European Journal of Radiology最新文献

{"title":"Interobserver variability of recall decisions between mammography readers in the English NHS breast screening programme: A comparison of interobserver variability measures","authors":"Laura Quinn ,&nbsp;David Jenkinson ,&nbsp;Sian Taylor-Phillips ,&nbsp;Yemisi Takwoingi ,&nbsp;Alice Sitch","doi":"10.1016/j.ejrad.2026.112723","DOIUrl":"10.1016/j.ejrad.2026.112723","url":null,"abstract":"<div><h3>Objectives</h3><div>To evaluate interobserver variability between mammogram readers’ recall decisions in the English NHS breast screening programme, comparing different variability measures.</div></div><div><h3>Methods</h3><div>Data from 401,682 women in 22 NHS centres who underwent mammographic screening interpreted independently by two mammogram readers were included. Percentage agreement, prevalence-adjusted bias-adjusted-kappa (PABAK), Gwet’s agreement coefficient (Gwet’s AC) and Cohen’s kappa were reported with 95% confidence intervals. Analyses were performed separately for women at first and subsequent screening appointments, by cancer diagnosis, reader recall rates and age group.</div></div><div><h3>Results</h3><div>Of 86,287 women at first screening, 6,491 (7.5%) were recalled, compared to 9,488 (3.0%) of 315,395 at subsequent screenings. Percentage agreement, Gwet’s AC, and PABAK were lower for first screening than subsequent (93.6%, 95%CI: 93.4–93.7 vs 97.2%, 95%CI: 97.2–97.3), (92.3, 95%CI:92.1 to 92.5 vs 97.0, 95% CI: 97.0 to 97.1) and (87.2, 95%CI: 86.9–87.4 vs 94.4, 95%CI: 94.3–94.5), whereas Cohen’s kappa, which is biased downwards when prevalence of recall is lower, did not change (61.6, 95%CI: 60.7–62.5 vs 61.8, 95%CI: 61.0–62.5). Percentage agreement, Gwet’s AC, and PABAK were lower for women with cancer detected than without, but Cohen’s kappa showed the opposite pattern, driven by prevalence bias. Percentage agreement, Gwet’s AC, and PABAK were lower when one/both readers had high recall rates, but Cohen’s kappa showed no important pattern.</div></div><div><h3>Conclusions</h3><div>Percentage agreement, Gwet’s AC, and PABAK showed lower agreement for interpreting the more challenging first screen, without assistance of previous mammograms, when women had cancer and when one/both readers had a high recall rate. Cohen’s kappa was heavily distorted by outcome prevalence. Despite widespread use, Cohen’s kappa is inappropriate for low prevalence settings such as screening, or making comparisons when prevalence varies.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112723"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161987","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":"The application of Machine learning in predicting the outcomes of minimally invasive treatments for uterine Fibroids: A systematic review and meta-analysis","authors":"Mohammad-Reza Hosseini-Siyanaki ,&nbsp;Seyyed Mohammad Hosseini ,&nbsp;Maryam Afshari ,&nbsp;Fatemeh Kanaani Nejad ,&nbsp;Hoda Mehrabi ,&nbsp;Reza Elahi ,&nbsp;Ahmadreza Sohrabi-Ashlaghi ,&nbsp;Babak Ahmadi ,&nbsp;Shakiba Houshi ,&nbsp;Fereshteh Yazdanpanah ,&nbsp;Zahra Beyzavi ,&nbsp;Shams Iqbal","doi":"10.1016/j.ejrad.2026.112726","DOIUrl":"10.1016/j.ejrad.2026.112726","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>Uterine fibroids (UFs) are common benign tumors that impact women’s health, particularly through symptoms such as abnormal bleeding or reproductive dysfunction. Interventional radiology (IR) techniques like uterine artery embolization (UAE) and high-intensity focused ultrasound (HIFU) are minimally invasive alternatives to surgery. Machine learning (ML) has shown promise in predicting treatment outcomes, though the optimal model remains uncertain. This systematic review and <em>meta</em>-analysis evaluate models predicting outcomes of minimally invasive treatments for uterine fibroids.</div></div><div><h3>Materials &amp; Methods</h3><div>A comprehensive search was conducted across five databases (PubMed, Embase, Scopus, Web of Science, and Cochrane) through November 2024, following PRISMA guidelines and registered in PROSPERO. Studies using ML to predict different outcomes of UFs treatment via minimally invasive treatments were included. PROBAST + AI was used to assess study quality. Pooled sensitivity, specificity, and AUC values were calculated using a bivariate random effect model.