European Journal of Radiology最新文献

{"title":"Dual-energy computed tomography angiography for lenticulostriate arteries: Stepwise optimization of virtual monochromatic imaging and kernel setting","authors":"Yangyang Yin ,&nbsp;Qiuxia Wang ,&nbsp;Zhihan Xu ,&nbsp;Xudong Ai ,&nbsp;Huan Liu ,&nbsp;Haoyue Shao ,&nbsp;Linhan Zhai ,&nbsp;Shen Gui ,&nbsp;Zhiwen Yang ,&nbsp;Yu Chen ,&nbsp;Baoyi Wang ,&nbsp;Jing Zhang","doi":"10.1016/j.ejrad.2026.112694","DOIUrl":"10.1016/j.ejrad.2026.112694","url":null,"abstract":"<div><h3>Background</h3><div>The lenticulostriate arteries (LSAs) are critical perforating vessels, but conventional CTA poorly depicts them. Dual-Energy CT offers Virtual Monochromatic Imaging and kernel adjustment, yet the optimal strategy for LSAs visualization remains unclear.</div></div><div><h3>Materials and Methods</h3><div>This retrospective study included 556 patients (59 [46–72] years; 310 males [55.8%]) who underwent DE-CTA between May 2023 to July 2024. Images were reconstructed Virtual Monochromatic Imaging at 40–90 KeV and multiple convolution kernels (Qr40, Hv36, Hv40, Hv44, and Hv49). Step 1 compared image quality across KeV levels, and Step 2 optimized kernels on the basis of the best KeV and compared these optimized reconstructions again. Quantitative metrics included CT value, SNR, CNR, edge rise distance, and edge rise slope; qualitative assessment and visible LSAs branch counts were performed.</div></div><div><h3>Results</h3><div>Step 1 demonstrated significant differences in CT value, and CNR across KeV levels (all <em>p</em> &lt; 0.001), with 40 KeV yielding the highest CT value and CNR and the best subjective scores for artery branches visualization. Step 2 showed that sharper kernels significantly improved ERS and reduced ERD, with Hv49-40 KeV achieving the greatest edge sharpness (ERS, 10374.4 [7407.0–13341.9]; ERD, 0.10 [0.08–0.13]) and the highest number of visible LSAs branches (6.5 [2.5–10.5]; all adjusted <em>p</em> &lt; . 001).</div></div><div><h3>Conclusion</h3><div>Hv49-40KeV on DE‑CTA of the head and neck substantially improves the visualization of arteries across different calibers, with a marked enhancement in the depiction of the LSAs, providing a solid technical foundation for the evaluation of LSAs with DE‑CT.</div></div><div><h3>Relevance statement</h3><div>This optimized Dual Energy-CT angiography reconstruction increases the utility of head and neck CTA by improving lenticulostriate artery visualization, thereby supporting routine evaluation of both large and small cerebral vessels in clinical practice.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112694"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074525","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":"Feasibility study of fast T2-weighted imaging with deep-learning reconstruction in volunteers and emergency patients with acute abdomen","authors":"Jia Xu ,&nbsp;Liang Zhu ,&nbsp;Wei Liu ,&nbsp;Wenjing Liu ,&nbsp;Yitong Lu ,&nbsp;Jingjuan Liu ,&nbsp;Chenxue Ma ,&nbsp;Yifei Zhang ,&nbsp;Xuan Wang ,&nbsp;Feng Feng","doi":"10.1016/j.ejrad.2026.112697","DOIUrl":"10.1016/j.ejrad.2026.112697","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the image quality and clinical utility of DLR-enhanced single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) for diagnosing acute abdominal conditions, compared to standard SSFSE and Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) T2WI sequences.</div></div><div><h3>Methods</h3><div>This prospective single-institutional study enrolled 70 participants (35 healthy volunteers and 35 patients with acute abdominal pain). Abdominopelvic MRI were performed, including SSFSE and PROPELLER sequences. SSFSE images were reconstructed with and without deep-learning algorithm. Three radiologists independently evaluated image quality and target organ conditions. The Friedman test was used to compare image quality across sequences. The diagnostic performance for identifying disorders (e.g., cholecystitis, appendicitis, etc.) was assessed using the area under receiver operating characteristic curves (AUCs) and compared using the Delong method. Three pregnant women and one elderly patient who underwent SSFSE protocols only were also analyzed.