European Journal of Radiology最新文献

{"title":"Spectral CT-Based habitat imaging for the prediction of occult lymph node metastasis in resectable pancreatic ductal Adenocarcinoma: Pathological validation via collagen ratio","authors":"Yi Chen ,&nbsp;Wei Liu ,&nbsp;Tiansong Xie ,&nbsp;Meng Gao ,&nbsp;Jing Sun ,&nbsp;Zehua Zhang ,&nbsp;Lei Chen ,&nbsp;Yu Wang ,&nbsp;Jin Xu ,&nbsp;Zhengrong Zhou","doi":"10.1016/j.ejrad.2026.112679","DOIUrl":"10.1016/j.ejrad.2026.112679","url":null,"abstract":"<div><h3>Importance</h3><div>Occult lymph node metastasis (LNM) remains challenging to detect preoperatively in resectable pancreatic ductal adenocarcinoma (PDAC), yet has significant implications for treatment and prognosis.</div></div><div><h3>Objective</h3><div>To evaluate the predictive value of spectral CT–based habitat imaging and CT-diagnosed peripancreatic invasion for occult LNM in resectable PDAC, with pathological validation using collagen ratio.</div></div><div><h3>Methods</h3><div>This retrospective study included 113 patients with resectable PDAC who underwent triple-phase spectral CT before surgery. Occult LNM was defined as pathologically confirmed nodal metastasis without radiologically suspicious lymph nodes; nodes with short-axis diameter ≥10 mm were excluded. Tumors were segmented into subregions based on pancreatic-to-venous phase iodine concentration ratio (PVICR), and subregional volume fractions were quantified. Correlations with collagen ratio were assessed via Spearman analysis. Patients were divided into a training cohort (n = 79; 30 with occult LNM) and a validation cohort (n = 34; 12 with occult LNM). A logistic regression model with backward stepwise selection was developed and evaluated by receiver operating characteristic analysis.</div></div><div><h3>Results</h3><div>Four subregions were identified. Subregion 1, characterized by the lowest PVICR, showed a moderate negative correlation with collagen ratio (r =  − 0.543, <em>p</em> &lt; 0.001). The combined model incorporating the Subregion 1 fraction and CT-diagnosed peripancreatic invasion yielded areas under the curve of 0.836 (95% CI: 0.733–0.921) and 0.820 (95% CI: 0.661–0.955) in the training and validation cohorts, respectively.</div></div><div><h3>Conclusions</h3><div>Subregion 1 fraction and CT-diagnosed peripancreatic invasion enable accurate preoperative prediction of occult LNM in resectable PDAC.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112679"},"PeriodicalIF":3.3,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146009445","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":"Synovitis mediates the association between medial meniscal extrusion and subchondral bone denudation in knee osteoarthritis: Data from the FNIH OA biomarkers consortium","authors":"Dongfan Liu ,&nbsp;Yingwei Sun ,&nbsp;Lunhao Bai ,&nbsp;Chunbo Deng","doi":"10.1016/j.ejrad.2026.112669","DOIUrl":"10.1016/j.ejrad.2026.112669","url":null,"abstract":"<div><h3>Background</h3><div>Medial meniscal extrusion (MME) accelerates structural progression in knee osteoarthritis (KOA). While its biomechanical impact has been established, its relationship with subchondral bone denudation and the potential mediating role of synovitis remain unclear.</div></div><div><h3>Purpose</h3><div>This study aimed to investigate the association between MME in the absence of medial meniscal posterior root tears and the size of denuded areas of subchondral bone (dABs), and to evaluate whether synovitis mediates this relationship.</div></div><div><h3>Methods</h3><div>Data from the Foundation for the National Institutes of Health (FNIH) Osteoarthritis Biomarkers Consortium were analyzed. MME and synovitis (effusion-synovitis and Hoffa-synovitis) were assessed semi-quantitatively using the MRI Osteoarthritis Knee Score (MOAKS) system. The size of medial tibiofemoral dABs was quantified at baseline and 24-month follow-up. Linear regression models evaluated cross-sectional and longitudinal associations. Causal mediation analysis was conducted to quantify the proportion of the total effect of MME on dABs mediated by synovitis.