European Journal of Radiology最新文献

{"title":"Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma","authors":"Djennifer K. Madzia-Madzou ,&nbsp;Margot Jak ,&nbsp;Bart de Keizer ,&nbsp;Jorrit-Jan Verlaan ,&nbsp;Monique C. Minnema ,&nbsp;Kenneth Gilhuijs","doi":"10.1016/j.ejrad.2025.112160","DOIUrl":"10.1016/j.ejrad.2025.112160","url":null,"abstract":"<div><h3>Objectives</h3><div>Optimize deep learning-based vertebrae segmentation in longitudinal CT scans of multiple myeloma patients using structural uncertainty analysis.</div></div><div><h3>Materials &amp; Methods</h3><div>Retrospective CT scans from 474 multiple myeloma patients were divided into train (179 patients, 349 scans, 2005–2011) and test cohort (295 patients, 671 scans, 2012–2020). An enhanced segmentation pipeline was developed on the train cohort. It integrated vertebrae segmentation using an open-source deep learning method (Payer’s) with a post-hoc structural uncertainty analysis. This analysis identified inconsistencies, automatically correcting them or flagging uncertain regions for human review. Segmentation quality was assessed through vertebral shape analysis using topology. Metrics included ‘identification rate’, ‘longitudinal vertebral match rate’, ‘success rate’ and ‘series success rate’ and evaluated across age/sex subgroups. Statistical analysis included McNemar and Wilcoxon signed-rank tests, with <em>p</em> &lt; 0.05 indicating significant improvement.</div></div><div><h3>Results</h3><div>Payer’s method achieved an identification rate of 95.8% and success rate of 86.7%. The proposed pipeline automatically improved these metrics to 98.8% and 96.0%, respectively (<em>p</em> &lt; 0.001). Additionally, 3.6% of scans were marked for human inspection, increasing the success rate from 96.0% to 98.8% (<em>p</em> &lt; 0.001). The vertebral match rate increased from 97.0% to 99.7% (<em>p</em> &lt; 0.001), and the series success rate from 80.0% to 95.4% (<em>p</em> &lt; 0.001). Subgroup analysis showed more consistent performance across age and sex groups.</div></div><div><h3>Conclusion</h3><div>The proposed pipeline significantly outperforms Payer’s method, enhancing segmentation accuracy and reducing longitudinal matching errors while minimizing evaluation workload. Its uncertainty analysis ensures robust performance, making it a valuable tool for longitudinal studies in multiple myeloma.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112160"},"PeriodicalIF":3.2,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143927567","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":"Choroid plexus volume and association with migraine Pathophysiology","authors":"Jianmei Xiong ,&nbsp;Mengqi Liu ,&nbsp;Xin Li ,&nbsp;Zhiye Chen","doi":"10.1016/j.ejrad.2025.112135","DOIUrl":"10.1016/j.ejrad.2025.112135","url":null,"abstract":"<div><h3>Background</h3><div>Direct evidence of choroid plexus structures involved in the presumed peripheral-central interaction in migraine is exceptionally scarce and, thus, which demands further attention.</div></div><div><h3>Objectives</h3><div>Our objective is to assess choroid plexus volumetric changes quantitatively in episodic and chronic migraine patients versus age and sex compared normal controls, and to elucidate the differences.</div></div><div><h3>Methods</h3><div>Total sixty-five participants including 18 episodic migraine patients, 16 chronic migraine patients and 31 normal controls were recruited and underwent brain MRI examinations with 3.0 T MR strength between September 2021 to May 2023. The choroid plexus of the ventricles was segmented automatically on T1-weighted MRI sequences using the FreeSurfer (Version 7.4.1) software. Lateral ventricular choroid plexus volume was normalized as the ratio of choroid plexus to ipsilateral lateral ventricle volume (CP/LV). Group differences were assessed cross-sectionally. The accuracy of CP/LV for prediction of migraine was assessed using the receiver operating characteristic curves analysis.