</div></div><div><h3>Results</h3><div>SSFSE-DLR demonstrated significantly higher image quality and lower noise than SSFSE and PROPELLER across all imaging planes (<em>p</em> &lt; 0.05). It exhibited fewer motion artifacts and superior clarity of the appendix, gallbladder, and common bile duct compared to PROPELLER (<em>p</em> &lt; 0.05). SSFSE-DLR achieved higher diagnostic accuracy for common acute abdominopelvic disorders (AUCs: 0.977–1.0), compared to SSFSE and PROPELLER (AUCs: 0.887–1.00 and 0.585–0.953, respectively, <em>p</em> &lt; 0.05). In vulnerable patients with fast protocol, SSFSE-DLR identified one appendicitis missed by ultrasound, enabling timely surgery.</div></div><div><h3>Conclusion</h3><div>SSFSE-DLR significantly improves image quality and diagnostic accuracy in healthy volunteers and patients with acute abdomen.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112697"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074526","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":"Enhancing liver diffusion-weighted imaging quality with correlation-weighted averaging: notable benefits in the left hepatic lobe","authors":"Tetsuro Kaga ,&nbsp;Yoshifumi Noda ,&nbsp;Masashi Asano ,&nbsp;Nobuyuki Kawai ,&nbsp;Shingo Omata ,&nbsp;Yukiko Takai ,&nbsp;Satoshi Ido ,&nbsp;Kimihiro Kajita ,&nbsp;Abdelazim Elsayed Elhelaly ,&nbsp;Hirohiko Imai ,&nbsp;Hiroki Kato ,&nbsp;Masayuki Matsuo","doi":"10.1016/j.ejrad.2026.112680","DOIUrl":"10.1016/j.ejrad.2026.112680","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the feasibility of correlation-weighted averaging factor (CWAF) in liver diffusion-weighted imaging (DWI).</div></div><div><h3>Materials and methods</h3><div>This prospective study included 103 participants who underwent liver MRI. DWI were reconstructed using both original data (DWI_Original) and CWAF-corrected data (DWI_CWAF). Two radiologists independently assessed high-<em>b</em> DWI images for overall image quality, image noise, hepatic edge sharpness, and lesion conspicuity in the right and left lobes using five-point scales. Signal intensity ratio (SIR) and apparent diffusion coefficient (ADC) values were measured in four hepatic segments and in liver lesions, with lesion measurements analyzed separately for each lobe. These parameters were compared between the two image sets.</div></div><div><h3>Results</h3><div>The scores for overall image quality (<em>P</em> &lt; 0.001), image noise (<em>P</em> &lt; 0.001), and hepatic edge sharpness in the right lobe (<em>P</em> = 0.001) were higher in DWI_Original compared with DWI_CWAF. In contrast, hepatic edge sharpness (<em>P</em> &lt; 0.001) and lesion conspicuity (<em>P</em> &lt; 0.001) in the left lobe were superior in DWI_CWAF. Liver and lesion SIRs were higher in DWI_CWAF across all segments than in DWI_Original (<em>P</em> &lt; 0.007). Liver ADC values were lower in DWI_CWAF than in DWI_Original in all segments (<em>P</em> &lt; 0.001). Lesion ADC values were also lower in DWI_CWAF than in DWI_Original in the right lobe (<em>P</em> &lt; 0.001) but were not different in the left lobe (<em>P</em> = 0.48).</div></div><div><h3>Conclusion</h3><div>CWAF improved hepatic edge sharpness and lesion conspicuity in the left lobe, although overall image quality was slightly reduced. ADC values were generally lower in DWI_CWAF than in DWI_Original.