Clinical radiology最新文献

{"title":"Correlation of PRECISE score with histological progression in prostate cancer patients","authors":"Kim Houng Lim, Mohammed Musheb, Anjali Nandakumar, Senthil Ragupathy","doi":"10.1016/j.crad.2025.106899","DOIUrl":"10.1016/j.crad.2025.106899","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106899"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828257","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":"Improving the process of CT thorax acquisition and reporting prior to lung resection","authors":"Adam Djouani, Claudia Tomei","doi":"10.1016/j.crad.2025.106881","DOIUrl":"10.1016/j.crad.2025.106881","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106881"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828219","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":"Audit of CT aortogram yield in evaluation of suspected acute aortic syndrome","authors":"Nikhil Nair, Geethu Punnen, Huma Khosa, Neelam Saleem, Mohd Shadab Siddique","doi":"10.1016/j.crad.2025.106900","DOIUrl":"10.1016/j.crad.2025.106900","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106900"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828258","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":"Preoperative chest imaging in elective cardiothoracic surgery in a tertiary cardiothoracic centre","authors":"Khaled Aljboor, Saif Alshdifat, Rebecca Storey, Rama Toukan, Wael Awad, Amir Awwad","doi":"10.1016/j.crad.2025.106902","DOIUrl":"10.1016/j.crad.2025.106902","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106902"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828260","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":"Radiological–pathological diagnostic rate of the British Thyroid Association ultrasound classification of thyroid nodules at North Middlesex University Hospital","authors":"Madeline Shenouda, Edwin Ruhinda","doi":"10.1016/j.crad.2025.106887","DOIUrl":"10.1016/j.crad.2025.106887","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106887"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828236","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":"Neonatal spinal ultrasound for closed spinal dysraphism: an audit of the referral indications and results across three north London hospitals","authors":"Jessica Carter , Ronica Pulikal , Jody Maclachlan , Maria Nordlander , Jeremy Berger","doi":"10.1016/j.crad.2025.106901","DOIUrl":"10.1016/j.crad.2025.106901","url":null,"abstract":"","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"83 ","pages":"Article 106901"},"PeriodicalIF":2.1,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143828259","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":"Radiomics across modalities: a comprehensive review of neurodegenerative diseases","authors":"M. Inglese ,&nbsp;A. Conti ,&nbsp;N. Toschi","doi":"10.1016/j.crad.2025.106921","DOIUrl":"10.1016/j.crad.2025.106921","url":null,"abstract":"<div><div>Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational resources required to generate them, they hold significant value in downstream automated processing. For instance, in statistical or machine learning frameworks, radiomic features enhance sensitivity and specificity, making them indispensable for tasks such as diagnosis, prognosis, prediction, monitoring, image-guided interventions, and evaluating therapeutic responses. This review explores the application of radiomics in neurodegenerative diseases, with a focus on Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. While radiomics literature often focuses on magnetic resonance imaging (MRI) and computed tomography (CT), this review also covers its broader application in nuclear medicine, with use cases of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) radiomics. Additionally, we review integrated radiomics, where features from multiple imaging modalities are fused to improve model performance. This review also highlights the growing integration of radiomics with artificial intelligence and the need for feature standardisation and reproducibility to facilitate its translation into clinical practice.</div></div>","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"85 ","pages":"Article 106921"},"PeriodicalIF":2.1,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143885557","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":"A magnetic resonance imaging (MRI)-based deep learning radiomics model predicts recurrence-free survival in lung cancer patients after surgical resection of brain metastases","authors":"B. Li ,&nbsp;H. Li ,&nbsp;J. Chen ,&nbsp;F. Xiao ,&nbsp;X. Fang ,&nbsp;R. Guo ,&nbsp;M. Liang ,&nbsp;Z. Wu ,&nbsp;J. Mao ,&nbsp;J. Shen","doi":"10.1016/j.crad.2025.106920","DOIUrl":"10.1016/j.crad.2025.106920","url":null,"abstract":"<div><h3>Aim</h3><div>To develop and validate a magnetic resonance imaging (MRI)-based deep learning radiomics model (DLRM) to predict recurrence-free survival (RFS) in lung cancer patients after surgical resection of brain metastases (BrMs).</div></div><div><h3>Materials and Methods</h3><div>A total of 215 lung cancer patients with BrMs confirmed by surgical pathology were retrospectively included in five centres, 167 patients were assigned to the training cohort, and 48 to the external test cohort. All patients underwent regular follow-up brain MRIs. Clinical and morphological MRI models for predicting RFS were built using univariate and multivariate Cox regressions, respectively. Handcrafted and deep learning (DL) signatures were constructed from BrMs pretreatment MR images using the least absolute shrinkage and selection operator (LASSO) method, respectively. A DLRM was established by integrating the clinical and morphological MRI predictors, handcrafted and DL signatures based on the multivariate Cox regression coefficients. The Harrell C-index, area under the receiver operating characteristic curve (AUC), and Kaplan–Meier's survival analysis were used to evaluate model performance.