</div></div><div><h3>Results</h3><div>Patients with migraine were more anxious and depressive, with heavier headache burden and impaired cognitive ability. Statistical analysis revealed group differences of the CP/LV in the right side. CP/LV ration decreased in episodic migraine patients, but the CP/LV size increased in chronic migraine patients. CP/LV of the right side was able to differentiate episodic migraine from controls with area under the ROC curve (AUC) 0.696 (95 % CI: 0.550–0.818, sensitivity 100 %, specificity 46.8 %, and the cut-off value 0.0741, <em>P</em> &lt; 0.05). The diagnostic efficacy was marginally higher in distinguishing chronic migraine from episodic migraine with AUC 0.715(95 % CI: 0.536–0.856, sensitivity 50 %, specificity 94.4 % and the cut-off value 0.0725, <em>P</em> &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>Our finding suggested dynamic alteration of Lateral ventricular choroid plexus volume in the pathogenesis of migraine. The normalized CP/LV was associated with different migraine subtype. The normalized CP/LV can be used as a potential imaging biomarker for migraine diagnosis.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112135"},"PeriodicalIF":3.2,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143916257","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 value of cardiac magnetic resonance imaging-based left atrial strain analysis for identifying cardiac diseases with overlapping phyotype","authors":"Constantin Reichardt ,&nbsp;Maximilian Moos ,&nbsp;Tilman Emrich ,&nbsp;Karl-Friedrich Kreitner ,&nbsp;Lukas Müller ,&nbsp;Lukas Hobohm ,&nbsp;Tobias Bäuerle ,&nbsp;Akos Varga-Szemes ,&nbsp;Moritz C. Halfmann","doi":"10.1016/j.ejrad.2025.112153","DOIUrl":"10.1016/j.ejrad.2025.112153","url":null,"abstract":"<div><h3>Background</h3><div>The main objective of this study was to compare diagnostic accuracies of cardiac magnetic resonance (CMR)-based left atrial (LA) volumetry and function, including LA strain analysis, for the detection of myocardial impairments in diseases of different etiologies such as hypertensive heart disease, Fabry disease and acute myocarditis.</div></div><div><h3>Methods</h3><div>Healthy volunteers (HV, n = 50) and patients with cardiomyopathies (n = 140), including patients with hypertensive heart disease (n = 40), Fabry disease (n = 49), and acute myocarditis (n = 51), underwent CMR at 3 T. Atrial volume and strain analysis based on long-axis cine acquisition was performed using a commercially available post-processing software.</div></div><div><h3>Results</h3><div>Patients exhibited impaired LA reservoir (28.60 ± 9.91 % vs. 41.27 ± 7.54 %), conduit (17.35 ± 7.72 % vs. 26.89 ± 5.25 %) and booster strain (11.30 ± 4.52 % vs. 14.61 ± 4.15 %) parameters compared to HV (all p &lt; 0.001). In contrast, the volumetric values showed no significant difference between patients and HV (p &gt; 0.05). Passive and total emptying fractions were significantly lower in patients (p &lt; 0.001), while active emptying fraction did not differ (p &gt; 0.05). Superior diagnostic accuracy for the LA reservoir strain demonstrated improved prognostic performance comparing to LA volumetric and functional parameters (area under the curve [AUC] 0.85 vs. e.g. passive emptying fraction AUC 0.78, p &lt; 0.05).</div></div><div><h3>Conclusion</h3><div>LA strain parameters effectively distinguish patients with cardiac diseases presenting overlapping phenotypes from HV and outperform volumetric and traditional functional assessments of the LA.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112153"},"PeriodicalIF":3.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143904389","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":"Identifying baseline rectal MRI features as predictive indicators for local recurrence and metastatic disease in rectal cancer treated with surgical resection and neoadjuvant therapy or surgical resection alone","authors":"Maria El Homsi ,&nbsp;Sidra Javed-Tayyab ,&nbsp;Charlotte Charbel ,&nbsp;Jennifer S Golia Pernicka ,&nbsp;Viktoriya Paroder ,&nbsp;Charlie White ,&nbsp;Marinela Capanu ,&nbsp;Lee Rodriguez ,&nbsp;Natalie Gangai ,&nbsp;Iva Petkovska","doi":"10.1016/j.ejrad.2025.112152","DOIUrl":"10.1016/j.ejrad.2025.112152","url":null,"abstract":"<div><h3>Background</h3><div>To identify baseline rectal MRI characteristics that may serve as predictive factors for recurrence in patients with rectal adenocarcinoma after surgical resection.