European Journal of Radiology最新文献

{"title":"Delineation of the brachial plexus by contrast-enhanced photon-counting detector CT and virtual monoenergetic images","authors":"Masahiro Nakashima,&nbsp;Tatsuya Kawai,&nbsp;Kazuhisa Matsumoto,&nbsp;Takatsune Kawaguchi,&nbsp;Nobuo Kitera,&nbsp;Seita Watanabe,&nbsp;Toshihide Itoh,&nbsp;Akio Hiwatashi","doi":"10.1016/j.ejrad.2025.111964","DOIUrl":"10.1016/j.ejrad.2025.111964","url":null,"abstract":"<div><h3>Objectives</h3><div>To improve the image quality of the brachial plexus in photon-counting detector CT (PCD-CT) using contrast media and virtual monoenergetic images (VMI).</div></div><div><h3>Materials &amp; Methods</h3><div>We retrospectively analyzed contrast-enhanced neck PCD-CT images scanned in March-July 2023. Unenhanced and contrast-enhanced images were compared, and then 40-, 70-, and 100-keV VMIs were compared. The qualitative evaluation used a five-point Likert scale regarding overall image quality (IQ), sharpness, and noise. The quantitative evaluation used the standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Freidman’s test and one-way ANOVA were performed.</div></div><div><h3>Results</h3><div>Forty patients (65 years ± 17, 21 males) were included. The median scores [interquartile range, IQR] for the unenhanced and contrast-enhanced groups were IQ, 3 [2,3] and 4 [3,4] (P &lt; 0.001); sharpness, 3 [2,3] and 4 [3,4] (P &lt; 0.001); and noise, 3 [3,4] and 3 [3,4] (P = 0.63). Mean ± SD scores were SD, 6.7 ± 1.4 and 6.7 ± 1.0 (P = 0.95); SNR, 5.1 ± 1.2 and 5.4 ± 1.4 (P = 0.04); and CNR, 4.8 ± 1.5 and 8.1 ± 2.3 (P &lt; 0.001). The 40-, 70-, and 100-keV groups’ IQ were 2 [2,3], 4 [3,4], and 3 [3,4]; their sharpness scores were 2 [2,3], 3 [3,4], and 3 [2,3] (all, P &lt; 0.05). Those for noise were 2 [1–3], 3 [3,4], and 4 [3,4] (all, P &lt; 0.001 except for 70-keV vs.100-keV: P = 0.16). The SDs were 13.1 ± 2.5, 7.5 ± 1.2, and 6.0 ± 1.1. The SNRs were 4.2 ± 1.9, 5.0 ± 1.2, and 5.7 ± 1.5 (all, P &lt; 0.001). The CNRs were 8.7 ± 4.0, 6.8 ± 2.3, and 6.5 ± 2.3 (all, P &lt; 0.001 except for 70-keV vs.100-keV: P = 0.51).</div></div><div><h3>Conclusion</h3><div>Contrast-enhanced PCD-CT and VMIs provided good delineation of the brachial plexus.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"184 ","pages":"Article 111964"},"PeriodicalIF":3.2,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT and MRI bimodal radiomics for predicting EGFR status in NSCLC patients with brain metastases: A multicenter study","authors":"Zhiqiang Ouyang ,&nbsp;Guodong Zhang ,&nbsp;Shaonan He ,&nbsp;Qiubo Huang ,&nbsp;Liren Zhang ,&nbsp;Xirui Duan ,&nbsp;Xuerong Zhang ,&nbsp;Yifan Liu ,&nbsp;Tengfei Ke ,&nbsp;Jun Yang ,&nbsp;Conghui Ai ,&nbsp;Yi Lu ,&nbsp;Chengde Liao","doi":"10.1016/j.ejrad.2024.111853","DOIUrl":"10.1016/j.ejrad.2024.111853","url":null,"abstract":"<div><h3>Background</h3><div>Leveraging the radiomics information from non-small cell lung cancer (NSCLC) primary lesion and brain metastasis (BM) to develop and validate a bimodal radiomics nomogram that can accurately predict epidermal growth factor receptor (EGFR) status.</div></div><div><h3>Methods</h3><div>A total of 309 NSCLC patients with BM from three independent centers were recruited. Among them, the patients of Center I were randomly allocated into the training and internal test cohorts in a 7:3 ratio. Meanwhile, the patients from Center Ⅱ and Center Ⅲ collectively constitute the external test cohort. All chest CT and brain MRI images of each patient were obtained for image registration and sequence combination within a single modality. After image preprocessing, 1037 radiomics features were extracted from each single sequence. Six machine learning algorithms were used to construct radiomics signatures for CT and MRI respectively. The best CT and MRI radiomics signatures were fitted to establish the bimodal radiomics nomogram for predicting the EGFR status.