World journal of radiology最新文献

{"title":"Immediate post-microwave ablation computed tomography model may better predict short-term response of stage I non-small cell lung cancer.","authors":"Qing-Jin Qin, Ming-Yuan Hou, Juan-Juan Tian, Yan-Zhuo Sun, Xiao-Han Jing, Tai-Yang Zuo","doi":"10.4329/wjr.124658","DOIUrl":"10.4329/wjr.124658","url":null,"abstract":"<p><strong>Background: </strong>Microwave ablation (MWA) is indicated for treating inoperable early-stage non-small cell lung cancer.</p><p><strong>Aim: </strong>To evaluate its therapeutic effect by developing multimodal models that integrate computed tomography (CT) radiomics features and simple clinical characteristics.</p><p><strong>Methods: </strong>This study enrolled 50 patients with stage I non-small cell lung cancer who were treated with MWA. Corresponding CT images were collected before and after the MWA, and radiomics features were extracted using the 3D-slicer software platform. In the study, statistical analyses were performed using R studio software. Firstly, radiomics features related to local tumor progression (LTP) at 6 months were screened from the pre-MWA and immediate post-MWA CT radiomics features by the max-relevance and min-redundancy features. This study aimed to evaluate its therapeutic effect by developing multimodal models that integrate CT radiomics features and simple clinical characteristics. Based on the selected radiomics features, prediction models for 6-month LTP were constructed. These models' performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC).</p><p><strong>Results: </strong>Three pre-MWA CT radiomics features and three post-MWA CT radiomics features were confirmed to be correlated with the LTP. For the ROC curves that only covered the pre-MWA CT radiomics, AUC was 0.689. For the ROC curves integrating the pre-MWA CT radiomics plus simple clinical characteristics, AUC was 0.849. For the ROC curves that only covered the immediate post-MWA CT radiomics features, AUC was 0.849. For the ROC curves integrating the immediate post-MWA CT features plus simple clinical characteristics, AUC was 0.907.</p><p><strong>Conclusion: </strong>This exploratory preliminary analysis revealed that the predictive model integrating immediate post-microwave-ablation CT radiomic features and clinical indicators yields superior prognostic performance relative to the model constructed solely from preoperative CT radiomic features.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"124658"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621293/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081355","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 multimodal MRI habitat-based deep learning fusion model for predicting ²⁵²Cf neutron therapy response in cervical cancer.","authors":"Shu-Peng Wang, Zhi-Guo Chen, Xi-Jing Shan, Miao Jin, Wei Zhao, Xu Tong, Xin Meng","doi":"10.4329/wjr.123597","DOIUrl":"10.4329/wjr.123597","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cervical cancer remains one of the leading causes of cancer-related mortality among women worldwide. Although californium-252 (&lt;sup&gt;252&lt;/sup&gt;Cf) neutron brachytherapy has demonstrated favorable therapeutic efficacy for locally advanced cervical cancer, substantial inter-patient heterogeneity in treatment response still exists. Therefore, developing a reliable non-invasive predictive model before treatment is of considerable clinical importance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Aim: &lt;/strong&gt;To develop and validate a predictive model that integrates multiparametric magnetic resonance imaging (MRI) habitat atlas, radiomics, and deep learning features for the non-invasive and accurate prediction of treatment efficacy in cervical cancer patients receiving &lt;sup&gt;252&lt;/sup&gt;Cf neutron intracavitary brachytherapy combined with external beam radiotherapy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 100 cervical cancer patients who underwent the aforementioned treatment at our institution from January 2020 to June 2025 were retrospectively enrolled. All patients underwent pretreatment multi-sequence MRI scans [T1-weighted imaging, T2-weighted imaging, dynamic contrast enhanced (DCE)-MRI, and diffusion weighted imaging (DWI)]. Based on DCE-MRI and DWI parameter maps, a &lt;i&gt;k&lt;/i&gt;-means clustering algorithm was employed to delineate the tumor habitat atlas, partitioning the tumor into three functional subregions (H1: High vascularity/high cellularity; H2: Low vascularity/high cellularity; H3: Low vascularity/low