</div></div><div><h3>Methods</h3><div>This retrospective, single-center study included 269 consecutive patients (median age, 55 years [interquartile range, 47–65]; 144 men and 125 women) diagnosed with rectal cancer from January 2015–December 2017 who underwent baseline rectal MRI followed by surgical resection. MRI characteristics were collected from rectal MRI synoptic reports. Recurrence-free survival was defined as the time between surgical resection and recurrence (local recurrence and/or metastatic disease) or death. Statistical analysis included Cox proportional hazards to determine associations between baseline rectal MRI/clinical characteristics and recurrence.</div></div><div><h3>Results</h3><div>The median recurrence-free survival in the study sample was 6.4 years. Baseline rectal MRI characteristics associated with recurrence at univariable analysis were: age &gt; 55 years (<em>P</em> = 0.044), low rectal tumor location (<em>P</em> = 0.04), craniocaudal length ≥ 5.0 cm (<em>P</em> = 0.007), anal canal involvement (<em>P</em> = 0.011), presence of suspicious total mesorectal excision (TME) lymph nodes &gt; 0.5 cm (<em>P</em> = 0.03), mesorectal fascia involvement (<em>P</em> = 0.04), T3 stage (<em>P</em> = 0.024), T4 stage (<em>P</em> = 0.008), and M1 stage (<em>P</em> = 0.024). At multivariable analysis, only age &gt; 55 years (<em>P</em> = 0.012) and the presence of suspicious TME lymph nodes &gt; 0.5 cm (<em>P</em> = 0.049) remained associated with recurrence.</div></div><div><h3>Conclusion</h3><div>Advanced age and the presence of suspicious TME adenopathy &gt; 0.5 cm on baseline rectal MRI are associated with higher risk of recurrent disease in patients with resected rectal cancer.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112152"},"PeriodicalIF":3.2,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901937","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":"Tumor grade-titude: XGBoost radiomics paves the way for RCC classification","authors":"Stephan Ellmann ,&nbsp;Felicitas von Rohr ,&nbsp;Selim Komina ,&nbsp;Nadine Bayerl ,&nbsp;Kerstin Amann ,&nbsp;Iris Polifka ,&nbsp;Arndt Hartmann ,&nbsp;Danijel Sikic ,&nbsp;Bernd Wullich ,&nbsp;Michael Uder ,&nbsp;Tobias Bäuerle","doi":"10.1016/j.ejrad.2025.112146","DOIUrl":"10.1016/j.ejrad.2025.112146","url":null,"abstract":"<div><div>This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 RCC patients who underwent contrast-enhanced CT scans were included in the analysis. Radiomic features were extracted, and a two-step feature selection methodology was applied to identify the most relevant features for classification. The XGBoost model demonstrated high performance in both training (AUC = 0.87) and testing (AUC = 0.92) sets, with no significant difference between the two (p = 0.521). The model also exhibited high sensitivity, specificity, positive predictive value, and negative predictive value. The selected radiomic features captured both the distribution of intensity values and spatial relationships, which may provide valuable insights for personalized treatment decision-making. Our findings suggest that the XGBoost model has the potential to be integrated into clinical workflows to facilitate personalized adjuvant immunotherapy decision-making, ultimately improving patient outcomes. Further research is needed to validate the model in larger, multicentre cohorts and explore the potential of combining radiomic features with other clinical and molecular data.