</div></div><div><h3>Results</h3><div>A total of 520 participants were included. Cross-sectionally, both baseline MME (β = 2.03,95 % CI: 0.67, 3.38) and synovitis score (β = 0.97,95 % CI: 0.48, 1.46) were significantly associated with central medial femoral (cMF) dABs. Longitudinal analysis revealed significant correlations between MME and both 24-month cMF dABs (β = 3.41,95 % CI: 1.49,5.33) and 24-month medial tibial (MT) dABs (β = 0.98,95 % CI: 0.47,1.87). Furthermore, the 24-month synovitis score showed significant associations with both cMF dABs (β = 2.06,95 % CI: 1.38,2.74) and MT dABs (β = 0.88,95 % CI: 0.55,1.21). Mediation analysis indicated that synovitis mediated 20.1 % (95 % CI: 6.6, 71.1) of the effect of MME on baseline cMF dABs. 24-month synovitis mediated 20.38 % (95 % CI: 6.61, 44.50) of the effect of MME on 24-month cMF dABs and 16.86 % (95 % CI: 2.71, 42.16) of its effect on 24-month MT dABs.</div></div><div><h3>Conclusion</h3><div>MME and dABs showed significant correlations in both cross-sectional and longitudinal studies. Synovitis acted as a mediator between MME and dABs, suggesting that inflammatory pathways may be involved in the pathological mechanisms of MME promoting KOA progression.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112669"},"PeriodicalIF":3.3,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146017550","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":"Utilizing baseline multiregional MRI radiomics for prediction of tumor deposition and prognosis following neoadjuvant therapy in resectable rectal cancer","authors":"Bingjie Wu ,&nbsp;Lingwei Wang ,&nbsp;Yang Wang ,&nbsp;Fan Liu ,&nbsp;Xujie Gao ,&nbsp;Wenpeng Wang ,&nbsp;Bohan Xiao ,&nbsp;Ying Liu","doi":"10.1016/j.ejrad.2026.112676","DOIUrl":"10.1016/j.ejrad.2026.112676","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate whether pre-treatment T2WI-based multiregional radiomics can predict the probability of post-treatment tumor deposit (TD) and prognostic outcomes in patients with resectable rectal cancer after neoadjuvant therapy.</div></div><div><h3>Materials and methods</h3><div>This retrospective study included 159 patients with pathologically confirmed rectal cancer who received neoadjuvant therapy and then underwent surgery from March 2013 to March 2024. Radiomics features were extracted from the intratumoral region, a 3-mm-region straddling the tumor margin, and peritumoral 3 mm region on pre-treatment T2WI images. Clinical-radiomics nomogram was developed based on the most predictive radiomics signatures and clinical risk factors. Prognostic model for 5-year recurrence-free survival (RFS) was constructed by Cox regression analysis.</div></div><div><h3>Results</h3><div>The nomogram integrating clinical risk factors (Tumor distance to anal margin and MRI-reported extramural vascular invasion (EMVI)) with an intra-straddle 3 mm radiomics signature score (radscore) demonstrated optimal predictive performance with area under the receiver operating characteristic curve (AUC) of 0.953 (95% CI: 0.877–0.988), 0.810 (95% CI: 0.629–0.928) and 0.952 (95% CI: 0.857–0.992) in the training cohort, validation cohort and test cohort, respectively. The prognostic model constructed by intra-straddle 3 mm radscore (hazard ratio [HR] = 3.60, 95% CI: 1.59–8.16) and MRI-reported EMVI (HR = 6.07, 95% CI: 2.51–14.63) showed good performance for predicting 5‑year RFS with AUC of 0.827 (95% CI: 0.772–0.890) in the entire cohort.</div></div><div><h3>Conclusion</h3><div>The nomogram, incorporating pre-treatment MRI-based intra-straddle 3 mm radscore along with clinical risk factors, facilitates noninvasive assessment of the likelihood of TD positivity following neoadjuvant therapy, and has the power to predict 5-year RFS in patients with resectable rectal cancer.