European Journal of Radiology最新文献

{"title":"Quantitative study of vestibular endolymphatic hydrops in Meniere’s disease based on Three-Dimensional real Inversion Recovery (3D-real IR) sequence","authors":"Jiajia Zhao ,&nbsp;Mengqiu Liu ,&nbsp;Siqi Sun ,&nbsp;Ruirui Guan ,&nbsp;Ying Liu","doi":"10.1016/j.ejrad.2025.112382","DOIUrl":"10.1016/j.ejrad.2025.112382","url":null,"abstract":"<div><h3>Objective</h3><div>To establish objective criteria for grading vestibular endolymphatic hydrops (EH) in Meniere’s disease (MD) using 3D-real IR MRI, and investigate its clinical correlations.</div></div><div><h3>Methods</h3><div>Retrospective analysis of 155 MD patients (189 ears) included clinical data, audiovestibular assessments, and gadolinium-enhanced MRI. Vestibule volume (VV) and the volume of vestibular endolymph (EndV) were outlined on 3D-real IR sequence images, and the volume of vestibular endolymph was calculated by the vestibular endolymphatic ratio (ELR) to evaluate the degree of EH, analyze the correlation between the degree of EH and specific clinical features, hearing and vestibular function, and determine the optimal ELR value to differentiate each degree of effusion by using receiver operating characteristic (ROC) curve analysis.</div></div><div><h3>Results</h3><div>EH severity significantly correlated with disease stage (P &lt; 0.001), pure-tone average (P &lt; 0.001), age (P &lt; 0.01), and caloric weakness (P &lt; 0.01), but not with gender, disease duration, vertigo frequency, tinnitus, aural fullness, or electrocochleography. Affected ears demonstrated significantly different EndV (0.013 ± 0.003 vs 0.005 ± 0.001 cm³) and ELR (33.6 ± 12.1 % vs 6.4 ± 2.7 %) compared to controls (P &lt; 0.01), while maintaining comparable VV (0.08 ± 0.016 cm³). ROC analysis established ELR thresholds of 16 % (AUC = 0.905), 34 % (AUC = 0.871), and 47 % (AUC = 0.899) differentiating no hydrops from grade I, grade I from II, and grade II from III, respectively.</div></div><div><h3>Conclusion</h3><div>3D-real IR MRI enables quantitative EH assessment, with ELR thresholds providing objective grading criteria. EH severity reflects pathophysiological progression through its associations with auditory/vestibular dysfunction and disease stage, while demonstrating stability of total vestibular volume. This methodology addresses limitations of subjective grading systems, offering standardized metrics for clinical research and therapeutic monitoring.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112382"},"PeriodicalIF":3.3,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144931591","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 of a multi-feature predictive model for risk stratification in stage IB-IIA non-small cell lung cancer: a multicenter analysis","authors":"Xiaomei Zhong ,&nbsp;Huan Lin ,&nbsp;Rong Zhang ,&nbsp;Yunlang She ,&nbsp;Xiaobo Chen ,&nbsp;Wei Zhao ,&nbsp;Shiwei Luo ,&nbsp;Entao Liu ,&nbsp;Qingyu Liu ,&nbsp;Jun Liu ,&nbsp;Xin Chen ,&nbsp;Zaiyi Liu","doi":"10.1016/j.ejrad.2025.112379","DOIUrl":"10.1016/j.ejrad.2025.112379","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to develop a comprehensive risk stratification model for stage IB-IIA non-small cell lung cancer (NSCLC) by integrating clinicopathological data with pre-treatment CT imaging.</div></div><div><h3>Methods</h3><div>This retrospective study included three independent cohorts of patients with stage IB-IIA NSCLC for model development and validation (Training: n = 370; Internal validation: n = 120; External validation: n = 70). Disease-free survival (DFS) was the primary endpoint. Radiomics features were extracted from both tumoral and peritumoral regions of CT images to construct a radiomics model. A ResNet50-based deep learning architecture was adopted to develop a deep learning model using CT imaging data. Logistic regression was used to identify significant clinicopathological factors. These components were integrated into a multi-feature combined model (CRD model) that utilized clinicopathological, radiomics, and deep learning features for DFS prediction. Model interpretability was assessed using the SHapley Additive exPlanations (SHAP) method.