{"title":"超声放射组学模型鉴别宫颈结核性淋巴结炎与颈淋巴结转移的临床应用。","authors":"Xiangyu Meng, Hongxiang Fu, Ying Wang, Ying Zhang, Peijun Chen, Litao Sun, Gaoyi Yang","doi":"10.1177/13860291251364588","DOIUrl":null,"url":null,"abstract":"<p><p>ObjectiveCervical tuberculous lymphadenitis (CTBL) and cervical lymph node metastasis (CLNM) share similar imaging characteristics, making differentiation challenging. This study aims to evaluate the clinical utility of a multimodal radiomics model combining grayscale ultrasound (GUS), elastography ultrasound (EUS), and contrast-enhanced ultrasound (CEUS) for distinguishing CTBL from CLNM.MethodsA high-quality dataset comprising 203 cases of CTBL was used to train and test the radiomics models. The performance of single-modal (GUS, EUS, CEUS) and combined models was compared using AUC, sensitivity, specificity, and accuracy metrics. An independent test set of 45 cases was included for validation.ResultsThe combined GUS + EUS + CEUS model outperformed single-modal models, achieving AUCs of 0.894, 0.832, and 0.919 in the training, validation, and test sets, respectively. Its diagnostic performance was comparable to a clinical model in validation and test sets, demonstrating superior generalizability and robustness. Wavelet features accounted for all selected features, enhancing the model's discrimination ability.ConclusionsThe integration of three ultrasound modalities captures multidimensional imaging features, reducing reliance on subjective interpretation. This multimodal radiomics approach provides a standardized diagnostic tool with significant clinical potential, particularly for less experienced physicians. Further validation with diverse datasets is needed to confirm its utility.</p>","PeriodicalId":93943,"journal":{"name":"Clinical hemorheology and microcirculation","volume":" ","pages":"13860291251364588"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clinical utility of ultrasound radiomics models in differentiating cervical tuberculous lymphadenitis from cervical lymph node metastasis.\",\"authors\":\"Xiangyu Meng, Hongxiang Fu, Ying Wang, Ying Zhang, Peijun Chen, Litao Sun, Gaoyi Yang\",\"doi\":\"10.1177/13860291251364588\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>ObjectiveCervical tuberculous lymphadenitis (CTBL) and cervical lymph node metastasis (CLNM) share similar imaging characteristics, making differentiation challenging. This study aims to evaluate the clinical utility of a multimodal radiomics model combining grayscale ultrasound (GUS), elastography ultrasound (EUS), and contrast-enhanced ultrasound (CEUS) for distinguishing CTBL from CLNM.MethodsA high-quality dataset comprising 203 cases of CTBL was used to train and test the radiomics models. The performance of single-modal (GUS, EUS, CEUS) and combined models was compared using AUC, sensitivity, specificity, and accuracy metrics. An independent test set of 45 cases was included for validation.ResultsThe combined GUS + EUS + CEUS model outperformed single-modal models, achieving AUCs of 0.894, 0.832, and 0.919 in the training, validation, and test sets, respectively. Its diagnostic performance was comparable to a clinical model in validation and test sets, demonstrating superior generalizability and robustness. Wavelet features accounted for all selected features, enhancing the model's discrimination ability.ConclusionsThe integration of three ultrasound modalities captures multidimensional imaging features, reducing reliance on subjective interpretation. This multimodal radiomics approach provides a standardized diagnostic tool with significant clinical potential, particularly for less experienced physicians. Further validation with diverse datasets is needed to confirm its utility.</p>\",\"PeriodicalId\":93943,\"journal\":{\"name\":\"Clinical hemorheology and microcirculation\",\"volume\":\" \",\"pages\":\"13860291251364588\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical hemorheology and microcirculation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/13860291251364588\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical hemorheology and microcirculation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/13860291251364588","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
目的宫颈结核性淋巴结炎(CTBL)与宫颈淋巴结转移(CLNM)具有相似的影像学特征,使其鉴别具有挑战性。本研究旨在评估结合灰度超声(GUS)、弹性超声(EUS)和对比增强超声(CEUS)的多模态放射组学模型在鉴别CTBL和CLNM方面的临床应用。方法采用203例CTBL患者的高质量数据集对放射组学模型进行训练和检验。使用AUC、敏感性、特异性和准确性指标比较单模态(GUS、EUS、CEUS)和组合模型的性能。采用45例独立试验集进行验证。结果GUS + EUS + CEUS联合模型优于单模态模型,在训练集、验证集和测试集的auc分别为0.894、0.832和0.919。在验证和测试集中,其诊断性能与临床模型相当,显示出优越的通用性和稳健性。小波特征占了所有选择的特征,增强了模型的识别能力。结论三种超声模式的整合捕获了多维成像特征,减少了对主观解释的依赖。这种多模式放射组学方法提供了一种具有重要临床潜力的标准化诊断工具,特别是对于经验不足的医生。需要用不同的数据集进一步验证以确认其实用性。
Clinical utility of ultrasound radiomics models in differentiating cervical tuberculous lymphadenitis from cervical lymph node metastasis.
ObjectiveCervical tuberculous lymphadenitis (CTBL) and cervical lymph node metastasis (CLNM) share similar imaging characteristics, making differentiation challenging. This study aims to evaluate the clinical utility of a multimodal radiomics model combining grayscale ultrasound (GUS), elastography ultrasound (EUS), and contrast-enhanced ultrasound (CEUS) for distinguishing CTBL from CLNM.MethodsA high-quality dataset comprising 203 cases of CTBL was used to train and test the radiomics models. The performance of single-modal (GUS, EUS, CEUS) and combined models was compared using AUC, sensitivity, specificity, and accuracy metrics. An independent test set of 45 cases was included for validation.ResultsThe combined GUS + EUS + CEUS model outperformed single-modal models, achieving AUCs of 0.894, 0.832, and 0.919 in the training, validation, and test sets, respectively. Its diagnostic performance was comparable to a clinical model in validation and test sets, demonstrating superior generalizability and robustness. Wavelet features accounted for all selected features, enhancing the model's discrimination ability.ConclusionsThe integration of three ultrasound modalities captures multidimensional imaging features, reducing reliance on subjective interpretation. This multimodal radiomics approach provides a standardized diagnostic tool with significant clinical potential, particularly for less experienced physicians. Further validation with diverse datasets is needed to confirm its utility.