</div></div><div><h3>Results</h3><div>The contrast-enhanced (CE) eXtreme gradient boosting (XG Boost) and T2-weighted imaging (T2WI) + T1-weighted contrast-enhanced imaging (T1CE) random forest models were chosen as the radiomics signature representing primary lesion and BM. Both models were found to be independent predictors of EGFR mutation. The bimodal radiomics nomogram, which incorporated CT radiomics signature and MRI radiomics signature, demonstrated a good calibration and discrimination in the internal test cohort [area under curve (AUC), 0.866; 95 % confidence intervals (CI), 0.778–0.950) and the external test cohort (AUC, 0.818; 95 % CI, 0.691–0.938).</div></div><div><h3>Conclusions</h3><div>Our CT and MRI bimodal radiomics nomogram could timely and accurately evaluate the likelihood of EGFR mutation in patients with limited access to necessary materials, thus making up for the shortcoming of plasma sequencing and promoting the advancement of precision medicine.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111853"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142794586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-invasive evaluation of Achilles tendon and its enthesis using ultrashort echo time adiabatic T1ρ (UTE-Adiab-T1ρ) magnetic resonance imaging (MRI) in psoriatic arthritis","authors":"Dina Moazamian ,&nbsp;Hamidreza Shaterian Mohammadi ,&nbsp;Jiyo Athertya ,&nbsp;Mahyar Daskareh ,&nbsp;Yajun Ma ,&nbsp;Monica Guma ,&nbsp;Dana C. Covey ,&nbsp;Tony Yaksh ,&nbsp;Abha Singh ,&nbsp;Arthur Kavanaugh ,&nbsp;Christine B. Chung ,&nbsp;Jiang Du ,&nbsp;Eric Y. Chang ,&nbsp;Saeed Jerban","doi":"10.1016/j.ejrad.2024.111841","DOIUrl":"10.1016/j.ejrad.2024.111841","url":null,"abstract":"<div><h3>Purpose</h3><div>This cross-sectional study investigates the utility of the quantitative ultrashort echo time (UTE) adiabatic T_1ρ (UTE-Adiab-T_1ρ) magnetic resonance imaging (MRI) in detecting potential differences in Achilles tendons and entheses of patients with psoriatic arthritis disease (PsA) compared with asymptomatic volunteers.</div></div><div><h3>Material and Method</h3><div>The Achilles tendons of forty-four PsA patients (59 ± 15 years old, 38 % female) and thirty-seven asymptomatic volunteers (32 ± 10 years old, 51 % female) were scanned on a 3 T clinical scanner in the sagittal plane using a 3-inch surface coil. The 3D UTE-Adiab-T_1ρ sequences with fat saturation (FS) were used to measure UTE-Adiab-T_1ρ. Tenderness of the tendons, the SF-12 health survey, and visual analog scale (VAS) were recorded for the patients. The Kruskal Wallis test was used to examine the differences in UTE-Adiab-T1_ρ values between asymptomatic volunteers and patients, as well as subgroups of patients with pain in the Achilles tendon region and those treated with Biologics. Spearman’s correlation coefficients were calculated between UTE-Adiab-T_1ρ and patient evaluations. P values &lt; 0.05 were considered significant.</div></div><div><h3>Results</h3><div>UTE-Adiab-T_1ρ was significantly higher for the PsA group compared with the asymptomatic group in the enthesis (11.4 ± 2.6 ms vs. 10.4 ± 2.4 ms) and tensile tendon regions (9.8 ± 2.8 ms vs. 7.7 ± 1.7 ms). PsA patients with active Achilles pain showed significantly lower T1ρ in the entheses compared with other patients (10.7 ± 2.6 ms vs. 11.7 ± 2.5 ms). PsA patients treated with Biologics showed significantly lower T_1ρ values in the tendon compared with other patients (9.5 ± 2.5 ms vs. 10.3 ± 3.3 ms). The VAS score of patients showed a significant negative but weak correlation (R = -0.2) with UTE-Adiab-T1ρ of the enthesis. Correlations with SF-12 scores were not significant.