Journal
EUROPEAN RADIOLOGY
Volume 29, Issue 7, Pages 3820-3829Publisher
SPRINGER
DOI: 10.1007/s00330-018-5981-2
Keywords
Breast cancer; Axillary lymph node metastasis; Radiomics; Preoperative prediction; MRI
Funding
- Special Fund for Research in the Public Interest of China [201402020]
- National Key R&D Program of China [2017YFA0205200, 2017YFC1308700, 2017YFC1308701, 2017YFC1309100, 2016YFC0103803]
- National Natural Science Foundation of China [81227901, 81771924, 81501616, 81671851, 81671854, 81527805]
- Beijing Natural Science Foundation [L182061]
- Bureau of International Cooperation of Chinese Academy of Sciences [173211KYSB20160053]
- Science and Technology Service Network Initiative of the Chinese Academy of Sciences [KFJ-SW-STS-160]
- Beijing Municipal Science and Technology Commission [Z171100000117023, Z161100002616022]
- Instrument Developing Project of the Chinese Academy of Sciences [YZ201502]
- Youth Innovation Promotion Association CAS [2017175]
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ObjectiveTo develop a radiomic nomogram for preoperative prediction of axillary lymph node (LN) metastasis in breast cancer patients.MethodsPreoperative magnetic resonance imaging data from 411 breast cancer patients was studied. Patients were assigned to either a training cohort (n=279) or a validation cohort (n=132). Eight hundred eight radiomic features were extracted from the first phase of T1-DCE images. A support vector machine was used to develop a radiomic signature, and logistic regression was used to develop a nomogram.ResultsThe radiomic signature based on 12 LN status-related features was constructed to predict LN metastasis, its prediction ability was moderate, with an area under the curve (AUC) of 0.76 and 0.78 in training and validation cohorts, respectively. Based on a radiomic signature and clinical features, a nomogram was developed and showed excellent predictive ability for LN metastasis (AUC 0.84 and 0.87 in training and validation sets, respectively). Another radiomic signature was constructed to distinguish the number of metastatic LNs (less than 2 positive nodes/more than 2 positive nodes), which also showed moderate performance (AUC 0.79).ConclusionsWe developed a nomogram and a radiomic signature that can be used to identify LN metastasis and distinguish the number of metastatic LNs (less than 2 positive nodes/more than 2 positive nodes). Both nomogram and radiomic signature can be used as tools to assist clinicians in assessing LN metastasis in breast cancer patients.Key Points center dot ALNM is an important factor affecting breast cancer patients' treatment and prognosis.center dot Traditional imaging examinations have limited value for evaluating axillary LNs status.center dot We developed a radiomic nomogram based on MR imagings to predict LN metastasis.
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