European Journal of Radiology最新文献

{"title":"Non-invasive radiogenomic assessment of growth-associated protein 43 in lung adenocarcinoma brain metastases.","authors":"Chen Sun, Yuqi Liu, Chenggang Jiang, Xue Yang, Wang Jia, Dainan Zhang","doi":"10.1016/j.ejrad.2026.113181","DOIUrl":"10.1016/j.ejrad.2026.113181","url":null,"abstract":"<p><strong>Background: </strong>To evaluate the prognostic role of growth-associated protein 43 (GAP43) in lung adenocarcinoma (LUAD) brain metastases and develop a non-invasive radiogenomic model combining MRI radiomics with transcriptomics for GAP43 prediction and survival estimation.</p><p><strong>Methods: </strong>This retrospective study included 308 patients with surgically resected LUAD brain metastases (2012-2021). Fifty-six patients with paired RNA sequencing and contrast-enhanced T1-weighted MRI (CE-T1WI) were used to build the radiomics model predicting GAP43 expression. An additional independent cohort of 252 patients was included for exploratory prognostic evaluation of the imaging-derived radiomics score (RS). Radiomic features (n = 1,130) were extracted using PyRadiomics and underwent sequential feature selection, including inter-observer reproducibility assessment using intraclass correlation coefficients (ICCs), univariate t-tests, correlation-based redundancy filtering, and least absolute shrinkage and selection operator (LASSO)-based feature selection. An optimized support vector machine (SVM) model was subsequently developed to predict GAP43 expression and generate the RS. Survival was analyzed via Kaplan-Meier and Cox regression.</p><p><strong>Results: </strong>A total of 56 patients were enrolled in the radiogenomics cohort. GAP43 was significantly independently associated with poorer overall survival (OS; P = 0.026). High GAP43 expression correlated positively with activated mast cells (R = 0.53), eosinophils (R = 0.34). The radiogenomic model showed favorable performance for predicting GAP43 expression in repeated nested cross-validation, with an AUC of 0.825 (95% CI, 0.791-0.858). In an independent prognostic cohort of 252 patients, a higher imaging-derived radiomics score (RS) was independently associated with poorer OS (P < 0.001). The RS-based nomogram showed acceptable prognostic performance, with time-dependent AUCs of 0.661, 0.666, and 0.631 for 3-, 6-, and 12-month OS, respectively.</p><p><strong>Conclusions: </strong>GAP43 is an adverse prognostic biomarker in LUAD brain metastases. A CE-T1WI radiogenomic model accurately predicts GAP43 expression, facilitating individualized short-term survival stratification.</p>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"204 ","pages":"113181"},"PeriodicalIF":3.9,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148826703","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 \"CT attenuation-based hepatic steatosis assessment using 3D organ segmentation: Impact of tube voltage and need for cutoff adjustment\". [Eur. J. Radiol. 203 (2026) 113021].","authors":"Jeongin Yoo, Ijin Joo, Sun Kyung Jeon, Junghoan Park, Jeong Min Lee","doi":"10.1016/j.ejrad.2026.113176","DOIUrl":"10.1016/j.ejrad.2026.113176","url":null,"abstract":"","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":" ","pages":"113176"},"PeriodicalIF":3.9,"publicationDate":"2026-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148857096","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":"Medical image analysis for three-dimensional reconstruction in adolescent idiopathic scoliosis: Imaging inputs, reconstruction methods, validation evidence, and research gaps.","authors":"Lianggui Dai, Liang Cheng, Chaomeng Wu, Zhenning Hou, Junlin Yang, Wenqing Wei","doi":"10.1016/j.ejrad.2026.113295","DOIUrl":"https://doi.org/10.1016/j.ejrad.2026.113295","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Adolescent idiopathic scoliosis (AIS) is a complex three-dimensional (3D) spinal deformity. Although standing full-spine radiography remains the cornerstone of clinical diagnosis and longitudinal follow-up, two-dimensional projections cannot fully characterize vertebral rotation, local osseous geometry, or global spatial alignment. In recent years, computed tomography (CT), magnetic resonance imaging (MRI), conventional radiography, EOS/biplanar radiography, 3D ultrasound, and surface imaging have increasingly been integrated with deep learning, statistical shape modeling, and generative approaches, substantially expanding the technical pathways for patient-specific 3D reconstruction in AIS. However, substantial heterogeneity remains across studies with respect to input constraints, target populations, reference