</div></div><div><h3>Conclusion</h3><div>This study highlighted the UTE-Adiab-T_1ρ sequence capability in evaluating tendons and entheses and their potential involvement in PsA disease or response to therapies.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111841"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142817575","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":"Addressing Inter-reconstruction variability in multi-energy myocardial CT Radiomics: The Benefits of combat harmonization","authors":"Sarv Priya ,&nbsp;Abigail Reutzel ,&nbsp;Otavio Augusto Ferreira Dalla Pria ,&nbsp;Sawyer Goetz ,&nbsp;Hanh Td Pham ,&nbsp;Aiah Alatoum ,&nbsp;Pritish Y Aher ,&nbsp;Sabarish Narayanasamy ,&nbsp;Prashant Nagpal ,&nbsp;Knute D. Carter","doi":"10.1016/j.ejrad.2024.111891","DOIUrl":"10.1016/j.ejrad.2024.111891","url":null,"abstract":"<div><h3>Rationale and Objectives</h3><div>To investigate the effect of ComBat harmonization on the stability of myocardial radiomic features derived from multi-energy CT reconstructions.</div></div><div><h3>Materials and Methods</h3><div>A retrospective study was conducted on 205 patients who underwent dual-energy chest CTA at a single center. The data was reconstructed into multiple spectral reconstructions (mixed energy simulating standard 120 Kv acquisition and monoenergetic images ranging from 40 to 190 keV in increments of 10). The left ventricle myocardium was segmented using semiautomated software (Syngo.Via FRONTIER, version 5.0.2; Siemens). Radiomic features were extracted from multiple spectral reconstructions (batches). The consistency of these radiomics features across different batches was evaluated with and without ComBat harmonization using Cohen’s d and Principal component analysis (PCA). Both parametric and nonparametric ComBat methods were considered.</div></div><div><h3>Results</h3><div>Without any ComBat technique, 43.40% of features remained consistent across all multienergy reconstructions. Applying ComBat harmonization increased this consistency to 98.37% with parametric empirical bayes (EB) ComBat and EB M−ComBat, and to 91.52% and 92.33% with nonparametric EB ComBat and nonparametric EB M−ComBat, respectively. PCA without ComBat revealed noticeable differences in the first two principal components between batches, indicating a batch effect or unstable radiomic features. Following ComBat harmonization, the principal components showed more consistency between batches, demonstrating radiomics feature stability between batches.</div></div><div><h3>Conclusion</h3><div>ComBat harmonization enhanced the consistency of radiomic features from multi-energy CT data. Integrating ComBat harmonization may lead to more reproducible results in multienergy CT radiomics studies.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111891"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871775","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 Kaiser score in MRI BI-RADS 3 Lesions: A Promising tool to reduce unnecessary biopsies","authors":"Eleonora Ostillio ,&nbsp;Serena Carriero ,&nbsp;Davide Razzini ,&nbsp;Léon Groenhoff ,&nbsp;Anna Tambasco ,&nbsp;Chiara Airoldi ,&nbsp;Anna Lucia Clelia Gambaro ,&nbsp;Alessandro Carriero ,&nbsp;Pietro Costantini","doi":"10.1016/j.ejrad.2024.111872","DOIUrl":"10.1016/j.ejrad.2024.111872","url":null,"abstract":"<div><h3>PURPOSE</h3><div>To evaluate the possibility of reducing unnecessary biopsies in patients with BI-RADS 3 lesions by implementing Kaiser score (KS).