Scopus
YÖKSİS Eşleşti
Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?
Clinical Imaging · Mayıs 2023
YÖKSİS Kayıtları
Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?
Clinical Imaging · 2023 SCI-Expanded
DOÇENT EMİNE UYSAL →
Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?
Elsevier BV · 2023 SCI-Expanded
PROFESÖR MUSTAFA KOPLAY →
Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?
Clinical Imaging · 2023 SCI-Expanded
DOÇENT HALİL ÖZER →
Makale Bilgileri
DergiClinical Imaging
Yayın TarihiMayıs 2023
Cilt / Sayfa97 · 44-49
Scopus ID2-s2.0-85149433985
Özet
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.
Yazarlar (5)
1
Emine Uysal
2
Ömer Faruk Topaloglu
3
Ayşe Arı
4
Halil Özer
ORCID: 0000-0003-1141-1094
5
M. Koplay
ORCID: 0000-0001-7513-4968
Anahtar Kelimeler
Breast cancer
Breast imaging-reporting and data system
Magnetic resonance imaging
Texture analysis
Kurumlar
Selçuk Tip Fakültesi
Konya Turkey
Metrikler
1
Atıf
5
Yazar
4
Anahtar Kelime