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112676"},"PeriodicalIF":3.3,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074619","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":"Association between cognitive status and structural brain changes in Alzheimer’s disease: Clinical implication of lightweight deep learning-aided diagnosis","authors":"Po-Hsuan Hsieh ,&nbsp;Ya-Fang Chen ,&nbsp;Ta-Fu Chen ,&nbsp;Wen-Chau Wu ,&nbsp;for the Alzheimer’s Disease Neuroimaging Initiative","doi":"10.1016/j.ejrad.2026.112678","DOIUrl":"10.1016/j.ejrad.2026.112678","url":null,"abstract":"<div><h3>Background</h3><div>The complex brain changes involved in Alzheimer’s disease (AD) development constitute a high-dimensional nonlinear feature space where deep learning (DL) classification/diagnosis may be advantageous over classical non-learning methods. However, the practicality of DL remains under debate among healthcare professionals, largely because many models are computationally expensive and operate without explicit interpretability. This study aimed to construct a lightweight DL model to disclose the association between cognitive status and structural brain changes in AD.</div></div><div><h3>Methods</h3><div>By using the data obtained from the Alzheimer’s Disease Neuroimaging Initiative database, 418 AD patients and 418 age-matched cognitively normal (CN) subjects were included for DL model construction based on their T1-weighted magnetic resonance images at baseline visit. A lightweight design was achieved by incorporating group convolution, global pooling, and efficient channel attention.</div></div><div><h3>Results</h3><div>The accuracy rate of our model was 90.6 %, competitive with previous models built with up-to-ten times more parameters. The occlusion maps showed that the medial temporal area and thalamus accounted the most for our model’s differentiation between AD and CN, in line with current knowledge of the pathological trajectory. Hierarchical regression further revealed that the logit of the DL model output explained a significant amount of variance in the mini mental state examination score, above and beyond the clinical indices including age, sex, and education duration (<em>R</em>² change = 0.341, <em>F</em>(1, 91) = 57.623, <em>p</em> &lt; 0.001).</div></div><div><h3>Conclusions</h3><div>Lightweight DL can be clinically practicable for AD diagnosis by focusing on pathologically interpretable structural changes and offering image-based assessment of cognitive status.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112678"},"PeriodicalIF":3.3,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146009423","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":"Performance analysis of liver segmentation using nn-UNet TotalSegmentator: Focus on atypical livers, pathologies, and variants","authors":"Joy-Marie Kleiß ,&nbsp;Sebastian Arndt ,&nbsp;Lisa Sommerfeld ,&nbsp;Maximilian Schmidt MD ,&nbsp;Florian Putz ,&nbsp;Teresa Graetz ,&nbsp;Leonard Stepansky ,&nbsp;Kaan Türkan ,&nbsp;Simon Mayr ,&nbsp;Michael Uder ,&nbsp;Matthias S May","doi":"10.1016/j.ejrad.2026.112674","DOIUrl":"10.1016/j.ejrad.2026.112674","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>This study evaluates the accuracy of the nn-UNet TotalSegmentator (TS) by Wasserthal et al. (2023) in segmenting atypical livers with pathologies and variants in CT scans.</div></div><div><h3>Materials and Methods</h3><div>CT scans were retrospectively collected from our RIS and divided into two cohorts: a reference group (67 healthy livers) and a study group (55 scans across eleven pathology and variant subgroups). TS performed automatic segmentation for all groups. For reference, the images were then manually segmented, with corrections reviewed by two radiologists. Accuracy was assessed using Dice similarity score, Hausdorff distance (HD), mean surface distance (MSD), volume difference, and clinical ratings.