W. Liu , C. Liu , Y. Yang , Y. Chen , A. Muhetaier , Z. Lin , Z. Weng , X. Wang , P. Zhang , J. Qin
{"title":"将常规磁共振成像(MRI)参数与临床病理数据相结合,对乳腺癌中三层人表皮生长因子受体2 (HER2)状态的分化进行研究","authors":"W. Liu , C. Liu , Y. Yang , Y. Chen , A. Muhetaier , Z. Lin , Z. Weng , X. Wang , P. Zhang , J. Qin","doi":"10.1016/j.crad.2025.106955","DOIUrl":null,"url":null,"abstract":"<div><h3>AIM</h3><div>To assess the three-tiered human epidermal growth factor receptor 2 (HER2) classification of breast cancer (BC) patients based on conventional magnetic resonance imaging (MRI) parameters combined with clinicopathologic data.</div></div><div><h3>MATERIALS AND METHODS</h3><div>211 patients with invasive BC were retrospectively evaluated and divided into the HER2-zero, HER2-low, and HER2-positive BC groups. Patients underwent conventional dynamic contrast-enhanced breast MRI. Radiologists assessed clinicopathologic features and measured the apparent diffusion coefficient (ADC) and haemodynamic parameters to differentiate HER2-zero/-low (n=129) from HER2-positive (n=82) BC (task 1) and then HER2-zero (n=90) from HER2-low (n=57) BC (task 2). Patients were randomly assigned to the training and test sets at a ratio of 7:3. Univariate and multivariate logistic regression analyses were applied to select the most useful predictors. Receiver operating characteristic curve analysis was applied to evaluate the discriminative performance of the models.</div></div><div><h3>RESULTS</h3><div>The ADC and Ki-67 status were independently associated factors both for task 1 (OR: 41.22, 5.68) and task 2 (OR: 0.02, 0.29). The models established combining conventional MRI parameters with clinicopathologic data in the training set for task 1 and task 2 yielded an area under the curve (AUC) of 0.836 and 0.874, respectively, and demonstrated effective prediction in the test set, with the AUC of 0.845 for task 1 and an AUC of 0.805 for task 2, respectively.</div></div><div><h3>CONCLUSION</h3><div>Models combining conventional magnetic resonance imaging (MRI) parameters and clinicopathologic data could be valuable for differentiating BC HER2 expression, which may aid in selecting patients for HER2-targeted therapies in those without fluorescence in situ hybridisation results.</div></div>","PeriodicalId":10695,"journal":{"name":"Clinical radiology","volume":"86 ","pages":"Article 106955"},"PeriodicalIF":2.1000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combining conventional magnetic resonance imaging (MRI) parameters with clinicopathologic data for differentiation of the three-tiered human epidermal growth factor receptor 2 (HER2) status in breast cancer\",\"authors\":\"W. Liu , C. Liu , Y. Yang , Y. Chen , A. Muhetaier , Z. Lin , Z. Weng , X. Wang , P. Zhang , J. Qin\",\"doi\":\"10.1016/j.crad.2025.106955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>AIM</h3><div>To assess the three-tiered human epidermal growth factor receptor 2 (HER2) classification of breast cancer (BC) patients based on conventional magnetic resonance imaging (MRI) parameters combined with clinicopathologic data.</div></div><div><h3>MATERIALS AND METHODS</h3><div>211 patients with invasive BC were retrospectively evaluated and divided into the HER2-zero, HER2-low, and HER2-positive BC groups. Patients underwent conventional dynamic contrast-enhanced breast MRI. Radiologists assessed clinicopathologic features and measured the apparent diffusion coefficient (ADC) and haemodynamic parameters to differentiate HER2-zero/-low (n=129) from HER2-positive (n=82) BC (task 1) and then HER2-zero (n=90) from HER2-low (n=57) BC (task 2). Patients were randomly assigned to the training and test sets at a ratio of 7:3. Univariate and multivariate logistic regression analyses were applied to select the most useful predictors. Receiver operating characteristic curve analysis was applied to evaluate the discriminative performance of the models.</div></div><div><h3>RESULTS</h3><div>The ADC and Ki-67 status were independently associated factors both for task 1 (OR: 41.22, 5.68) and task 2 (OR: 0.02, 0.29). The models established combining conventional MRI parameters with clinicopathologic data in the training set for task 1 and task 2 yielded an area under the curve (AUC) of 0.836 and 0.874, respectively, and demonstrated effective prediction in the test set, with the AUC of 0.845 for task 1 and an AUC of 0.805 for task 2, respectively.</div></div><div><h3>CONCLUSION</h3><div>Models combining conventional magnetic resonance imaging (MRI) parameters and clinicopathologic data could be valuable for differentiating BC HER2 expression, which may aid in selecting patients for HER2-targeted therapies in those without fluorescence in situ hybridisation results.</div></div>\",\"PeriodicalId\":10695,\"journal\":{\"name\":\"Clinical radiology\",\"volume\":\"86 \",\"pages\":\"Article 106955\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0009926025001606\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical radiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0009926025001606","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Combining conventional magnetic resonance imaging (MRI) parameters with clinicopathologic data for differentiation of the three-tiered human epidermal growth factor receptor 2 (HER2) status in breast cancer
AIM
To assess the three-tiered human epidermal growth factor receptor 2 (HER2) classification of breast cancer (BC) patients based on conventional magnetic resonance imaging (MRI) parameters combined with clinicopathologic data.
MATERIALS AND METHODS
211 patients with invasive BC were retrospectively evaluated and divided into the HER2-zero, HER2-low, and HER2-positive BC groups. Patients underwent conventional dynamic contrast-enhanced breast MRI. Radiologists assessed clinicopathologic features and measured the apparent diffusion coefficient (ADC) and haemodynamic parameters to differentiate HER2-zero/-low (n=129) from HER2-positive (n=82) BC (task 1) and then HER2-zero (n=90) from HER2-low (n=57) BC (task 2). Patients were randomly assigned to the training and test sets at a ratio of 7:3. Univariate and multivariate logistic regression analyses were applied to select the most useful predictors. Receiver operating characteristic curve analysis was applied to evaluate the discriminative performance of the models.
RESULTS
The ADC and Ki-67 status were independently associated factors both for task 1 (OR: 41.22, 5.68) and task 2 (OR: 0.02, 0.29). The models established combining conventional MRI parameters with clinicopathologic data in the training set for task 1 and task 2 yielded an area under the curve (AUC) of 0.836 and 0.874, respectively, and demonstrated effective prediction in the test set, with the AUC of 0.845 for task 1 and an AUC of 0.805 for task 2, respectively.
CONCLUSION
Models combining conventional magnetic resonance imaging (MRI) parameters and clinicopathologic data could be valuable for differentiating BC HER2 expression, which may aid in selecting patients for HER2-targeted therapies in those without fluorescence in situ hybridisation results.
期刊介绍:
Clinical Radiology is published by Elsevier on behalf of The Royal College of Radiologists. Clinical Radiology is an International Journal bringing you original research, editorials and review articles on all aspects of diagnostic imaging, including:
• Computed tomography
• Magnetic resonance imaging
• Ultrasonography
• Digital radiology
• Interventional radiology
• Radiography
• Nuclear medicine
Papers on radiological protection, quality assurance, audit in radiology and matters relating to radiological training and education are also included. In addition, each issue contains correspondence, book reviews and notices of forthcoming events.