Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer
Abstract Purpose The goal of this study is to develop and validate a radiomics nomogram integrating the radiomics features from DCE-MRI and clinical factors for the preoperative diagnosis of axillary lymph node (ALN) metastasis in breast cancer patients. Procedures A total of 432 patients with breas...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-04-01
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| Series: | Cancer Imaging |
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| Online Access: | https://doi.org/10.1186/s40644-022-00450-w |
| _version_ | 1819045421656309760 |
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| author | Deling Song Fei Yang Yujiao Zhang Yazhe Guo Yingwu Qu Xiaochen Zhang Yuexiang Zhu Shujun Cui |
| author_facet | Deling Song Fei Yang Yujiao Zhang Yazhe Guo Yingwu Qu Xiaochen Zhang Yuexiang Zhu Shujun Cui |
| author_sort | Deling Song |
| collection | DOAJ |
| description | Abstract Purpose The goal of this study is to develop and validate a radiomics nomogram integrating the radiomics features from DCE-MRI and clinical factors for the preoperative diagnosis of axillary lymph node (ALN) metastasis in breast cancer patients. Procedures A total of 432 patients with breast cancer were enrolled in this retrospective study and divided into a training cohort (n = 296) and a validation cohort (n = 136). Radiomics features were extracted from the second phase of dynamic contrast enhanced (DCE) MRI images. The least absolute shrinkage and selection operator (LASSO) regression method was used to screen optimal features and construct a radiomics signature in the training cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on the radiomics signature and clinical factors. The predictive performance of the nomogram was quantified with respect to discrimination and calibration, which was further evaluated in the independent validation cohort. Results Fourteen ALN metastasis-related features were selected to construct the radiomics signature, with an area under the curve (AUC) of 0.847 and 0.805 in the training and validation cohorts, respectively. The nomogram was established by incorporating the histological grade, multifocality, MRI report lymph node status and radiomics signature and showed good calibration and excellent performance for ALN detection (AUC of 0.907 and 0.874 in the training and validation cohorts, respectively). The decision curve, which demonstrated the radiomics nomogram, displayed promising clinical utility. Conclusions The radiomics nomogram can be used as a noninvasive and reliable tool to assist clinicians in accurately predicting ALN metastasis in breast cancer preoperatively. |
| first_indexed | 2024-12-21T10:28:18Z |
| format | Article |
| id | doaj.art-a099a10505204200a850f4247a2db358 |
| institution | Directory Open Access Journal |
| issn | 1470-7330 |
| language | English |
| last_indexed | 2024-12-21T10:28:18Z |
| publishDate | 2022-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Cancer Imaging |
| spelling | doaj.art-a099a10505204200a850f4247a2db3582022-12-21T19:07:15ZengBMCCancer Imaging1470-73302022-04-0122111310.1186/s40644-022-00450-wDynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancerDeling Song0Fei Yang1Yujiao Zhang2Yazhe Guo3Yingwu Qu4Xiaochen Zhang5Yuexiang Zhu6Shujun Cui7Graduate Faculty, Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityDepartment of Radiology, The First Affiliated Hospital of Hebei North UniversityAbstract Purpose The goal of this study is to develop and validate a radiomics nomogram integrating the radiomics features from DCE-MRI and clinical factors for the preoperative diagnosis of axillary lymph node (ALN) metastasis in breast cancer patients. Procedures A total of 432 patients with breast cancer were enrolled in this retrospective study and divided into a training cohort (n = 296) and a validation cohort (n = 136). Radiomics features were extracted from the second phase of dynamic contrast enhanced (DCE) MRI images. The least absolute shrinkage and selection operator (LASSO) regression method was used to screen optimal features and construct a radiomics signature in the training cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on the radiomics signature and clinical factors. The predictive performance of the nomogram was quantified with respect to discrimination and calibration, which was further evaluated in the independent validation cohort. Results Fourteen ALN metastasis-related features were selected to construct the radiomics signature, with an area under the curve (AUC) of 0.847 and 0.805 in the training and validation cohorts, respectively. The nomogram was established by incorporating the histological grade, multifocality, MRI report lymph node status and radiomics signature and showed good calibration and excellent performance for ALN detection (AUC of 0.907 and 0.874 in the training and validation cohorts, respectively). The decision curve, which demonstrated the radiomics nomogram, displayed promising clinical utility. Conclusions The radiomics nomogram can be used as a noninvasive and reliable tool to assist clinicians in accurately predicting ALN metastasis in breast cancer preoperatively.https://doi.org/10.1186/s40644-022-00450-wBreast cancerAxillary lymph node metastasisRadiomicsPreoperative prediction |
| spellingShingle | Deling Song Fei Yang Yujiao Zhang Yazhe Guo Yingwu Qu Xiaochen Zhang Yuexiang Zhu Shujun Cui Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer Cancer Imaging Breast cancer Axillary lymph node metastasis Radiomics Preoperative prediction |
| title | Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| title_full | Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| title_fullStr | Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| title_full_unstemmed | Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| title_short | Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| title_sort | dynamic contrast enhanced mri radiomics nomogram for predicting axillary lymph node metastasis in breast cancer |
| topic | Breast cancer Axillary lymph node metastasis Radiomics Preoperative prediction |
| url | https://doi.org/10.1186/s40644-022-00450-w |
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