Academic Radiology最新文献

{"title":"Radiology's Surprising Role in the Soviet Resistance: Bone Music.","authors":"Wyatt D Reed, Molly Beatty, Richard B Gunderman","doi":"10.1016/j.acra.2025.04.050","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.050","url":null,"abstract":"","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144133240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unraveling Rescue Thrombectomy for Mild Large Vessel Occlusion Stroke Following Medical Management: Insights From a Multicenter Retrospective Study.","authors":"Hu Huang, Chunjie Song, Yuanyuan Han","doi":"10.1016/j.acra.2025.04.074","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.074","url":null,"abstract":"<p><strong>Background: </strong>Although rescue thrombectomy is performed in mild (National Institutes of Health Stroke Scale ≤ 5) large vessel occlusion (LVO) stroke patients who experience early neurological deterioration (END) following best medical management (BMM), clinical outcomes remain highly variable. This study aimed to identify key determinants influencing outcomes in this population.</p><p><strong>Methods: </strong>We retrospectively analyzed consecutive mild LVO patients who initially received BMM and later underwent rescue thrombectomy for END, across four centers between January 2019 and June 2024. END was defined as an NIHSS increase of ≥ 4 points or a total score of ≥ 6 within the first 24 h, without hemorrhage. Multivariable logistic regression was performed to identify factors associated with outcomes. Receiver operating characteristic curve analysis was performed to assess the predictive performance using the area under the curve (AUC).</p><p><strong>Results: </strong>Among 347 patients with mild LVO who underwent BMM, 66 patients who developed END and underwent rescue thrombectomy were included in this study. Of these, 31 (47.0%) achieved poor outcome (90-day modified Rankin Scale score of 3-6). Multivariable analysis identified prolonged deterioration-to-groin puncture time (OR: 1.79 per 10-minute increase, 95% CI: 1.48-2.54) and basilar artery occlusion (OR: 1.42, 95% CI: 1.16-2.08) were independently associated with poor outcomes. The AUC for predicting poor outcomes was 0.828 for deterioration-to-groin puncture time, 0.690 for basilar artery occlusion, and 0.906 for their combination.</p><p><strong>Conclusion: </strong>Delayed initiation of thrombectomy and basilar artery occlusion were predictors for poor outcomes in patients who underwent rescue thrombectomy after BMM.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Ultrasound-Based Deep Learning Radiomics Nomogram for Tumor and Axillary Lymph Node Status Prediction After Neoadjuvant Chemotherapy\" [Academic Radiology 32 (2025) 12-23].","authors":"Yue-Xia Liu, Qing-Hua Liu, Quan-Hui Hu, Jia-Yao Shi, Gui-Lian Liu, Han Liu, Sheng-Chun Shu","doi":"10.1016/j.acra.2025.05.010","DOIUrl":"https://doi.org/10.1016/j.acra.2025.05.010","url":null,"abstract":"","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Right Ventricular Strain as a Key Feature in Interpretable Machine Learning for Identification of Takotsubo Syndrome: A Multicenter CMR-based Study.","authors":"Zeliu Du, Hongfei Hu, Chenqi Shen, Jie Mei, Ye Feng, Yechao Huang, Xinyu Chen, Xinyu Guo, Zhanning Hu, Liyan Jiang, Yanping Su, Jumatay Biekan, Lingchun Lyv, TouKun Chong, Cunxue Pan, Kan Liu, Jiansong Ji, Chenying Lu","doi":"10.1016/j.acra.2025.04.068","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.068","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To develop an interpretable machine learning (ML) model based on cardiac magnetic resonance (CMR) multimodal parameters and clinical data to discriminate Takotsubo syndrome (TTS), acute myocardial infarction (AMI), and acute myocarditis (AM), and to further assess the diagnostic value of right ventricular (RV) strain in TTS.</p><p><strong>Materials and methods: </strong>This study analyzed CMR and clinical data of 130 patients from three centers. Key features were selected using least absolute shrinkage and selection operator regression and random forest. Data were split into a training cohort and an internal testing cohort (ITC) in the ratio 7:3, with overfitting avoided using leave-one-out cross-validation and bootstrap methods. Nine ML models were evaluated using standard performance metrics, with Shapley additive explanations (SHAP) analysis used for model interpretation.</p><p><strong>Results: </strong>A total of 11 key features were identified. The extreme gradient boosting model showed the best performance, with an area under the curve (AUC) value of 0.94 (95% CI: 0.85-0.97) in the ITC. Right ventricular basal circumferential strain (RVCS-basal) was the most important feature for identifying TTS. Its absolute value was significantly higher in TTS patients than in AMI and AM patients (-9.93%, -5.21%, and -6.18%, respectively, p < 0.001), with values above -6.55% contributing to a diagnosis of TTS.