European Radiology最新文献

{"title":"Predicting early progression to atezolizumab-bevacizumab in hepatocellular carcinoma: a clinical and imaging-based scoring system.","authors":"Jae Hyon Park, Myung Ji Goh, Dong Hyun Sinn, Jaeseung Shin, Hyungjin Rhee","doi":"10.1007/s00330-025-12040-y","DOIUrl":"https://doi.org/10.1007/s00330-025-12040-y","url":null,"abstract":"<p><strong>Objectives: </strong>To develop a predictive model incorporating both clinical and imaging findings to predict early progression in patients with advanced hepatocellular carcinoma (HCC) undergoing atezolizumab plus bevacizumab (Atezo-Bev) therapy.</p><p><strong>Materials and methods: </strong>A total of 140 consecutive patients with HCC who initiated Atezo-Bev therapy between January 2020 and May 2022 at two tertiary care centres were retrospectively enrolled. Early progression was defined as progressive disease in the first response evaluation conducted at 4 weeks and 12 weeks after treatment initiation using dynamic CT or MRI. Images were reviewed by two radiologists. Logistic regression analysis was performed to determine the early progression scores.</p><p><strong>Results: </strong>The first response evaluation of Atezo-Bev therapy was conducted at a median of 56 days (interquartile range, 42-64 days) after treatment initiation. Approximately 40% (56/140) of patients with HCC showed early progression. The early progression score was defined as follows: (age < 60 years; 1 point) + (serum alpha-fetoprotein level ≥ 300 ng/mL; 3 points) + (neutrophil-to-lymphocyte ratio ≥ 2.8; 1 point) + (infiltrative appearance; 2 points). At a score of 3 or higher, the early progression score showed sensitivity of 91.1% (95% confidence interval [CI]: 83.6-98.5%) and a specificity of 53.6% (95% CI: 42.9-64.2%). At a score of 6 or higher, the score demonstrated a sensitivity of 55.4% (95% CI: 42.3-68.4%) and a specificity of 91.7% (95% CI: 85.8-97.6%).</p><p><strong>Conclusion: </strong>We developed an early progression score that integrates clinical and imaging factors with high specificity to accurately predict early progression in patients with advanced HCC undergoing Atezo-Bev therapy.</p><p><strong>Key points: </strong>Question No validated imaging-based tool currently exists to predict early progression to Atezo-Bev therapy in advanced HCC. Findings Infiltrative tumour appearance, high AFP, high neutrophil-to-lymphocyte ratio, and younger age were significantly associated with early progression. Clinical relevance A composite early progression score integrating clinical and imaging features showed high diagnostic accuracy for predicting treatment failure.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228618","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":"Preoperative staging of cervical cancer: time to shift from cystoscopy to MRI.","authors":"Matteo Bonatti, Riccardo Valletta, Luca D'Erme, Miriam Dolciami, Roberta Chianura, Pietro Paolo Maria Azzaro, Chiara Innocenzi, Nicolò Bizzarri, Vincenzo Vingiani, Giovanni Negri, Martin Steinkasserer, Sara Notaro, Francesca Vanzo, Elena Magri, Benedetta Gui, Evis Sala, Giacomo Avesani","doi":"10.1007/s00330-025-12039-5","DOIUrl":"https://doi.org/10.1007/s00330-025-12039-5","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the impact of MRI-defined bladder wall invasion from uterine cervical cancer (CC) on disease recurrence and overall survival.</p><p><strong>Materials and methods: </strong>IRB-approved multicenter retrospective study including women who underwent staging MRI for histologically confirmed CC (Jan 2015-Dec 2020). Image analysis was independently performed by two radiologists. Bladder wall invasion was diagnosed if ≥ 3 of the following criteria were met: loss of the cervix-bladder fat plane, bladder wall thickening, loss of bladder wall T2-hypointensity, and presence of endoluminal tumor growth. MRI findings were compared with endoscopy/cytology. The impact of MRI-defined bladder wall invasion on tumor recurrence and survival was assessed using logistic regression. Survival curves were compared using the log-rank test.