</div></div><div><h3>Results</h3><div>The DLRM showed satisfactory performance in predicting RFS and 6- to 18-month intracranial recurrence in lung cancer patients after BrMs resection, achieving a C-index of 0.79 and AUCs of 0.84–0.90 in the training set and a C-index of 0.74 and AUCs of 0.71–0.85 in the external test set. The DLRM outperformed the clinical model, morphological MRI model, handcrafted signature, DL signature, and clinical-morphological MRI model in predicting RFS (<em>P</em> &lt; 0.05). The DLRM successfully classified patients into high-risk and low-risk intracranial recurrence groups (<em>P</em> &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>This MRI-based DLRM could predict RFS in lung cancer patients after surgical resection of BrMs.</div></div>","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"85 ","pages":"Article 106920"},"PeriodicalIF":2.1,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879105","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":"Differential practice of peer review and peer feedback between National Health Service (NHS) imaging departments and teleradiology companies; how big is the gap?","authors":"R. Balasubramaniam,&nbsp;K. Drinkwater,&nbsp;M. Beavon,&nbsp;R. Greenhalgh","doi":"10.1016/j.crad.2025.106919","DOIUrl":"10.1016/j.crad.2025.106919","url":null,"abstract":"<div><h3>AIM</h3><div>Assessing the performance of peer review (PR) and peer feedback (PF) within National Health Service (NHS) imaging departments (NIDs) and teleradiology companies (TRCs) within the United Kingdom.</div></div><div><h3>MATERIAL AND METHODS</h3><div>All NHS providers with a clinical radiology audit lead registered with the Royal College of Radiologists and the major TRCs that provided services within the UK were invited to participate via a questionnaire.</div></div><div><h3>RESULTS</h3><div>All 6 TRCs (6/6) and 73% (146/200) of NIDs responded. All 6 TRCs performed formal PR and apportioned time for the role. Only 14/146 (10%) NIDs undertook formal PR, of which 4/14 (29%) received no remuneration for the work. In comparison, most NIDs 120/146 (82%) performed informal PR, using methods like multidisciplinary team meetings (MDTM) which occurred in 113/146 (77%). Peer feedback was practised by 104/146 (71%) NIDs and 5/6 (83%) TRCs, but only 30% to 49% of NIDs and 33% of TRCs used the content for reflective notes or incorporated it within appraisal. Electronic PF was possible in 36/146 (25%) NIDs and 3/6 (50%) TRCs. A peer moderator was present in 35% of NIDs and 50% of TRCs.</div></div><div><h3>CONCLUSION</h3><div>Formal PR was performed by all TRCs but underutilised within NIDs, where it was poorly remunerated. NHS imaging departments relied more on informal methods of PR, such as MDTM. The majority of NIDs and TRCs performed PF; however, the educational benefits of integrating PF within reflection and appraisal were often not implemented. Information technology systems to provide contemporaneous PF and a peer moderator could improve engagement but weren't present in most departments.</div></div>","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"85 ","pages":"Article 106919"},"PeriodicalIF":2.1,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143885551","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":"Local anaesthetics in interventional radiology: a primer for radiologists on applications and management of complications","authors":"J. Steinman ,&nbsp;K.T. Tan","doi":"10.1016/j.crad.2025.106917","DOIUrl":"10.1016/j.crad.2025.106917","url":null,"abstract":"<div><div>Local anaesthetics (LAs) allow a range of procedures to be performed in interventional radiology (IR) through improving patient comfort and reducing pain. This review serves as a primer for interventional radiologists, providing an overview of commonly used LAs and practical tips for their implementation. With its quick onset time and moderate duration of action, the amide lidocaine is the most used and applicable to a variety of procedures such as biopsies and embolization. In contrast, bupivacaine and ropivacaine (both amides) have longer durations of action, and are therefore suitable for lengthy procedures and pain control post-procedurally. Procaine, an ester, may be used in cases of amide anaesthetic allergies. This review examines the clinical applications of LAs in radiology and management of their adverse effects including local anaesthetic systemic toxicity (LAST) and allergic reactions. It concludes with a discussion of LAST, emphasising techniques for early intervention and management. The role of lipid emulsion therapy and modifications to the advanced cardiac life support (ACLS) protocol are highlighted, including a discussion of other aspects such as airway management. By presenting the latest strategies to manage LAST and adverse effects, this research aims to help standardise anaesthetic management in radiology. It provides actionable steps for selecting and injecting anaesthetics, and management of complications that will be beneficial for interventional radiologists performing a diverse array of procedures.</div></div>","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"85 ","pages":"Article 106917"},"PeriodicalIF":2.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882295","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}