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112680"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074550","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":"Deep learning outperformed radiomics based on MRI in the differentiation of sinonasal small round cell and non-small round cell malignant tumors","authors":"Yuchen Wang ,&nbsp;Xiaoxia Qu ,&nbsp;Zheng Li ,&nbsp;Dinggang Shen ,&nbsp;Junfang Xian","doi":"10.1016/j.ejrad.2026.112700","DOIUrl":"10.1016/j.ejrad.2026.112700","url":null,"abstract":"<div><h3>Objective</h3><div>Differentiating sinonasal small round cell malignant tumors (SRCMTs) from non-SRCMTs is challenging due to overlapping MRI features. This study aimed to compare the diagnostic performance of deep learning and radiomics models for preoperative MRI-based classification.</div></div><div><h3>Methods</h3><div>We retrospectively analyzed 325 patients with pathologically confirmed sinonasal malignancies (163 SRCMTs and 162 non-SRCMTs). Each patient underwent T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and contrast-enhanced T1-weighted imaging (CE-T1WI). Tumors were manually segmented. Five convolutional neural networks (CNNs)—ResNet-18, ResNet-34, ResNet-50, VGG13, and VGG16—were trained on each sequence. For radiomics, 1200 features were extracted per sequence, and multiple machine learning classifiers were trained. Model performance was assessed by area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The DeLong test was used to compare AUCs between models, with statistical significance set at P &lt; 0.05.</div></div><div><h3>Results</h3><div>The CE-T1WI-based ResNet-34 model achieved the best performance, with an average AUC of 0.830, the accuracy of 0.755, sensitivity of 0.918, specificity of 0.592, PPV of 0.692, and NPV of 0.879. The corresponding CE-T1WI-based radiomics model using a support vector machine yielded an AUC of 0.758 (accuracy = 0.755, sensitivity = 0.840, specificity = 0.667, PPV = 0.724, NPV = 0.800). On the independent test cohort, ResNet-34 showed numerically higher discriminative performance than the radiomics model, although this difference did not reach statistical significance. For T1WI and T2WI, deep learning and radiomics models demonstrated broadly comparable performance.</div></div><div><h3>Conclusions</h3><div>A CE-T1WI-based ResNet-34 network provided high diagnostic efficacy, and in our cohort deep learning models achieved numerically higher comparable performance to MRI-based radiomics models for differentiating SRCMTs from non-SRCMTs.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112700"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074551","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 gastric ultrasound in evaluating the efficacy of preoperative neoadjuvant therapy for gastric carcinoma","authors":"Xiaohong Deng,&nbsp;Zhongshi Du,&nbsp;Zhougui Wu,&nbsp;Weiqin Huang,&nbsp;Yaoqin Wang,&nbsp;Lina Tang","doi":"10.1016/j.ejrad.2025.112546","DOIUrl":"10.1016/j.ejrad.2025.112546","url":null,"abstract":"<div><h3>Purpose</h3><div>To evaluate the efficacy of gastric ultrasound in the neoadjuvant treatment of gastric carcinoma.</div></div><div><h3>Methods</h3><div>This retrospective study involved patients with locally advanced gastric carcinoma treated with preoperative neoadjuvant therapy (NAT) and surgery at<!--> <!-->our institute from<!--> <!-->April 2022 to<!--> <!-->June 2024.<!--> <!-->Ultrasound examinations<!--> <!-->were conducted<!--> <!-->at two time points: pre-NAT and within a week pre-surgery. We calculated changes in ultrasound measurements, including length and thickness, as well<!--> <!-->as the rate of these changes. The tumor regression grade (TRG) obtained from surgical pathology was used as the gold standard. We performed univariate<!--> <!-->and binary logistic<!--> <!-->regression analysis to explore potential<!--> <!-->risk factors<!--> <!-->associated with TRG. Additionally, we assessed the<!--> <!