</p><p><strong>Results: </strong>We included 214 women with a median age of 55 (IQR 47-65) years. MRI-defined bladder wall invasion was observed in 21.5% of patients. Cystoscopy revealed bladder mucosal infiltration in 7.0% of patients, all of whom demonstrated MRI-defined bladder wall invasion. No patients without MRI-defined bladder wall invasion showed mucosal infiltration on cystoscopy/cytology. The median follow-up was 32 months: 46.7% of patients had recurrence, and 23.4% had CC-related death. On logistic regression, MRI-defined bladder wall invasion was an independent risk factor for tumor recurrence (OR 2.24, p = 0.047) and mortality (OR 3.55, p = 0.006), whereas cystoscopy-defined bladder mucosa infiltration was not. The log-rank test demonstrated a significant difference in survival between patients with and without MRI-defined bladder wall invasion (χ² = 15.40, p = 0.0001).</p><p><strong>Conclusions: </strong>MRI-defined bladder wall invasion represents an independent negative prognostic factor in patients with cervical cancer.</p><p><strong>Key points: </strong>Question The prognostic significance of MRI-defined bladder wall invasion in patients with cervical cancer remains unclear with respect to disease recurrence and survival. Findings Bladder wall invasion identified on MRI is an independent predictor of tumor recurrence and tumor-specific mortality, whereas mucosal infiltration detected via cystoscopy is not. Clinical relevance MRI can safely replace cystoscopy in the preoperative staging of patients with uterine cervical cancer. This approach can reduce costs and expedite the staging process.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225174","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":"Longitudinal wash-in slope changes on dynamic contrast enhancement MRI for predicting response to neoadjuvant chemotherapy in breast cancer.","authors":"Yanbo Li, Jingbo Wang, Jinxia Guo, Caifeng Yue, Tianhui Liu, Yuchen Xue, Yuxin Cai, Wenqi Wang, Junnan Li, Jiahui Wang, Hong Lu","doi":"10.1007/s00330-025-12042-w","DOIUrl":"https://doi.org/10.1007/s00330-025-12042-w","url":null,"abstract":"<p><strong>Objectives: </strong>To determine whether wash-in slope (WIS) changes can predict pathologic complete response (pCR) following NAC in breast cancer.</p><p><strong>Materials and methods: </strong>This single-center retrospective study included consecutive females with breast cancer who received NAC followed by surgery between January 2016 and December 2022. All patients received dynamic contrast-enhanced MRI (DCE-MRI) pretreatment, after 2 cycles, 4 cycles, and after completion of treatment. The percentage change in tumor WIS from that before treatment (ΔWIS) was measured at each time point. Predictive performance for pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and across molecular subtypes.</p><p><strong>Results: </strong>A total of 162 patients were included in this study (mean age, 51.9 years ± 9.1 [SD]), and 43 (26.5%) achieved pCR. Overall, ΔWIS demonstrated comparable performance in predicting pCR after 2 cycles (AUC, 0.82; 95% CI: 0.73, 0.91), 4 cycles (AUC, 0.86; 95% CI: 0.78, 0.93), and after completion of NAC (AUC, 0.87; 95% CI: 0.8, 0.93), with no significant differences observed (all p > 0.05). Utilizing optimal threshold values of -33%, -44%, and -59% at each time point, ΔWIS yielded sensitivities ranging from 74.4% to 86.0% and specificities ranging from 75.6% to 80.7%. In molecular subtype analysis, ΔWIS after 4 cycles exhibited excellent predictive performance for pCR in triple-negative breast cancers (AUC, 0.96; 95% CI: 0.9, 1), outperforming its performance in Luminal B tumors (AUC, 0.83; 95% CI: 0.71, 0.94; p = 0.04).</p><p><strong>Conclusion: </strong>Tumor WIS changes from DCE-MRI could dynamically monitor neoadjuvant chemotherapy (NAC).</p><p><strong>Key points: </strong>Question Currently, there is no widely accepted standard imaging biomarker for predicting pCR in breast cancer patients undergoing NAC. Findings WIS changes outperformed tumor size in predicting pCR at four time points during NAC, and showed comparable predictive performance across all time points. Clinical relevance Longitudinal changes in the WIS derived from dynamic contrast-enhanced MRI enable real-time prediction of pathologic response to NAC in patients with breast cancer, supporting personalized treatment monitoring and decision-making.