European Radiology最新文献

{"title":"We may be closer to automated Kellgren-Lawrence grading for knee osteoarthritis than we thought.","authors":"Yin Xi, Avneesh Chhabra","doi":"10.1007/s00330-024-11064-0","DOIUrl":"10.1007/s00330-024-11064-0","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2296-2297"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142282503","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":"Contrast-enhanced mammography-guided biopsy: Is it safe to be implemented in clinical practice?","authors":"Linei Augusta Brolini Dellê Urban","doi":"10.1007/s00330-024-11099-3","DOIUrl":"10.1007/s00330-024-11099-3","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2116-2118"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142461247","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":"Further insights into the use of contrast-enhanced imaging for breast cancer follow-up: the cons view.","authors":"Matthew G Wallis","doi":"10.1007/s00330-024-11097-5","DOIUrl":"10.1007/s00330-024-11097-5","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2144-2146"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142461253","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":"The unquestionable marriage between AI and structured reporting.","authors":"Jacob J Visser","doi":"10.1007/s00330-024-11038-2","DOIUrl":"10.1007/s00330-024-11038-2","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"1935-1937"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142079748","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":"Can deep learning classify cerebral ultrasound images for the detection of brain injury in very preterm infants?","authors":"Tahani Ahmad, Alessandro Guida, Samuel Stewart, Noah Barrett, Xiang Jiang, Michael Vincer, Jehier Afifi","doi":"10.1007/s00330-024-11028-4","DOIUrl":"10.1007/s00330-024-11028-4","url":null,"abstract":"<p><strong>Objectives: </strong>Cerebral ultrasound (CUS) is the main imaging screening tool in preterm infants. The aim of this work is to develop deep learning (DL) models that classify normal vs abnormal CUS to serve as a computer-aided detection tool providing timely interpretation of the scans.</p><p><strong>Methods: </strong>A population-based cohort of very preterm infants (22⁰-30⁶ weeks) born between 2004 and 2016 in Nova Scotia, Canada. A set of nine sequential CUS images per infant was retrieved at three specific coronal landmarks at three pre-identified times (first, sixth weeks, and term age). A radiologist manually labeled each image as normal or abnormal. The dataset was split into training/development/test subsets (80:10:10). Different convolutional neural networks were tested, with filtering of the most uncertain prediction. The model's performance was assessed using precision/recall and the receiver operating area under the curve.</p><p><strong>Results: </strong>Sequential CUS retrieved for 538/665 babies (81% of the cohort). Four thousand one hundred eighty images were used to develop and test the model. The model performance was only discrete at the beginning but, through different machine learning strategies was boosted to good levels averaging 0.86 ROC AUC (95% CI: 0.82, 0.90) and 0.87 PR AUC (95% CI: 0.84, 0.90) (model uncertainty estimation filters using normalized entropy threshold = 0.5).</p><p><strong>Conclusion: </strong>This study offers proof of the feasibility of applying DL to CUS. This basic diagnostic model showed good discriminative ability to classify normal versus abnormal CUS. This serves as a CAD and a framework for constructing a prognostic model.</p><p><strong>Clinical relevance statement: </strong>This DL model can serve as a computer-aided detection tool to classify CUS of very preterm babies as either normal or abnormal. This model will also be used as a framework to develop a prognostic model.</p><p><strong>Key points: </strong>Binary computer-aided detection models of CUS are applicable for classifying ultrasound images in very preterm babies. This model acts as a step towards developing a model for predicting neurodevelopmental outcomes in very preterm babies. This model serves as a tool for interpretation of CUS in this patient population with a heightened risk of brain injury.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"1948-1958"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142105754","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":"Complications of ultrasound-guided thermal ablation of thyroid nodules and associated risk factors: an experience from 9667 cases.","authors":"Xi Liang, Bo Jiang, Yongjiao Ji, Yanna Xu, Yanting Lv, Si Qin, Lanlan Huo, Huimiao Zhang, Hongrui Liu, Tongming Shi, Yukun Luo","doi":"10.1007/s00330-024-11023-9","DOIUrl":"10.1007/s00330-024-11023-9","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the safety of ultrasound-guided thermal ablation (UGTA) for thyroid nodules (TNs) by analysing complications and related risks.</p><p><strong>Materials and methods: </strong>This retrospective, single-centre study reviewed patients who underwent UGTA (microwave or radiofrequency ablation) between January 2018 and March 2023. The incidence of complications was recorded and assessed during and immediately after ablation,1-3 h later, and at 1 month, 3 months, and 6 months. Univariate and multivariate analyses were performed to identify risk factors for hoarseness and haemorrhagic complications.