</p><p><strong>Conclusion: </strong>This study developed an interpretable ternary classification ML model for identifying TTS and used SHAP analysis to elucidate the significant value of RVCS-basal in TTS diagnosis. An online calculator (https://lsszxyy.shinyapps.io/XGboost/) based on this model was developed to provide immediate decision support for clinical use.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum Carotenoid Concentrations Are Associated with Enlarged Choroid Plexus, Lateral Ventricular Volume, and Perivascular Spaces on Magnetic Resonance Imaging: A Large Cohort Study.","authors":"Jusei Kudo, Keita Watanabe, Miho Sasaki, Tomohiro Shintaku, Shinya Kakehata, Sera Kasai, Kana Saito, Tatsuya Mikami, Daichi Kokubu, Yusuke Ushida, Masashi Matsuzaka, Shingo Kakeda","doi":"10.1016/j.acra.2025.04.048","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.048","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>Since carotenoids have various physiological activities, including antioxidant activity, several epidemiological studies have linked the consumption of a carotenoid-rich diet to a decreased risk of neurodegenerative diseases. Increased choroid plexus volume (CPV) and enlarged perivascular spaces (PVS) on brain magnetic resonance imaging (MRI) may be indicators of impaired glymphatic system function. The purpose of this large-scale elderly population study was to assess whether serum concentrations of major carotenoids (α-carotene, β-carotene, cis-lycopene, trans-lycopene, β-cryptoxanthin, zeaxanthin, and lutein) concentrations are associated with CPV, lateral ventricular volume (LVV), and PVS.</p><p><strong>Materials and methods: </strong>This cross-sectional study included 2050 individuals (median age, 69 years; 61.02% females) who underwent 3 T MRI. The imaging characteristics included total intracranial volume (ICV), CPV, LVV, and basal ganglia-enlarged PVS on T2-weighted images.</p><p><strong>Results: </strong>Low serum β-carotene concentration was a significant independent predictor of increased CPV/ICV (p=0.046), increased LVV/ICV (p=0.035), and enlarged PVS (p=0.009) after adjusting for potential confounders (age, sex, body mass index, HbA1c level, systolic blood pressure, smoking history, drinking history, educational history, and Mini-Mental State Examination score, CRP level). Low serum α-carotene concentration was also a significant independent predictor of an enlarged PVS (p=0.014).</p><p><strong>Conclusion: </strong>In this study, β-carotene concentration was associated to the CPV, LVV, and PVS, suggesting that the antioxidant activity of β-carotene may have an important role in maintaining glymphatic system function. Since β-carotene is a dietary carotenoid, our results emphasize the importance of interventions for effective β-carotene intake among elderly people.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144120702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of Muscle and Fat Measurements Between True Noncontrast and Virtual Noncontrast Images From Three Phases of Dual-Energy Dynamic Liver CT.","authors":"Sheen-Woo Lee, Moon Hyung Choi, Young Joon Lee, Maria Choi","doi":"10.1016/j.acra.2025.04.063","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.063","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To determine whether virtual noncontrast (VNC) images derived from three-phase dynamic dual-energy CT (DECT) imaging can reliably substitute true noncontrast (TNC) images in assessing muscle and fat with automatic segmentation software.</p><p><strong>Materials and methods: </strong>The data from 476 dynamic liver DECT examinations performed between April 2019 and December 2020 were retrospectively analyzed. VNC images were generated from arterial (VNC_a), portal-venous (VNC_p), and delayed (VNC_d) phase images. Automated software measured muscle, visceral fat (VF), and subcutaneous fat (SF) areas. Sarcopenia was defined using muscle-related indices. Differences in muscle and fat measurements, as well as sarcopenia prevalence, between TNC and VNC images were assessed using paired t tests and McNemar tests, respectively.</p><p><strong>Results: </strong>The average age of the 476 patients (307 men) was 58.4±12.5years. Muscle density and area differed significantly between the TNC and VNC images; TNC images showed higher mean muscle density and smaller skeletal muscle area (SMA) than all VNC images (P<0.001). VF and SF attenuations were significantly lower on TNC images than on all VNC images (P<0.001). The proportions of sarcopenic patients did not differ significantly between TNC and VNCp or VNCd, regardless of the muscle index used.</p><p><strong>Conclusion: </strong>Despite significant differences in muscle and fat attenuations between TNC and VNC images, VNC_p and VNC_d may be acceptable alternatives for measuring muscle and fat areas. However, TNC and VNC images should not be used interchangeably for assessing tissue attenuation or specific muscle components such as LAMA or NAMA.