Frontiers in radiology最新文献

{"title":"Anatomical characteristics of the styloid process associated with internal carotid artery dissection: a systematic review and meta-analysis of controlled trials.","authors":"Tomas Klail, Emmanouil Kalioras, Marc von Gernler, Roland Giger, Aristomenis K Exadaktylos, Martin Müller, Franca Wagner","doi":"10.3389/fradi.2026.1788985","DOIUrl":"10.3389/fradi.2026.1788985","url":null,"abstract":"<p><strong>Purpose: </strong>Internal carotid artery dissection (ICA-D) is an important cause of stroke in adults. The styloid process (SP) may be associated with ICA-D due to potential (micro)trauma resulting from its close anatomical proximity to the internal carotid artery (ICA). The aim of this systematic review with meta-analysis is to investigate the association between SP characteristics -particularly SP-ICA distance - and ICA-D.</p><p><strong>Methods: </strong>A systematic review was conducted across six databases to identify observational studies comparing ICA-D patients to controls. The primary outcome of interest was the association between SP-ICA distance and ICA-D. Secondary outcomes included associations between ICA-D and the SP length or angulation. A random-effects meta-analysis was performed, including a subgroup analysis of moderate/high-quality studies. Effect sizes were expressed as standardized mean differences (SMD, Hedges' g).</p><p><strong>Results: </strong>Six studies were included in the systematic review, of which five were eligible in the meta-analysis. The pooled analysis of all five case-control studies (270 ICA-D patients and 377 controls) showed no significant difference in SP-ICA distance (SMD = -0.92, <i>p</i> = 0.143); with a high degree of heterogeneity (I² = 98%). Subgroup analysis of moderate/high-quality studies evaluating the SP-ICA distance ipsilateral to the ICA-D (4 studies) yielded a negative pooled SMD (-0.29, <i>p</i> = 0.047; moderate heterogeneity: I² = 64%), consistent with a shorter SP-ICA distance in ICA-D cases. Meta-analysis of the SP length (3 studies) found no significant association (SMD 0.24, <i>p</i> = 0.139) and two studies also found no significant relationship between ICA-D and SP angulation.</p><p><strong>Conclusion: </strong>A shorter SP-ICA distance was associated with ICA-D, whereas no significant associations were observed for SP length or angulation. However, the available evidence remains limited and heterogeneous.</p><p><strong>Systematic review registration: </strong>CRD42024582594.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1788985"},"PeriodicalIF":4.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148019221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning-based denoising in cardiac CT: effects on image quality, calcium scoring interchangeability, and reporting workflow.","authors":"Daniel Wessling, Jan Magnus, Jan M Brendel, Sebastian Werner, Patrick Krumm, Konstantin Nikolaou, Saif Afat, Andreas S Brendlin","doi":"10.3389/fradi.2026.1764357","DOIUrl":"10.3389/fradi.2026.1764357","url":null,"abstract":"<p><strong>Objectives: </strong>Ischemic heart disease is a major global health burden requiring timely diagnosis. Although coronary artery calcium (CAC) scoring and coronary computed tomography angiography (CCTA) are valuable tools, image noise can distort assessment. Deep learning-based denoising (DLD) algorithms may enhance quality, yet their impact on cardiac CT workflows remains unclear. This study evaluated DLD effects on CAC and CCTA image quality, clinical interchangeability, and workflow efficiency compared with iterative reconstruction (IR).</p><p><strong>Materials and methods: </strong>A retrospective analysis of 100 patients with CAC and CCTA scans from the same CT scanner was performed. IR and DLD reconstructions yielded 400 datasets, rated by two radiologists using a semiquantitative scoring system. Objective metrics (CT number stability, noise, contrast-to-noise ratio) were measured. Clinical interchangeability and Workflow efficiency were evaluated.</p><p><strong>Results: </strong>DLD showed significantly higher overall image quality than IR (<i>p</i> < 0.001), while preserving CT attenuation and improving noise and CNR. Although cardiac age classifications did not differ between reconstruction methods, Agatston scores were significantly higher in IR before manual correction (<i>p</i> < 0.001. After manual correction, Agatston scores were not significantly different between IR and DLD (<i>p</i> ≥ 0.158), supporting clinical comparability of the derived clinical metrics between the two approaches. DLD also reduced manual correction time (<i>p</i> < 0.001).</p><p><strong>Conclusions: </strong>The investigated DLD algorithm improves image quality and radiological workflows thus potentially enhancing overall patient care. Key limitations include the retrospective single-center design and inherent subjectivity in image-quality evaluation; therefore, findings should be confirmed in prospective studies with more objective measures.