</p><p><strong>Results: </strong>We reviewed 9667 cases in this study. Overall, 4494 (46.49%) cases underwent microwave ablation, while 5173 (53.51%) cases underwent radiofrequency ablation. The overall complication rate was 4.43%. The incidence of major complications was 1.94% (haemorrhage, 1.32%; hoarseness, 0.54%; and symptomatic aseptic necrosis, 0.08%). The incidence of minor complications was 2.45%. A large nodule volume, radiofrequency ablation, hyper-enhancing nodules, benign nodules, higher preoperative blood pressure, hyperthyroidism, and higher ablation power were independent risk factors for haemorrhage. Dorsal nodules and a higher ablation power were independent risk factors for hoarseness. All complications were resolved.</p><p><strong>Conclusion: </strong>This study suggests that UGTA is a safe treatment for TNs. Several risk factors for haemorrhage and hoarseness should be considered before performing UGTA. Different ablation modalities should be considered for patients with different conditions.</p><p><strong>Clinical relevance statement: </strong>Thermal ablation may be a safe treatment for eligible patients with TNs.</p><p><strong>Key points: </strong>We analysed the complications and risk factors associated with UGTA in 9667 cases. The complication rate was 4.43%; 1.94% were major complications. Risk factors of haemorrhage and hoarseness should be considered. UGTA was a safe method for the treatment of TNs.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2307-2319"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142035593","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":"Letter to the Editor: \"Efficacy of single‑session radiofrequency ablation (RFA) in rendering euthyroidism for persistent/relapsed Graves' disease, a pilot study\".","authors":"Shuhang Xu","doi":"10.1007/s00330-024-11044-4","DOIUrl":"10.1007/s00330-024-11044-4","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2351-2352"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142105758","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":"Generating synthetic high-resolution spinal STIR and T1w images from T2w FSE and low-resolution axial Dixon.","authors":"Robert Graf, Paul-Sören Platzek, Evamaria Olga Riedel, Su Hwan Kim, Nicolas Lenhart, Constanze Ramschütz, Karolin Johanna Paprottka, Olivia Ruriko Kertels, Hendrik Kristian Möller, Matan Atad, Robin Bülow, Nicole Werner, Henry Völzke, Carsten Oliver Schmidt, Benedikt Wiestler, Johannes C Paetzold, Daniel Rueckert, Jan Stefan Kirschke","doi":"10.1007/s00330-024-11047-1","DOIUrl":"10.1007/s00330-024-11047-1","url":null,"abstract":"<p><strong>Objectives: </strong>To generate sagittal T1-weighted fast spin echo (T1w FSE) and short tau inversion recovery (STIR) images from sagittal T2-weighted (T2w) FSE and axial T1w gradient echo Dixon technique (T1w-Dixon) sequences.</p><p><strong>Materials and methods: </strong>This retrospective study used three existing datasets: \"Study of Health in Pomerania\" (SHIP, 3142 subjects, 1.5 Tesla), \"German National Cohort\" (NAKO, 2000 subjects, 3 Tesla), and an internal dataset (157 patients 1.5/3 Tesla). We generated synthetic sagittal T1w FSE and STIR images from sagittal T2w FSE and low-resolution axial T1w-Dixon sequences based on two successively applied 3D Pix2Pix deep learning models. \"Peak signal-to-noise ratio\" (PSNR) and \"structural similarity index metric\" (SSIM) were used to evaluate the generated image quality on an ablations test. A Turing test, where seven radiologists rated 240 images as either natively acquired or generated, was evaluated using misclassification rate and Fleiss kappa interrater agreement.</p><p><strong>Results: </strong>Including axial T1w-Dixon or T1w FSE images resulted in higher image quality in generated T1w FSE (PSNR = 26.942, SSIM = 0.965) and STIR (PSNR = 28.86, SSIM = 0.948) images compared to using only single T2w images as input (PSNR = 23.076/24.677 SSIM = 0.952/0.928). Radiologists had difficulty identifying generated images (misclassification rate: 0.39 ± 0.09 for T1w FSE, 0.42 ± 0.18 for STIR) and showed low interrater agreement on suspicious images (Fleiss kappa: 0.09 for T1w/STIR).</p><p><strong>Conclusions: </strong>Axial T1w-Dixon and sagittal T2w FSE images contain sufficient information to generate sagittal T1w FSE and STIR images.</p><p><strong>Clinical relevance statement: </strong>T1w fast spin echo and short tau inversion recovery can be retroactively added to existing datasets, saving MRI time and enabling retrospective analysis, such as evaluating bone marrow pathologies.</p><p><strong>Key points: </strong>Sagittal T2-weighted images alone were insufficient for differentiating fat and water and to generate T1-weighted images. Axial T1w Dixon technique, together with a T2-weighted sequence, produced realistic sagittal T1-weighted images. Our approach can be used to retrospectively generate STIR and T1-weighted fast spin echo sequences.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"1761-1771"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913981/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142132250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breast radiation dose with contrast-enhanced mammography-guided biopsy: a retrospective comparison with stereotactic and tomosynthesis guidance.","authors":"Rodrigo Alcantara, Javier Azcona, Mireia Pitarch, Natalia Arenas, Xavier Castells, Pablo Milioni, Valentina Iotti, Giulia Besutti","doi":"10.1007/s00330-024-10920-3","DOIUrl":"10.1007/s00330-024-10920-3","url":null,"abstract":"<p><strong>Objectives: </strong>This retrospective study aimed to compare the average glandular dose (AGD) per acquisition in breast biopsies guided by contrast-enhanced mammography (CEM), conventional stereotactic breast biopsy (SBB), and digital breast tomosynthesis (DBT). The study also investigated the influence of compressed breast thickness (CBT) and density on AGD. Furthermore, the study aimed to estimate the AGD per procedure for each guidance modality.