</div></div><div><h3>Results</h3><div>Out of 1,114 records, fourteen studies met the inclusion criteria, with 12 focusing on HIFU and two on UAE. Logistic regression was the most commonly used approach, while gradient‑boosting models reported high discrimination in some individual studies; however, external validation was uncommon and risk of bias was frequently high. AUCs for radiomics-based models ranged from 0.668 to 0.887, and combined models ranged from 0.773 to 0.93. Meta-analysis of five HIFU-based radiomics studies demonstrate pooled sensitivity of 75% and specificity of 76% respectively, with an AUC of 0.82.</div></div><div><h3>Conclusion</h3><div>ML models, particularly those integrating radiomics and clinical data, show strong performance in predicting image-guided treatment outcomes in UFs. These approaches support a promising path toward individualized treatment planning and may improve patient selection in clinical workflow.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112726"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146200578","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":"Explainable and evidence-linked recommendations for spine surgery via a retrieval-augmented LLM agent","authors":"Yiren Li,&nbsp;Mingyu Lv,&nbsp;Liang Cheng,&nbsp;Yongxu Xie,&nbsp;Qian Gu,&nbsp;Haozheng He,&nbsp;Zhuguang Chen,&nbsp;Duopei Fang,&nbsp;Xiang Zhou","doi":"10.1016/j.ejrad.2026.112734","DOIUrl":"10.1016/j.ejrad.2026.112734","url":null,"abstract":"<div><h3>Background</h3><div>Clinical decision-making in spinal and spinal cord diseases requires a comprehensive assessment of imaging findings, neurological status, bone integrity, and patient-centered goals. Recently, the emergence of Large Language Models (LLMs) has provided new tools for intelligent decision support; however, their reliability and clinical interpretability remain to be systematically evaluated.</div></div><div><h3>Methods</h3><div>We propose a novel retrieval augmented generation (RAG)-based framework specifically tailored for spinal disease decision support and systematically evaluated four advanced LLM agents (Gemini 2.5 Flash, DeepSeek, GPT-4o, GPT-4o-mini). The framework integrates domain-specific prompting, structured response formatting, and evidence citation tracking.We used 200 real-world spinal cases, each involving diagnostic, therapeutic, and follow-up tasks. Five spine surgeons independently evaluated model outputs using an 11-dimension rubric; each dimension rated on a 5-point Likert scale to evaluate both clinical and technical performance. Inter-group differences were analyzed using the Kruskal–Wallis and Dunn’s tests (P &lt; 0.05), with radar plots used for multidimensional visualization.</div></div><div><h3>Results</h3><div>The proposed expert-evaluated framework enables a comprehensive, real-case-based comparison of four LLM agents. Gemini 2.5 Flash achieved the highest overall score (49.25 ± 2.88), significantly outperforming DeepSeek (47.49 ± 3.34, <em>P</em> &lt; 0.001), GPT-4o (45.59 ± 3.89, <em>P</em> &lt; 0.001), and GPT-4o-mini (41.23 ± 5.96, <em>P</em> &lt; 0.001). It demonstrated leading performance particularly in humanistic care, follow-up suggestion, and test recommendation. DeepSeek showed superior capability in differential completeness (mean = 4.76), significantly outperforming the other three models (<em>P</em> &lt; 0.001). Although GPT-4o-mini demonstrated stable system performance (mean = 4.61), it underperformed in core clinical reasoning dimensions. These findings reveal substantial inter-model variability in spine-specific clinical reasoning, an aspect often overlooked in prior non-benchmark LLM evaluations.