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1764357"},"PeriodicalIF":4.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13167992/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147944124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a nomogram using interpretable machine learning to integrate CT radiomics and PET metabolic parameters for predicting benign-malignant differentiation of pulmonary space-occupying lesions.","authors":"Xue Liu, Xinghua Liu, Li Bin, Yu Zhang, Huiting Liu, Cailiang Gao","doi":"10.3389/fradi.2026.1782678","DOIUrl":"10.3389/fradi.2026.1782678","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;To construct a multimodal machine learning model integrating computed tomography (CT) radiomics, Positron Emission Tomography (PET) metabolic parameters, and clinical data for differentiating benign from malignant pulmonary space-occupying lesions (PSOLs), and develop an interpretable nomogram for clinical application.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methodology: &lt;/strong&gt;This study enrolled 384 patients with PSOLs who underwent dual-time-point &lt;sup&gt;1&lt;/sup&gt;⁸F-FDG PET/CT examinations. The cohort was divided into a training set (&lt;i&gt;n&lt;/i&gt; = 268, 145 malignant, 123 benign) and an independent temporal validation set (&lt;i&gt;n&lt;/i&gt; = 116, 69 malignant, 47 benign) at a 7:3 ratio according to the chronological order of patient enrollment, to avoid data leakage and rigorously assess model generalizability. All malignant lesions were confirmed by pathological examination, while benign lesions were confirmed by pathology (82%) or clinical-imaging follow-up for at least 12 months (18%). CT radiomic features with Intraclass Correlation Coefficient (ICC) values &gt;0.75 were selected, and a Radiomics-score (Rad-score) was generated using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm. Integrated models [Logistic regression, random forest (RF), support vector machine (SVM), eXtreme Gradient Boosting (XGBoost)] were developed by fusing the Rad-score, clinical variables, and PET metabolic parameters. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, F1-score, and Brier score. Model calibration was assessed via calibration curves, and clinical utility was validated by decision curve analysis (DCA). Model interpretability was achieved using SHapley Additive exPlanations (SHAP) values for the optimal XGBoost model, and a clinically applicable, interpretable nomogram was constructed based on the core predictive features identified by SHAP analysis to facilitate clinical translation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A Rad-score was constructed from 17 optimally selected features. In the independent temporal validation set, the single-modality models achieved AUCs of 0.808 (Radiomics Model), 0.732 (Clinical Model), and 0.874 (Metabolic Model). Among all tested models, the XGBoost integrated model achieved the highest AUC of 0.967, which was significantly higher than that of all other models (Bonferroni-adjusted &lt;i&gt;P&lt;/i&gt; = 0.002-0.032, all adjusted &lt;i&gt;P&lt;/i&gt; &lt; 0.05). SHAP analysis identified &lt;i&gt;Δ&lt;/i&gt;SUVmax, Rad-score, and delayed phase total lesion glycolysis (TLG_d) as the top three key predictive features.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The predictive logic of the optimal XGBoost model was decoded via SHAP analysis to identify core predictive features, and a clinically applicable, interpretable nomogram was further established based on a multivariate logistic regression model using these core features, to facilitate the clinical translati","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1782678"},"PeriodicalIF":4.0,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13139110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147847012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vietnamese expert consensus on the treatment of hepatocellular carcinoma with transarterial chemoembolization.","authors":"Vu Dang Luu, Do Dang Tan, Pham Minh Thong, Le Van Khang, Le Thanh Dung, Le Trong Binh, Nguyen Ngoc Trang, Nguyen Ngoc Cuong, Nguyen Dinh Luan, Ngo Le Lam, Trinh Ha Chau, Than Van Sy, Nguyen Duy Anh, Le Duc Tho, Tran Duc Huy, Dang Ngoc Hieu, Pham Quang Son, Le Doan Tri, Nguyen Dinh Huong, Pham Cam Phuong, Nguyen Tien Thinh, Vo Duy Thong, Ho Tan Phat, Phan Thi Hong Duc, Pham Gia Anh, Vo Hoi Trung Truc, Lam Quoc Trung, Le Ba Thao, Le Tuan Anh, Tran Cong Duy Long","doi":"10.3389/fradi.2026.1763042","DOIUrl":"10.3389/fradi.2026.1763042","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) remains a major public health challenge in Vietnam and, according to GLOBOCAN 2022, accounted for 24,502 new cases in 2022, making it the