</p><p><strong>Methods: </strong>The study included 163 female patients (mean age 57 ± 10 years) who underwent mammography-guided biopsies using SBB (9%), DBT (65%), or CEM (26%) guidance. AGD and CBT data were extracted from DICOM headers, and breast density was visually assessed. Statistical analyses included two-sample t-tests and descriptive statistics.</p><p><strong>Results: </strong>Mean AGD per acquisition varied slightly among CEM (1.48 ± 0.22 mGy), SBB (1.49 ± 0.40 mGy), and DBT (1.55 ± 0.47 mGy), with CEM presenting higher AGD at lower CBTs and less dose escalation at higher CBTs. For CBT > 55 mm, CEM showed reduced AGD compared to SBB and DBT (p < 0.001). Breast density had minimal impact on AGD, except for category A. The estimated AGD per procedure was approximately 11.84 mGy for CEM, 11.92 mGy for SBB, and 6.2 mGy for DBT.</p><p><strong>Conclusion: </strong>The study found mean AGD per acquisition to be similar for CEM and SBB, with DBT slightly higher. CEM demonstrated higher AGD at lower CBT but lower AGD at higher CBT, indicating reduced dose escalation with increasing thickness. While breast density had minimal overall impact, variations were noted in category A. DBT was more dose-efficient per procedure due to fewer acquisitions required.</p><p><strong>Clinical relevance statement: </strong>CEM guidance provides effective lesion visualization within safe radiation limits, improving the precision of percutaneous image-guided breast interventions and supporting its potential consideration in a wider range of breast diagnostic procedures.</p><p><strong>Key points: </strong>Limited data exist on the AGD using CEM guidance for breast biopsies. CEM and SBB exhibit similar AGD per acquisition; DBT demonstrated the lowest AGD per procedure. Radiation from CEM guidance fits within safe limits for percutaneous image-guided breast interventions.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"2119-2129"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141982002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ESR Essentials: staging and restaging with FDG-PET/CT in oncology-practice recommendations by the European Society for Hybrid, Molecular and Translational Imaging.","authors":"Ricarda Ebner, Gabriel T Sheikh, Matthias Brendel, Jens Ricke, Clemens C Cyran","doi":"10.1007/s00330-024-11094-8","DOIUrl":"10.1007/s00330-024-11094-8","url":null,"abstract":"<p><p>Positron emission tomography (PET) stands as the paramount clinical molecular imaging modality, especially in oncology. Unlike conventional anatomical-morphological imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI), PET provides detailed visualizations of internal activity at the molecular and cellular levels. 18-fluorine-fluorodeoxyglucose ([¹⁸F]FDG)-PET combined with contrast-enhanced CT (ceCT) significantly improves the detection of various cancers. Appropriate patient selection is crucial, and physicians should carefully assess the appropriateness of [¹⁸F]FDG-PET/CT based on specific clinical criteria and evidence. Due to its high diagnostic accuracy, [¹⁸F]FDG-PET/CT is indispensable for evaluating the extent of disease, staging, and restaging known malignancies, and assessing the response to therapy. PET/CT imaging offers significant advantages in patient management, particularly by identifying occult metastases that might otherwise go undetected. This can help prevent unnecessary surgeries, allowing many patients to be redirected to systemic chemotherapy instead. However, it is important to note that the gold standard for surgical planning remains CT and/or MRI, depending on the body region. These imaging modalities, with or without associated angiography, provide superior contrast and spatial resolution, essential for detailed surgical preparation and planning. [¹⁸F]FDG-PET/CT has a central role in the precise and early diagnosis of cancer, contributing significantly to personalized treatment plans. However, it has limitations, including non-tumor-specific uptake and the potential to inaccurately capture the metabolic activity of certain tumor types due to low uptake in some well-differentiated tumor cell lines. Therefore, it should be utilized in clinical scenarios where it offers crucial diagnostic insights not readily available with other imaging modalities. KEY POINTS: Use [¹⁸F]FDG-PET/CT selectively based on clinical appropriateness criteria and existing evidence to optimize resource utilization and minimize patient exposure. Employ [¹⁸F]FDG-PET/CT in treatment planning and monitoring, particularly for assessing chemotherapy or radiotherapy response in FDG-avid lymphoma and solid tumors. When available, [¹⁸F]FDG-PET/CT can be integrated with other diagnostic tools, such as MRI, to enhance overall diagnostic accuracy.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"1894-1902"},"PeriodicalIF":4.7,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11914360/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}