Textural analysis in breast MRI improves diagnostic accuracy, finds study
Cincinnati, OH: MRI textural analysis (TA) is helpful in differentiating malignant from being axillary lymph nodes in women with breast cancer, suggests a recent study in the Journal of Breast Imaging.
Rifat A Wahab, University of Cincinnati Medical Center, Department of Radiology, Cincinnati, OH, and colleagues conducted the study to determine the diagnostic accuracy of MRI TA to differentiate malignant from benign axillary lymph nodes in breast cancer patients.
The researchers conducted an institutional review board-approved retrospective study of axillary lymph nodes in breast cancer women who underwent ultrasound-guided biopsy and contrast-enhanced (CE) breast MRI from January 2015 to December 2018. TA of axillary lymph nodes was performed on 3D dynamic CE T1-weighted fat-suppressed, 3D delayed CE T1-weighted fat-suppressed and T2-weighted fat-suppressed MRI sequences. Areas under the curve (AUC) were calculated using receiver operating characteristic curve analysis to distinguish between malignant and benign lymph nodes.
Key findings of the study include:
- Twenty-three biopsy-proven malignant lymph nodes and 24 benign lymph nodes were analyzed.
- The delayed CE T1-weighted fat-suppressed sequence had the greatest ability to differentiate malignant from benign outcome at all spatial scaling factors, with the highest AUC (0.84–0.93), sensitivity (0.78 [18/23] to 0.87 [20/23]), and specificity (0.76 [18/24] to 0.88 [21/24]).
- Kurtosis on the 3D delayed CE T1-weighted fat-suppressed sequence was the most prominent TA parameter differentiating malignant from benign lymph nodes.
"This study suggests that MRI TA could be helpful in distinguishing malignant from benign axillary lymph nodes. Kurtosis has the greatest potential on 3D delayed CE T1-weighted fat-suppressed sequences to distinguish malignant and benign lymph nodes," concluded the authors.
The study, "Textural Characteristics of Biopsy-proven Metastatic Axillary Nodes on Preoperative Breast MRI in Breast Cancer Patients: A Feasibility Study," is published in the Journal of Breast Imaging.