cellularity). Radiomics features were extracted from both the whole tumor region and each habitat subregion, while deep learning features were extracted using a pre-trained ResNet50 network. The aforementioned features, along with clinical-dosimetric parameters, were fused. Following feature selection &lt;i&gt;via&lt;/i&gt; the least absolute shrinkage and selection operator, a fusion prediction model was constructed using a support vector machine. The dataset was split into a training set (&lt;i&gt;n&lt;/i&gt; = 70) and a validation set (&lt;i&gt;n&lt;/i&gt; = 30) at a 7:3 ratio for model evaluation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Habitat analysis successfully identified three types of functional subregions, whose distribution was significantly associated with tumor heterogeneity. The fusion model (Model-Fusion) achieved an area under curve (AUC) of 0.892 (95% confidence interval: 0.821-0.963) and an accuracy of 0.867 in the validation set, significantly outperforming the model based solely on clinical features (AUC = 0.712), the whole-tumor radiomics model (AUC = 0.783), and the radiomics combined with deep learning model (AUC = 0.835) (all &lt;i&gt;P&lt;/i&gt; &lt; 0.05). Decision curve analysis demonstrated that the fusion model provided the highest clinical net benefit. The 3-year overall survival rate was significantly higher in the model-predicted high-benefit group (92.5%) compared to the low-benefit group (71.4%, &lt;i&gt;P&lt;/i&gt; = 0.003).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study integ","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"123597"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081294","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":"Letter to the Editor: Reconsidering relevance of endoscopic ultrasound-guided radiofrequency ablation in pancreatic cancer treatment: Future perspectives on artificial intelligence.","authors":"Avinash D Gautam, Hira Lal","doi":"10.4329/wjr.124226","DOIUrl":"10.4329/wjr.124226","url":null,"abstract":"<p><p>Despite advances in curative and technological approaches, pancreatic cancer (PC) remains a major global health challenge. In the majority of cases, PC is diagnosed at an advanced stage and/or in patients with significant comorbidities, which limits treatment options, including the feasibility of surgical resection. To address these challenges, endoscopic ultrasound-guided radiofrequency ablation (EUS-RFA) has emerged as a promising approach, although its outcomes remain debatable. Tong <i>et al</i> highlighted the role of EUS-RFA in PC treatment in their recent review. Furthermore, the existing literature lacks sufficient evidence regarding post-treatment outcomes, comparative assessments through multi-arm studies, and survival benefits. The exploration of artificial intelligence may potentially assist in optimizing radiofrequency ablation parameters, reducing operator dependency and inter-operator variability, thereby enhancing the efficacy of EUS-RFA procedures in future hypothetically.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"124226"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081539","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":"High-resolution computed tomography assessment of connective tissue disease-associated interstitial lung disease: Advances in diagnosis and prognostic evaluation.","authors":"Si-Yu Jiang, Kai-Xiang Su, Cai-Feng Pang, Yu-Qing Tang, Yu-Jie Xiang, Ju Han, Yong-Long He, Rui Li","doi":"10.4329/wjr.125041","DOIUrl":"10.4329/wjr.125041","url":null,"abstract":"<p><p>Connective tissue disease-associated interstitial lung disease (CTD-ILD), an important pulmonary manifestation of systemic autoimmune diseases and a major determinant of morbidity and mortality, is highly heterogeneous across disease subtypes, requiring reliable imaging assessment. High-resolution computed tomography (HRCT) remains the cornerstone imaging modality in this setting. This narrative review summarizes recent advances in HRCT-based assessment of CTD-ILD, based on a structured literature search of PubMed/MEDLINE, EMBASE, and Web of Science through May 31, 2026, with emphasis on diagnosis, prognostic assessment, and longitudinal monitoring. Conventional visual interpretation and semiquantitative scoring remain the established foundation of clinical assessment. Quantitative computed tomography provides an emerging objective adjunct but remains variably implemented across centers, whereas radiomics, machine learning, and deep learning offer promising capabilities for automated