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound-Based Prediction Model for Distinguishing Malignant from Benign Thyroid Nodules with Peripheral Calcification.","authors":"Song Bai, Linghu Wu, Youhuan Su, Jinfeng Xu, Fajin Dong","doi":"10.1016/j.acra.2025.04.073","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.073","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>The differential diagnosis of thyroid nodules with peripheral calcifications by ultrasound (US) has always been source of confusion. This study aimed to develop and validate a predictive US-based nomogram model to differentiate malignant from benign nodules with peripheral calcifications.</p><p><strong>Methods: </strong>Of the 8359 thyroid nodules scanned by ultrasonography between January 2017 and January 2025, 380 nodules with peripheral calcifications were included, with confirmed pathological results and US examinations. 268 nodules were included in the training cohort, and 112 nodules were included in the validation cohort. The candidate variables included age, gender, and the image features obtained from grayscale US. Independent risk factors for malignant thyroid nodules were determined by univariate and multivariate analyses, and a predictive nomogram model was developed. The performance of the US nomogram was assessed by the area under the curve (AUC), calibration curve, and decision curve analysis (DCA) results.</p><p><strong>Results: </strong>Univariate and multivariate logistic regression analyses revealed that the halo sign, extrusion beyond calcification, type of peripheral calcification, margin, internal echogenicity, and composition were significant independent predictors for malignant thyroid nodules with peripheral calcifications. The nomogram model based on the six variables exhibited excellent calibration and discrimination in the training and validation cohorts, with AUC values of 0.904 and 0.882, respectively. The DCA showed that a probability threshold of 0.11-0.83 could benefit patients clinically.</p><p><strong>Conclusion: </strong>The US-based nomogram model can potentially predict the malignant risk of thyroid nodules with peripheral calcifications, thereby helping to enhance diagnostic accuracy.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Liver Fibrosis with Multisample Point Shear Wave Elastography in Obese Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease.","authors":"Meng Sun, Mingwei Zhong, Fangqiong Luo, Meng Lan, Xinru Zhang, Zhe Ma","doi":"10.1016/j.acra.2025.04.070","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.070","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To evaluate the diagnostic performance of multisample point shear wave elastography (pSWE) for liver fibrosis in obese patients with metabolic dysfunction-associated steatotic liver disease (MASLD) using liver biopsy as the reference standard and to compare it with the FIB-4 index and aspartate to platelet ratio index (APRI).</p><p><strong>Methods: </strong>Patients with obesity who met the diagnostic criteria for MASLD between April 2023 and December 2024 were selected for this retrospective single-centre study. Liver stiffness measurements were reported as median values of measurements, and Auto-pSWVs (m/s) were measured using the multisample pSWE technique. The diagnostic performance of auto shear wave velocities (Auto-pSWVs), FIB-4 index and APRI for significant fibrosis (≥F2) and advanced fibrosis (≥F3) of the liver was evaluated and compared using receiver operating characteristic curves with liver biopsy as the criterion. The correlation between Auto-pSWVs and the clinical variables of the subjects was evaluated.</p><p><strong>Results: </strong>Data from 241 patients were analysed. Auto-pSWVs were positively correlated with the pathological diagnosis of liver fibrosis (r=0.34, p<0.001), and the liver fibrosis stage was an independent risk factor for Auto-pSWVs (beta coefficient: 0.42, p< 0.001). In addition, Auto-pSWVs was superior to FIB-4 index and APRI when comparing the diagnostic performance of significant liver fibrosis (≥F 2) and advanced fibrosis (≥F3) (p < 0.05). The AUC of Auto-pSWVs was 0.75 (95% CI 0.66-0.85) and 0.96 (95% CI 0.89-1.0) in the ≥ F2 and ≥ F3 groups, respectively. The cut-off value for Auto-pSWVs were determined as follows: grade F2 ≥ 1.02 m/s; and grade F3 ≥ 1.30 m/s.</p><p><strong>Conclusion: </strong>Multisample pSWE appears to be a valuable tool for the diagnosis of liver fibrosis in obese patients with MASLD.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Deep Learning-Based Grading of Partial-thickness Supraspinatus Tendon Tears with Guided Diffusion Augmentation.","authors":"Ming Ni, Dina Jiesisibieke, Yuqing Zhao, Qizheng Wang, Lixiang Gao, Chunyan Tian, Huishu Yuan","doi":"10.1016/j.acra.2025.04.072","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.072","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>To develop and validate a deep learning system with guided diffusion-based data augmentation for grading partial-thickness supraspinatus tendon (SST) tears and to compare its performance with experienced radiologists, including external validation.