</div></div><div><h3>METHOD</h3><div>In this retrospective, single-center study, we included 79 female patients with BI-RADS 3 lesions and risk factors who underwent biopsy following magnetic resonance imaging. Three readers (two experienced breast radiologists and a radiology resident) blinded evaluated the lesions using KS. Lesions with a KS ≤ 4 were considered benign. Results were compared with the histopathological findings (gold standard) assessing sensitivity and specificity along with 95 % confidence intervals (CI) for each reader. Inter-reader agreement was assessed using Fleiss’ kappa with 95 % CIs. Moreover, Cohen’s kappa was used to assess concordance between two readers at time.</div></div><div><h3>RESULTS</h3><div>79 female patients (mean age, 50.9 ± 12.2 (standard deviation)) were evaluated. The area under the receiver operating characteristic curve for the three readers was excellent: 0.99, 0.99, and 0.90), respectively. The sensitivity of the two breast radiologists and the resident was 0.92 (95 % CI: 0.62 – 0.99), 1.00 (95 % CI: 0.95 – 1.00) and 0.75 (95 % CI: 0.42 – 0.95), respectively, while the specificity was 1.00 (95 % CI: 0.95–––1.00), 0.99 (95 % CI: 0.92 – 1.00), and 1.00 (95 % CI: 0.95 – 1.00) respectively. By using a KS ≤ 4 value to indicate benignity, 66 to 67 biopsies (84 to 85 % of all the biopsies) would have been avoided. Inter-reader concordance via Fleiss’ kappa was 0.792 (95 % CI: 0.68 – 0.91).</div></div><div><h3>CONCLUSIONS</h3><div>The implementation of KS could have spared 84–85% of biopsies, proving to be a quick, user-friendly tool with strong inter-observer agreement and high specificity.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111872"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142789445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An MRI-Based Radiomics Model for Preoperative Prediction of Microvascular Invasion and Outcome in Intrahepatic Cholangiocarcinoma","authors":"Gengyun Miao ,&nbsp;Xianling Qian ,&nbsp;Yunfei Zhang ,&nbsp;Kai Hou ,&nbsp;Fang Wang ,&nbsp;Haoxiang Xuan ,&nbsp;Fei Wu ,&nbsp;Beixuan Zheng ,&nbsp;Chun Yang ,&nbsp;Mengsu Zeng","doi":"10.1016/j.ejrad.2024.111896","DOIUrl":"10.1016/j.ejrad.2024.111896","url":null,"abstract":"<div><h3>Purpose</h3><div>Microvascular invasion (MVI) serves as a significant predictor of poor prognosis in intrahepatic cholangiocarcinoma (ICC). This study aims to establish a comprehensive model utilizing MR radiomics for preoperative MVI status stratification and outcome prediction in ICC patients.</div></div><div><h3>Materials and methods</h3><div>A total of 249 ICC patients were randomly assigned to training and validation cohorts (174:75), along with a time-independent test cohort consisting of 47 ICC patients. Independent clinical and imaging predictors were identified by univariate and multivariate logistic regression analyses. The radiomic model was developed based on robust radiomic features extracted using a logistic regression classifier. The predictive efficacy of the models was evaluated by receiver operating characteristic curves, calibration curves and decision curves. Multivariate Cox analysis identified the independent risk factors for recurrence-free survival and overall survival, Kaplan-Meier curves were plotted, and a nomogram was used to visualize the predictive model.</div></div><div><h3>Results</h3><div>The imaging model included tumor size and intrahepatic duct dilatation. The radiomics model comprised 25 stable radiomics features. The Imaging-Radiomics (IR) model, which integrates independent predictors and robust radiomics features, demonstrates desirable performance for MVI (AUC_training= 0.890, AUC_validation= 0.885 and AUC_test= 0.815). The calibration curve and decision curve validate the clinical utility. Preoperative MVI prediction based on IR model demonstrated comparable accuracy in MVI stratification and outcome prediction when compared to histological MVI.</div></div><div><h3>Conclusion</h3><div>The IR model and the nomogram based on IR model-predicted MVI status may serve as potential tools for MVI status stratification and outcome prediction in ICC patients preoperatively.