European Radiology最新文献

{"title":"VIBESegmentator: full body MRI segmentation for the NAKO and UK Biobank.","authors":"Robert Graf, Paul Platzek, Evamaria Olga Riedel, Constanze Ramschütz, Sophie Starck, Hendrik K Möller, Matan Atad, Henry Völzke, Robin Bülow, Carsten Oliver Schmidt, Julia Rüdebusch, Matthias Jung, Marco Reisert, Jakob Weiss, Maximilian T Löffler, Fabian Bamberg, Benedikt Wiestler, Johannes C Paetzold, Daniel Rueckert, Jan Stefan Kirschke","doi":"10.1007/s00330-025-12035-9","DOIUrl":"https://doi.org/10.1007/s00330-025-12035-9","url":null,"abstract":"<p><strong>Objectives: </strong>To present a publicly available deep learning-based torso segmentation model that provides comprehensive voxel-wise coverage, including delineations that extend to the boundaries of anatomical compartments.</p><p><strong>Materials and methods: </strong>We extracted preliminary segmentations from TotalSegmentator, spine, and body composition models for magnetic resonance tomography (MR) images, then improved them iteratively and retrained an nnUNet model. Using a random retrospective subset of German National Cohort (NAKO), UK Biobank, internal MR and computed tomography (CT) data (Training: 2897 series from 626 subjects, 290 female; mean age 53 ± 16; 3-fold-cross validation (20% hold-out). Internal testing 36 series from 12 subjects, 6 male; mean age 60 ± 11), we segmented 71 structures in torso MR and 72 in CT images: 20 organs, 10 muscles, 19 vessels, 16 bones, ribs in CT, intervertebral discs, spinal cord, spinal canal and body composition (subcutaneous fat, unclassified muscles and visceral fat). For external validation, we used existing automatic organ segmentations, independent ground truth segmentations on gradient echo images, and the Amos data. We used non-parametric bootstrapping for confidence intervals and the Wilcoxon rank-sum test for computing statistical significance.</p><p><strong>Results: </strong>We achieved an average Dice score of 0.90 ± 0.06 on our internal gradient echo test set, which included 71 semantic segmentation labels. Our model ties with the best model on Amos with a Dice of 0,81 ± 0.14, while having a larger field of view and a considerably higher number of structures included.</p><p><strong>Conclusion: </strong>Our work presents a publicly available full-torso segmentation model for MRI and CT images that classifies almost all subject voxels to date.</p><p><strong>Key points: </strong>Question No completed MRI segmentation model exists that delineates the true transition boundaries of the anatomical structures of bone and muscles. Findings We provide a simple-to-use model that automatically segments MRI images, that can be utilized as a backbone for computer-aided automatic analysis. Clinical relevance Our segmentation model enables accurate and detailed full-torso segmentation on MRI and CT, improving automated analysis in large-scale epidemiological studies and facilitating more precise body composition and organ assessments for clinical and research applications.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145257610","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":"Safe for kids? AI medical devices in radiology overlook paediatric suitability.","authors":"Brendan S Kelly, Jennifer Lee, Edward Antram, Owen Arthurs, Susan C Shelmerdine","doi":"10.1007/s00330-025-11975-6","DOIUrl":"https://doi.org/10.1007/s00330-025-11975-6","url":null,"abstract":"<p><strong>Objectives: </strong>Prior publications have highlighted inconsistent labelling of intended use cases and target population for U.S. Food and Drug Administration-approved AI medical devices, especially for children. The extent to which this issue applies to devices within Europe remains unaddressed.</p><p><strong>Materials and methods: </strong>A comprehensive review was conducted of all regulatory-approved AI medical devices for use in radiology from a non-profit, publicly available database. Two independent reviewers assessed information about all the devices regarding use case, modality and intended population. A third reviewer resolved any discrepancies. Where the intended population was unclear, a standardised review of the available evidence and marketing materials for the AI device was conducted.</p><p><strong>Results: </strong>Only four (4/213, 2%) AI medical devices were clearly labelled for paediatric use. A further 11% were intended for all ages, including children. The majority (88/213; 41%) of all AI medical devices did not clearly demonstrate their intended population on the database. Further examination of the scientific literature and marketing of these \"unclear\" devices showed that 6 (6/88, 7%) of these included patients under 18 in their intended target population, but 47% (41/88) still remained unclear after further review.