segmentation, high-dimensional phenotyping, pattern classification, and individualized risk prediction but remain predominantly investigational. Current evidence supports a layered imaging framework in which conventional and advanced approaches are complementary rather than competing; however, the maturity and strength of evidence vary substantially across CTD subtypes and clinical applications. Relatively more evidence is available for systemic sclerosis-associated ILD, rheumatoid arthritis-associated ILD, and inflammatory myopathy-associated ILD, whereas evidence for Sjögren syndrome-associated ILD and systemic lupus erythematosus-associated ILD remains comparatively limited. Future research should prioritize standardized imaging workflows, reproducibility, harmonized endpoints, prospective multicenter validation, and demonstration of clinical utility before broader implementation of advanced HRCT-derived biomarkers.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"125041"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621298/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081287","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":"Comparing the reliability of three software programmes for manual and (semi-)automatic volumetry in healthy livers.","authors":"Ariadne L van der Velden, Robrecht R M M Knapen, Sinéad James, Hossein Rahmani, Ralph Brecheisen, Sander M J van Kuijk, Joachim E Wildberger, Ronald M van Dam, Christiaan van der Leij","doi":"10.4329/wjr.123720","DOIUrl":"10.4329/wjr.123720","url":null,"abstract":"<p><strong>Background: </strong>Multiple software programs are available for manual or (semi-)automated liver segmentation. Although manual segmentation has traditionally been the standard, it is time-intensive and susceptible to inter-observer variability. Conversely, (semi-)automated approaches have been shown to reduce segmentation time, but the availability and use of different software tools can introduce variability in liver volumetry outcomes.</p><p><strong>Aim: </strong>To evaluate the reliability of three segmentation software programs (Synapse 3D (Fujifilm), OsiriX^® (Pixmea), and Syngo.via (Siemens Healthineers)) for liver volumetry.</p><p><strong>Methods: </strong>Patients (≥ 18 years) with abdominal computed tomography images without liver pathology were included. Total liver volume (TLV) and segment II/III volume - a surrogate for the future liver remnant (FLR) - were measured. Two blinded independent researchers performed volumetric assessments. The intraclass correlation coefficient (ICC) was calculated for interobserver variability for the first 30 scans between both researchers. This was also performed for intra-observer variability between the software programs in 200 randomly selected patients (52.5% male; mean age: 63.5 years).</p><p><strong>Results: </strong>Mean TLV's reported by Synapse 3D, Syngo.via and OsiriX^® were 1705 ± 462 mL, 1672 ± 463 mL, and 1627 ± 449 mL, respectively. Mean segment II/III volumes reported were 304 ± 115 mL, 282 ± 109 mL, and 277 ± 108 mL, respectively. The highest interobserver agreement (<i>n</i> = 30) was for TLV with Synapse 3D (ICC: 0.999; 95%CI: 0.998-0.999), and highest intraobserver ICC was between Synapse 3D and Syngo.via for TLV (ICC: 0.997; 95%CI: 0.985-0.999). Mean standardized FLR for Synapse 3D, Syngo.via and OsiriX^® were 18.6%, 17.2%, and 16.9%, respectively.</p><p><strong>Conclusion: </strong>Although absolute volumes varied slightly, the standardized FLR remained comparable across the software programs, indicating that all three are suitable for reliable computed tomography liver volumetry.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"123720"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149081229","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":"Amiodarone-induced liver injury with bright liver sign: A case report.","authors":"Zheng-Qing Shen, Xiao-Xiao Xia, Die-Wen Dong, Xian-Feng Zhang, Nan-Jing Shi","doi":"10.4329/wjr.125365","DOIUrl":"10.4329/wjr.125365","url":null,"abstract":"<p><strong>Background: </strong>Amiodarone is an antiarrhythmic drug with well-recognized hepatotoxicity; however, its radiologic appearance mimicking hepatic iron deposition has been rarely reported. We describe a case in which the initial imaging findings were misinterpreted as hemochromatosis, whereas the final diagnosis was amiodarone-induced liver injury (AILI).