standards, and validation endpoints, and the evidentiary boundaries between technical performance, AIS-specific validity, and clinical validity have not been systematically clarified. This review adopted a structured methodological framework and systematically searched the Web of Science Core Collection, PubMed/MEDLINE, and IEEE Xplore, supplemented by forward and backward citation tracking. Study-level evidence was synthesized across imaging inputs, reconstruction tasks, algorithmic paradigms, and validation designs. A total of 115 core studies were included, comprising 32 AIS-specific studies (27.8%), 21 scoliosis-specific or mixed-population studies (18.3%), and 62 studies based on general spinal-image-analysis evidence (53.9%). Based on the reference standards and validation endpoints used, we established a five-level validation framework ranging from image/segmentation-level validation (L1), anatomical-structure-level validation (L2), and clinical-parameter-level validation (L3), to workflow/generalization-level validation (L4) and clinical-translation-level validation (L5). An evidence-gap matrix based on \"imaging modality × methodological task\" was also constructed. Among the 115 studies, 28 (24.3%) reached a maximum of L1, 49 (42.6%) reached L2, 34 (29.6%) reached L3, and only 4 (3.5%) reached L4; no study met the L5 criteria, and no explicit AIS-specific external validation was identified. Current evidence indicates that CT provides a strong basis for high-fidelity osseous reconstruction, EOS has accumulated relatively continuous AIS-specific evidence for weight-bearing 3D parameter assessment, and 3D ultrasound offers advantages for repeated radiation-free parameter measurement, whereas MRI-based reconstruction and limited-projection 3D recovery remain rapidly evolving fields. The principal challenge has therefore shifted from whether a 3D structure can be generated to whether structural fidelity can be translated into reliable clinical parameters and whether models can generalize consistently across independent AIS populations, imaging systems, and acquisition protocols. Future work should prioritize AIS-specific multicen","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"206 ","pages":"113295"},"PeriodicalIF":3.9,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149223610","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":"CT-based Node-RADS for standardized evaluation of lymph node metastasis in rectal cancer and its clinicopathological correlates.","authors":"Xiaoyi Xiao, Fei Jiang, You Chen, Meiyan Qu, Liang Yang, Taifu Gu, Lianggeng Gong, Jia Qiu","doi":"10.1016/j.ejrad.2026.113306","DOIUrl":"https://doi.org/10.1016/j.ejrad.2026.113306","url":null,"abstract":"<p><strong>Background: </strong>Lymph node metastasis identification has important clinical implications for treatment decision-making in rectal cancer (RC). To evaluate the diagnostic performance of the CT-based Node Reporting and Data System 1.0 (Node-RADS) for lymph node metastasis risk in treatment-naive RC patients, and to investigate the correlation between the Node-RADS score and clinicopathological factors.</p><p><strong>Methods: </strong>A single-center retrospective study was performed to RC patients (Aug 2020-Dec 2025) who underwent radical resection surgery and preoperative contrast-enhanced CT examination. Lymph node status was assessed using Node-RADS score ranging from 1 to 5. Sensitivity, specificity, and Youden's index were calculated for different Node-RADS cut-off values. The overall diagnostic performance was evaluated using receiver operating characteristic curves and the area under the curve (AUC). The associations between Node-RADS score and clinicopathological parameters were analyzed.</p><p><strong>Results: </strong>A total of 459 RC patients were evaluated, including 174 pN + and 285 pN-. Node-RADS scores ≥ 3 and ≥ 4 have the satisfactory diagnostic performance, with sensitivity/ specificity/Youden's index of 87.36 %/58.25 %/0.46 for Node-RADS scores ≥ 3 by Reader 1, 89.08 %/54.04 %/0.43 for Node-RADS scores ≥ 3 by Reader 2, 74.14 %/78.95 %/0.53 for Node-RADS scores ≥ 4 by Reader 1, and 72.99 %/75.44 %/0.48 for Node-RADS scores ≥ 4 by Reader 2, respectively. The AUC of Node-RADS scores were 0.831(95 %CI:0.793-0.864) and 0.806(95 %CI:0.767-0.841) by Reader 1 and Reader 2, respectively. Node-RADS score correlated with pathological T stage, N stage, and lymphovascular invasion. The inter-reader agreement for Node-RADS score were substantial, with weighted kappa values of 0.650.