</p><p><strong>Conclusion: </strong>Most regulated radiology AI medical devices have missing or unclear information regarding the appropriate use in children. This poses significant potential risk, including inadvertent off-label use, which could compromise patient safety. The EU AI Act emphasises the need for transparency and accountability in AI device deployment, and we therefore advocate for a standardised paediatric safety indicator to clearly communicate suitability.</p><p><strong>Key points: </strong>Question To what extent do European-approved radiology AI devices provide clear labelling of intended use and suitability for paediatric populations? Findings Many radiology AI medical devices in Europe lack explicit paediatric use information, raising concerns about unintended off-label use. Clinical relevance Clear labelling of AI device suitability for children is essential to ensure safe use. A standardised safety indicator could aid clinicians in appropriate device selection.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145250208","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":"Navigating the CT wave: multicentric chest imaging trends before, during, and after COVID-19 Pandemic.","authors":"Thiago Lima, Natalia Saltybaeva, Tobias Gassenmaier, Lukas Ebner, Justus E Roos","doi":"10.1007/s00330-025-12030-0","DOIUrl":"https://doi.org/10.1007/s00330-025-12030-0","url":null,"abstract":"<p><strong>Objective: </strong>The COVID-19 pandemic has significantly impacted healthcare practices worldwide, including the use of computed tomography (CT) in chest examinations. This study aims to analyse the trends in CT chest examinations before, during, and after the pandemic.</p><p><strong>Material and methods: </strong>Data were retrospectively collected from 10 public hospitals over a period spanning from pre-pandemic years (2019 until February 2020) through the pandemic (March 2020-April 2023) (as defined by the World Health Organisation) and into the post-pandemic phase (May 2023-December 2024). Patient exposure information from more than 240,000 CT examinations was collected and analysed using a commercial dose management system. Statistical analysis was performed with descriptive and inferential statistics employed to compare the number of CT chest examinations and patient radiation exposure across different periods.</p><p><strong>Results: </strong>The results indicate a marked increase in CT chest examinations during the pandemic, which reached a plateau and remained stable post-pandemic (p-value < 0.001). Importantly, the average radiation exposure per patient has decreased with the evolution of technology, indicating improved dose management practices. The results also showed a shift between protocols used for CT chest examinations during the pandemic, with the move towards more dedicated procedures.</p><p><strong>Conclusion: </strong>These findings highlight the sustained demand for CT chest examinations and the effective management of patient radiation exposure during and after the pandemic. The study underscores that those possible practices obtained during the pandemic became the norm after the end of the pandemic.</p><p><strong>Key points: </strong>Question This study analyses trends in CT chest examinations and patient radiation exposure before, during, and after the COVID-19 pandemic. Findings CT chest examinations rose sharply during the pandemic, then stabilised, while average patient radiation exposure remained consistent throughout. Clinical relevance The findings demonstrate ongoing demand for CT chest scans and radiation management, emphasizing the need for sustainable imaging practices in future healthcare planning.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145250281","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 for breast cancer prevention: the vision ahead.","authors":"Francesco Sardanelli, Gianfranco Scaperrotta","doi":"10.1007/s00330-025-12036-8","DOIUrl":"https://doi.org/10.1007/s00330-025-12036-8","url":null,"abstract":"<p><p>Over the past decade, artificial intelligence (AI) has entered the medical field, particularly in radiology. Fifty years after the transition from \"silver to silicon\", we are experiencing a second digital revolution fueled by AI and radiomics. Breast imaging-and mammography in particular-plays a special role in this transformation due to the availability of large screening datasets. The advantages that AI tools bring to mammography interpretation are substantial: they can increase cancer detection rates by over 25% and reduce reading workload by more than 40%. In addition, AI can aid in quality control of mammograms and-importantly-in stratifying breast cancer risk, enabling personalized screening strategies. However, enhancing screening programs alone is not sufficient for BC prevention. True prevention aims to stop cancer before it starts. As defined by the Oxford Learner's Dictionary of Academic English, prevention is \"the act of stopping something bad from happening.