</p><p><strong>Case summary: </strong>An 85-year-old woman received oral amiodarone hydrochloride for 5 months for the treatment of atrial fibrillation and subsequently developed recurrent nausea, vomiting, and progressive elevation of liver enzymes. Given the well-documented medication history and a Roussel Uclaf Causality Assessment Method score of 8, AILI secondary to intrahepatic drug deposition was clinically suspected. Non-contrast chest computed tomography (CT) demonstrated diffusely increased hepatic attenuation, and hemochromatosis was initially diagnosed on imaging. However, abdominal magnetic resonance imaging (MRI) revealed mildly decreased hepatic signal intensity on T2-weighted imaging without other characteristic features of iron overload, and iron studies were within normal limits. AILI was subsequently diagnosed. Following discontinuation of amiodarone, the patient's gastrointestinal symptoms resolved, and liver enzyme levels gradually returned to baseline.</p><p><strong>Conclusion: </strong>Amiodarone deposition within the liver can result in hepatic injury accompanied by diffuse hepatic hyperattenuation on CT, mimicking other conditions associated with increased liver attenuation. MRI plays a crucial role in differential diagnosis. By combining this case with a review of the relevant literature, we summarize the characteristic imaging features of AILI to facilitate its diagnosis and management.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 9","pages":"125365"},"PeriodicalIF":1.2,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149082221","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":"Letter to the Editor: De-escalation of branch duct intraductal papillary mucinous neoplasms surveillance.","authors":"Cesare Maino, Riccardo Inchingolo","doi":"10.4329/wjr.123527","DOIUrl":"10.4329/wjr.123527","url":null,"abstract":"<p><p>We comment on the recent observational study by Hopley <i>et al</i> reporting outcomes of 17-year branch duct intraductal papillary mucinous neoplasm surveillance and proposing de-escalation criteria based on cyst stability below 30 mm and serum carbohydrate antigen 19-9 below 43 KU/L after two years of follow-up. While acknowledging the clinical value of these findings, we raise several radiological concerns that deserve further consideration before these criteria can be safely implemented across institutions. Specifically, we discuss the absence of standardised imaging protocols and field strength reporting, the well-documented inter-observer variability in magnetic resonance imaging (MRI)-based cyst size measurement, the evolving radiological definitions of worrisome and high-risk features across guidelines updates, the complementary roles of MRI/ magnetic resonance cholangiopancreatography and endoscopic ultrasound, and the lack of a specified imaging algorithm for the de-escalated surveillance phase. These considerations are intended to help refine the safe implementation of the proposed de-escalation strategy rather than to argue against it.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 8","pages":"123527"},"PeriodicalIF":1.2,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527543/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866094","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":"Imaging-guided adaptive radiation therapy in limited-stage small cell lung cancer: Current evidence and clinical perspectives.","authors":"Omer Sager","doi":"10.4329/wjr.124830","DOIUrl":"10.4329/wjr.124830","url":null,"abstract":"<p><p>Small cell lung cancer (SCLC) remains among the most aggressive thoracic malignancies and continues to present major therapeutic challenges despite advances in multimodality treatment. Limited-stage SCLC (LS-SCLC), representing approximately one-third of cases, is conventionally managed with concurrent chemoradiotherapy delivered with curative intent. Radiation therapy (RT) is central to treatment; however, rapid treatment related anatomical and volumetric changes may alter target geometry and reduce the accuracy of plans generated from baseline imaging. Adaptive RT (ART) has emerged as an imaging-guided strategy that enables treatment modification according to evolving anatomy during RT delivery. This narrative review examines the rationale and current evidence supporting imaging-guided ART in LS-SCLC, with emphasis on imaging-informed decision-making and contemporary implementation considerations. LS-SCLC represents a biologically compelling setting for adaptive treatment because of its rapid treatment responsiveness; however, important uncertainties remain regarding patient selection, imaging schedules, adaptive triggers, and workflow standardization. Prospective studies incorporating standardized adaptive workflows and clinically meaningful endpoints are required to determine whether observed dosimetric advantages translate into measurable clinical benefit.