</div></div><div><h3>Results</h3><div>Automatic segmentation underestimated liver volume by a mean of 48.11  ml (3.1%) in the reference group and overestimated it in 84% of study group cases by 79.09 ml (4%).</div><div>The average Dice score was 0.980 ± 0.007 for the reference group and 0.933 ± 0.113 for the study group. Hepatomegaly achieved the highest score (0.979 ± 0.006), Polycystic liver disease (PLD) the lowest (0.656 ± 0.230). Cirrhosis with Ascites, Beavertail, and PLD had significantly lower Dice scores than the reference group. Clinical ratings were often lower than Dice scores suggested, especially in Beavertail, Cirrhosis with Ascites, Ablation defects, Metastases, and Hemihepatectomy.</div></div><div><h3>Conclusion</h3><div>TS performs excellently on healthy and well on most pathological livers. Despite high Dice scores in many pathological cases, clinical ratings reveal limitations. Clinical evaluation remains essential. Inclusion of PLD and Beavertail cases in training data may reduce bias and improve performance.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112674"},"PeriodicalIF":3.3,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035336","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":"Relationship between resource utilization and diagnostic accuracy of large language models for efficient multimodal reasoning in radiologic image interpretation","authors":"Taewon Han ,&nbsp;Jeong Hyun Lee ,&nbsp;Woo Kyoung Jeong,&nbsp;Jaeseung Shin,&nbsp;Yun Hwa Roh,&nbsp;Min Je Kim","doi":"10.1016/j.ejrad.2026.112677","DOIUrl":"10.1016/j.ejrad.2026.112677","url":null,"abstract":"<div><h3>Objectives</h3><div>We evaluated the diagnostic performance and resource efficiency of three multimodal-reasoning-models for radiological image interpretation.</div></div><div><h3>Methods</h3><div>Using three multimodal-reasoning-models, we analyzed 73 cases under different conditions (Imaging-Only and Combined-Descriptive-Text) with three system prompt types (basic [without system prompt], original [specialized-role], and chain-of-thought [CoT] prompts). Quiz cases were extracted from the Korean Society of Ultrasound in Medicine Website, along with corresponding human benchmark data. Diagnostic performance was assessed through Multiple-Choice (MCQ) and Differential-Diagnosis (DDx) outputs. Resource utilization was measured by token consumption for each case across all scenarios. Pearson correlation coefficients were calculated to evaluate associations between token usage and diagnostic accuracy.</div></div><div><h3>Results</h3><div>For imaging-only input, under CoT prompt, o1 demonstrated superior accuracy of 56.2 %, surpassing the 55.9 % human benchmark compared to Claude-3.7-Sonnet (49.3 %) and Gemini-2.0-Flash-Thinking-Experimental (37 %) for MCQ. The integration of descriptive-text inputs substantially increased performance across all models, with o1 achieving the highest accuracy (71.2 %, with basic and original). This performance advantage was most pronounced in DDx. Original prompts utilized fewer output tokens while maintaining comparable accuracy for o1 (Imaging-Only with DDx: original vs. basic, CoT prompts, all p &lt; 0.01). Intra-model analysis revealed a negative correlation between accuracy and output token for o1 (r = -0.41), while inter-model analysis showed strong positive correlations between total token and accuracy (r = 0.93 for Imaging-Only with MCQ).</div></div><div><h3>Conclusion</h3><div>The paradoxical relationship between resource utilization and diagnostic accuracy suggests that model architecture fundamentally determines baseline performance, while prompt optimization influences efficiency within architectural constraints on multimodal-reasoning-models.