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145212092","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":"ESR Essentials: diffusion-weighted MRI-practice recommendations by the European Society for Magnetic Resonance in Medicine and Biology.","authors":"Marco Palombo, Benedetta Bodini, Francesco Grussu, Denis Le Bihan, Markus Nilsson, Raquel Perez-Lopez, Edwin H G Oei, Ivo G Schoots, Marion Smits, Ileana O Jelescu","doi":"10.1007/s00330-025-12033-x","DOIUrl":"https://doi.org/10.1007/s00330-025-12033-x","url":null,"abstract":"<p><p>Diffusion-weighted imaging (DWI) offers critical insights into tissue microstructure through the assessment of water molecule random displacements and plays a central role in the assessment of neoplastic and non-neoplastic diseases. To successfully implement and use DWI in clinical practice, guidelines for acquisition, interpretation of image contrast and of artefacts should be followed, taking the disease process and body part into account. We recommend covering a b-value range of 0-1000 s/mm² in the brain (along at least six directions for white matter), and 50-800 s/mm² in the body. Available acquisition acceleration options should be used to reduce repetition time (TR), echo time (TE), and echo-planar imaging (EPI) distortions, while considering the penalty in signal-to-noise ratio (SNR) and image sharpness. DW images and the apparent diffusion coefficient (ADC) map should be read jointly for the clinical interpretation. Areas of slower diffusion are hyperintense on DW images and hypointense on the ADC map, and vice versa. Magnetic susceptibility distortions and signal drop-outs or pile-ups are particularly pronounced at air-tissue or metal-tissue interfaces and may obscure areas of interest or hinder the co-localisation with structural scans. By following these guidelines and recommendations, radiologists and imaging professionals can enhance diagnostic accuracy, reduce variability, and maximise the clinical value of DWI across diverse applications. KEY POINTS: This article provides an overview of DWI principles, clinical applications, potential pitfalls, and emerging advances, alongside expert recommendations for optimal implementation. We provide key considerations tailored to specific applications (neuro and whole-body imaging), including protocol optimisation, adherence to established guidelines, and quality assurance measures to minimise artefacts and ensure reproducibility. By following the guidelines and recommendations summarised in this work, radiologists and imaging professionals can enhance diagnostic accuracy, reduce variability, and maximise the clinical value of DWI across diverse applications.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206054","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":"Intratumoral heterogeneity of CT enhancement for component prediction and prognostic significance in combined hepatocellular carcinoma‑cholangiocarcinoma.","authors":"Wei Cai, Yongjian Zhu, Dengfeng Li, Bingzhi Wang, Xiaohong Ma, Xinming Zhao","doi":"10.1007/s00330-025-12034-w","DOIUrl":"https://doi.org/10.1007/s00330-025-12034-w","url":null,"abstract":"<p><strong>Objectives: </strong>To construct a combined nomogram using CT enhancement ratio-based habitat imaging and radiological features in predicting the main component of combined hepatocellular carcinoma‑cholangiocarcinoma (cHCC-CCA), and to assess its ability for stratifying the prognosis.</p><p><strong>Materials and methods: </strong>Patients with pathologically diagnosed cHCC-CCA who underwent contrast-enhanced CT examinations were retrospectively included and randomized into the training and validation cohorts. Tumors were grouped into high hepatocellular carcinoma (HCC) component (high-HCC%) and low-HCC component (low-HCC%) according to pathology. Voxels of tumor from early enhancement ratio and late enhancement ratio maps were clustered into different habitats through the k-means algorithm. The volume fractions of different habitats were quantified. Logistic regression analyses were utilized to identify independent predictors for high-HCC%, construct prediction models, and visualize them as a nomogram. The predictive performance was assessed by receiver operating characteristic analysis. Survival analysis was conducted using the Kaplan-Meier method.