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 8","pages":"124830"},"PeriodicalIF":1.2,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866018","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":"Radiomics and anaesthetic planning: Quantitative imaging as a new frontier in preoperative risk assessment.","authors":"Prateek Maurya, Prashant Sirohiya, Manisha Sahoo, Sidharth Puri, Brajesh Kumar Ratre, Ram Singh, Balbir Kumar","doi":"10.4329/wjr.121065","DOIUrl":"10.4329/wjr.121065","url":null,"abstract":"<p><p>Radiomics-the high-throughput extraction of quantitative features from standard medical images-has transformed oncologic imaging by revealing subvisual patterns linked to tissue biology, yet its role in perioperative medicine remains largely unexplored. This narrative review summarises current evidence linking imaging-derived radiomic biomarkers to perioperative outcomes and proposes a conceptual framework for integrating radiomics into precision anaesthesia. Quantitative assessment of body composition, organ function, and vascular morphology from routine preoperative computed tomography and magnetic resonance imaging can provide objective indicators of physiologic reserve, drug-handling capacity, and recovery potential. Across heterogeneous, largely oncological cohorts, combined radiomic-clinical models have reported higher discrimination (area under the curve 0.84-0.93) than conventional risk scores for selected postoperative complications, and artificial intelligence-based airway assessment has shown sensitivity and specificity exceeding traditional bedside tests; these figures are pooled from methodologically diverse studies rather than single validated estimates. The Image Biomarker Standardisation Initiative has substantially reduced cross-platform feature variability. However, perioperative-specific, prospectively validated evidence remains scarce. Prospective multicentre trials, standardized and automated feature-extraction pipelines, transparent cost and equity appraisal, and integration with electronic health records are critical priorities before radiomics-driven preoperative assessment can enter routine anaesthetic practice.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 8","pages":"121065"},"PeriodicalIF":1.2,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866097","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":"Dual-energy computed tomography quantification of creeping fat in Crohn's disease: A new radiologic biomarker for transmural disease monitoring.","authors":"Hunter Jack, Mohadese Ahmadzade, Gary Lloyd Horn, Mohammad Ghasemi-Rad","doi":"10.4329/wjr.124486","DOIUrl":"10.4329/wjr.124486","url":null,"abstract":"<p><p>Accurate, noninvasive assessment of disease activity remains one of the central challenges in the management of Crohn's disease (CD). The study by Dong <i>et al</i> in <i>World Journal of Radiology</i> represents a meaningful advance in this effort, demonstrating that dual-energy computed tomography with the material decomposition algorithm can reliably quantify intestinal creeping fat (CrF), a pathological hallmark of CD, and that this measurement correlates robustly with clinical, endoscopic, histological, and molecular indicators of disease activity. Notably, CrF volume tracked not only inflammatory burden and fibrosis, but also the expression of peroxisome proliferator-activated receptor gamma 2 and occludin, implicating CrF in both adipogenesis and intestinal barrier dysfunction. Crucially, CrF remained elevated during clinical remission, underscoring its potential as a more sensitive marker of subclinical disease persistence than conventional activity indices alone. As the field continues to seek non-invasive surrogates for mucosal healing and histological remission, dual-energy computed tomography-based CrF quantification emerges as a promising, clinically accessible tool. With further validation in larger, multicenter cohorts, this approach could meaningfully reshape how we monitor disease activity, evaluate treatment response, and predict disease course in CD.</p>","PeriodicalId":23819,"journal":{"name":"World journal of radiology","volume":"18 8","pages":"124486"},"PeriodicalIF":1.2,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13527542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866036","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}