Preoperative evaluation of histologic grade in invasive breast cancer with T2W-MRI based radiomics signature.
10.11817/j.issn.1672-7347.2019.03.009
- Author:
Yucun HUANG
1
,
2
;
Zixuan CHENG
2
,
3
;
Xiaomei HUANG
1
,
2
;
Cuishan LIANG
4
;
Changhong LIANG
1
,
2
;
Zaiyi LIU
1
,
2
Author Information
1. Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515
2. Department of Radiology, Guangdong Provincial People's Hospital, Guangzhou 510080, China.
3. School of Medicine, South China University of Technology, Guangzhou 510006
4. Second School of Clinical Medicine, Southern Medical University, Guangzhou 510515, China.
- Publication Type:Journal Article
- MeSH:
Breast Neoplasms;
diagnostic imaging;
Humans;
Magnetic Resonance Imaging;
Preoperative Care;
ROC Curve;
Retrospective Studies
- From:
Journal of Central South University(Medical Sciences)
2019;44(3):285-289
- CountryChina
- Language:Chinese
-
Abstract:
To develop and validate a fat-suppressed (T2 weighted-magnetic resonance imaging, T2W-MRI) based radiomics signature to preoperatively evaluate the histologic grade (grade I/II VS. grade III) of invasive breast cancer.
Methods: A total of 202 patients with MRI examination and pathologically confirmed invasive breast cancer from June 2011 to February 2017 were retrospectively enrolled. After retrieving fat-suppressed T2W images and tumor segmentation, radiomics features were extracted and valuable features were selected to build a radiomic signature with the least absolute shrinkage and selection operator (LASSO) method. Mann-Whitney U test was used to explore the correlation between radiomics signature and histologic grade. Receiver operating characteristics (ROC) curve was applied to determine the discriminative performance of the radiomics signature [area under curre (AUC), sensitivity, specificity, and accuracy]. An independent validation dataset was used to confirm the discriminatory power of radiomics signature.
Results: Eight radiomics features were selected to build a radiomics signature, which showed good performance for preoperatively evaluating histologic grade of invasive breast cancer, with an AUC of 0.802 (95% CI 0.729 to 0.875), sensitivity of 78.7%, specificity of 70.3% and accuracy of 73.7% in training dataset and AUC of 0.812 (95% CI 0.686 to 0.938), sensitivity of 80.0%, specificity of 73.3% and accuracy of 76.0% in the validation dataset.
Conclusion: The fat-suppressed T2W-MRI based radiomics signature can be used to preoperatively evaluate the histologic grade of invasive breast cancer, which may assist clinical decision-maker.