</div></div><div><h3>Conclusion</h3><div>Among the four evaluated LLM agents, Gemini 2.5 Flash and DeepSeek demonstrated superior clinical accuracy, comprehensiveness, and usability in spine-related decision support. These findings support the potential of domain-adapted RAG agents to enhance evidence-based spinal care by providing accurate and comprehensive decision support. Future research should focus on multimodal integration data (e.g., imaging and clinical notes) and conducting prospective validation in real-world clinical environments.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112734"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146776188","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":"Development and validation of a nomogram to predict surgical resection after conversion therapy in unresectable hepatocellular carcinoma","authors":"Yuhao Su ,&nbsp;Yuxin Liang ,&nbsp;Deyuan Zhong,&nbsp;Yahui Chen,&nbsp;Hongtao Yan,&nbsp;Qinyan Yang,&nbsp;Ming Wang,&nbsp;Zhengwei Leng,&nbsp;Xiaolun Huang","doi":"10.1016/j.ejrad.2026.112724","DOIUrl":"10.1016/j.ejrad.2026.112724","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to explore factors associated with the likelihood of surgical resection after triple-combination conversion therapy in patients with initially unresectable hepatocellular carcinoma (uHCC) and to develop an exploratory predictive model.</div></div><div><h3>Methods</h3><div>A retrospective analysis was conducted using clinical data from 210 patients with uHCC who underwent triple-combination conversion therapy at Sichuan Cancer Hospital between January 2022 and January 2025. Patients were randomly assigned to a training cohort (n = 147) and a validation cohort (n = 63) in a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) regression was applied to screen candidate predictors, followed by multivariate logistic regression to identify factors associated with surgical conversion. A nomogram was constructed based on these variables, and its discriminative ability, calibration, and potential clinical utility were internally assessed using receiver operating characteristic (ROC) analysis, calibration plots, the Hosmer–Lemeshow test, and decision curve analysis (DCA).</div></div><div><h3>Results</h3><div>Among the 210 patients, 47 (22.4%) successfully underwent conversion and radical resection. Multivariate logistic regression analysis suggested that lower tumor burden score (TBS; OR = 0.663), lower neutrophil-to-lymphocyte ratio (NLR; OR = 0.572), lower C-reactive protein-to-albumin ratio (CAR; OR = 0.057), and absence of cirrhosis (OR = 0.289) were associated with a higher likelihood of successful surgical conversion (P &lt; 0.05). The nomogram showed moderate to good discriminative performance, with areas under the ROC curve (AUCs) of 0.850 (95% CI: 0.784–0.915) in the training cohort and 0.871 (95% CI: 0.783–0.962) in the validation cohort. Calibration plots and decision curve analysis provided descriptive information regarding model performance within the study cohort.</div></div><div><h3>Conclusion</h3><div>The proposed nomogram, incorporating TBS, NLR, CAR, and cirrhosis status, represents an exploratory tool for estimating the probability of surgical conversion following triple-combination therapy in patients with uHCC. While the model may provide supplementary information to support clinical assessment and patient stratification, further multicenter and prospective studies are required to externally validate and refine its performance before broader clinical application.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112724"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146219026","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":"Mri-based diagnostic model integrating clinical features for placenta accreta spectrum in non-previa placenta","authors":"Yoshiko Ueno ,&nbsp;Takahiro Tsuboyama ,&nbsp;Naoya Ebisu ,&nbsp;Hitomi Imafuku ,&nbsp;Toshiki Hyodo ,&nbsp;Keitaro Sofue ,&nbsp;Daigo Kobayashi ,&nbsp;Izumi Imaoka ,&nbsp;Kenji Tanimura ,&nbsp;Takamichi Murakami","doi":"10.1016/j.ejrad.2026.112717","DOIUrl":"10.1016/j.ejrad.2026.112717","url":null,"abstract":"<div><h3>Objectives</h3><div>To identify clinical and MRI features useful for diagnosing placenta accreta spectrum (PAS) in non-previa placenta and to develop diagnostic models integrating these features.