</div></div><div><h3>Results</h3><div>The combined CRD model demonstrated superior performance in predicting DFS, achieving areas under the curve (AUC) of 0.865, 0.798, and 0.803 in the training, internal validation, and external validation cohorts, respectively. Patients were stratified into high- and low-risk groups using the CRD model, and in the external validation cohort, the hazard ratio (HR) for high-risk patients was 17.509, with a C-index of 0.73. SHAP analysis revealed that radiomics features contributed most significantly to the performance of the CRD model.</div></div><div><h3>Conclusions</h3><div>The multi-feature combined model effectively predicts DFS and identifies high-risk patients with stage IB-IIA NSCLC. It could facilitate personalized postoperative treatment strategies, improving patient outcomes.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112379"},"PeriodicalIF":3.3,"publicationDate":"2025-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144931592","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":"Automatic analysis of carpal angles using dynamic CT imaging: Reference values in healthy wrists and assessment of scapholunate ligament injuries","authors":"Maranda Haenen ,&nbsp;Erin Teule ,&nbsp;Stefan Hummelink ,&nbsp;Ioannis Sechopoulos ,&nbsp;Brigitte van der Heijden","doi":"10.1016/j.ejrad.2025.112374","DOIUrl":"10.1016/j.ejrad.2025.112374","url":null,"abstract":"<div><h3>Introduction</h3><div>Dynamic CT imaging is a promising modality for evaluating wrist pathologies like scapholunate ligament (SL) injuries. The primary objective of this study is to extract carpal angles from dynamic CT datasets using an automated motion analysis algorithm to provide reference values for healthy wrist motion. Secondly, the feasibility of this automatic method to detect SL ligament pathology was evaluated.</div></div><div><h3>Methods</h3><div>Dynamic CT scans of healthy wrists and wrists with arthroscopically-confirmed complete SL injuries (Geissler IV) were analysed. Each scan consisted of one static image and two dynamic imaging sequences: wrist radial-ulnar deviation (RUD) and flexion–extension (FE). Bones were automatically segmented, and the radioscaphoid (RSA), scapholunate (SLA), capitolunate (CLA), and radiolunate (RLA) angles were automatically determined in each wrist position. A linear mixed model was applied to compare carpal angles between the two groups (p &lt; 0.05).</div></div><div><h3>Results</h3><div>A total of 84 wrists scans were analysed, of which 73 healthy and 11 injured. Reference values for healthy wrists were provided, with an average and maximum 95% CI width during all movements of 5°and 7°, respectively. Feasibility analysis showed that the SLA, CLA, and RLA were different between the healthy and injured groups during all movements. No differences were found for the RSA.</div></div><div><h3>Conclusion</h3><div>Reference values of the moving wrist of healthy participants were automatically extracted. Furthermore, our results suggest that the RLA, CLA, and SLA may be useful parameters for distinguishing wrists with complete SL injuries from healthy ones, making the automatic approach feasible.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112374"},"PeriodicalIF":3.3,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144921743","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":"Predictive model based on mesorectal fat radiomics for pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer","authors":"Shuhong Fan ,&nbsp;Ning Wang ,&nbsp;Yi Wen ,&nbsp;Weicai Shi ,&nbsp;Yonghe Chen ,&nbsp;Kaikai Wei","doi":"10.1016/j.ejrad.2025.112378","DOIUrl":"10.1016/j.ejrad.2025.112378","url":null,"abstract":"<div><h3>Purpose</h3><div>To explore the predictive value of MRI radiomics based on mesorectal fat for pathological complete response (pCR) to neoadjuvant chemoradiotherapy in locally advanced rectal cancer, and to develop a combined predictive model incorporating MRI radiomics, quantitative fat parameters and clinical features.