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112677"},"PeriodicalIF":3.3,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146035636","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":"Ultrashort echo time MRI radiomics as a predictor of clinical outcomes in patellar tendinopathy: Insights from a large prospective clinical trial","authors":"Yijie Fang ,&nbsp;Jie Deng ,&nbsp;Stephan J. Breda ,&nbsp;Robert-Jan de Vos ,&nbsp;Edwin H.G. Oei ,&nbsp;Jukka Hirvasniemi","doi":"10.1016/j.ejrad.2026.112675","DOIUrl":"10.1016/j.ejrad.2026.112675","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the predictive utility of radiomic features extracted from ultrashort echo time (UTE) MRI in comparison to conventional proton density (PD) sequences for short-term (24-week) and long-term (5-year) clinical outcomes in patients with patellar tendinopathy (PT) receiving exercise therapy.</div></div><div><h3>Materials and methods</h3><div>This prospective study of 76 PT patients undergoing 24-week exercise therapy underwent baseline 3D UTE and PD MRI at 3.0 T. The patellar tendon segmentation used nnU-Net, evaluated with Dice coefficient. Six predictive models consisting of clinical covariates and radiomic features from UTE and PD were developed using Elastic Net with 10-fold cross-validation. Model performance in predicting responsiveness of the patient-reported Victorian Institute of Sports Assessment (VISA-P) score was evaluated using the area under the receiver operating characteristic curve (ROC AUC) and the precision-recall curve (PR AUC), with 95% confidence intervals.</div></div><div><h3>Results</h3><div>The mean Dice similarity coefficient for the automatic segmentation of the patellar tendon from 3D-PD was 0.92 (SD: 0.02) and from 3D-UTE-Cones 0.89 (SD: 0.03). The UTE-based radiomics model demonstrated the highest predictive performance at 24 weeks (ROC AUC: 0.714 [95% CI: 0.701–0.727]; PR AUC: 0.848 [0.837–0.858]), while the PD-based model showed the lowest (ROC AUC: 0.569 [0.553–0.584]; PR AUC: 0.710 [0.692–0.727]). At the 5-year follow-up, UTE radiomics maintained robust performance (ROC AUC: 0.692 [0.677–0.706]; PR AUC: 0.822 [0.810–0.834]), whereas PD radiomics remained limited (ROC AUC: 0.578 [0.561–0.594]; PR AUC: 0.694 [0.676–0.713]).</div></div><div><h3>Conclusions</h3><div>Radiomics features extracted from UTE MRI demonstrate the highest predictive performance for clinical outcomes.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112675"},"PeriodicalIF":3.3,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145997644","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":"2026-01-13","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":"VIPs outperforms established models for predicting post-TIPS prognosis in viral hepatitis-dominant cirrhosis","authors":"Zhongsong Gao ,&nbsp;Kun Zhang ,&nbsp;Bo Li ,&nbsp;Zhaogang Zhang ,&nbsp;Hengtao Zhang ,&nbsp;Xin Zhang ,&nbsp;Bo Feng ,&nbsp;Ruihang Wang ,&nbsp;Wen Shen ,&nbsp;Kefeng Jia","doi":"10.1016/j.ejrad.2026.112672","DOIUrl":"10.1016/j.ejrad.2026.112672","url":null,"abstract":"<div><h3>Background</h3><div>Transjugular intrahepatic portosystemic shunt (TIPS) manages portal hypertension complications in cirrhosis, but predicting post-TIPS outcomes remains challenging, especially in viral hepatitis-dominated populations.</div></div><div><h3>Purpose</h3><div>To systematically evaluate the predictive performance of the novel Viral-Associated Index of Post-TIPS Score (VIPs) for post-TIPS prognosis. We also comprehensively compare it with six established clinical prognostic models and one imaging-based model (the spleen volume-based model, SvBM).</div></div><div><h3>Materials and methods</h3><div>We retrospectively analyzed 247 cirrhotic patients undergoing TIPS (56.7 % viral hepatitis). Baseline data calculated prognostic scores (VIPs, MELD, MELD-Na, FIPS, Child-Pugh, ALBI, MOTS, and SvBM). The primary endpoint was transplant-free survival (TFS). Discrimination was assessed by the area under the receiver operating characteristic curve (AUROC) at 6, 12, 36, and 60 months post-TIPS. Calibration (Brier score), explanatory power (R²), and decision curve analysis (DCA) were also evaluated.