second most common cancer and the leading cause of cancer-related mortality. Transarterial chemoembolization (TACE), introduced in 1977, is a pivotal treatment for unresectable HCC, delivering chemotherapeutic agents and embolic materials to induce tumor necrosis through cytotoxicity and ischemia. TACE is versatile and, in selected early-stage HCC (BCLC 0-A) treated with a highly selective approach, may achieve complete response; in intermediate-stage disease (BCLC B), it can prolong survival and enable downstaging, and in advanced-stage disease (BCLC C), it may complement systemic therapy. Despite its global use, TACE practices vary, and Vietnam lacks standardized guidelines tailored to its unique clinical landscape. The Vietnamese Society of Radiology and Nuclear Medicine and The Vietnamese Society of Interventional Radiology conducted three workshops in Da Nang, An Giang, and Can Tho between August and December 2024. These workshops engaged interventional radiologists from major hospitals and regional centers to develop consensus-based TACE recommendations. Through literature reviews, discussions, and physician voting, the recommendations cover pre-TACE diagnostic imaging, patient selection criteria, TACE techniques, choice of embolic materials and chemotherapeutic agents, intra- and post-procedure monitoring, and integration with combination therapies. This initiative aligns international standards with local needs, aiming to enhance the efficacy and consistency of TACE for HCC management in Vietnam.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1763042"},"PeriodicalIF":4.0,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13140673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147847007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YOLO11-based detection of manometry sensors in video-fluoroscopy imaging for computer-aided multimodal assessment of swallowing.","authors":"Dionne S Brandsma, Manuel Maria Loureiro da Rocha, Lisette van der Molen, Maarten J A van Alphen, Michiel W M van den Brekel, Françoise J Siepel","doi":"10.3389/fradi.2026.1767875","DOIUrl":"10.3389/fradi.2026.1767875","url":null,"abstract":"<p><strong>Purpose: </strong>Accurate assessment of swallowing function is essential in the diagnosis and monitoring of dysphagia following head and neck cancer (HNC). The simultaneous analysis of video-fluoroscopy swallow studies (VFSS) and high-resolution impedance manometry (HRIM) offers a more comprehensive evaluation, reducing subjectivity in VFSS and improving anatomical context of HRIM in HNC patients.</p><p><strong>Methods: </strong>The inherently low pharyngeal pressures in post-treatment HNC patients hinder the analysis of HRIM. As such, this study proposes a deep learning method for the automatic detection of HRIM sensors in VFSS using a YOLO11-based detector, aimed at enabling the automatic delineation of manometric regions. Detection performance was evaluated on 268 frames from 8 HNC patients using a leave-one-patient-out cross-validation approach. EigenCAM-based heatmaps were produced to analyze the model's attention patterns.</p><p><strong>Results: </strong>The model achieved 95.8% Precision, 97.4% Recall, 96.6% F1-score with minimal variation between folds. Under different noise levels and bolus-simulated obstructions, performance remained robust. Our method outperformed previous template-matching methods for manometric sensor detection in VFSS. EigenCAM visualizations confirmed consistent attention to catheter regions.</p><p><strong>Conclusion: </strong>The proposed YOLO11-based detector provides accurate and robust localization of manometric sensors in VFSS sequences to facilitate computer-assisted HRIM-VFSS fusion for objective swallowing assessment.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1767875"},"PeriodicalIF":4.0,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13121316/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining computed tomography features and histogram analysis facilitates differentiation between solitary pulmonary invasive mucinous and non-mucinous adenocarcinomas.","authors":"Duiming Yang, Hao Hu, Zhimei Li, Shuilan Zhang, Jing Ai, Handan Zhang","doi":"10.3389/fradi.2026.1793604","DOIUrl":"10.3389/fradi.2026.1793604","url":null,"abstract":"<p><strong>Objective: </strong>To assess the value of combining computed tomography (CT) morphological and histogram features for the differentiation of solitary pulmonary invasive mucinous adenocarcinoma (PIMA) from pulmonary invasive non-mucinous adenocarcinoma (PINMA).</p><p><strong>Methods: </strong>This retrospective study analyzed the CT images and clinical data of 58 and 105 patients with PIMA and PINMA, respectively. CT histogram features were extracted after delineating regions of interest using 3D Slicer software. CT morphological and histogram features were compared between the PIMA and PINMA groups, and those that differed significantly were included in multivariate logistic regression models. The independent predictive factors identified were used to create CT morphological, CT histogram-based, and combined prediction models. The best-performing model was visualized and evaluated by constructing a nomogram.