-->correlation between preoperative ultrasound measurements<!--> <!-->and postoperative gross specimen measurements.</div></div><div><h3>Results</h3><div>The study included 126 patients and identified 126 lesions, achieving a detection<!--> <!-->rate of 100 %. Changes in ultrasound thickness between<!--> <!-->the two time points served as<!--> <!-->a protective factor for postoperative TRG staging (Odds Ratio = 0.012; <em>P</em> &lt; 0.001). A<!--> <!-->higher rate of thickness<!--> <!-->change was associated with a lower TRG stage, indicating a more effective NAT. A<!--> <!-->significant positive correlation was observed between preoperative ultrasound length and postoperative lesion length (P &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>Gastric ultrasound is a viable method<!--> <!-->to evaluate the efficacy of preoperative NAT in patients with<!--> <!-->gastric carcinoma.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112546"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146074620","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":"2026-03-01","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":"Diagnostic performance of iodine map for differentiating colorectal cancer from benign colorectal wall thickening","authors":"Sonaz Malekzadeh ,&nbsp;Ioannis Rotas ,&nbsp;Ian Fournier ,&nbsp;Philippe Hiroz ,&nbsp;Floryn Cherbanyk ,&nbsp;Dominic Staudenmann ,&nbsp;Roberto Cannella ,&nbsp;Lucien Widmer","doi":"10.1016/j.ejrad.2026.112709","DOIUrl":"10.1016/j.ejrad.2026.112709","url":null,"abstract":"<div><h3>Objectives</h3><div>To evaluate the diagnostic performance of iodine density map (IDM) using dual-energy CT (DECT) in differentiating colorectal cancer from benign colorectal wall thickening.</div></div><div><h3>Material and Methods</h3><div>This IRB-approved dual-center retrospective exploratory study included 71 consecutive patients with colorectal wall thickening due to tumoral or non-tumoral origin, confirmed by colonoscopy and assessed with DECT. Thirty-eight had pathology-proven colorectal adenocarcinoma, and 33 had non-neoplastic thickening (inflammation, physiologic collapse, or post-radiotherapy change). Iodine density values were measured from regions of interest on three consecutive CT slices on portal venous phase, normalized to aortic iodine concentration. Diagnostic performance was determined by ROC analysis, and inter-reader agreement was evaluated with intraclass correlation coefficients (ICC) and limits of agreement (LOA).</div></div><div><h3>Results</h3><div>Mean IDM value was significantly higher in tumors than in benign thickening (2.31 ± 0.42 vs 1.43 ± 0.24 mg/mL; <em>p</em> &lt; 0.001). Mean normalized iodine density map (NIDM) value was likewise elevated in tumors (0.46 ± 0.10 vs 0.31 ± 0.07; <em>p</em> &lt; 0.001). ROC analysis demonstrated excellent performance for both IDM (AUC 0.98; optimal cutoff 1.72 mg/mL; sensitivity 92.1%, specificity 90.9%, NPV 90.9%) and NIDM (AUC 0.88; cutoff 0.35; sensitivity 92.1%, specificity 69.7%, NPV 88.7%). There was no significant difference between the inflammatory and collapsed-wall subgroups. Inter-reader agreement was excellent (ICC: 0.93 for IDM; 0.92 for NIDM).</div></div><div><h3>Conclusion</h3><div>IDM and NIDM on DECT provide robust, reproducible markers that differentiate colorectal carcinoma from benign wall thickening with high diagnostic accuracy. These quantitative parameters may improve diagnostic confidence and reduce unnecessary colonoscopies, supporting their integration into colorectal cancer evaluation.