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112146"},"PeriodicalIF":3.2,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143912346","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":"Impact of Background Parenchymal Enhancement (BPE) on diagnostic performance of Contrast-Enhanced Mammography (CEM) for breast cancer diagnosis","authors":"Sonja Bechyna,&nbsp;Ambra Santonocito,&nbsp;Nina Pötsch,&nbsp;Paola Clauser,&nbsp;Thomas H Helbich,&nbsp;Pascal A.T. Baltzer","doi":"10.1016/j.ejrad.2025.112145","DOIUrl":"10.1016/j.ejrad.2025.112145","url":null,"abstract":"<div><h3>Objectives</h3><div>This study investigates how background parenchymal enhancement (BPE) impacts diagnostic performance in interpretation of contrast-enhanced mammography (CEM) for breast cancer diagnosis.</div></div><div><h3>Materials &amp; methods</h3><div>Retrospective IRB-approved single-center observational study on CEM-patients between 07/2020–09/2022. Indications for CEM were inconclusive or suspicious breast lesions identified by screening or diagnostic mammography and/or ultrasound. CEM was evaluated using the BI-RADS lexicon CEM supplement. BPE was assessed by one supervised reader and dichotomized as minimal/mild and moderate/marked. Exclusion criteria included patients without a 24-month follow-up, histology or CEM images were not available for technical reasons. Image interpretation was conducted by board-certified radiologists. All readers were blinded to patient clinical data and histopathology results. Statistical analysis included Kappa statistics and ROC analysis. Diagnostic metrics were calculated at a BI-RADS &gt; 3 cut-off. P-values &lt; 0.05 indicated statistical significance.</div></div><div><h3>Results</h3><div>229 female patients (mean age 53.8 ± 10.7 years) were included. BPE was minimal in 49.3 %, mild in 36.8 %, moderate in 12.5 %, and marked in 1.4 % of patients. Overall AUC was higher in minimal/mild BPE (0.94 ± 0.01) compared to moderate/marked BPE (0.82 ± 0.04), which proved statistically significant (difference 0.12, <em>p</em> = 0.004). Sensitivity was higher in the minimal/mild BPE group at 90.9 % compared to 66.7 % in the moderate/marked BPE group (<em>p</em> = 0.05). Specificity was significantly higher in the minimal/mild vs. moderate/marked BPE group, p = 0.0006).</div></div><div><h3>Conclusion</h3><div>BPE significantly affects the diagnostic performance of CEM, particularly sensitivity. This highlights the importance of assessing and reporting BPE in CEM to provide a simple metric indicating the reliability of test results.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112145"},"PeriodicalIF":3.2,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899186","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 and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images","authors":"Hajin Kim ,&nbsp;Kang-Hyeon Seo ,&nbsp;Kyuseok Kim ,&nbsp;Jina Shim ,&nbsp;Youngjin Lee","doi":"10.1016/j.ejrad.2025.112137","DOIUrl":"10.1016/j.ejrad.2025.112137","url":null,"abstract":"<div><div>Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ model for cerebral artery segmentation in CTA images, focusing on optimizing pruning levels by analyzing the trade-off between segmentation performance and computational cost. Dual-energy CTA and direct subtraction CTA datasets were utilized to segment the internal carotid and vertebral arteries in close proximity to the bone. We implemented four pruning levels (L1-L4) in the U-Net++ model and evaluated the segmentation performance using accuracy, intersection over union, F1-score, boundary F1-score, and Hausdorff distance. Statistical analyses were conducted to assess the significance of segmentation performance differences across pruning levels. In addition, we measured training and inference times to evaluate the trade-off between segmentation performance and computational efficiency. Applying deep supervision improved segmentation performance across all factors. While the L4 pruning level achieved the highest segmentation performance, L3 significantly reduced training and inference times (by an average of 51.56 % and 22.62 %, respectively), while incurring only a small decrease in segmentation performance (7.08 %) compared to L4. These results suggest that L3 achieves an optimal balance between performance and computational cost. This study demonstrates that pruning levels in U-Net++ models can be optimized to reduce computational cost while maintaining effective segmentation performance. By simplifying deep learning models, this approach can improve the efficiency of cerebrovascular segmentation, contributing to faster and more accurate diagnoses in clinical settings.