</div></div><div><h3>Methods</h3><div>This retrospective study included 101 pregnant women with non-previa placenta who underwent MRI between January 2022 and June 2024. Nineteen were confirmed as PAS. Clinical variables and 11 MRI findings were evaluated using intraoperative or pathological results as the reference standard. Diagnostic performance was assessed using univariable analysis and repeated cross-validation of a random forest (RF) model, with ROC analysis used to assess discriminative performance.</div></div><div><h3>Results</h3><div>Hormone replacement cycle–frozen embryo transfer (HRC-FET) (sensitivity 0.89, specificity 0.63) and abnormal placental bed vascularization (sensitivity 0.63, specificity 0.90) showed the strongest univariable performance. The RF model using six variables with acceptable interobserver agreement achieved an AUC of 0.88, sensitivity 0.92, specificity 0.79, demonstrating higher discriminative performance than individual predictors. Feature importance analysis highlighted HRC-FET and abnormal placental bed vascularization as the most influential factors.</div></div><div><h3>Conclusions</h3><div>Integrating clinical and MRI features improves PAS diagnosis in non-previa placenta. The RF model demonstrated a more balanced diagnostic profile than individual predictors in this exploratory cohort and may aid preoperative risk assessment. HRC-FET and abnormal placental bed vascularization were key contributors, supporting their relevance for risk stratification.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112717"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146172727","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":"Artificial intelligence-assisted CCTA for coronary stenosis detection: Diagnostic promise, methodological nuances, and directions for clinical translation","authors":"Weihao Cheng ,&nbsp;Zekai Yu","doi":"10.1016/j.ejrad.2026.112670","DOIUrl":"10.1016/j.ejrad.2026.112670","url":null,"abstract":"","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112670"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975420","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":"Letter to Editor: Correlation between MRI-derived and biopsy-confirmed liver iron concentration in patients with chronic liver disease","authors":"Sari Luthfiyah ,&nbsp;Triwiyanto Triwiyanto ,&nbsp;Luthfi Rusyadi ,&nbsp;Mohammed Ismath","doi":"10.1016/j.ejrad.2026.112701","DOIUrl":"10.1016/j.ejrad.2026.112701","url":null,"abstract":"<div><div>We comment on Ba-Ssalamah et al.’s study comparing MRI-derived and biopsy-confirmed liver iron concentration in chronic liver disease. The strong agreement between two R2*-based methods supports the robustness of relaxometry-based LIC estimation in the low–mild iron range. We discuss physics-related considerations, including R2* nonlinearity, spatial sampling, signal modeling, and calibration dependence, and outline future directions toward volumetric mapping and cross-platform harmonization for quantitative liver MRI.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112701"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146099918","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":"Pelvic floor dysfunction: Anatomical characterization and functional imaging with MRI defecography","authors":"Rosa Alba Pugliesi,&nbsp;Roberto Cannella,&nbsp;Federica Vernuccio,&nbsp;Marika Triscari Barberi,&nbsp;Giovanni Roccella,&nbsp;Giuseppe Brancatelli,&nbsp;Giuseppe Lo Re","doi":"10.1016/j.ejrad.2026.112706","DOIUrl":"10.1016/j.ejrad.2026.112706","url":null,"abstract":"<div><div>Pelvic floor dysfunction encompasses a spectrum of disorders characterized by organ descent, muscular weakness, and impaired coordination across the anterior, middle, and posterior compartments. MRI defecography has become an established non-invasive technique for comprehensive assessment of both static anatomy and dynamic function of the pelvic floor. This review describes the MRI defecography technique, protocol components, and quantitative parameters that provide an objective evaluation of pelvic floor dysfunction. Standard MRI defecography protocol incorporates