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112709"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146118439","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":"Clinical-Radiomics hybrid prediction of the Risks of pedicle screw loosening after posterior lumbar fusion","authors":"Weitao Han ,&nbsp;Songbo Gao ,&nbsp;Shun Han ,&nbsp;Xiaolin Zhong ,&nbsp;Penghui Zhang ,&nbsp;Yuliang Wu ,&nbsp;Haotian Tian ,&nbsp;Fuxin Wei ,&nbsp;Shifeng Wen ,&nbsp;Shen Zhao ,&nbsp;Wei Ye","doi":"10.1016/j.ejrad.2026.112718","DOIUrl":"10.1016/j.ejrad.2026.112718","url":null,"abstract":"<div><h3>Objective</h3><div>We aimed to construct a risk prediction model for PSL after posterior lumbar fusion using machine learning and radiomic methods.</div></div><div><h3>Summary Of Background Information</h3><div>Posterior lumbar fusion surgery is a routine procedure for the treatment of lumbar degenerative disease (LDD). Pedicle screw loosening (PSL) is a common complication after posterior lumbar fusion that can lead to postoperative pain and infection in the implant area.</div></div><div><h3>Methods</h3><div>A total of 304 patients who underwent posterior lumbar fusion for LDD at Sun Yat-sen Memorial Hospital were reviewed in this study. 80 patients at the Seventh Affiliated Hospital of SYSU and Guangzhou First People’s Hospital made up the external validation datasets. Preoperative demographic and surgical information was collected. One-year-postoperative radiological follow-up was conducted, and patients were divided into PSL and non-PSL groups. Clinical and surgical information was subjected to Student’s <em>t</em> test for feature selection. Lumbar CT images were analyzed using radiomic methods, and PSL prediction models were constructed by machine learning methods. The best model was selected and externally validated on the data from the two other hospitals.</div></div><div><h3>Results</h3><div>All 304 patients were included. Age (<em>p</em>＜0.001), Preoperative lumbar lordosis (LL) (<em>p</em> = 0.006), mean CT Hounsfield units (<em>p</em> = 0.007), and number of fixed segments (<em>p</em> &lt; 0.001) differed between the two groups. Logistic regression revealed that the number of fixed segments was an independent risk factor (OR = 2.147, <em>p</em> &lt; 0.001). Radiomic features were selected after feature extraction and selection. After model training and testing, the clinical + radiomic model showed acceptable predictive performance (AUC 0.894). Its AUCs in the two external validation datasets were 0.821 and 0.892 respectively.</div></div><div><h3>Conclusion</h3><div>Combining clinical and radiomic features can better predict the risk of PSL after posterior lumbar fusion surgery. This investigation revalidated the risk factors for PSL after posterior lumbar fusion as well.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112718"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146164664","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":"Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features","authors":"Hongmei Yu ,&nbsp;Min Chen ,&nbsp;Depeng Kong ,&nbsp;Xiang Qiu ,&nbsp;Jingang Yang ,&nbsp;Fa Wu ,&nbsp;Yi Huang ,&nbsp;Rui Jiang","doi":"10.1016/j.ejrad.2026.112667","DOIUrl":"10.1016/j.ejrad.2026.112667","url":null,"abstract":"<div><h3>Objective</h3><div>To develop and validate an integrated model combining Gd-EOB-DTPA–enhanced MRI habitat imaging with clinical features for preoperative prediction of microvascular invasion (MVI) and early recurrence in hepatocellular carcinoma (HCC).</div></div><div><h3>Methods</h3><div>This retrospective study enrolled 230 pathologically confirmed HCC patients, classified as MVI-positive or −negative. Radiomics features were extracted from the total tumor volume and a 3-mm peritumoral region. Tumor regions were segmented into three spatial habitats via K-means clustering, and habitat-specific features were obtained. Key features were selected using least absolute shrinkage and selection operator (LASSO) regression. Seven machine learning algorithms were trained; the intratumoral heterogeneity (ITH) score model showed optimal performance. Four models were developed: Clinical, Peritumoral Radiomics, ITH Score, and Combined (ITH + Peritumoral Radiomics + Clinical). Performance was assessed with ROC analysis, calibration, decision curve analysis (DCA), and SHapley Additive exPlanations (SHAP). A prognostic model was developed using the DeepSurv network to assess early recurrence-free survival (RFS) following HCC resection, with Kaplan-Meier curves plotted for evaluation.