</p><p><strong>Conclusions: </strong>The CT-based Node-RADS demonstrates stability and satisfactory diagnostic performance for identifying patients with lymph node metastasis in treatment-naive RC.</p>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"206 ","pages":"113306"},"PeriodicalIF":3.9,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149223545","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":"Factors associated with structural progression of the sacroiliac joints on MRI in axial spondyloarthritis: a retrospective longitudinal study.","authors":"Kunhua Fang, Xiao Zhang, Shengsheng Yang, Shun Yu","doi":"10.1016/j.ejrad.2026.113298","DOIUrl":"https://doi.org/10.1016/j.ejrad.2026.113298","url":null,"abstract":"<p><strong>Purpose: </strong>To identify clinical and routine sacroiliac joint (SIJ) MRI variables associated with structural damage progression in axial spondyloarthritis (axSpA).</p><p><strong>Materials and methods: </strong>This retrospective longitudinal study enrolled 234 patients with axSpA who underwent at least two SIJ MRI examinations between August 2011 and March 2024 (643 examinations, 409 consecutive visit pairs). Progression at each follow-up examination relative to the previous one was adjudicated using an SSS-based three-step algorithm. Mixed-effects logistic regression with patient-specific random intercepts identified factors associated with progression, with the MRI follow-up interval as a covariate. Multicollinearity was assessed using variance inflation factors, and treatment exposure was evaluated in a sensitivity analysis.</p><p><strong>Results: </strong>Progression was identified in 260 of 409 follow-up examinations (63.6%). After adjustment for the MRI follow-up interval, a higher erosion SSS score (odds ratio [OR] 1.178, 95% confidence interval [CI] 1.099-1.262, P < 0.001), smoking (OR 2.023, 95% CI 1.091-3.751, P = 0.025), and HLA-B27 positivity (OR 2.929, 95% CI 1.225-7.007, P = 0.016) were independently associated with increased progression risk, whereas older age at diagnosis (OR 0.970, 95% CI 0.946-0.993, P = 0.012) was associated with decreased risk; these associations were essentially unchanged after forced entry of treatment exposure.</p><p><strong>Conclusion: </strong>A higher erosion burden at the previous examination, smoking, and HLA-B27 positivity were associated with SIJ structural damage progression; patients diagnosed at a younger age also warrant attention. Given the retrospective observational design, these are statistical associations whose causality and clinical utility require prospective validation.</p>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"206 ","pages":"113298"},"PeriodicalIF":3.9,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149220153","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 “Short occipital circulation time derived from quantitative digital subtraction angiography is associated with headache risk in patients with unruptured brain arteriovenous malformations” [Eur. J. Radiol. 192 (2025) 112402]","authors":"Yong-Sin Hu ,&nbsp;Jr-Wei Wu ,&nbsp;Huai-Che Yang ,&nbsp;Hsiu-Mei Wu ,&nbsp;Cheng-Chia Lee ,&nbsp;Feng-Chi Chang ,&nbsp;Kang-Du Liu ,&nbsp;Chung-Jung Lin","doi":"10.1016/j.ejrad.2026.112719","DOIUrl":"10.1016/j.ejrad.2026.112719","url":null,"abstract":"","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112719"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161988","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 value of a multimodal ultrasound radiomics-based nomogram in predicting central lymph node metastasis of papillary thyroid microcarcinoma","authors":"Minhao Lin ,&nbsp;Xiaohong Xu ,&nbsp;Jianling Peng ,&nbsp;Qiuxia Huang ,&nbsp;Jiajian Wu ,&nbsp;Lijuan Liu","doi":"10.1016/j.ejrad.2026.112725","DOIUrl":"10.1016/j.ejrad.2026.112725","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to develop a multimodal ultrasound-based nomogram integrating radiomic features from grayscale ultrasound (GSUS) and contrast-enhanced ultrasound (CEUS) with clinical-ultrasound factors for the noninvasive prediction of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC), and to evaluate its predictive performance to support clinical decision-making.</div></div><div><h3>Methods</h3><div>This retrospective cohort study included 449 pathologically confirmed PTMC patients from June 2023 to December 2024, randomly divided into training (n = 314) and validation (n = 135) cohorts. Radiomic features were extracted using PyRadiomics software, and feature selection was performed through Spearman correlation analysis and LASSO regression. Multivariate regression analysis identified independent clinical risk factors for CLNM. A multimodal ultrasound combined model was then developed, serving as the basis for the nomogram. The model’s discriminative ability, calibration performance, and clinical utility were evaluated using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA).</div></div><div><h3>Results</h3><div>Multivariate analysis identified male sex, age &lt; 40 years, and capsular invasion as independent risk factors for CLNM. Single-modal models (Clinical, GSUS, CEUS) achieved AUCs ranging from 0.654 to 0.787 in the validation cohort. The Combined model integrating these features significantly outperformed all single-modal ones, with AUCs of 0.925 and 0.885 in the training and validation cohorts. Calibration curves and DCA confirmed its good fit and high clinical net benefit.</div></div><div><h3>Conclusion</h3><div>We successfully developed and validated a nomogram model based on multimodal ultrasound features for accurately predicting CLNM risk in PTMC patients, highlighting the value of radiomics in clinical risk assessment.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112725"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146212681","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":"Interpretable machine learning based on intratumoral and peritumoral ultrasound radiomics for predicting central lymph node metastasis in papillary thyroid carcinoma","authors":"Wanting Yang ,&nbsp;Xuejiao Su ,&nbsp;Can Yue,&nbsp;Weizheng Chen,&nbsp;Yang Chen,&nbsp;Yan Luo,&nbsp;Buyun Ma","doi":"10.1016/j.ejrad.2026.112727","DOIUrl":"10.1016/j.ejrad.2026.112727","url":null,"abstract":"<div><h3>Objectives</h3><div>This retrospective and single-center study aimed to develop machine learning (ML) model integrating clinical features, ultrasound (US) features, and radiomics signatures extracted from both intratumoral and peritumoral regions to predict central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC). The SHapley Additive exPlanations (SHAP) method was applied to visualize the prediction process and enhance clinical interpretability.</div></div><div><h3>Materials and methods</h3><div>A total of 879 patients with PTC who underwent preoperative US examination between January 2023 and January 2024 were retrospectively analyzed. Patients were randomly divided into training (n = 615) and test (n = 264) sets. Radiomics signatures were extracted from intratumoral regions and peritumoral regions extending 3 mm and 5 mm beyond the tumor margin. After feature selection, Radscore were computed. Five ML models incorporating clinical features, US features and Radscore were developed. Model performance was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and the Hosmer–Lemeshow test. SHAP was used to explain ML model predictions.</div></div><div><h3>Results</h3><div>CLNM occurred in approximately 52% of PTC. Patients with CLNM were younger and more often male (p &lt; 0.001). Multifocal tumors, extrathyroidal extension, and suspicious lymph nodes on US were also associated with higher CLNM risk (p &lt; 0.05). The Radscore derived from intratumoral and peritumoral regions were significantly different between patients with and without CLNM (p &lt; 0.05). Combined ML models outperformed those based on clinical and US features (p &lt; 0.05). The best performing model (XGB) achieved an AUC of 0.868 (sensitivity = 0.777, specificity = 0.803 and accuracy = 0.749) in the training set and an AUC of 0.787 (sensitivity = 0.704, specificity = 0.695 and accuracy = 0.713) in the test set. The XGB model demonstrated superior clinical utility and well-calibrated for CLNM prediction. SHAP analysis identified the Radscore from the combination of intratumoral and 3-mm peritumoral regions as the most CLNM predictor and provided patient-level interpretability.</div></div><div><h3>Conclusions</h3><div>Intratumoral and peritumoral radiomics features based on US show potential for predicting CLNM in PTC. The integration of SHAP analysis enhances model transparency and may support individualized treatment decision-making.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112727"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146212672","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":"Differentiating large-duct pancreatic ductal adenocarcinoma from malignant intraductal papillary mucinous neoplasm: MRI characteristics and diagnostic implications","authors":"Se Jin Choi ,&nbsp;Dong Wook Kim ,&nbsp;Byung-Kwan Jeong ,&nbsp;Seung-Mo Hong ,&nbsp;Jae Ho Byun ,&nbsp;Seung Soo Lee ,&nbsp;Hyoung Jung Kim ,&nbsp;Jin Hee Kim ,&nbsp;Ki Byung Song ,&nbsp;Jae Hoon Lee ,&nbsp;Dae Wook Hwang","doi":"10.1016/j.ejrad.2026.112735","DOIUrl":"10.1016/j.ejrad.2026.112735","url":null,"abstract":"<div><h3>Objective</h3><div>To evaluate magnetic resonance imaging (MRI) characteristics that differentiate large-duct pancreatic ductal adenocarcinoma (LD-PDAC) from malignant intraductal papillary mucinous neoplasm (IPMN).