</div></div><div><h3>Materials and Methods</h3><div>In this retrospective study, 235 rectal cancer patients who received neoadjuvant chemoradiotherapy followed by resection were enrolled, with their pretreatment MRI. Patients were randomly allocated into training (n = 164) and test (n = 71) cohorts. Mesorectal fat was manually segmented on T2-weighted imaging. Radiomics model to predict pCR were built through maximum Relevance Minimum Redundancy algorithm and Least Absolute Shrinkage and Selection Operator regression. Univariate and multivariate logistic regression analyses were performed to select independent predictive factors from imaging and clinical features. Then a combined radiomic-clinical predictive model and a nomogram were constructed. Model performances were evaluated using the area under the curve (AUC) and compared using the DeLong test.</div></div><div><h3>Results</h3><div>The radiomics model demonstrated AUCs of 0.78 in the test set. A radiomics-clinical model integrating Radscore, N stage, posterior mesorectal thickness, and mesorectal fat area, reached an AUC of 0.92 (95% CI: 0.89–0.95) in the test cohort.</div></div><div><h3>Conclusion</h3><div>Radiomics-clinical model based on mesorectal fat could be a useful approach for pretreatment pCR prediction in locally advanced rectal cancer.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112378"},"PeriodicalIF":3.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912839","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":"Enlarged choroid plexus is associated with reduced gray matter volumes and increased plasma amyloid-beta: a population-based study of older adults","authors":"Qianqian Xie ,&nbsp;Ziwei Chen ,&nbsp;Jiafeng Wang ,&nbsp;Yan Wang ,&nbsp;Huisi Zhang ,&nbsp;Xiaoyu Wang ,&nbsp;Chunyan Li ,&nbsp;Yongxiang Wang ,&nbsp;Lin Cong ,&nbsp;Lin Song ,&nbsp;Yifeng Du ,&nbsp;Chengxuan Qiu","doi":"10.1016/j.ejrad.2025.112372","DOIUrl":"10.1016/j.ejrad.2025.112372","url":null,"abstract":"<div><h3>Objectives</h3><div>To characterize brain structures and plasma Alzheimer’s-related biomarkers associated with enlarged choroid plexus (ChP) among rural older adults in China.</div></div><div><h3>Methods</h3><div>This population-based cross-sectional study included 1115 older adults (age ≥ 60 years) derived from the Multimodal Interventions to delay Dementia and disability in rural China, who underwent structural brain MRI scans (3.0 T) in 2018–2020; of these, plasma biomarkers for Alzheimer’s disease and neurodegeneration, i.e., β-amyloid (Aβ) 40, Aβ42, neurofilament light chain (NfL), and total tau, were measured using the Simoa platform for 814 persons. ChP was automatically segmented and quantified on T1-weighted images. Data were analyzed using the voxel-based morphometry (VBM) analysis, general linear regression model, and mediation model.</div></div><div><h3>Results</h3><div>The enlarged ChP volume was significantly associated with reduced gray matter volume (GMV) mainly in the insular region, hippocampus, parahippocampal gyrus, and left thalamus (<em>P</em> &lt; 0.05). In the plasma biomarker subsample, larger ChP volume was associated with higher plasma Aβ40 and Aβ42, and the association was significant only in men (<em>P</em> for ChP volume × sex interaction &lt; 0.05). The mediation analysis suggested that plasma Aβ40 significantly mediated the association of enlarged ChP volume with the reduced GMV of insular region, hippocampus, and left thalamus in men, with the proportion of mediation being 10.73 %, 6.32 %, and 11.45 %, respectively.</div></div><div><h3>Conclusions</h3><div>Enlarged ChP volume was associated with reduced regional GMV and increased plasma Aβ40 in older adults, suggesting that the enlarged ChP might be a neuroimaging marker for the brain aging.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112372"},"PeriodicalIF":3.