</p><p><strong>Methods: </strong>This retrospective study included 1150 patients with arthroscopically confirmed SST tears, divided into a training set (741 patients), validation set (185 patients), and internal test set (185 patients). An independent external test set of 224 patients was used for generalizability assessment. To address data imbalance, MRI images were augmented using a guided diffusion model. A ResNet-34 model was employed for Ellman grading of bursal-sided and articular-sided partial-thickness tears across different MRI sequences (oblique coronal [OCOR], oblique sagittal [OSAG], and combined OCOR+OSAG). Performance was evaluated using AUC and precision-recall curves, and compared to three experienced musculoskeletal (MSK) radiologists. The DeLong test was used to compare performance across different sequence combinations.</p><p><strong>Results: </strong>A total of 26,020 OCOR images and 26,356 OSAG images were generated using the guided diffusion model. For bursal-sided partial-thickness tears in the internal dataset, the model achieved AUCs of 0.99, 0.98, and 0.97 for OCOR, OSAG, and combined sequences, respectively, while for articular-sided tears, AUCs were 0.99, 0.99, and 0.99. The DeLong test showed no significant differences among sequence combinations (P=0.17, 0.14, 0.07). In the external dataset, the combined-sequence model achieved AUCs of 0.99, 0.97, and 0.97 for bursal-sided tears and 0.99, 0.95, and 0.95 for articular-sided tears. Radiologists demonstrated an ICC of 0.99, but their grading performance was significantly lower than the ResNet-34 model (P<0.001). The deep learning system improved grading consistency and significantly reduced evaluation time, while guided diffusion augmentation enhanced model robustness.</p><p><strong>Conclusion: </strong>The proposed deep learning system provides a reliable and efficient method for grading partial-thickness SST tears, achieving radiologist-level accuracy with greater consistency and faster evaluation speed.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thrombus Size Matters: A Risk Assessment Model for Predicting Pulmonary Embolism in Isolated Distal Deep Vein Thrombosis.","authors":"Xi Chen, Xiaoyu Li, Zhifang Yang, Yun Feng, Juan Guo, Fuzhou Yi, Yue Song, Ri Ji","doi":"10.1016/j.acra.2025.04.057","DOIUrl":"https://doi.org/10.1016/j.acra.2025.04.057","url":null,"abstract":"<p><strong>Rationale and objectives: </strong>Isolated distal deep vein thrombosis (IDDVT) is an insidious condition that can lead to pulmonary embolism (PE). This study aimed to develop and validate a risk assessment model based on thrombus size and patient characteristics to predict the risk of concomitant PE in IDDVT patients.</p><p><strong>Methods: </strong>A retrospective analysis of 494 IDDVT patients was conducted, divided into a derivation cohort (n=398) and a validation cohort (n=96). Patients were categorized into PE and non-PE groups based on computed tomography pulmonary angiography (CTPA) results. Clinical, laboratory, and ultrasound data-including thrombus diameter and length-were collected. Independent risk factors for PE were identified using multivariate logistic regression, and a nomogram was developed. Model performance was evaluated through internal and external validation. Additionally, the study compared the diagnostic efficacy of the thrombus size threshold for IDDVT complicating PE with the threshold recommended by the guidelines.</p><p><strong>Results: </strong>Independent predictors of PE in IDDVT patients included thrombus diameter ≥5mm, thrombus length ≥30mm, pulmonary artery pressure >40 mmHg, elevated D-dimer, male sex, and recent surgical history. The model achieved a C-statistic of 0.78 and a Brier score of 0.19. Internal validation confirmed robust discriminative power (C-statistic 0.78, 95% CI 0.73-0.82), while external validation yielded a C-statistic of 0.71 and a Brier score of 0.22. DCA demonstrated a net benefit within a threshold risk range of 12-83%. Compared to previous thrombus size thresholds (7 mm diameter and 50 mm length), the new thresholds (5 mm diameter and 30 mm length) improved discrimination by 11% (95% CI 0.08-0.15, p<0.001) and net reclassification by 52% (95% CI 0.33-0.71, p<0.001).</p><p><strong>Conclusion: </strong>This retrospective study developed a validated risk assessment model using thrombus size indices of ≥5 mm in diameter and ≥30mm in length, alongside clinical factors, to effectively evaluate the risk of concomitant PE in IDDVT patients. This model may offer a valuable tool for individualized risk stratification and clinical decision-making.</p>","PeriodicalId":50928,"journal":{"name":"Academic Radiology","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144112674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}