</p><p><strong>Results: </strong>165 patients were finally included, and 78 (47.27%) patients were grouped as high-HCC%. Four tumor habitats were determined. The fraction of habitat 1 (f₁) was significantly higher, while the fraction of habitat 4 (f₄) was significantly lower in the high-HCC% group than in the low-HCC% group. Tumor capsule, corona enhancement, delayed enhancement, f₁, and f₄ were used to construct the combined nomogram with AUCs of 0.927 and 0.923 in training and validation cohorts, respectively. The combined nomogram predicted-high-HCC% exhibited better prognoses than the predicted-low-HCC% groups in terms of recurrence-free survival and overall survival.</p><p><strong>Conclusion: </strong>Enhancement-based CT habitat imaging exhibited potential for predicting the main component cHCC-CCA, and provided a tool for prognosis stratification.</p><p><strong>Key points: </strong>Question The component of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) significantly affected the prognosis, but there is no effective method for predicting the main component of cHCC-CCA. Findings The combined nomogram integrated habitat parameters and radiological features can predict the main component of cHCC-CCA and help stratify the prognosis after hepatectomy. Clinical relevance The habitat-based combined nomogram offers an effective tool for personalized and appropriate treatment in cHCC-CCA patients.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206076","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":"MRI-detected extranodal extension as a marker of prostate cancer aggressiveness.","authors":"Aline Araújo Naves, Gabriel de Lion Gouvea, Camila V B Machado, Leandro Machado Colli, Fernando Chahud, Rodolfo B Reis, Valdair F Muglia","doi":"10.1007/s00330-025-11532-1","DOIUrl":"10.1007/s00330-025-11532-1","url":null,"abstract":"<p><strong>Objective: </strong>Extranodal extension (ENE) is a histological marker of aggressiveness for various cancers. We evaluated if clinical ENE, detected by Magnetic Resonance Imaging, can also serve as a biological marker of Prostate Cancer (PCa) aggressiveness.</p><p><strong>Materials and methods: </strong>This retrospective, single-center study analyzed patients diagnosed with PCa and had MRI on a 3-T scanner from January 2013 to December 2017. After exclusions, 461 patients were included and divided into: Group 1, no lymph node involvement (LNI), Group 2 (LNI without ENE), and Group 3 (LNI and ENE). Two experienced radiologists assessed the MRI scans for primary lesion characteristics, LNI and ENE. Reproducibility assessment was calculated for ENE and PI-RADS. Clinical outcomes, including Overall Survival (OS), Specific Survival Rate (SSR), and Progression-Free Survival (PFS), were analyzed.</p><p><strong>Results: </strong>Group 1 included 410 patients, Group 2, 32 patients, and Group 3, 19 patients. The prevalence of ENE was 4.1%. Significant differences between groups were observed for age, PSA, dPSA, ISUP scores, clinical risk stratification, and staging (all p < 0.01). The Kappa coefficient for ENE was 0.75 (95% CI: 0.56-0.90), and 0.48 (0.14-1.0) for PI-RADS. Cox proportional hazards model showed PSA (HR: 1.009; 95% CI = 1.003-1.015, p < 0.01) and ENE (HR: 8.50; 1.76-40.98, p < 0.01) were associated with SSR, and both ENE (HR: 8.18; 2.34-28.58, p < 0.01) and LNI (HR: 5.99, 1.97-18.17, p < 0.01) were linked to poor PFS.</p><p><strong>Conclusion: </strong>MRI-detected ENE, despite low prevalence, is a predictor of SSR and PFS in PCa. These findings support ENE as an independent prognostic marker. Further prospective, multi-institutional studies are required to validate these results.</p><p><strong>Key points: </strong>Question Pathological extranodal extension (pENE) has been described as a marker of worrisome prognosis in prostate cancer (PCa), but clinical ENE has not been evaluated as a marker of prognosis in PCa. Findings MRI-detected clinical ENE, had a low prevalence in our cohort (4.1%), but it was a predictor of specific survival rate and progression-free survival. Clinical relevance MRI-detected clinical ENE, a reproducible imaging feature, may serve as a non-invasive biomarker for aggressive prostate cancer. It correlates with poorer progression-free survival and specific survival rates, offering valuable prognostic insights for patient management.