To investigate the correlations of peripheral blood lymphocyte subsets and magnetic resonance imaging (MRI) features with axillary lymph node (ALN) metastasis of
breast cancer and the value of improving the diagnosis accuracy of ALN metastasis.
Methods:
The data of peripheral blood lymphocyte subsets and MRI characteristics of 348 patients with breast cancer were retrospectively analyzed
and the patients were divided into lymph node metastasis group and non-metastasis group according to the results of surgical evaluation of ALNs. The differences in clinicopathology
peripheral blood lymphocyte subsets and breast MRI between the two groups were analyzed
and the independent factors of ALN of breast cancer were analyzed by logistic regression
and the diagnostic efficiency was evaluated by receiver operating characteristic (ROC) curve.
Results:
Among the 348 breast cancer patients
103 patients had ALN metastasis and 245 patients had no metastasis; and patients with multiple lesions
positive human epidermal growth factor receptor 2 (HER2)
Ki-67 proliferation index>20% and lymphovascular invasion were more likely to have ALN metastasis (
P
<0.05). The absolute numbers of total T lymphocytes and toxic T lymphocytes were decreased statistically in ALN metastasis group (
P
were 0.044 and 0.023
respectively). On MRI
patients with larger lesion size were morelikely to have ALN metastasis (
P
<0.001); for MRI morphological diagnostic criteria
146 (42.0%) patients with suspected ALN metastasis were detected in our study
and the sensitivity
specificity and accuracy were 77.7%
73.1% and 74.4%
respectively. For diagnosis of ALN metastasis
the AUCs of the methods of clinicopathology and lesion MRI
MRI morphological diagnostic criteria and the combined were 0.761
0.755 and 0.851
respectively.
Conclusion:
The clinicopathology
peripheral blood lymphocyte subsets and lesion MRI features were correlated with ALN metastasis in breast cancer
and clinicopathological and lesion MRI features are helpful to improve the accuracy of diagnosis of ALN metastasis.
The value of radiomics features derived from the T2WI-FS assisted preoperative prediction of axillary lymph node metastasis of breast cancer
Value of deep learning ultrasound radiomics in predicting axillary lymph node metastasis of breast cancer
Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models
The progress of breast MRI in evaluating breast conservation therapy and ipsilateral breast tumor recurrence
Prediction value of breast MRI in ipsilateral breast tumor recurrence after breast-conserving surgery and distant metastasis following secondary surgery
Related Author
WANG Meng
LIU Zhou
WEN Jie
HE Cuiju
GENG Yayuan
LUO Dehong
Jiaojiao HU
Xiaohong FU
Related Institution
Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Huiying Medical Technology Beijing Co., Ltd
Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Department of Radiology, The First Affiliated Hospital of Soochow University
Department of Ultrasound, Gongli Hospital, Shanghai Pudong New Area