOIUrl":"https://doi.org/10.1016/j.radi.2025.103168","url":null,"abstract":"<p><strong>Introduction: </strong>Biological Image Guided Adaptive Radiotherapy Treatments (BIGART) rely on the ability to utilise quantitative imaging biomarkers, qMRI. Our aim is to evaluate the performance of MRI scanners in terms of apparent diffusion coefficient (ADC) values, a form of qMRI, and compare with reference data, as a prelude for BIGART.</p><p><strong>Methods: </strong>ADC values for various materials were measured by two MRI scanners (Siemens SOLA 1.5T) using a dedicated phantom developed by CaliberMRI. The data acquisition followed the protocol developed by QIBA and the data analysis carried out using the QCAL-MR® software platform.</p><p><strong>Results: </strong>The scanners produced ADC values for different materials that had a mean deviation of less than 4 % from those certified by the National Institute of Standards and Technology (NIST, USA), and were within 3.6 % between each scanner (inter-scanner variability).</p><p><strong>Conclusion: </strong>It is feasible to benchmark the performance of MRI scanners vis-à-vis qMRI data, such as those inferred from DWI, i.e. ADC. Moreover, our investigation showed that the ADC values produced by two MRI scanners conform to the QIBA brain profile, thus offering the assurance that \"A measured change in the ADC of a brain lesion of 11 % or larger indicates that a true change has occurred with 95 % confidence\".<sup>6</sup> IMPLICATIONS FOR PRACTICE: Our work encourages the development of multicentre BIGART trial protocols that utilise qMRI biomarkers, like ADC, for the treatment of de novo GBM or other tumours. These qMRI biomarkers can be utilised for the personalisation of radiotherapy treatments, either upfront or during the course of radiotherapy, by adapting the treatment plan to the patient's response.</p>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":" ","pages":"103168"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Supporting therapeutic radiographer research amidst growing pressures: "Why is it so challenging to advance radiographer involvement in research development?" 在日益增长的压力下支持治疗放射技师的研究:“为什么推动放射技师参与研究开发如此具有挑战性?”
IF 2.8
Radiography Pub Date : 2025-09-16 DOI: 10.1016/j.radi.2025.103167
S Fernandez, K Cox, D Fairweather
{"title":"Supporting therapeutic radiographer research amidst growing pressures: \"Why is it so challenging to advance radiographer involvement in research development?\"","authors":"S Fernandez, K Cox, D Fairweather","doi":"10.1016/j.radi.2025.103167","DOIUrl":"https://doi.org/10.1016/j.radi.2025.103167","url":null,"abstract":"","PeriodicalId":47416,"journal":{"name":"Radiography","volume":" ","pages":"103167"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145081964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence aided ultrasound imaging of foetal congenital heart disease: A scoping review 人工智能辅助胎儿先天性心脏病超声成像:范围综述。
IF 2.8
Radiography Pub Date : 2025-09-16 DOI: 10.1016/j.radi.2025.103170
L. Norris, P. Lockwood
{"title":"Artificial intelligence aided ultrasound imaging of foetal congenital heart disease: A scoping review","authors":"L. Norris,&nbsp;P. Lockwood","doi":"10.1016/j.radi.2025.103170","DOIUrl":"10.1016/j.radi.2025.103170","url":null,"abstract":"<div><h3>Objectives</h3><div>Congenital heart diseases (CHD) are a significant cause of neonatal mortality and morbidity. Detecting these abnormalities during pregnancy increases survival rates, enhances prognosis, and improves pregnancy management and quality of life for the affected families. Foetal echocardiography can be considered an accurate method for detecting CHDs. However, the detection of CHDs can be limited by factors such as the sonographer's skill, expertise and patient specific variables. Using artificial intelligence (AI) has the potential to address these challenges, increasing antenatal CHD detection during prenatal care.</div><div>A scoping review was conducted using Google Scholar, PubMed, and ScienceDirect databases, employing keywords, Boolean operators, and inclusion and exclusion criteria to identify peer-reviewed studies. Thematic mapping and synthesis of the found literature were conducted to review key concepts, research methods and findings.</div></div><div><h3>Key findings</h3><div>A total of <em>n</em> = 233 articles were identified, after exclusion criteria, the focus was narrowed to <em>n</em> = 7 that met the inclusion criteria. Themes in the literature identified the potential of AI to assist clinicians and trainees, alongside emerging new ethical limitations in ultrasound imaging.</div></div><div><h3>Conclusion</h3><div>AI-based tools in ultrasound imaging offer great potential in assisting sonographers and doctors with decision-making in CHD diagnosis. However, due to the paucity of data and small sample sizes, further research and technological advancements are needed to improve reliability and integrate AI into routine clinical practice.</div></div><div><h3>Implications for practice</h3><div>This scoping review identified the reported accuracy and limitations of AI-based tools within foetal cardiac ultrasound imaging. AI has the potential to aid in reducing missed diagnoses, enhance training, and improve pregnancy management. There is a need to understand and address the ethical and legal considerations involved with this new paradigm in imaging.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 6","pages":"Article 103170"},"PeriodicalIF":2.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Response letter: Breast density assessment in Ghana - Beyond visual mammographic density. 回复信:加纳的乳腺密度评估-超越视觉乳房x线摄影密度。