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896034","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":"Application of contrast-enhanced CT-driven multimodal machine learning models for pulmonary metastasis prediction in head and neck adenoid cystic carcinoma","authors":"Wei Gong ,&nbsp;Qingying Cui ,&nbsp;Shuai Fu ,&nbsp;Yong Wu","doi":"10.1016/j.ejrad.2025.112377","DOIUrl":"10.1016/j.ejrad.2025.112377","url":null,"abstract":"<div><h3>Objective</h3><div>This study explores radiomics and deep learning for predicting pulmonary metastasis in head and neck Adenoid Cystic Carcinoma (ACC), assessing machine learning(ML) algorithms’ model performance.</div></div><div><h3>Methods</h3><div>The study retrospectively analyzed contrast-enhanced CT imaging data and clinical records from 130 patients with pathologically confirmed ACC in the head and neck region. The dataset was randomly split into training and test sets at a 7:3 ratio. Radiomic features and deep learning-derived features were extracted and subsequently integrated through multi-feature fusion. Z-score normalization was applied to training and test sets. Hypothesis testing selected significant features, followed by LASSO regression (5-fold CV) identifying 7 predictive features. Nine machine learning algorithms were employed to build predictive models for ACC pulmonary metastasis: ada, KNN, rf, NB, GLM, LDA, rpart, SVM-RBF, and GBM. Models were trained using the training set and tested on the test set. Model performance was evaluated using metrics such as recall, sensitivity, PPV, F1-score, precision, prevalence, NPV, specificity, accuracy, detection rate, detection prevalence, and balanced accuracy.</div></div><div><h3>Results</h3><div>Machine learning models based on multi-feature fusion of enhanced CT, utilizing KNN, SVM, rpart, GBM, NB, GLM, and LDA, demonstrated AUC values in the test set of 0.687, 0.863, 0.737, 0.793, 0.763, 0.867, and 0.844, respectively. Rf and ada showed significant overfitting. Among these, GBM and GLM showed higher stability in predicting pulmonary metastasis of head and neck ACC.</div></div><div><h3>Conclusion</h3><div>Radiomics and deep learning methods based on enhanced CT imaging can provide effective auxiliary tools for predicting pulmonary metastasis in head and neck ACC patients, showing promising potential for clinical application.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112377"},"PeriodicalIF":3.3,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896035","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":"More than a rebuttal: a field guide to letters to the editor in radiology","authors":"Naoko Mori ,&nbsp;Yu Mori ,&nbsp;Motoko Konno ,&nbsp;Tomoki Tozawa ,&nbsp;Kento Hatakeyama ,&nbsp;Shunji Mugikura","doi":"10.1016/j.ejrad.2025.112375","DOIUrl":"10.1016/j.ejrad.2025.112375","url":null,"abstract":"<div><div>Letters to the Editor (LTEs) provide an important platform for academic communication. They enable researchers to engage with recently published studies, share their opinions, and contribute to the ongoing discussions in their fields. While traditionally viewed as rebuttal-type responses to target articles, LTEs can be written in more flexible formats, including matchmaking-type, agreement/praise-type, building-upon-type, independent-type, and case report-type LTEs. These variations allow for discussions that range from methodological critiques to new insights, interdisciplinary perspectives, or important clinical experiences.</div><div>Unlike the text-based critiques common in other fields, LTEs in radiology often involve discussion of visual data or technical performance measures. Further, engaging with sociological issues such as the ethical considerations of radiation exposure or contrast agent use can help improve clinical judgment, not only for researchers but also for radiologists in daily practice. This review article introduces and classifies multiple types of LTEs based on examples of LTEs in journals related to radiology. Practical guidance is provided on how to select appropriate topics, structure arguments, and adhere to journal-specific submission guidelines. We also outline the publication process from submission to potential reply by the original authors.