</div></div><div><h3>Results</h3><div>VIPs demonstrated good-to-moderate discrimination for TFS, with AUROCs (95 % CI) of 0.794 (0.689–0.899), 0.753 (0.649–0.858), 0.721 (0.645–0.797), and 0.692 (0.617–0.767) at 6, 12, 36, and 60 months, respectively. This advantage was most pronounced in the viral hepatitis subgroup, with AUROCs ranging from 0.699 (0.603–0.796) to 0.822 (0.715–0.930) across follow-up. VIPs significantly outperformed Child-Pugh, ALBI, FIPS, MOTS and SvBM at all timepoints (all <em>p</em> &lt; 0.05), and surpassed MELD and MELD-Na for long-term predictions (36/60 months, both <em>p</em> &lt; 0.05). It also exhibited the best calibration (lowest Brier scores: 0.076–0.217) and the highest explanatory power (R² = 0.121–0.142). Subgroup analyses further confirmed robust performance in females and patients with variceal bleeding.</div></div><div><h3>Conclusions</h3><div>VIPs demonstrates superior predictive accuracy for post-TIPS survival in a viral hepatitis-dominated cohort and may serve as a preferred prognostic tool to guide individualized decision-making.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112672"},"PeriodicalIF":3.3,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145975733","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":"Cortical vein opacification measurement using hounsfield unit values is a predictor for outcome in anterior circulation acute ischemic stroke","authors":"Erling Wang ,&nbsp;Yueyan Bian ,&nbsp;Xiaoxu Yang ,&nbsp;Huihui Xie ,&nbsp;Xiuqin Jia ,&nbsp;Qi Yang","doi":"10.1016/j.ejrad.2026.112671","DOIUrl":"10.1016/j.ejrad.2026.112671","url":null,"abstract":"<div><h3>Objectives</h3><div>In acute ischemic stroke (AIS) patients, the cortical vein opacification on computed tomographic angiography (CTA) imaging is usually asymmetric. We aimed to explore the correlation between CT perfusion parameters and cortical vein opacification evaluated by Hounsfield unit (HU) values, which is more accurately, and compare the predictive ability between them for outcome in AIS.</div></div><div><h3>Methods</h3><div>Patients with AIS obtained within 24 h after onset from June 2023 to January 2024 were reviewed. Opacification of the cortical vein of Labbé, sphenoparietal sinus, and the Trolard vein was measured on CTA imaging using HU. Then HU ratio (rHU) was calculated by dividing the affected side by the controlateral side (rHU = HU-affected/HU-control). The sum of rHU of three cortical veins opacification (CVOR, CVOR = rHU_Labbé+ rHU_{sphenoparietal sinus} + rHU _{Trolard vein}) was calculated. The correlations between CVOR and CT perfusion parameters, hypoperfusion and ischemic core volume, were explored. Outcome was assessed at 90 days using the modified Rankin Scale (mRS), a standardized measure of disability ranging from 0 (no symptoms) to 6 (death). An mRS score of 2 or less is considered as functional outcome.</div></div><div><h3>Results</h3><div>A total of 143 patients (mean age, 67.3 ± 12.5 years; 106 men) were included. We found that CVOR had a strong negative correlation with hypoperfusion volume (<em>r</em> = -0.759, <em>P</em> &lt; 0.001) and had a moderate negative correlation with ischemic core volume (<em>r</em> = -0.517, <em>P</em> &lt; 0.001). Receiver operating characteristic curve analysis revealed CVOR performed better than hypoperfusion volume (area under the curve [AUC], 0.784 vs 0.711; <em>P</em> = 0.008) and ischemic core volume (AUC, 0.784 vs 0.693; <em>P</em> = 0.02) in predicting the favorable 90-day mRS. Multivariable analysis showed CVOR was an independent predictor for poor outcome after adjusting for confounding factors [odds ratio 0.06 (0.02–0.32), p &lt; 0.001].</div></div><div><h3>Conclusion</h3><div>Cortical vein opacification evaluated by HU values, had a strong negative correlation with hypoperfusion volume, and was also a novel independent predictor for clinical outcome.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112671"},"PeriodicalIF":3.3,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146028803","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}