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112137"},"PeriodicalIF":3.2,"publicationDate":"2025-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937252","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":"Improved evaluation of patients with small clusters of microcalcifications on mammograms: Implementation of vacuum assisted excision with “cavity margins shaving” technique","authors":"Rossella Rella ,&nbsp;Giovanna Romanucci ,&nbsp;Paolo Belli ,&nbsp;Mariagrazia Ramunno ,&nbsp;Josè Nunnari ,&nbsp;Gianluca Russo ,&nbsp;Francesca Morciano ,&nbsp;Sebastiano Croce ,&nbsp;Lucrezia Papalia ,&nbsp;Francesca Fornasa ,&nbsp;Oscar Tommasini ,&nbsp;Marco Conti","doi":"10.1016/j.ejrad.2025.112138","DOIUrl":"10.1016/j.ejrad.2025.112138","url":null,"abstract":"<div><div><u>Rationale and Objectives:</u> The purpose of our study is to assess the diagnostic performance and treatment effectiveness of vacuum assisted excision (VAE) under digital breast tomosynthesis (DBT) guidance with “cavity margins shaving” technique to ensure total lesion removal in patients with ≤ 15 mm clusters of microcalcifications.</div></div><div><h3>Materials and Methods</h3><div>Patients with a single cluster of microcalcifications (BI-RADS &gt; 3) &lt; 15 mm who underwent DBT-guided VAE were enrolled. The “cavity margins shaving” technique was used: 12 focus samples (FS) and 12 cleaning samples (CS) were taken and the histopathologic assessment of the FS and CS was performed separately. The presence of residual disease within the CS was assessed. The surgical excision results were compared according to the CS status.</div></div><div><h3>Results</h3><div>A total of 72 patients were included, with 12 benign (16.7%), 45 B3 (62.5%) and 15 malignant (20.8%) lesions. Among the 13 ductal carcinomas in situ (DCIS) and 17 atypical ductal hyperplasia (ADH) cases without residual disease within the CS (21/30, 70%), in 2 cases residual pathology was detected in the subsequent surgery, without any case of upgrade.</div><div>Comparing the presence of malignant disease (residual DCIS or upgrade of ADH) at surgical excision according to the CS status, the rates were 1/5 (20.0 %) and 4/5 (80.0 %) respectively for negative and positive CS (P = 0.007). The NPV of the absence of residual lesion in the CS was 95.24 % (95 %CI: 76.39 %-99.20 %).</div></div><div><h3>Conclusion</h3><div>VAE with cavity margins shaving technique could represent a valuable alternative to surgical excision in selected patients (such as those with ADH or low-grade DCIS) who met the radiologic and histologic criteria.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112138"},"PeriodicalIF":3.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886869","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":"Preoperative prediction of Ki-67 expression in medullary thyroid carcinoma based on ultrasonographic features: a 10-year retrospective study","authors":"Qianru Zhang ,&nbsp;Yan Hu ,&nbsp;Xiaoyan Chen ,&nbsp;Zhifang Yang ,&nbsp;Xiaoyu Li ,&nbsp;Xiaofeng Ni ,&nbsp;Shangyan Xu ,&nbsp;Weiwei Zhan","doi":"10.1016/j.ejrad.2025.112134","DOIUrl":"10.1016/j.ejrad.2025.112134","url":null,"abstract":"<div><h3>Purpose</h3><div>To identify ultrasonographic features that help distinguish Ki-67 expression levels in patients with medullary thyroid carcinoma (MTC).