\" Screening represents secondary prevention and, on its own, is not enough. As physicians-and not merely image analysts-we must also focus on primary (true) prevention by promoting a healthier lifestyle, regular physical exercise, balanced diet and weight control, and smoking cessation. Pharmacological prevention should be considered when indicated, such as for women who were diagnosed with selected B3 lesions or have a personal history of breast cancer. Web-based tools and mobile apps-especially when combined with wearable devices-can support these efforts. AI has the potential to help both primary and secondary breast cancer prevention. Much research is expected in this area. KEY POINTS: AI can enhance screening mammography by increasing detection rates (by over 25%) and reducing the reading workload (by over 40%), as well as through deep learning-based risk stratification. Breast radiologists should prioritize primary (true) prevention by promoting healthy lifestyle choices, open to integrating web-based tools, mobile apps, and wearable devices. AI holds promise for both supporting primary and secondary breast cancer prevention, with radiologists playing a pivotal role in its implementation.</p>","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145250119","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":"Toward personalized hepatocellular carcinoma treatment using liver MRI: predicting intratumoral tertiary lymphoid structure maturity.","authors":"Dong Ho Lee, Jeong Min Lee","doi":"10.1007/s00330-025-11992-5","DOIUrl":"https://doi.org/10.1007/s00330-025-11992-5","url":null,"abstract":"","PeriodicalId":12076,"journal":{"name":"European Radiology","volume":" ","pages":""},"PeriodicalIF":4.7,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145238444","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":"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":"Recurrence patterns and survival outcomes after irreversible electroporation for hepatocellular carcinoma: a 6-year multicenter experience.","authors":"Min Xu, Shanyu Yin, Qiyu Zhao, Guo Tian, Jinhua Pan, Gang Dong, Wu Zhang, Tuerganaili Aji, Jiansong Ji, Xinhua Chen, Danxia Xu, Tian'an Jiang","doi":"10.1007/s00330-025-12044-8","DOIUrl":"https://doi.org/10.1007/s00330-025-12044-8","url":null,"abstract":"<p><strong>Objectives: </strong>Irreversible electroporation (IRE) is a relatively recent non-thermal ablation technique for hepatocellular carcinoma (HCC) in high-risk anatomical locations, but post-procedural recurrence limits long-term survival. This study aimed to investigate the risk factors, patterns, and outcomes of post-IRE recurrence.</p><p><strong>Materials and methods: </strong>This study retrospectively analyzed 180 patients with solitary HCC (≤ 5 cm) who underwent IRE at five centers. Recurrence was categorized as local tumor progression (LTP), intrahepatic distant recurrence (IDR), aggressive intrasegmental recurrence (AIR), and extrahepatic distant recurrence (EDR). Competing-risk regression models and dynamic risk curves were utilized to assess risk factors and temporal trends.</p><p><strong>Results: </strong>Over a mean follow-up of 40.9 ± 12.6 months, 50.6% of patients developed recurrence. IDR was the predominant pattern (41.7%), followed by LTP (10.0%), EDR (8.3%), and AIR (1.7%). Multivariate analysis identified cirrhosis and tumor size as predictors of LTP; recurrent HCC and cirrhosis as predictors of IDR; and the male sex, cirrhosis, and tumor size as predictors of EDR (all p < 0.05). Only EDR was an independent risk factor for worse overall survival (p < 0.001). Recurrence risk demonstrated a bimodal pattern, with peaks at 21 and 33 months.</p><p><strong>Conclusion: </strong>IDR is the dominant post-IRE recurrence pattern, but only EDR predicts survival. The identified risk factors and bimodal recurrence peaks contribute to guiding stratified therapeutic strategies for HCC in high-risk locations.</p><p><strong>Key points: </strong>Question Current knowledge of post-ablation recurrence patterns for hepatocellular carcinoma is primarily derived from thermal ablation, lacking data for non-thermal irreversible electroporation. Findings Intrahepatic distant recurrence was the most common recurrence pattern, while only extrahepatic distant recurrence predicted worse survival. Clinical relevance Irreversible electroporation provided excellent local control for high-risk hepatocellular carcinoma but struggled with recurrence. While extrahepatic distant recurrence predicted reduced survival, local or intrahepatic recurrences yielded favorable outcomes with salvage therapy.</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":"145212154","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}