IF 2.8
Radiography Pub Date : 2025-09-15 DOI: 10.1016/j.radi.2025.103175
E Dzidzornu, S K Angmorterh, N A Angaag, E K Ofori, K Dzefi-Tettey, S Aboagye
{"title":"Response letter: Breast density assessment in Ghana - Beyond visual mammographic density.","authors":"E Dzidzornu, S K Angmorterh, N A Angaag, E K Ofori, K Dzefi-Tettey, S Aboagye","doi":"10.1016/j.radi.2025.103175","DOIUrl":"https://doi.org/10.1016/j.radi.2025.103175","url":null,"abstract":"","PeriodicalId":47416,"journal":{"name":"Radiography","volume":" ","pages":"103175"},"PeriodicalIF":2.8,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Perception of medical imaging educators on the addition of AI education to the medical imaging curriculum: A cross-sectional survey 医学影像教育者对在医学影像课程中加入人工智能教育的看法:一项横断面调查
IF 2.8
Radiography Pub Date : 2025-09-15 DOI: 10.1016/j.radi.2025.103153
G. Doherty , C. Hughes , J. McConnell , R. Bond , L. McLaughlin , S. McFadden
{"title":"Perception of medical imaging educators on the addition of AI education to the medical imaging curriculum: A cross-sectional survey","authors":"G. Doherty ,&nbsp;C. Hughes ,&nbsp;J. McConnell ,&nbsp;R. Bond ,&nbsp;L. McLaughlin ,&nbsp;S. McFadden","doi":"10.1016/j.radi.2025.103153","DOIUrl":"10.1016/j.radi.2025.103153","url":null,"abstract":"<div><h3>Introduction</h3><div>As one of the most technologically advanced fields in healthcare, it is unsurprising that artificial intelligence (AI) is significantly impacting medical imaging. The Health and Care Professions Councils (HCPC) updated Standards of Proficiency (SoP) require clinicians to demonstrate awareness of AI principles and their application in practice. Imaging curricula must be updated to ensure professionals meet these standards. This study explores medical imaging educators’ perspectives on AI education, examining their awareness, attitudes, and preparedness to deliver AI content.</div></div><div><h3>Methods</h3><div>A survey was developed to assess the perceptions of academic educators in European medical imaging programmes. The survey was hosted online via the Joint Information Systems Committee (JISC) platform and included a mix of closed and open-ended questions. Convenience sampling was used to recruit attendees at the European Congress of Radiology (ECR) in Vienna in March 2023.</div></div><div><h3>Results</h3><div>A total of 33 responses were received from across 14 countries. Respondents were from a diagnostic radiography background (<em>n</em> = 21) or dual-qualified (<em>n</em> = 12). Only 15.1 % (<em>n</em> = 5) had completed formal AI training. Self-reported preparedness levels indicated a low to moderate preparedness to deliver AI content. Mean AI awareness was 9.21 (of a possible 12), SD = 2.83.</div></div><div><h3>Conclusion</h3><div>While medical imaging educators demonstrate relatively high AI awareness, their preparedness to deliver AI content remains low. Many expressed the need for greater support from higher education institutions (HEIs) to ensure staff are adequately equipped to integrate AI education into medical imaging curricula.</div></div><div><h3>Implications for practice</h3><div>The gap between AI awareness and preparedness among medical imaging educators underscores the need for institutional support. HEIs should prioritise AI-focused and curriculum resources to better equip educators in integrating AI into medical imaging education, ensuring future radiographers develop essential AI competencies.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 6","pages":"Article 103153"},"PeriodicalIF":2.8,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving patient preparation and comfort in voluntary DIBH – Single-centre quality improvement evaluation 改善自愿DIBH患者的准备和舒适度——单中心质量改善评价
IF 2.8
Radiography Pub Date : 2025-09-13 DOI: 10.1016/j.radi.2025.103162
A. Thornley, K. Taylor, S. Goldsworthy
{"title":"Improving patient preparation and comfort in voluntary DIBH – Single-centre quality improvement evaluation","authors":"A. Thornley,&nbsp;K. Taylor,&nbsp;S. Goldsworthy","doi":"10.1016/j.radi.2025.103162","DOIUrl":"10.1016/j.radi.2025.103162","url":null,"abstract":"<div><h3>Introduction</h3><div>Voluntary deep-inspiration breath-hold (vDIBH) is commonly used in left breast cancer patients during radiotherapy to reduce cardiac dose and improve setup accuracy. However, some patients have trouble maintaining a consistent, adequate, breath-hold during radiotherapy. This service evaluation assessed the impact of the RESPIRE tool—an online resource offering instructional videos and audio guides—introduced prior to simulation to improve patient compliance and preparedness.