Principal component analysis of breast DCE-MRI adjusted with a model-based method.
OBJECTIVE
To investigate a fast, objective, and standardized method for analyzing breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) applying principal component analysis (PCA) adjusted with a model-based method.


METHODS
3D gradient-echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model-based three-timepoints (3TP) method.


RESULTS
Intensity-scaled (IS) and enhancement-scaled (ES) datasets were reduced by PCA yielding a first IS-eigenvector that captured the signal variation between fat and fibroglandular tissue; two IS-eigenvectors and the two first ES-eigenvectors captured contrast-enhanced changes, whereas the remaining eigenvectors captured predominantly noise changes. Rotation of the two contrast-related eigenvectors led to a high congruence between the projection coefficients and the 3TP parameters. The ES-eigenvectors and the rotation angle were highly reproducible across malignant lesions, enabling calculation of a general rotated eigenvector base. Receiver operating characteristic (ROC) curve analysis of the projection coefficients of the two eigenvectors indicated high sensitivity of the first rotated eigenvector to detect lesions (area under the curve [AUC] > 0.97) and of the second rotated eigenvector to differentiate malignancy from benignancy (AUC = 0.87).


CONCLUSIONS
PCA adjusted with a model-based method provided a fast and objective computer-aided diagnostic tool for breast DCE-MRI.
Eyal
Erez
E
Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel.
Badikhi
Daria
D
Furman-Haran
Edna
E
Kelcz
Fredrick
F
Kirshenbaum
Kevin J
KJ
Degani
Hadassa
H
D000328:Adult; D000368:Aged; D000465:Algorithms; D019540:Area Under Curve; D001940:Breast / Q000473:pathology*; D003287:Contrast Media / Q000494:pharmacology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D025341:Principal Component Analysis; D012372:ROC Curve; D012189:Retrospective Studies
D003287:Contrast Media