resting, contraction, straining, and evacuation phases, with single-shot fast spin-echo and real-time sequences enabling visualization of pelvic structures throughout motion. Quantitative parameters, including the anorectal angle, pubococcygeal line, H and M lines, minimal prolapse level, and levator plate angle, allow for objective evaluation of pelvic floor dysfunction. MRI defecography is particularly valuable in complex and postoperative scenarios, allowing detection of cystoceles, rectoceles, enteroceles, uterine or vaginal prolapse, intussusception, and post-surgical complications. In addition, MRI-defecography highlights the importance of stabilizing structures such as the urogenital diaphragm, endopelvic fascia, and levator ani complex. By integrating anatomic and functional findings, MRI defecography supports individualized therapeutic planning, guides surgical decision-making, and improves long-term outcomes. MRI defecography has thus emerged as a cornerstone in the multidisciplinary management of pelvic floor dysfunction.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112706"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146118375","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":"Corrigendum to “Degeneration of the cartilage quality is correlated with a higher intramuscular fat infiltration of the vastus medialis in older adults with pre-to-mild knee osteoarthritis” [Eur. J. Radiol. 183 (2025) 111930]","authors":"Shogo Okada ,&nbsp;Masashi Taniguchi ,&nbsp;Masahide Yagi ,&nbsp;Yoshihiro Fukumoto ,&nbsp;Tetsuya Hirono ,&nbsp;Momoko Yamagata ,&nbsp;Ryusuke Nakai ,&nbsp;Masashi Kobayashi ,&nbsp;Noriaki Ichihashi","doi":"10.1016/j.ejrad.2026.112714","DOIUrl":"10.1016/j.ejrad.2026.112714","url":null,"abstract":"","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112714"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146131874","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":"Quantitative assessment of lung density and developmental patterns in preterm infants using three-dimensional ultrashort echo time MRI (UTE-MRI)","authors":"Yujie Chen ,&nbsp;Yan Sun ,&nbsp;Yu Song ,&nbsp;Yi Liao ,&nbsp;Xuesheng Li ,&nbsp;Xijian Chen ,&nbsp;Gang Ning","doi":"10.1016/j.ejrad.2026.112696","DOIUrl":"10.1016/j.ejrad.2026.112696","url":null,"abstract":"<div><h3>Background</h3><div>Three-dimensional ultrashort echo time (3D-UTE) MRI enables proton-density assessment of lung parenchyma without radiation. We aimed to evaluate the feasibility of 3D-UTE for quantifying lung density of preterm infants and characterize gestational-age (GA)-dependent developmental patterns.</div></div><div><h3>Methods</h3><div>101 infants (1 day-24 months) were enrolled as extremely-to-very preterm (EVP, &lt;32 weeks, n = 33), moderate-to-late preterm (MLP, 32–&lt;37 weeks, n = 34), and full-term (FT, 37–42 weeks, n = 34). Lung protocol including 3D-UTE, 3D-GRE (gradient-echo) and T2-FSE (fast spin-echo) sequences were used. Image quality was assessed qualitatively and quantitatively. Lung density was quantified using UTE-derived lung-to-muscle ratios (LMRs), and group differences and age-related patterns were evaluated.</div></div><div><h3>Results</h3><div>UTE-MRI provided superior visualization of lung structure with significantly higher signal-to-noise and contrast-to-noise ratios. Lung-to-muscle ratios demonstrated a consistent anterior–posterior gradient (R² = 0.582, <em>p</em> &lt; 0.001) and decreased with lower gestational age (LMR-total: FT 50.8 ± 9.7; MLP 48.7 ± 7.6; EVP 45.1 ± 7.6), with EVP significantly lower than FT (<em>p</em> &lt; 0.05). Within the first year of life, age-related analyses revealed distinct developmental patterns across gestational age groups.</div></div><div><h3>Conclusions</h3><div>UTE-MRI enables radiation-free quantification of lung density. UTE-MRI-derived lung-to-muscle ratios provide a radiation-free biomarker of preterm lung structural deficits and support risk-adapted follow-up.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112696"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146060911","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}