</div></div><div><h3>Materials and methods</h3><div>A total of 210 patients (245 nodules) with pathological diagnosis of MTC were included in this retrospective study between January 2013 and April 2024. Based on preoperative clinical and ultrasonographic features, univariate analysis and multivariate logistic regression analysis were performed to determine the risk factors associated with Ki-67 ≥ 5 %. A prediction model was subsequently established to evaluate the differential diagnostic performance of Ki-67 by the area under the curve (AUC).</div></div><div><h3>Results</h3><div>Among the 210 MTC patients (245 nodules), 35 patients (41 nodules) exhibited high Ki-67 expression (Ki-67 ≥ 5 %), while 175 patients (204 nodules) had low Ki-67 expression (Ki-67 &lt; 5 %). There were no significant differences in age, sex, body mass index (BMI), preoperative calcitonin and preoperative CEA levels between the two groups (P &gt; 0.05). Multivariate analysis of the nodules in the two groups revealed that the ultrasound features, including location in the upper or middle region, tumor size &gt; 2.15 cm, and markedly hypoechoic were independent risk factors for high Ki-67 expression. A prediction model was established with the AUC of 0.812 (95 % CI 0.743–0.882).</div></div><div><h3>Conclusions</h3><div>Compared to the low Ki-67 expression group, Ki-67 ≥ 5 % group were more likely to exhibit the ultrasound characteristics of location in the upper or middle region, tumor size &gt; 2.15 cm, and markedly hypoechoic. The prediction model demonstrated preferable diagnostic value.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112134"},"PeriodicalIF":3.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143887498","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":"Contrast-enhanced orbital MRI for activity assessment and treatment response prediction in thyroid eye disease","authors":"Duojin Xia ,&nbsp;Sien Ping Chew ,&nbsp;Haiyang Zhang ,&nbsp;Runchuan Li ,&nbsp;Jing Sun ,&nbsp;Yinwei Li ,&nbsp;Zhangsheng Yu ,&nbsp;Huifang Zhou","doi":"10.1016/j.ejrad.2025.112136","DOIUrl":"10.1016/j.ejrad.2025.112136","url":null,"abstract":"<div><h3>Objective</h3><div>To investigate the performance of contrast-enhanced orbital MRI (T1-weighted contrast-enhanced [T1CE] and dynamic contrast-enhanced MRI [DCE-MRI]) for activity assessment and prediction of treatment response to intravenous glucocorticoid (IVGC) treatment in thyroid eye disease (TED).</div></div><div><h3>Methods</h3><div>A retrospective study of 59 active moderate-to-severe TED patients (36 responsive and 23 unresponsive) treated with IVGC, matched with 31 inactive TED patients were included. T1CE and DCE-MRI were collected from each subject. Univariate and multivariate logistic regression analyses, as well as receiver operating characteristic (ROC) curves (evaluated by area under the curve, AUC) were used to evaluate the diagnostic and predictive models.</div></div><div><h3>Results</h3><div>Active patients showed a higher signal intensity ratio of lateral rectus (LR-SIR) on T1CE and a higher wash-in rate of inferior rectus (IR-WIR) on DCE-MRI compared to inactive patients (<em>p</em> &lt; 0.05). The AUC for T1CE and DCE-MRI based models were 0.866, and 0.844, respectively. The combined model (LR-SIR and IR-WIR) significantly enhanced model performance (AUC = 0.914, 95 % CI: 0.858–0.970). Responsive patients demonstrated a longer time to peak of lateral rectus (LR-TTP) than unresponsive patients (<em>p</em> &lt; 0.05). The cutoff value of prediction probability was 0.678, and the AUC based on this model was 0.739 (95 % CI: 0.608–0.807).</div></div><div><h3>Conclusions</h3><div>T1CE and DCE-MRI could effectively assist in TED activity assessment, and DCE-MRI could help predict IVGC treatment response. Specifically, LR-SIR and IR-WIR were indicators of TED activity, and IR-TTP was predictive of IVGC treatment response. Combining both contrast-enhanced sequences could further enhance the efficiency of TED activity assessment.</div></div>","PeriodicalId":12063,"journal":{"name":"European Journal of Radiology","volume":"188 ","pages":"Article 112136"},"PeriodicalIF":3.2,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886870","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}