Highlights
- •MRI texture analysis detects independent predictors of breast cancer.
- •MRI texture analysis increases the accuracy rate in the diagnosis of breast cancer.
- •MRI texture analysis can accurately downgrade the majority of benign BI-RADS 4a lesions to BI-RADS 3.
Abstract
Purpose
This study aimed to reveal magnetic resonance imaging (MRI) texture analysis (TA)'s
contribution to categorizing breast lesions according to the Breast Imaging-Reporting
and Data System (BI-RADS) lexicon.
Method
Two hundred and seventeen women with BI-RADS category 3, 4, and 5 lesions on breast
MRI were included in the study. For TA, the region of interest was drawn manually
to encompass the entire lesion on the fat-suppressed T2W and the first post-contrast
T1W images. To identify the independent predictors of breast cancer, multivariate
logistic regression analyses were performed using texture parameters. Estimated benign
and malignant groups were formed according to the TA regression model.
Results
Texture parameters extracted from T2WI, including median, gray-level co-occurrence
matrix (GLCM) contrast, GLCM correlation, GLCM joint entropy, GLCM sum entropy, and
GLCM sum of squares, and parameters extracted from T1WI, including maximum, GLCM contrast,
GLCM joint entropy, GLCM sum entropy, were independent predictors of breast cancer.
In the estimated new groups according to the TA regression model, 19 (91%) of the
benign 4a lesions were downgraded to BI-RADS category 3.
Conclusions
The addition of quantitative parameters obtained by MRI TA to BI-RADS criteria significantly
increased the accuracy rate in differentiating benign and malignant breast lesions.
When categorizing BI-RADS 4a lesions, the use of MRI TA in addition to conventional
imaging findings may reduce unnecessary biopsy rates.
Keywords
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Article info
Publication history
Published online: March 04, 2023
Accepted:
February 28,
2023
Received in revised form:
February 19,
2023
Received:
August 13,
2022
Identification
Copyright
© 2023 Elsevier Inc. All rights reserved.