</div></div><div><h3>Results</h3><div>Extreme Gradient Boosting (XGBoost) achieved the best performance for ITH and traditional radiomics models. The ITH score model outperformed the Peritumoral Radiomics model. The Combined model achieved the highest performance on the training set (AUC: 0.925; sensitivity: 0.926; specificity: 0.785; accuracy: 0.863; F1-score: 0.882). Calibration and DCA confirmed reliability and clinical benefit. SHAP analysis clarified feature contributions.The HCC prognostic model-defined MVI-High risk patients, who exhibited significantly different risk scores, also had a significantly poorer early RFS per Kaplan-Meier analysis (<em>P</em> &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>The integrated MRI habitat–clinical model outperformed standalone approaches, showing promise for individualized surgical planning and recurrence risk stratification in HCC.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112667"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146009433","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":"Evaluation of Age-Related compositional changes in the infrapatellar fat pad using MRI-Derived PDFF and T2* at 1.5 T","authors":"Kecheng Yuan ,&nbsp;Qingyun Liu ,&nbsp;Weijie Zheng ,&nbsp;Xiaoqiong Tang ,&nbsp;Chuang Zhang ,&nbsp;Jiantai Zhou ,&nbsp;Penghui Luo ,&nbsp;Fulang Qi ,&nbsp;Lin Chen ,&nbsp;Bensheng Qiu","doi":"10.1016/j.ejrad.2025.112632","DOIUrl":"10.1016/j.ejrad.2025.112632","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate age-related compositional changes in the infrapatellar fat pad (IFP) using chemical shift-encoded MRI-derived proton density fat fraction (PDFF) and T₂* at 1.5 T, and to evaluate their associations with clinical symptoms and structural abnormalities.</div></div><div><h3>Methods</h3><div>A cross-sectional study was performed in 100 adults (mean age: 44 ± 14 years; 54 men, 46 women) who underwent 1.5 T MRI using a six-echo spoiled gradient-echo sequence for quantitative assessment of PDFF and T₂* in the IFP. Clinical symptoms were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and structural abnormalities were evaluated using the Whole-Organ Magnetic Resonance Imaging Score (WORMS). Spearman correlation and mediation analyses were performed.</div></div><div><h3>Results</h3><div>Age showed a strong negative correlation with IFP PDFF (r =  − 0.46, p &lt; 0.001) and a moderate inverse association with T₂* (r =  − 0.30, p = 0.003). Lower PDFF was associated with worse WOMAC pain (r =  − 0.33, p = 0.001) and WORMS scores (r =  − 0.41, p &lt; 0.001). The mediation analysis revealed a significant indirect pathway linking age to both pain (ACME = 0.19, 95 % CI: 0.02–0.38) and WORMS scores (ACME = 0.24, 95 % CI: 0.06–0.45) through PDFF. In contrast, the indirect pathway through T₂* was weaker and less precise (ACME = 0.12, 95 % CI: 0.01–0.28).</div></div><div><h3>Conclusions</h3><div>PDFF and T₂* reflect age-related compositional and microstructural changes in the IFP, with PDFF demonstrating stronger associations with clinical symptoms and joint degeneration. These findings indicate PDFF as a superior imaging biomarker for early detection, monitoring, and potential therapeutic targeting in age-related musculoskeletal degeneration.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"196 ","pages":"Article 112632"},"PeriodicalIF":3.3,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145959128","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}