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111896"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142893343","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":"Effect of needle size on outcomes of vacuum-assisted excision of breast lesions. A randomized controlled trial","authors":"Athanasios Zouzos ,&nbsp;Irma Fredriksson ,&nbsp;Andreas Karakatsanis ,&nbsp;Iliana Aristokleous ,&nbsp;Theodoros Foukakis ,&nbsp;Fredrik Strand","doi":"10.1016/j.ejrad.2024.111895","DOIUrl":"10.1016/j.ejrad.2024.111895","url":null,"abstract":"<div><h3>Background</h3><div>Utilizing a larger needle-size instead of a smaller one in vacuum-assisted excision of breast lesions might enhance the effectiveness of the method. We conducted a clinical trial to investigate the effects of needle size 7G compared to 10G regarding excision completeness and procedural efficiency.</div></div><div><h3>Materials and methods</h3><div>In this prospective, single-blinded, randomized clinical trial, the patients were enrolled between November 2019 and August 2022. Follow-up examinations were performed at 6 and 24 months after the procedure<strong>.</strong> In total, 208 patients were screened and enrolled, and following withdrawal of consent, the trial population comprised 194 patients. All patients with ultrasound-visible lesions of &lt;30 mm in size and biopsy confirmation corresponding to a B2 or B3 lesion were included in the study. Additionally, patients with BI-RADS 3 and 4a microcalcifications measuring &lt;15 mm were also eligible. Eighty-five percent of the patients attended the 6-month follow-up, and 65 % attended the 24-month follow-up.</div></div><div><h3>Results</h3><div>There were no significant difference between the two randomization arms in terms of age, and lesion size. The mean procedure time was 7.7 min and 8.5 min for 7G and 10G needle size, respectively (=0.126). Of the 164 patients who attended the 6-month follow-up, no remaining lesions were found in 90 % and 81.5 % (p = 0.109) patients for 7G and 10G needle size respectively. Thirty percent (6/20) of the patients with microcalcifications excised stereotactically, guided by mammography, had a residual lesion compared to 2.5 % (1/42) of the patients with intraductal lesions excised under ultrasound guidance.</div></div><div><h3>Conclusions</h3><div>Using a 10G compared to a 7G needle size resulted in no difference in procedure time or excision completeness. Among the analyzed parameters, only a larger lesion size was consistently associated with a longer procedure time and a higher risk of incomplete excision.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111895"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142893364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma","authors":"Qi Zeng ,&nbsp;Fangxu Jia ,&nbsp;Shengming Tang ,&nbsp;Haoling He ,&nbsp;Yan Fu ,&nbsp;Xueying Wang ,&nbsp;Jinfan Zhang ,&nbsp;Zeming Tan ,&nbsp;Haiyun Tang ,&nbsp;Jing Wang ,&nbsp;Xiaoping Yi ,&nbsp;Bihong T. Chen","doi":"10.1016/j.ejrad.2024.111900","DOIUrl":"10.1016/j.ejrad.2024.111900","url":null,"abstract":"<div><h3>Objective</h3><div>Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning model based on MRI radiomics data.</div></div><div><h3>Methods</h3><div>This retrospective study included 235 patients with confirmed solitary BM and 273 patients with GBM. Patients were randomly assigned to the training (n = 356) or the validation (n = 152) cohort. Conventional brain MRI sequences including T1-weighted imaging (T1WI), contrast-enhanced_T1WI, and T2-weighted imaging (T2WI) were acquired. Brain tumors were delineated on all three sequences and segmented. Features were selected from demographic, clinical, and radiomic data. An integrated ensemble machine learning model, i.e., the elastic regression-SVM-SVM model (ERSS) and a multivariable logistic regression (LR) model combining demographic, clinical, and radiomic data were built for predictive modeling. Model efficiency was evaluated using discrimination, calibration, and decision curve analyses. Additionally, external validation was performed using an independent cohort consisting of 47 patients with GBM and 43 patients with isolated BM to assess the ERSS model generalizability.