</div><div>Writing LTEs has several benefits: it encourages critical thinking, improves scientific writing skills, and promotes participation in academic communication. Furthermore, LTEs contribute to the transparency in peer-reviewed literature and may inspire future research. When written respectfully and constructively, LTEs serve as a high-level tool for academic communication and scientific development. This review aims to make LTEs more accessible and practical for researchers, particularly in the field of radiology, by demonstrating their flexible formats and academic value.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112375"},"PeriodicalIF":3.3,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144889502","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":"Optimized post-processing parameters for dry bone computed tomography imaging: Recommendations for diverse research applications","authors":"Haiyang Xing ,&nbsp;Jiajing Zhu ,&nbsp;Ruiqi Zou ,&nbsp;Xiongfeng Tang ,&nbsp;Min Yi ,&nbsp;Zhuoting Xie ,&nbsp;Quanchao Zhang ,&nbsp;Yanguo Qin","doi":"10.1016/j.ejrad.2025.112376","DOIUrl":"10.1016/j.ejrad.2025.112376","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to compare the performance of different convolution kernels and reconstruction matrices in enhancing computed tomography (CT) image quality and three-dimensional (3D) reconstruction quality. Based on these findings, recommendations for optimizing CT post-processing parameters are provided to meet various research needs.</div></div><div><h3>Methods</h3><div>Forty-nine dry human femurs, excavated from archaeological sites, were selected for analysis. Two blinded reviewers scored the CT images from four convolution kernel and reconstruction matrix combinations using a five-point Likert scale for image quality. For 3D reconstruction quality, models generated by optical scanners served as the gold standard and were compared with four CT groups. Measurements included length, angle, cross-sectional area, and volume.</div></div><div><h3>Results</h3><div>CT images processed with the Br59 + 512 group achieved the highest image quality scores. For 3D reconstruction quality, a significant difference in length measurements was observed between the Br40 + 512 and Br40 + 1024 groups (P &lt; 0.05). Angle measurements showed no significant differences across all groups. In cross-sectional area and volume measurements, the Br40 + 1024 group showed no statistically significant difference from the reference group.</div></div><div><h3>Conclusion</h3><div>Sharp convolution kernels are associated with higher image quality, whereas soft kernels help reduce noise and enhance 3D reconstruction quality. Although larger reconstruction matrices do not significantly improve image quality based on visual assessment, they contribute to higher-quality 3D models. We recommend the Br59 kernel with a 512 matrix for optimal image observation and the Br40 kernel with a 1024 matrix for 3D reconstruction and morphological analyses.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112376"},"PeriodicalIF":3.3,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144890733","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":"Sarcopenia diagnosed by chest CT predicts long-term mortality in critically ill patients with exacerbation of chronic obstructive pulmonary disease","authors":"Xinyu Dai ,&nbsp;Qiqiang Zhou ,&nbsp;Qizheng Wang ,&nbsp;Meng Wang ,&nbsp;Weili Zhao ,&nbsp;Qingtao Zhou ,&nbsp;Ke Liu ,&nbsp;Ning Lang ,&nbsp;Ying Liang","doi":"10.1016/j.ejrad.2025.112373","DOIUrl":"10.1016/j.ejrad.2025.112373","url":null,"abstract":"<div><h3>Background</h3><div>Sarcopenia is a prevalent comorbidity in patients with chronic obstructive pulmonary disease (COPD). We aimed to investigate the impact of sarcopenia diagnosed by chest CT on mortality in critically ill patients with exacerbation of COPD (ECOPD).