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6020-6030"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143788051","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":"An interpretable radiomics-based machine learning model for predicting reverse left ventricular remodeling in STEMI patients using late gadolinium enhancement of myocardial scar.","authors":"Xiuzheng Yue, Jianing Cui, Sicong Huang, Wenjia Liu, Jing Qi, Kunlun He, Tao Li","doi":"10.1007/s00330-025-11419-1","DOIUrl":"10.1007/s00330-025-11419-1","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the added value of the late gadolinium enhancement (LGE)-scar radiomics features in predicting reverse left ventricular remodeling (r-LVR) in ST-segment elevation myocardial infarction (STEMI) patients using machine learning (ML).</p><p><strong>Materials and methods: </strong>This retrospective study included 105 STEMI patients who underwent CMR within 7 days and 5 months post-percutaneous coronary intervention (PCI) on 1.5-T or 3.0-T MRI scanners (January 2014-2023). Radiomics features from LGE scar images and routine CMR markers were analyzed using a LightGBM model enhanced by Shapley Additive exPlanations (SHAP) for interpretability. Patients were divided into training (80) and test (25) sets. Three predictive models were developed: traditional CMR, LGE-scar radiomics, and a combined model integrating both. Model performance was assessed using ROC curves and AUC analysis.</p><p><strong>Results: </strong>In the training set, the traditional CMR model achieved an AUC of 0.745 (95% CI: 0.62-0.86), the LGE-scar radiomics model had an AUC of 0.712 (95% CI: 0.58-0.83), and the combined model showed the highest AUC of 0.754 (95% CI: 0.63-0.86). In the test set, the traditional CMR model's AUC decreased to 0.656 (95% CI: 0.42-0.88), while the LGE-scar radiomics model improved to 0.818 (95% CI: 0.59-1.00). The combined model achieved the highest AUC of 0.890 (95% CI: 0.75-1.00). SHAP analysis highlighted significant predictors such as infarct percentage of LV mass and wavelet-transformed texture features.</p><p><strong>Conclusion: </strong>Integrating LGE scar radiomics features with traditional CMR parameters in a LightGBM model enhances predictive accuracy for r-LVR in STEMI patients, potentially improving patient stratification and treatment personalization.</p><p><strong>Key points: </strong>Question Predicting r-LVR in STEMI patients remains challenging due to limitations in current imaging approaches. Findings Integrating LGE-scar radiomics and cardiac magnetic resonance markers in the LightGBM model significantly improves prediction accuracy for r-LVR. Clinical relevance This interpretable ML model enhances r-LVR prediction, supporting patient stratification and optimizing treatment strategies to improve patient outcomes.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6302-6312"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143779539","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":"ESR Bridges: imaging and management of carotid atherosclerosis through a standardized classification system-a multidisciplinary view.","authors":"Riccardo Cau, Kosmas I Paraskevas, Peter Libby, Luca Saba","doi":"10.1007/s00330-025-11607-z","DOIUrl":"10.1007/s00330-025-11607-z","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"5878-5880"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143977630","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":"Reply to the Letter to the Editor: ABO incompatibility in liver transplantation-How should we face it?","authors":"Kyowon Gu, Woo Kyoung Jeong","doi":"10.1007/s00330-025-11592-3","DOIUrl":"10.1007/s00330-025-11592-3","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6620-6621"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143993853","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":"Developments, challenges and opportunities in radiological ultrasound-fit for the future?","authors":"Maija Radzina, Paul Sidhu, Thomas Fischer","doi":"10.1007/s00330-025-11595-0","DOIUrl":"10.1007/s00330-025-11595-0","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":"6101-6103"},"PeriodicalIF":4.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143984921","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}