</div></div><div><h3>Results</h3><div>The ERSS model demonstrated more optimal classification performance (AUC: 0.9548, 95% CI: 0.9337–0.9734 in training cohort; AUC: 0.9716, 95% CI: 0.9485–0.9895 in validation cohort) as compared to the LR model according to the receiver operating characteristic (ROC) curve and decision curve for the internal cohort. The external validation cohort had less optimal but still robust performance (AUC: 0.7174, 95% CI: 0.6172–0.8024). The ERSS model with integration of multiple classifiers, including elastic net, random forest and support vector machine, produced robust predictive performance and outperformed the LR method.</div></div><div><h3>Conclusion</h3><div>The results suggested that the integrated machine learning model, i.e., the ERSS model, had the potential for efficient and accurate preoperative differentiation of BM from GBM, which may improve clinical decision-making and outcomes of patients with brain tumors.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111900"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142902371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A nomogram based on multiparametric magnetic resonance imaging improves the diagnostic performance of breast lesions diagnosed as BI-RADS category 4: A comparative study with the Kaiser score","authors":"Xiao Yang ,&nbsp;Zhou Lu ,&nbsp;Xiaoying Tan ,&nbsp;Lin Shao ,&nbsp;Jie Shi ,&nbsp;Weiqiang Dou ,&nbsp;Zongqiong Sun","doi":"10.1016/j.ejrad.2025.111920","DOIUrl":"10.1016/j.ejrad.2025.111920","url":null,"abstract":"<div><h3>Purpose</h3><div>To construct a nomogram combining Kaiser score (KS), synthetic MRI (syMRI) parameters, apparent diffusion coefficient (ADC), and clinical features to distinguish benign and malignant breast lesions better.</div></div><div><h3>Methods</h3><div>From December 2022 to February 2024, a retrospective cohort of 168 patients with breast lesions diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 by ultrasound and/or mammography was included. The research population was divided into the training set (n = 117) and the validation set (n = 51) by random sampling with a ratio of 7:3. Breast lesions’ KS, ADC, relaxation time of syMRI, and clinical and imaging features were statistically analyzed and compared between malignant and benign groups. Two experienced radiologists independently assigned KS, and measured quantitative values of ADC and parameters of syMRI, and the intraclass correlation coefficient (ICC) was calculated. Independent predictors were identified by univariable and multivariable logistic regression analysis. Then, a nomogram was established, and its performance was evaluated by the area under the curve (AUC), calibration curve, and decision curve.</div></div><div><h3>Results</h3><div>There were 168 lesions (118 malignant and 50 benign) in 168 female patients confirmed by histopathology. The interobserver agreement for each quantitative parameter was excellent. Older patient (OR = 1.091, 95 % confidence interval [CI]: 1.017–1.170, P = 0.014), higher lesions’ KS (OR = 288.431, 95 % CI: 34.930–2381.654, P &lt; 0.001), lower ADC (OR = 0.077, 95 % CI: 0.011–0.558, P = 0.011), and lower T2 relaxation time (OR = 0.918, 95 % CI: 0.868–0.972, P = 0.003) were independent predictors of breast malignancies and utilized to establish