</div></div><div><h3>Materials and Methods</h3><div>We retrospectively analyzed preoperative MRI data from 42 LD-PDAC patients, 201 malignant IPMN patients (166 with high-grade dysplasia and 35 with invasive carcinoma), and 8 LD-PDAC arising from IPMN patients. Two radiologists independently assessed MRI features including tumor morphology and accompanying imaging features. Multivariable logistic regression, diagnostic performance of combined imaging predictors, and survival outcomes across disease entities were evaluated.</div></div><div><h3>Results</h3><div>LD-PDAC predominantly appeared as solid-dominant tumors, either solid masses with internal cystic portions (69.0%) or pure solid masses (16.7%). Malignant IPMN presented mainly as cyst-dominant tumors, either pure cystic masses (55.2%) or cystic masses with internal solid components (42.8%). Multivariable logistic regression analysis identified solid-dominant tumor morphology (odds ratio [OR], 77.89; 95% confidence interval [CI], 4.94–1229.16), peripancreatic infiltration (OR, 34.47; 95% CI, 2.49–476.79), and absence of disproportionate pancreatic duct dilatation (OR, 0.06; 95% CI, 0.01–0.59) as independent imaging features favoring LD-PDAC. LD-PDAC showed significantly shorter overall and recurrence-free survival than malignant IPMN (p &lt; 0.001), while survival did not differ significantly between LD-PDAC and IPMN with associated invasive carcinoma. Overall, 26.2% of LD-PDAC cases were misdiagnosed, mainly due to misinterpretation of cyst wall characteristics and atypical duct dilatation.</div></div><div><h3>Conclusion</h3><div>MRI may aid in differentiating LD-PDAC from malignant IPMN by integrating tumor morphology and accompanying imaging features, including pancreatic ductal dilatation patterns and peripancreatic infiltration; however, substantial imaging overlap persists, resulting in a clinically meaningful misdiagnosis rate.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112735"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147270181","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":"Gallbladder adenomyomatosis revisited – Does size matter? is follow-up required for large lesions?","authors":"Shirley Shechter,&nbsp;Dana Ben-Ami Shor,&nbsp;Roie Tzadok,&nbsp;Hila Yashar,&nbsp;Sapir Lazar,&nbsp;Yuval Katz,&nbsp;Arthur Chernomorets,&nbsp;Rivka Kessner","doi":"10.1016/j.ejrad.2026.112698","DOIUrl":"10.1016/j.ejrad.2026.112698","url":null,"abstract":"<div><h3>Objectives</h3><div>Adenomyomatosis (ADM) is generally considered a benign condition. However, it can be associated with chronic cholecystitis − a known risk factor for gallbladder cancer. Therefore, studies have proposed follow-up with ultrasound for asymptomatic patients with focal ADM. Currently, there are no formal recommendations regarding the frequency and length of follow-up. The aims of this study were to assess the growth of ADM lesions during follow-up and to examine the differences between larger and smaller ADM lesions.</div></div><div><h3>Methods</h3><div>144 patients who underwent MRI-MRCP at our institution between the years 2014–2024 were identified through radiological reports as having a diagnosis of ADM. 43 patients had more than one examination. Demographic, clinical and radiological data were collected retrospectively. We divided the cohort into two groups based on the primary lesion size (axial diameter below or above 1.5 cm) and compared between them.</div></div><div><h3>Results</h3><div>The group of small lesions included 98 patients and the larger lesions group included 46 patients. We did not find a statistically significant correlation between the size of.</div><div>ADM and the demographic or clinical characteristics examined. Only 9 ADM lesions grew during follow-up − 6 from the smaller lesions group and 3 from the large lesions group (p &gt; 0.05). The median follow-up period was 35 months. None of our patients developed gallbladder carcinoma.</div></div><div><h3>Conclusions</h3><div>Our results confirm the common hypothesis that ADM are benign lesions. Therefore, we believe that follow-up is not needed for lesions with a clear diagnosis of focal ADM.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"197 ","pages":"Article 112698"},"PeriodicalIF":3.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146200556","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}