</div></div><div><h3>Methods</h3><div>Fifteen eligible breast cancer patients received RESPIRE information during a clinic appointment for Radiotherapy consent, followed by a telephone check-in prior to CT planning. Breath-hold quality was assessed using planning CT metrics and treatment-image reproducibility, and patient experience was qualitatively evaluated.</div></div><div><h3>Results</h3><div>Compared to historical controls, the fifteen RESPIRE users reported feeling significantly more prepared, and blinded reviews of CBCT images confirmed improved breath-hold reproducibility. Lung volume increased by an average of 32 %, and heart-to-chest wall separation improved following use of the tool.</div></div><div><h3>Conclusion</h3><div>The results align with existing evidence that guided preparation reduces anxiety and supports successful vDIBH implementation. The intervention addresses current ESTRO-ACROP and national safety priorities by promoting patient engagement, comfort, and technical accuracy.</div></div><div><h3>Implications for practice</h3><div>Pre-treatment education using scalable tools like RESPIRE offers a low-cost, high-impact strategy to enhance radiotherapy outcomes and patient-centred care. Future work could hope to make this tool accessible to a wider cohort of patients, addressing some of the limitations discussed.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 6","pages":"Article 103162"},"PeriodicalIF":2.8,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Radiographer - Clinician agreement on imaging selection for extremity injuries in the emergency department – A pilot study 放射科医师。急诊科四肢损伤影像学选择的临床医师共识。一项初步研究
IF 2.8
Radiography Pub Date : 2025-09-13 DOI: 10.1016/j.radi.2025.103166
S. Meredith , A. McBurnie , I. Tavete , C. Edwards
{"title":"Radiographer - Clinician agreement on imaging selection for extremity injuries in the emergency department – A pilot study","authors":"S. Meredith ,&nbsp;A. McBurnie ,&nbsp;I. Tavete ,&nbsp;C. Edwards","doi":"10.1016/j.radi.2025.103166","DOIUrl":"10.1016/j.radi.2025.103166","url":null,"abstract":"<div><h3>Introduction</h3><div>The Emergency Department (ED) is a critical setting for multidisciplinary care, where medical imaging plays an essential role. Approximately 50 % of ED presentations involve imaging to support diagnosis and treatment planning. Nurse-initiated and physiotherapist-initiated X-ray requests are now common in some settings. This pilot study examines the feasibility of expanding radiographers' scope of practice by assessing their ability to determine the appropriate imaging for musculoskeletal injuries.</div></div><div><h3>Methods</h3><div>A retrospective audit of the ED Information System (EDIS) was conducted to identify triage notes from March 2022 to March 2023. Of 5769 musculoskeletal presentations, 90 scenarios were purposively selected across nine anatomical regions. These were embedded in an online survey distributed to 15 participants, grouped into three equal cohorts: radiographers, ED nurse practitioners, and ED consultants. Participants independently identified the most appropriate anatomical region for X-ray imaging based on the clinical scenarios. Inter-rater agreement was assessed using Fleiss' Kappa (FK).</div></div><div><h3>Results</h3><div>Inter-rater agreement was excellent across all cohorts, with overall FK = 0.948 (95 % CI: 0.943–0.953). Radiographers demonstrated the highest internal agreement (FK = 0.977), followed by nurse practitioners (FK = 0.932) and ED consultants (FK = 0.928). Agreement between radiographers and ED consultants was also high (FK = 0.952), supporting alignment in clinical decision-making.</div></div><div><h3>Conclusion</h3><div>Radiographers demonstrated strong agreement with ED consultants in determining appropriate imaging for musculoskeletal injuries, supporting the feasibility of radiographer-initiated X-ray (RIX) protocols.</div></div><div><h3>Implications for practice</h3><div>Structured RIX protocols could help alleviate ED workflow pressures, reduce unnecessary delays, and streamline imaging pathways for low-acuity injuries. These findings support future scope of practice reform and the development of competency-based RIX models in emergency settings.</div></div>","PeriodicalId":47416,"journal":{"name":"Radiography","volume":"31 6","pages":"Article 103166"},"PeriodicalIF":2.8,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Response to Aphale et al.: "Critical appraisal of 'A prospective study of bladder volume assessment using ultrasound in prostate cancer radiotherapy: Comparison with cone-beam computed tomography (CBCT)'". 对Aphale等人的回应:对“前列腺癌放疗中超声膀胱体积评估的前瞻性研究:与锥束计算机断层扫描(CBCT)的比较”的批判性评价。
IF 2.8
Radiography Pub Date : 2025-09-12 DOI: 10.1016/j.radi.2025.103172
B Bąk, K Kaczmarek, D Radoła, T Winiecki, T Bajon
{"title":"Response to Aphale et al.: \"Critical appraisal of 'A prospective study of bladder volume assessment using ultrasound in prostate cancer radiotherapy: Comparison with cone-beam computed tomography (CBCT)'\".","authors":"B Bąk, K Kaczmarek, D Radoła, T Winiecki, T Bajon","doi":"10.1016/j.radi.2025.103172","DOIUrl":"https://doi.org/10.1016/j.radi.2025.103172","url":null,"abstract":"","PeriodicalId":47416,"journal":{"name":"Radiography","volume":" ","pages":"103172"},"PeriodicalIF":2.8,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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