the nomogram. The accuracy of KS, ADC, T2, and patient age in predicting malignant breast lesions was 88.89 %, 79.48 %, 82.05 %, and 58.97 %, respectively. No significant differences in AUCs of KS, ADC and T2 were observed in distinguishing benign from malignant breast lesions. The nomogram yielded higher AUCs of 0.968 (0.934–0.996) and 0.959 (0.863–0.995) in training and validation sets than KS, ADC, T2, and patient age (p &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>Although there were no significant differences among the AUCs of KS, ADC, and T2, the constructed nomogram incorporating these parameters significantly improves diagnostic performance for distinguishing benign and malignant BI-RADS 4 breast lesions. Future external validation is needed in practical applications.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111920"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142964298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pelvic insufficiency fractures in locally advanced cervical cancer: the diagnostic yield of post-treatment MRI in a tertiary centre","authors":"Consolato Gullì ,&nbsp;Luca Russo ,&nbsp;Diana Gavrila ,&nbsp;Matteo Mangialardi ,&nbsp;Giorgio Mazzotta ,&nbsp;Matteo Mancino ,&nbsp;Rosa Autorino ,&nbsp;Evis Sala ,&nbsp;Antonio Leone ,&nbsp;Benedetta Gui","doi":"10.1016/j.ejrad.2025.111918","DOIUrl":"10.1016/j.ejrad.2025.111918","url":null,"abstract":"<div><h3>Purpose</h3><div>To assess the incidence of pelvic insufficiency fractures (PIFs) after concurrent chemoradiotherapy (CCRT) in patients with locally advanced cervical cancer (LACC), their time of onset and risk factors. We also analysed the inter-observer agreement between gynaecologic radiologists (GYN readers) and radiologists expert in musculoskeletal imaging (MSK reader) in detecting PIFs in our tertiary care centre.</div></div><div><h3>Methods</h3><div>Patients with confirmed LACC who underwent concurrent chemoradiation (CCRT) at our institution from June 2019 to November 2022 were retrospectively included. These patients underwent follow-up pelvic MRI every 3–6 months after CCRT. Cohen’s kappa statistics was employed to assess the inter-observer agreement between GYN and MSK readers.<!--> <!-->Logistic regression analysis was performed calculating odds ratios (OR) to identify risk factors for PIFs, such as age, body mass index (BMI), diabetes, smoking, hypertension, renal function and tumour size.</div></div><div><h3>Results</h3><div>Eighty-seven patients were included. PIFs were diagnosed in 21/87 (24.1 %) patients with a median onset time of 7.4 months from the end of EBRT. Among risk factors, age was statistically associated with PIFs (OR = 1.057, 95 % CI: 1.005–1.118, <em>p</em> = 0.033) with median age in the fracture group of 61.1 years (range: 52.0–71.5) and 53.8 years (range: 43.8–63.3). BMI was a significant predictor of PIFs (OR = 1.134; 95 % CI: 1.013–1.285; <em>p</em> = 0.027), with a higher median BMI among patients with PIFs (26.5; range: 21.5–31.2) compared to non-fractured patients (23.1; range: 20.2–25.1). Also patients with reduced renal function (eGFR &lt; 60 mL/min) had 3.437 times higher odds of experiencing fractures compared to those with normal eGFR. The GYN readers correctly identified PIFs in 2/21 cases and agreed with the MSK reader in 68/87 cases. The interobserver agreement was poor to fair (K = 0.138; 95 % CI: 0–0.311).</div></div><div><h3>Conclusions</h3><div>PIFs are a common complication of CCRT. Their identification on post-CCRT MRI may decrease the need for further targeted investigations and invasive treatments.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"183 ","pages":"Article 111918"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142964300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}