</p><p><strong>Results: </strong>The CT morphological prediction model included nodule type, vacuole sign, and tumor location as factors predictive of PIMA and had an area under the curve of 0.754. The CT histogram-based prediction model included kurtosis and the 90th percentile as factors predictive of PIMA and had an area under the curve of 0.820. The combined prediction model, which included tumor location, vacuole sign, kurtosis, and the 90th percentile, had an area under the curve of 0.845, suggesting greater diagnostic accuracy than the separate models. The combined prediction model also exhibited good calibration and high clinical applicability.</p><p><strong>Conclusion: </strong>Integrating CT morphological features and histogram analysis improves the accuracy of differentiating PIMA from PINMA. The nomogram provides a practical and effective tool for the non-invasive diagnosis of lung cancer subtypes.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1793604"},"PeriodicalIF":4.0,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13121248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coronary artery calcium scoring in 2026: strengths, limitations, and optimized clinical use.","authors":"Pierre Sabouret, Domenico Mario Giamundo, Julien Rosencher, Stefano Figliozzi","doi":"10.3389/fradi.2026.1822303","DOIUrl":"10.3389/fradi.2026.1822303","url":null,"abstract":"<p><p>Coronary artery calcium (CAC) scoring on non-contrast ECG-gated CT remains a robust, reproducible marker of total coronary atherosclerotic burden with clear prognostic value and consistent risk reclassification beyond contemporary clinical calculators. Recent studies (2018-2026) reinforce the 'power of zero' for near-term risk de-escalation, identify very high CAC (≥1,000) as a distinct, very-high-risk phenotype, and, importantly, provide randomized evidence that CAC-guided treatment reduces plaque progression. Advances in artificial intelligence (AI), spectral CT, and standardized reporting (SCCT/STR; CAC-DRS) expand opportunities for automated and incidental CAC detection. This mini-review summarizes updated strengths, limitations, and practice guidance; synthesizes new evidence (2024-2026); and includes a practical clinical decision flowchart for the selective use of CAC in prevention pathways.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1822303"},"PeriodicalIF":4.0,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13111553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CT-based subchondral bone microstructural analysis in knee osteoarthritis via MR-guided distillation learning.","authors":"Yuqi Hu, Xiangyu Zhao, Gaowei Qing, Kai Xie, Chenglei Liu, Lichi Zhang","doi":"10.3389/fradi.2026.1798348","DOIUrl":"10.3389/fradi.2026.1798348","url":null,"abstract":"<p><p>Reliable analysis of subchondral trabecular microstructure is critical for knee osteoarthritis assessment. However, this analysis largely relies on high-resolution MRI acquired using balanced fast field echo (BFFE) sequences, which are rarely included in routine clinical protocols. Clinical CT is widely acquired, yet its limited spatial resolution and soft-tissue contrast makes direct trabecular parameter estimation unreliable. Therefore, it is specifically demanded to enable accurate trabecular microstructural analysis and osteoarthritis diagnosis using routine clinical CT, while also approaching the reliability of MR-based analysis. In this paper, we propose CT-based Subchondral Microstructural Analysis (CT-SMA) method, which utilizes distillation learning technology to transfer high-resolution structural knowledge from MR to CT while enforcing CT-only inference. The core idea of CT-SMA is to transfer microstructural knowledge learned from high-resolution MR to CT through cross-modal knowledge distillation, using a pre-trained MR-based teacher model to supervise CT-based student model on feature maps. To support effective distillation, CT-SMA further introduces a synthesis-based, multi-stage MR-CT registration strategy that establishes patch-level correspondences across modalities, despite substantial differences in resolution, contrast, and appearance. Experiments on a clinical knee imaging cohort demonstrate that CT-SMA substantially improves CT-based trabecular parameter estimation, achieving strong agreement (ICC = 0.742) with MR-derived references across key trabecular biomarkers. Moreover, when aggregated using a Transformer-based model, the regressed CT-derived parameters enable patient-level osteoarthritis diagnosis with an AUC of 0.883, substantially outperforming CT-based prediction without distillation (AUC = 0.778). These results indicate that routine clinical CT can support reliable subchondral bone analysis via proposed CT-SMA, establishing a practical foundation for large-scale studies.