BMC Medical Imaging最新文献

{"title":"DefaceQA - automated quality assessment of brain MRI defacing software.","authors":"Maryam Khodaei Dolouei, Sina Sadeghi, Toralf Kirsten","doi":"10.1186/s12880-026-02207-4","DOIUrl":"https://doi.org/10.1186/s12880-026-02207-4","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137299","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":"Radiography-based AI decision support for further post-traumatic knee MRI referral in children.","authors":"Nikolaus Stranger, Mario Scherkl, Andreea Ciornei-Hoffman, Christina Flucher, Georg Singer, Franko Hrzic, Georg Mattiassich, Dieter Szolar, Manfred Tillich, Sebastian Tschauner","doi":"10.1186/s12880-026-02185-7","DOIUrl":"https://doi.org/10.1186/s12880-026-02185-7","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137277","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":"Commercial AI platforms improve reproducibility but fail to meet clinical precision thresholds for intracranial aneurysm measurement: implications for serial surveillance.","authors":"Can Yin, Linan Hu, Shengwu Duan, Xiqing Deng","doi":"10.1186/s12880-026-02209-2","DOIUrl":"https://doi.org/10.1186/s12880-026-02209-2","url":null,"abstract":"<p><strong>Background: </strong>Intracranial aneurysm affect 3-7% of the global population, with rupture causing > 80% of non-traumatic subarachnoid hemorrhage and approximately 50% mortality. Clinical management relies on precise measurement of aneurysm neck width and maximum length, where ≥ 1 mm growth signals elevated rupture risk. computed tomography angiography enables non-invasive monitoring but manual measurements suffer from inter-observer variability. Commercial artificial intelligence platforms offer potential improvements, yet their consistency and accuracy versus digital subtraction angiography, the gold standard, are understudied.</p><p><strong>Methods: </strong>This retrospective study analyzed 148 patients with 163 Intracranial aneurysms via computed tomography angiography, including a subgroup of 86 with digital subtraction angiography within 1 week. Measurements were obtained using Shukun artificial intelligence, UIH artificial intelligence, manual computed tomography angiography (intra-observer repeated at 1 month), and digital subtraction angiography. Reproducibility was assessed by coefficient of variation; agreement by Bland-Altman analysis, with 95% limits of agreement within ± 1.0 mm considered clinically acceptable.</p><p><strong>Results: </strong>Results For aneurysm neck width, manual measurements had a mean difference of -1.62 mm and 95% limits of agreement of -4.87 to 1.62 mm vs. digital subtraction angiography, while UIH artificial intelligence and Shukun artificial intelligence had mean differences of + 0.80 mm and - 1.01 mm, and 95% limits of agreement of -3.68 to 2.08 mm and - 3.06 to 1.04 mm, respectively. For aneurysm maximum length, UIH artificial intelligence systematically overestimated (mean difference: +3.46 mm) and Shukun artificial intelligence underestimated (mean difference: -2.20 mm) vs. digital subtraction angiography. Both artificial intelligence platforms had narrower coefficients of variation (0.31-0.36 for aneurysm neck width, 0.23-0.26 for aneurysm maximum length) than manual measurements (0.36-0.42, 0.23-0.24). However, all methods exceeded the clinically acceptable ± 1.0 mm threshold.</p><p><strong>Conclusions: </strong>Artificial intelligence platforms have better reproducibility than manual measurements but show systematic biases, not meeting the clinical ± 1.0 mm precision vs. the digital subtraction angiography gold standard. Inter-platform variability exceeds the aneurysm growth threshold, requiring consistent use of the same artificial intelligence platform in serial surveillance to prevent misinterpreting changes.</p>","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146137254","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":"ICG combined with medical adhesive in preoperative localization of complex pulmonary nodules: a retrospective study.","authors":"Wenhao Wang, Yulong Tan, Dong Xu, Haoxin Liu, Yifeng Qian, Huijun Zhang, Meng Shi, Xiaofeng Chen","doi":"10.1186/s12880-026-02183-9","DOIUrl":"https://doi.org/10.1186/s12880-026-02183-9","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146130970","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":"Study protocol for neuroimaging using 7 T MRI in the investigation of baricitinib for reduction of HIV in the CNS: a randomized placebo-controlled trial.","authors":"Candace C Fleischer, Kaundinya Gopinath, Eva Martinez Luque, Lei Zhou, Howard L Pope, Ryan B Peterson, Alicarmen Alvarez, Julianna L McNeice, Minh L Nguyen, Taylor B Harrison, David W Loring, Kirk A Easley, Christina Gavegnano, Vincent C Marconi, Albert M L Anderson, William Tyor","doi":"10.1186/s12880-026-02202-9","DOIUrl":"https://doi.org/10.1186/s12880-026-02202-9","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146130982","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":"UMUD: a web application for easy access to musculoskeletal ultrasonography datasets.","authors":"Paul Ritsche, Fabio Sarto, Francesco Santini, Christoph Leitner, Martino V Franchi, Oliver Faude, Taija Finni, Olivier Seynnes, Neil Cronin","doi":"10.1186/s12880-026-02170-0","DOIUrl":"https://doi.org/10.1186/s12880-026-02170-0","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146130979","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":"Fusion of deep learning and radiomics with dynamic spatiotemporal modeling for non-small cell lung cancer recurrence risk assessment after microwave ablation.","authors":"Meng Li, Yongzhao Li, Xiangming Wang, Hui Feng, Yang Li, Ying Zhang, Gaofeng Shi","doi":"10.1186/s12880-026-02179-5","DOIUrl":"https://doi.org/10.1186/s12880-026-02179-5","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146123651","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":"Validation of an AI model for pediatric myelin maturation age assessment and benefits for junior radiologists.","authors":"Qiaoqiao Zou, Kexin Wang, Yaofeng Zhang, Zuqiang Xi, Zijian Cai, Xincheng Li, Xiaoying Wang","doi":"10.1186/s12880-026-02198-2","DOIUrl":"https://doi.org/10.1186/s12880-026-02198-2","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146117781","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":"Diffusion kurtosis imaging for detecting renal functional changes in glomerulonephritis: a longitudinal experimental study.","authors":"Jian Liu, Yu Wu, Daoyu Yang, Xunlan Zhang, Rongpin Wang, Xianchun Zeng","doi":"10.1186/s12880-026-02197-3","DOIUrl":"https://doi.org/10.1186/s12880-026-02197-3","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146117756","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":"Noninvasive preoperative prediction of perineural invasion in intrahepatic cholangiocarcinoma based on dynamic contrast-enhanced MRI.","authors":"Sisi Zhang, Yayuan Feng, Da He, Yuxian Wu, Ningyang Jia, Xingpeng Pan, Yiping Liu","doi":"10.1186/s12880-026-02188-4","DOIUrl":"https://doi.org/10.1186/s12880-026-02188-4","url":null,"abstract":"","PeriodicalId":9020,"journal":{"name":"BMC Medical Imaging","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146117806","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}