</div></div><div><h3>Methods</h3><div>This retrospective study enrolled 148 patients hospitalized in the intensive care unit due to ECOPD from 2018 to 2023. Sarcopenia was defined by the skeletal muscle index measured at the 12th thoracic vertebra (T12) level on chest CT. Patients were categorized into the sarcopenia and non-sarcopenia groups. Hospitalization duration, short-term (30 and 90-day) and long-term (1-year and overall) COPD-related mortality and all-cause mortality were compared between the two groups. Cox regression analyses were conducted to recognize the risk factors for mortality, and a sarcopenia-based nomogram was developed.</div></div><div><h3>Results</h3><div>Eighty-four patients (56.76 %) with sarcopenia were identified through chest CT measurements. The 1-year COPD-related and all-cause mortality, as well as overall COPD-related and all-cause mortality, were significantly higher in the sarcopenia group than the non-sarcopenia group (19.05 % <em>vs.</em> 4.69 %, <em>p</em> = 0.010; 28.57 % <em>vs.</em> 6.25 %, <em>p</em> = 0.001; 33.33 % <em>vs.</em> 15.63 %, <em>p</em> = 0.015; 47.62 % <em>vs.</em> 29.69 %, <em>p</em> = 0.027, respectively). Multivariate Cox regression analyses revealed sarcopenia as a risk factor for 1-year (HR = 3.981 [1.137–13.938], <em>p</em> = 0.031) and overall (HR = 2.308 [1.310–4.065], <em>p</em> = 0.004) mortality. The sarcopenia-based nomogram demonstrated favorable prognostic performance.</div></div><div><h3>Conclusions</h3><div>Sarcopenia evaluated at the T12 level on chest CT may serve as a prognostic factor for predicting long-term mortality among critically ill patients with ECOPD.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112373"},"PeriodicalIF":3.3,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892074","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":"Time-varying relationship between ischemic core volume and outcomes after mechanical thrombectomy","authors":"Kota Maekawa ,&nbsp;Yoshinori Matsuoka ,&nbsp;Nobuyuki Ohara ,&nbsp;Chisato Miyakoshi ,&nbsp;Michi Kawamoto ,&nbsp;Nobuyuki Sakai ,&nbsp;Tsuyoshi Ohta","doi":"10.1016/j.ejrad.2025.112369","DOIUrl":"10.1016/j.ejrad.2025.112369","url":null,"abstract":"<div><h3>Background and purpose</h3><div>The time-varying relationship between ischemic core volume and neurological outcomes remains uncertain. This study aimed to evaluate how this relationship changes over time in patients undergoing mechanical thrombectomy (MT) and create visual probability heat maps to help clinical decision-making.</div></div><div><h3>Methods</h3><div>We reviewed data from 168 patients who underwent successful MT (mTICI 2b-3) between March 2021 and December 2023. Patients underwent preoperative computed tomography perfusion (CTP) evaluation using RAPID software, with ischemic core defined as relative cerebral blood flow &lt; 30 % of contralateral blood flow. We used logistic regression models with interaction terms between time from onset to CTP (OTCTP) and ischemic core volume, adjusting for age, sex, time from CTP to reperfusion, and premorbid mRS score. Outcomes were assessed using 90-day mRS scores.</div></div><div><h3>Results</h3><div>The median patient age was 78.0 years, with 50.5 % male. The median ischemic core volume was 9 mL, and the median OTCTP was 126 min. Poor outcomes, defined as mRS 5–6 were observed in 23.8 % of patients. The probability of poor outcomes increased with longer OTCTP intervals, even with identical ischemic core volumes. An ischemic core volume of 50 mL was associated with probabilities of poor outcomes of 0.18 at 3.0 h, 0.25 at 8.0 h, and 0.56 at 24 h after onset. Compared with final infarct volumes on magnetic resonance imaging, CTP-derived core volumes showed over- and underestimation within 3.0 h, while consistent underestimation was observed beyond 6.0 h.</div></div><div><h3>Conclusions</h3><div>The clinical significance of CTP-derived ischemic core volume is time dependent and should be considered when selecting patients for treatment. The heat map developed in this study may assist in identifying appropriate candidates for MT.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"192 ","pages":"Article 112369"},"PeriodicalIF":3.3,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880077","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}