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1798348"},"PeriodicalIF":4.0,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13106955/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Case Report: Embolization of a cognard type V cavernous sinus dural arteriovenous fistula via occluded Inferior petrosal sinus.","authors":"Zhaolong Zhang, Yanan Jiang, Qi Zhang, Liming Shao, Hongzhang Xu, Yixing Xie, Xiaolong Zhao, Chengjian Sun, Rui Xu","doi":"10.3389/fradi.2026.1795775","DOIUrl":"10.3389/fradi.2026.1795775","url":null,"abstract":"<p><strong>Background: </strong>Cavernous sinus dural arteriovenous fistula (CS-DAVF) with cortical venous drainage to the spinal perimedullary veins (Cognard type V) is a rare clinical entity. The treatment becomes particularly challenging when such a case is complicated by occlusion of the inferior petrosal sinus. We report a rare case of Cognard type V cavernous sinus dural arteriovenous fistula (CS-DAVF) embolized with Onyx via the occluded inferior petrosal sinus (IPS).</p><p><strong>Case description: </strong>A 62-year-old woman presented to our hospital with nausea, vomiting and progressive weakness in both lower limbs. Magnetic resonance imaging (MRI) revealed extensive edema of pons and medulla oblongata with flow voids. Cerebral angiography demenstrated a dural arteriovenous fistula (DAVF) in the left cavernous sinus, supplied by the meningohypophyseal trunk and branches of the middle meningeal artery. The fistula drained into the intercavernous sinus and right cavernous sinus, ultimately draining into the spinal perimedullary veins. Transarterial approach was tried first. Onyx-18 was injected into the branches of middle meningeal artery, partially casting the fistula. However, the DAVF was not completely occluded due to residual supply from the meningohypophyseal trunk. The second operation was performed using transvenous approach. The microcatheter was successfully navigated to the fistulous point via the occluded right IPS and the intercavernous sinus. Left cavernous sinus (CS) and intercavernous sinus were casted using Onyx-18 and the DAVF was completely eliminated.</p><p><strong>Conclusion: </strong>We report a Cognard type V CS-DAVF that was embolized with Onyx through an occluded IPS, demonstrating that this technique is a feasible and effective treatment option.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1795775"},"PeriodicalIF":4.0,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13106297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic review of pituitary gland and pituitary adenoma automatic segmentation techniques in magnetic resonance imaging.","authors":"Mubaraq Yakubu, Navodini Wijithilake, Jonathan Shapey, Andrew King, Alexander Hammers","doi":"10.3389/fradi.2026.1737075","DOIUrl":"10.3389/fradi.2026.1737075","url":null,"abstract":"<p><p>Accurate segmentation of both the pituitary gland and adenomas from magnetic resonance imaging (MRI) is essential for diagnosis and treatment of pituitary adenomas. This systematic review evaluates automatic segmentation methods for improving the accuracy and efficiency of MRI-based segmentation of pituitary adenomas and the gland itself. We analysed 34 studies that employed automatic and semi-automatic segmentation methods out of 353 reviewed studies. We extracted and synthesized data on segmentation techniques and performance metrics (such as Dice overlap scores). The majority of reviewed studies utilized deep learning approaches, with U-Net-based models being the most prevalent. Automatic methods yielded Dice scores of 0%-89% for pituitary gland and 4%-96% for adenoma segmentation. Semi-automatic methods reported 80%-92% for pituitary gland and 75%-88% for adenoma segmentation. Most studies did not report important metrics such as MR field strength, age and adenoma size (macro/micro/giant) or even adenoma type and human subject numbers. Automated segmentation techniques such as U-Net-based models show promise, especially for adenoma segmentation, but further improvements are needed to achieve consistently good performance in small structures like the normal pituitary gland. Future progress will require methodological innovation and larger, more diverse datasets to enhance clinical applicability. <b>Systematic Review Registration:</b> https://www.crd.york.ac.uk/PROSPERO/view/CRD42023407127, PROSPERO CRD42023407127.</p>","PeriodicalId":73101,"journal":{"name":"Frontiers in radiology","volume":"6 ","pages":"1737075"},"PeriodicalIF":4.0,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13106132/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}